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It's impossible to talk about workforce innovation without addressing artificial intelligence.During a virtual roundtable, we asked Business Insider's <a target="_blank" class="" href="https://www.businessinsider.com/workforce-innovation-board-tackles-topics-such-as-c-suite-innovation-ai-worker-wellness-2024-8">Workforce Innovation board</a> to tell us how AI would transform companies over the next year.One major topic was reskilling and upskilling employees. BI's Tim Paradis, who focuses on the future of work, asked whether there were any fears that <a target="_blank" class="" href="https://www.businessinsider.com/vinod-khosla-universal-basic-income-ai-job-loss-2024-9">dire predictions of AI</a> outpacing human capabilities to learn, like those advanced in a recent article by Sun Microsystems cofounder <a target="_blank" class="" href="https://www.khoslaventures.com/ai-dystopia-or-utopia/">Vinod Khosla</a>, would prove true."The basic drivers of job creation will change with a technology that does not only augment human capabilities, but also may surpass them altogether," Khosla wrote, "leaving education and upskilling — a historical avenue for retraining and relevance — somewhat impotent."Board members rejected the grim prognostication."I disagree with that statement," said Justina Nixon-Saintil, IBM's vice president and chief impact officer, though she agreed that AI would exacerbate the digital divide."We made a commitment to scale 2 million people in AI by 2026," Nixon-Saintil said. "There's a sense of urgency in making sure we are not leaving people behind."AARP's Marjorie Powell argued that the global labor shortage was evidence of an enduring need for human workers but that no one can afford to be complacent. "You're going to have to relearn how to do your job," Powell said.Others described the importance of communicating clearly with workers about what AI means for their jobs now and in the future."We're trying to figure out how this transformation is going to occur," said Chris Deri, the president of the corporate advisory businesses at Weber Shandwick. "There has to be transparent communications and stakeholder engagement alongside figuring out these enterprise and strategic matters."The following has been edited for length and clarity.<h3 id="4a721470-9d79-4540-a871-62ad779b2870">How will the most innovative companies be transformed by AI over the next 12 months?</h3><h2 id="58f968af-3acb-493b-870e-b8d2bf021db1">Justina Nixon-Saintil, vice president and chief impact officer, IBM</h2><h3 id="a436d836-8481-4230-8a70-68bd3cfe6353">"Any tasks or jobs in the company that could be automated by AI will happen within the next year."</h3>A lot is going to change. Any tasks or jobs in the company that could be automated by AI will happen within the next year. For any jobs that cannot be automated, workers will need to understand how to work alongside AI.You need to understand what AI means for your role, how to use it to <a target="_blank" class="" href="https://www.businessinsider.com/how-use-ai-save-time-work-best-ways-use-chatgpt-2024-9">increase productivity or efficiency</a>, and how to create new products and solutions leveraging AI. That's going to be the big shift, and here we actually continue to upskill our employees to prepare for that shift.Last year, we had an AI challenge across the company, and a huge percentage of our employees participated. They had to get training first, and then they were part of a team to come up with innovative solutions leveraging AI. We did it again this summer. So the company is very focused on how to upskill all employees, because it's going to impact every role in the company.<h2 id="82ccd740-f6d2-4536-8e3d-54d9f225dac0">Anant Adya, EVP, service offering head, and head of Americas delivery, Infosys</h2><h3 id="66cbaa75-725e-4e65-880c-285d5d102e74">"How can we eat our own dog food right before we start telling customers to adopt AI?"</h3>We have two objectives. One is to become an AI-first enterprise. The first task is to see how we can start using AI in everything we do, whether it's in our claims or travel expenses, procurement, or handling invoices.Our philosophy is very simple. AI is not about replacing an individual or replacing an employee but how we can amplify our productivity by using the tools. How can we eat our own dog food right before we start telling customers to adopt AI?Second is that for all the offerings that we have today, we want to make sure we infuse AI into them. When we go and talk to our customers about task-level automation, coding or developing an application, or migrating a workload into the cloud — how can we infuse AI into everything that we do? So it doesn't just become a people-based offering but a people-plus-AI-based offering.<h2 id="961badc0-cb06-4d47-9329-ac1f1b2d70dd">Marjorie Powell, chief HR officer and senior vice president, AARP</h2><h3 id="0aee923e-e647-43c9-bf57-4c2ecc03a872">"It's important that everyone learns how to deal with prompt engineering; we are not going to hire prompt engineers."</h3>We believe there's going to be a greater emphasis on <a target="_blank" class="" href="https://www.businessinsider.com/ai-will-change-most-jobs-employers-help-workers-keep-up-2024-8">upskilling and reskilling</a> alongside AI technologies.It's important that everyone learns how to deal with prompt engineering; we are not going to hire prompt engineers. It's going to become a skill for employees to craft clear and specific prompts, adjust to the right audience, and utilize elements and problem-solving skills to identify inaccurate responses.It's about adaptability. Employees are going to have to be open to continuous learning and adapting to new AI tools and technologies in their jobs. So we make sure we're providing some kind of atmosphere and culture for being excited and energetic about learning.The workforce will have to problem-solve regardless of the tool and the technology, and it will require test-and-learn approaches. We created a "community of practice" in the company where individuals can join and help with peer learning and have a sandbox to play around with AI, depending on where they are.They can cross-pollinate across business-unit lines, and that has become very exciting. We also use that group to pilot the new technologies we're considering rolling out to the company.Data literacy is going to be very important — understanding how to read and interpret and tell a story of the data.We're also developing power users in the company, people who are really, really good at this that other employees can tap into when they need help.<h2 id="0ef1d87b-57f3-4474-bfdc-21c4f4fc1b74">Alicia Pittman, global people team chair, Boston Consulting Group</h2><h3 id="dd47519b-c973-4a00-b508-f05159afdea8">"Gen AI also offers an opportunity to avoid leakage of human capital, which obviously we all care quite a lot about."</h3>We have 35,000 employees, and north of 70% are active users of <a target="_blank" class="" href="https://www.businessinsider.com/companies-using-ai-bain-survey-roi-2024-6">generative AI</a> now. We've taken a full-company approach of upskilling and rolling out both custom and off-the-shelf tools, regardless of the job.The bottom-up innovation power of gen AI is super exciting. For example, our teams and employees have created more than a thousand custom GPTs, mini automation machines, to-do scripts, and dashboards to create bespoke analyses and build newsletters — it's super quick, and it doesn't require big investments or processes.That's one thing that's specific to gen AI versus other types of technology innovation — it's sparking a lot of energy and unlocking human capacity.Gen AI also offers an opportunity to avoid leakage of human capital, which obviously we all care quite a lot about. It really changes the game in terms of the amount of learning you can keep within the team and not lose as people move around.We're also seeing how gen AI is creating an exoskeleton for generalists to be able to take on more technical tasks. It's not going to turn a generalist analyst into an expert coder, but actually our analysis would show that they can get 80%-plus there on some coding tasks, which then you still need the expert coder to do quality control.<h2 id="d130e1cc-4600-48d2-941b-e5e5b1eddc1f">Maggie Hulce, chief revenue officer, Indeed</h2><h3 id="d4c2bf89-e522-4f0d-bbff-d8d4f916c1e1">"Do I have to build this huge team of AI engineers? The answer is no."</h3>We're trying to infuse AI in all our externally facing products and solutions to make them more insightful, intuitive, and delightful to use — and, in many ways, to create experiences that mimic what a personalized human experience might be like, but at scale.We also see most roles and workflows becoming augmented with AI. That's becoming more and more obvious as the months go on and as teams engage with AI and find applications and new ways of working.I was at Dreamforce recently in San Francisco. What Salesforce <a target="_blank" class="" href="https://www.salesforce.com/news/press-releases/2024/09/17/google-autonomous-agent-partnership/">unveiled</a> was how it wants to help companies essentially launch AI agents in sales, <a target="_blank" class="" href="https://www.businessinsider.com/verizon-is-using-generative-ai-to-streamline-business-relationships-2024-7">customer service</a>, marketing, and commerce.For many companies to get the full power of what AI can do, you have to be able to link up lots of different datasets that are usually in disparate places. It's hard work, and it's very time-consuming. To hear the stories of companies being like, "Guess what, you don't actually have to move that data around anymore," this is going to change how a lot of companies experiment and start to play with AI-oriented applications that will fundamentally change their operations.There are a lot of companies out there that have already started to light it up. We're thinking a lot about how sales, customer service, marketing, and product have operated for a long time in various silos. When you think about customer experiences, they really shouldn't be that way. They should be much more integrated than they are today. Some of these technologies can be part of the accelerants for how customer experiences can be reimagined.Part of what's been hard for people is like, "OK, but do I have to get all of these disparate parts of my company to all work together in a new way? Do I have to build this huge team of AI engineers?" The answer is no. You don't have to be the tip of the spear in terms of sophistication.<h2 id="8b49bd10-b04d-4857-afbc-b2979d5711e9">Kenon Chen, executive vice president of strategy and growth, Clear Capital</h2><h3 id="550eee1b-ffef-4a90-bbea-a94d7a6ba7a2">"As AI accelerates, you also have to accelerate the handling of data in a way that can produce accurate models."</h3>At Clear Capital, we participate in the highly regulated housing-finance industry. To enable AI to be used in accordance with our clients' expectations of governance and quality control, we've taken a three-pronged approach.First, we've been investing in creating good industry standards and working with the industry to ensure there's agreement on how AI models should be tested, how they ensure compliance with antidiscrimination and fairness practices, and how the data should be handled.Second, we've been investing a lot in higher-quality data. As AI accelerates, you also have to accelerate the handling of data in a way that can produce accurate models. So we've invested quite a bit in better digitization and generation of data.Third is fostering collaboration between innovators, industry players, policymakers, and regulators. We participated this year in the Federal Housing Finance Agency's generative-AI tech sprint, where about 80 leaders from different aspects of the housing industry brainstormed ways to apply generative AI to the lending process to improve borrowers' experience.One thing that became clear after participating in that was where we have more tools and more capabilities to accelerate. We always have to go back to the why: What is the mission? And we have to make the mission at the company level that much more clear so that as we apply these new tools, it's always for the sake of the mission.<h2 id="5e045b5f-3490-4435-8321-bab58740eaa8">Chris Deri, president, corporate advisory businesses, The Weber Shandwick Collective</h2><h3 id="79930c20-445b-4959-b644-53f07e252292">"There's a mega-trend need for all of us to adopt AI and understand it, but that means something different for different parts of our organization."</h3>We're a public-relations firm, so we're looking at AI for ourselves and for our clients.In terms of our own people, one lesson we've already learned is that there was an instinct to take a top-down approach, as in everybody's got to figure out how AI is going to change their business, but we need to take a bottom-up approach.In the simplest sense, we do consumer marketing, healthcare marketing, and corporate advisory work. We really need to design training for each of the different practitioner types.There's a mega-trend need for all of us to adopt AI and understand it, but that means something different for different parts of our organization.Another thing we're doing is creating a futuristic think-tank group in our company — three or four people who have been putting together an ecosystem to give us constant learning. We also have academic institutions, investors, technologists, and other practitioners to help.We're also looking at our business model and how we budget and scope. The classic assignment we get is companies call us and say, "We want to map our stakeholders and what their expectations are of us." That used to be a project that we would figure out with just consultant time. Now we're applying AI to do some of that.We need to figure out how to take advantage of those efficiencies to add new value — that human value. So we need to relook at our entire business and service model, and we haven't figured it all out yet.Anant talked about "eating your own dog food." We've mapped out the implementation of that stack for ourselves to test and learn, and then we will start to use that in how we show up as advisors to our clients on the same journey.<h2 id="3bf33684-0da6-43af-856a-e0d807c42725">Sharawn Tipton, chief people and culture officer, LiveRamp</h2><h3 id="2513253b-1145-4ac9-afad-cb752e1513d8">"What we're trying to do is really keep people at the center of this transformation."</h3>We're thinking a lot about the AI trust gap. I'm in San Francisco today, and I was walking around and I saw all these autonomous vehicles, and it dawned on me that my mother would never ride in one. She just does not trust that technology.As a data company, we're thinking a lot about how do we ensure that our customers, our clients, and our partners trust that we're going to protect their data and use AI when appropriate and be certain that we have safeguards for when it isn't appropriate. And then I think the biggest area that my team is focused on with this trust gap is job security and what this means for the average worker.So what we're trying to do is really keep people at the center of this transformation. We're thinking a lot about employee resource groups. That way we've been able to reach all different types of team members. So how do we target our ERGs and think about who are the slow adapters? Who are the folks that typically get left behind, and how do we give them a little extra push?What we want to do is think about how to continue to have our team members trust their leaders, but also trust AI and where we're going, and get them to understand this isn't about replacing jobs. We are really focused on transforming jobs. That is a huge shift and a huge opportunity for us.<h2 id="c0d7e4c7-96a5-41d7-8c3f-29dee443e291">Shane Koller, senior vice president and chief people officer, Ancestry</h2><h3 id="2fb41060-9718-4c06-940a-5ac8246457b5">"The more people we get thinking about governance, the better AI technology will be used."</h3>There are a lot of different points of view on what AI will and will not do and how quickly.I was reading an article in The Wall Street Journal over the weekend that said for every one person who believes that AI is going to replace everyone's jobs, there are three or four who think there's going to be this boom in AI and then it's going to settle down. And that the promise we think AI is going to deliver will probably take longer than we think to come to fruition.One of the things that we've been doing at Ancestry very intentionally is bringing up the subject of governance, because I think we all think of AI as this steamroller that's going to come and either we're going to step aside from it or we're going to get steamrolled.The more people we get thinking about governance, the better AI technology will be used. And I say that within Ancestry as well as within companies in general and within governments. We have more of a role to play in how this rolls out than we think.We've been building AI into our product for over 10 years now, and we've been giving more thought to how would we govern the use of AI within our own company so that we're not, for example, putting our customers' data at risk. We're very conscious that security and privacy is first and foremost in every discussion. It's really about how you govern such an amazing technology.

Leaders from BCG, Infosys, AARP, and more predict how AI will transform top companies in the next 12 months

Last week, tech giant <keyword id="19906778" type="General" weightage="100" keywordseo="Infosys" source="keywords" meta.keywordsubtype="org" meta.entityname="Infosys" meta.hostid="153" meta.entityid="Infosys">Infosys</keyword> was making headlines for delaying onboarding of thousands of freshers for more than two years. It was reported that freshers had been awaiting onboarding since 2022 but nothing was happening on that front. The Nascent Information Technology Employees Senate (<keyword id="20033579" type="General" weightage="20" keywordseo="NITES" source="keywords" meta.keywordsubtype="org" meta.entityname="NITES" meta.hostid="153" meta.entityid="NITES">NITES</keyword>) even filed a formal complaint against the company. Now, <keyword id="21949326" type="General" weightage="20" keywordseo="Infosys-CEO" source="keywords">Infosys CEO</keyword> Salil Parekh has said that everyone with a job offer will be a part of the company even though there are “delays.” <h2>Infosys CEO reassures graduates</h2> Infosys has confirmed its commitment to honour all <keyword id="20345755" type="General" weightage="20" keywordseo="offers" source="keywords">offers</keyword> extended to fresh engineering graduates, despite ongoing delays in the onboarding process. CEO Salil Parekh recently addressed concerns that have been brewing among thousands of freshers, saying that while some joining dates have been adjusted, every candidate who received an offer will join the company. In a statement, Parekh told PTI, "Every offer that we have given, that offer will be honored, and those individuals will join Infosys. We have adjusted some dates, but beyond that, there is no change in our approach." According to a CNBC report, Parekh also said that the rising interest in Generative AI (GenAI) among clients is a positive sign for future growth. He added that while GenAI is driving significant change within the industry, it will not lead to layoffs at Infosys, a point of distinction compared to trends seen at other tech firms. <div type="Article" hostid="261" msid="112669758" title="Infosys delays onboarding of 2,000 graduates for more than 2 years, NITES files complaint" mstype="2" mssubtype="0"></div> Parekh’s reassurances come in response to growing unrest among freshers from the 2022 batch, many of whom have been waiting for nearly two years to start their careers at Infosys. <h2>What is happening with Infosys hiring?</h2> For the unversed, the Nascent Information Technology Employees Senate (NITES), a Pune-based IT employee union, recently filed a formal complaint with the Ministry of Labour and Employment, accusing Infosys of delaying the onboarding of over 2,000 engineering graduates. These graduates were selected for roles such as system engineers and digital specialist engineers during the company’s 2022-23 recruitment drive. According to NITES, the affected graduates received their offer letters as early as April 2022 but have since faced continuous delays, unpaid pre-training programs, and additional assessments that were not initially communicated. Despite fulfilling all the requirements, these professionals have been left in limbo, unable to begin their careers. SEE ALSO: <a href="https://www.businessinsider.in/careers/news/work-life-balance-is-a-myth-photo-of-man-working-in-front-of-momo-stall-goes-viral-internet-reacts/articleshow/112516510.cms" data-type="tilCustomLink" target="_blank">'Work-life balance is a myth’: Photo of man working in front of momo stall goes viral, Internet reacts</a> <a href="https://www.businessinsider.in/tech/article/arrange-or-love-marriage-debate-is-passe-people-are-now-marrying-their-ai-partners/articleshow/112522764.cms" data-type="tilCustomLink" target="_blank">Arrange or love marriage debate is passe, people are now marrying their AI partners</a>

Everyone will join, there is no change: Infosys CEO after delaying joining of 2,000 freshers for over two years

In an era where customer experience is a primary business differentiator, the role of service hubs has evolved from merely answering calls to becoming innovation centers. With the infusion of advanced technologies like <keyword id="107950" type="General" weightage="20" keywordseo="artificial-intelligence" source="Orion">Artificial Intelligence</keyword> (<keyword id="6355999" type="General" weightage="20" keywordseo="AI" source="Orion">AI</keyword>) and Generative AI (Gen-AI), the service hub industry is now undergoing a transformation that promises to redefine customer interactions, according to experts. “The nature of the industry will change. I think even calling it <keyword id="19945906" type="General" weightage="20" keywordseo="customer-service" source="keywords">customer service</keyword> or service industry may be a very different outlook 5 years from now,” said Sameer Bapat, SVP and COO of Cognizant IOA, during a panel discussion on “Revolutionsing Customer Experience Innovating Service Hubs Through Technology,” hosted by Business Insider India. Leaders in the industry believe that India is entering the golden age of customer service, one powered by data-driven insights, AI-driven empathy, and evolving human-machine collaboration. “The net amount of venture capital and private equity capital that you’re going to see in the customer service industry going forward is going to 5-10x of what it has been in the last 5 years,” predicted panelist Vijay Narsapur, SVP and Business Head of Infosys BPM. <div type="Youtube" id="E23CeECUh9A" title="Revolutionizing Customer Experience: Innovating Service Hubs Through Technology" thumbUrl="https://i.ytimg.com/vi/E23CeECUh9A/mqdefault.jpg"><url><![CDATA[https://www.youtube.com/watch?v=E23CeECUh9A]]></url></div> <h2>The evolution of service hubs: More than customer service</h2>No longer just centers for addressing customer complaints or technical issues, today’s service hubs are integrating innovative technologies to become the nerve center of business operations. According to Sanjay Kukreja, Global Technology Head at Eclerx, tools like data engineering and cloud computing have shifted customer service into real-time interactions, allowing businesses to assist customers faster and more efficiently than ever before. For Narsapur, service hubs are now the lifeblood of the business process management (BPM) industry. End customers have become increasingly comfortable interacting with AI and automated systems. However, they still crave human connection, especially when complex or emotionally charged issues arise. Narsapur points out that this blending of technology and human touch is crucial for refining the customer journey. As businesses scale, service hubs are expected to balance these elements more tightly to deliver both efficiency and empathy. <h2>AI and Gen-AI: Disruptors or Enhancers?</h2>Arguably, the most significant driver of change in the service hub industry has been the integration of AI and Gen-AI. Bapat explains that these technologies have transformed how service hubs operate. Automation tools have led to productivity gains ranging between 20% to 60%, primarily by streamlining mundane tasks, improving scalability, and delivering more personalized customer interactions. This isn’t just an incremental improvement—it’s a deep, domain-led transformation of how companies interact with their customers. But, as Abhinandan Jain, Chief Growth Officer at Startek, notes, AI doesn’t just enhance efficiency—it also amplifies empathy. Service hubs are learning how to use AI as an "empathy amplifier," where AI-driven systems handle routine queries, and human agents step in for more complex, emotionally charged interactions. This helps agents focus on delivering the high-touch experiences customers expect when they escalate an issue to a real person. While there has been some anxiety surrounding AI replacing jobs, the experts argue that this technology will instead create more high-value roles. ““There is going to be an increase of anywhere between 2x to 5x in the number of jobs that are going to be created in this particular industry,” said Narsapur. For example, there will be an increasing demand for professionals skilled in data science, machine learning, and algorithm management to maintain and improve AI systems. According to a <a href="https://www.mckinsey.com/mgi/our-research/generative-ai-and-the-future-of-work-in-america">McKinsey</a> report, AI will automate 25-30% of jobs in customer service, but the technology will also create new roles in AI supervision, data analysis, and customer experience management. <h2>Data-driven insights and the role of <keyword id="23232621" type="General" weightage="20" keywordseo="CRM-tools" source="keywords">CRM tools</keyword></h2>One of the most promising developments in the service hub sector is the increasing reliance on data to drive customer interactions. Jain explains that service hubs are now equipped with sophisticated Customer Relationship Management (CRM) tools that can mine both structured and unstructured data, enabling companies to gain a holistic view of customer behavior. This level of insight allows businesses to not only address customer queries more efficiently but also predict future needs, making the customer journey more proactive than reactive. These CRM platforms are evolving, too. Narsapur notes that many service hubs, particularly in industries like banking and telecom, now use platforms that integrate various aspects of customer interaction, from onboarding to relationship management. These platforms provide a unified view of customer interactions, allowing agents to access the information they need quickly, which ultimately drives faster resolution times and higher customer satisfaction. A <a href="https://www.gartner.com/en/newsroom/press-releases/2021-01-12-gartner-predicts-80--of-customer-service-organization">Gartner</a> study revealed that by 2025, 80% of customer service interactions will be handled by AI and CRM systems, up from 52% in 2020. <h2>The economic impact of AI on service hubs</h2>The rise of AI and Gen-AI is also fueling an economic boom in the service hub sector. Jain predicts that the influx of venture capital and private equity in AI research for customer service hubs will increase five- to ten-fold in the coming years. This investment is primarily driven by the need for businesses to remain competitive in an increasingly tech-driven market. The economic growth potential is massive, especially in regions like India, where the talent pool for AI and data science is unmatched. Kukreja echoes this sentiment, noting that India’s service hubs are well-positioned to lead this transformation due to their depth of talent in areas such as data engineering, mathematics, and AI development. This gives Indian service hubs a competitive edge as companies look to scale their customer service operations with tech-driven solutions. Global spending on Gen-AI is expected to reach $26 billion by 2027, with Japan and India set to become the most rapidly expanding markets in the forthcoming years, according to <a href="https://www.idc.com/getdoc.jsp?containerId=prAP52048824">IDC</a>. <h2>What lies ahead for service hubs?</h2>As we look to the future, the role of service hubs will likely expand even further. Narsapur warns that while platforms and AI will drive efficiency, businesses should not rely solely on technology. Competitive advantage will come from the integration of human expertise, technology, and industry-specific solutions. Different sectors, such as banking, telecom, and retail, each have unique needs that service hubs must adapt to in order to provide effective, personalized customer experiences. AI will play a central role in this transformation. But as Jain points out, it won’t replace human agents entirely. Instead, it will coexist with them, moving people up the value chain to focus on higher-value tasks. AI will handle the routine, while humans will step in where emotional intelligence and complex problem-solving are required. In the end, the future of service hubs is not just about technology; it’s about blending tech and humanity in a way that elevates customer experiences to new heights. We are at the dawn of a new era for customer service hubs. The infusion of AI and Gen-AI, along with data-driven insights and sophisticated CRM tools, is transforming the industry from the ground up. Far from being a threat to jobs, AI will create new opportunities, leading to a more dynamic, efficient, and empathetic customer experience. With significant economic growth on the horizon, particularly in regions like India, the service hub industry is set to play a pivotal role in the future of business. The golden age of customer service is here, and the best is yet to come. This article is part of a four-part webinar series in partnership with nasscom. These monthly webinars aim to delve deep and offer insights into the evolving BPM landscape. You can watch the full video of the second session <a href="https://www.youtube.com/watch?v=E23CeECUh9A">here</a>. Disclaimer: This article is generated and published by the Insider Studios team. You can get in touch with them on insiderstudios@businessinsider.in

Customer service hubs: Entering the golden age with Gen-AI and tech-driven solutions

<ul><li><keyword id="19906778" type="General" weightage="100" keywordseo="Infosys" source="keywords" meta.keywordsubtype="org" meta.entityname="Infosys" meta.hostid="261" meta.entityid="Infosys">Infosys</keyword> has delayed hiring of 2000 young professionals</li><li><keyword id="20033579" type="General" weightage="20" keywordseo="NITES" source="keywords" meta.keywordsubtype="org" meta.entityname="NITES" meta.hostid="261" meta.entityid="NITES">NITES</keyword> has filed a complaint in the matter</li><li>Infosys is also making headlines for its new Power Programme</li></ul> The Nascent Information Technology Employees Senate (NITES), a Pune-based <keyword id="22859482" type="General" weightage="20" keywordseo="IT-employee-union" source="keywords">IT employee union</keyword>, has filed a formal complaint with the Ministry of Labour and Employment against Infosys. The union alleges that Infosys has delayed the <keyword id="22570539" type="General" weightage="20" keywordseo="onboarding-process" source="keywords">onboarding process</keyword> for around 2,000 <keyword id="22859483" type="General" weightage="20" keywordseo="fresh-engineering-graduates" source="keywords">fresh engineering graduates</keyword> for over two years, leaving them in a state of uncertainty and distress. <h2>Infosys delayed freshers' onboarding for more than two years</h2>According to NITES, these graduates were selected for roles such as system engineer and digital specialist engineer as early as April 2022. Despite receiving offer letters, the onboarding process has been repeatedly postponed. The affected graduates were required to participate in unpaid pre-training programs and undergo additional, unexpected assessments, further complicating their entry into the workforce. NITES claims that despite fulfilling all the prerequisites set by Infosys, these young professionals have been kept in limbo, leading to significant frustration and anxiety. The union views this situation as a serious breach of trust by Infosys, which has long been regarded as one of the pillars of India’s IT industry. Harpreet Singh Saluja, President of NITES, expressed deep concern over the situation, emphasizing the broader implications for the Indian IT sector. “We believe that this is not just a breach of trust by one of India’s largest IT companies, but also a significant issue that impacts the future of our country’s <keyword id="22360158" type="General" weightage="20" keywordseo="IT-workforce" source="keywords">IT workforce</keyword> and economy. We are calling on the government to take immediate and strict action against Infosys to ensure that such exploitative practices are halted and that the rights of these young professionals are protected,” Saluja said, according to a report by The Economic Times. The complaint filed by NITES highlights that even after long delays, the graduates were asked to participate in an unpaid virtual pre-training program from July 1 to July 24, 2024. They were promised final joining dates of either August 19 or September 2, 2024. However, despite completing the training, they were informed that they would need to retake the exam offline, once again without pay. This has only added to their frustration and uncertainty about their future with the company. <h2>Infosys’ Power Programme</h2>In a contrasting development, Infosys is also making headlines for its recent campus placement drive, where it has introduced a new 'power programme.' According to a report by The Times of India, the company is offering pay packages of up to Rs 9 lakh per annum to select colleges, a significant increase from its standard entry-level packages, which typically range from Rs 3-3.5 lakh. This move is seen as part of Infosys’ strategy to attract highly specialized talent in areas such as coding, software development, cloud computing, AI/ML, and cybersecurity. Infosys plans to hire between 15,000 and 20,000 graduates in FY25. During its earnings call last month, Infosys announced plans to resume campus placements and off-campus fresher hiring in the current fiscal year. The top four IT firms in India are expected to collectively add about 82,000 freshers in FY25. Among them, HCLTech and <keyword id="19945574" type="General" weightage="20" keywordseo="wipro" source="keywords">Wipro</keyword> plan to hire 10,000 and up to 12,000 freshers, respectively. SEE ALSO: <a href="https://www.businessinsider.in/careers/news/work-life-balance-is-a-myth-photo-of-man-working-in-front-of-momo-stall-goes-viral-internet-reacts/articleshow/112516510.cms" data-type="tilCustomLink" target="_blank">'Work-life balance is a myth’: Photo of man working in front of momo stall goes viral, Internet reacts</a> <a href="https://www.businessinsider.in/tech/article/arrange-or-love-marriage-debate-is-passe-people-are-now-marrying-their-ai-partners/articleshow/112522764.cms" data-type="tilCustomLink" target="_blank">Arrange or love marriage debate is passe, people are now marrying their AI partners</a>

Infosys delays onboarding of 2,000 graduates for more than 2 years, NITES files complaint

IT services company <keyword id="6354512" type="General" weightage="80" keywordseo="infosys" source="Orion">Infosys</keyword> on Thursday announced a three-year partnership with <keyword id="24244" type="General" weightage="50" keywordseo="rafael-nadal" source="Orion">Rafael Nadal</keyword>, onboarding the global tennis star as ambassador for the brand and Infosys' Digital Innovation. To mark Nadal's first-ever collaboration with a digital services company, Infosys and Nadal's coaching team are developing an AI-powered match analysis tool, the Bengaluru-headquartered company said in a release. This personalised tool will be available in real time to Nadal's coaching team to simultaneously track insights from his live matches, when he is back on tour, along with historical data from his earlier matches. The company release announced the partnership, saying "Infosys onboards tennis icon Rafael Nadal as ambassador for the brand and Infosys' Digital Innovation." According to Infosys, Nadal is a perfect embodiment of what it takes individuals or business leaders to evolve and continually navigate their next. Globally acknowledged as one of the legends in sports, he also has had the ability to change with the changing rigors of tennis over the years. "I'm very happy to work closely with Infosys, as they work to not only evolve the experience of tennis to the times, but also empower people in our communities to be part of a brighter future. I love the way Infosys has brought its digital expertise across industries to the global tennis ecosystem," Nadal said. <keyword id="328377" type="General" weightage="50" keywordseo="salil-parekh" source="Orion">Salil Parekh</keyword>, Chief Executive Officer and Managing Director, Infosys said it is an honour to welcome Nadal, one of the world's most respected champion athletes and humanitarians, as an ambassador for Infosys. "He is someone who personifies the spirit of always evolving, never giving up, utmost dedication and determination to give the very best in every situation," Parekh said.

Infosys ropes in tennis icon Rafael Nadal as brand ambassador

Executives from 10 companies who are participants in our first-ever Workforce Innovation Board convened for a virtual roundtable on August 21.The group was asked to share which topics they're most focused on between AI, worker well-being, diversity, equity, and inclusion, and C-suite transformation.While worker well-being and AI were the most commonly cited trends, there's clear overlap and intersectionality across all four topics.Successful employees need training and support, equitable and fair access to opportunities, and reassurances about the integration of AI. C-suite leaders, facing internal and external scrutiny and pressures, need a productive and motivated workforce, and to organize in new ways to enable innovation.At the inflection point is the enormous job companies have to not only encourage AI adoption but also equip employees with what they need to take part in the transformation that is underway."There's a positive story to be told," said Jack Azagury, the group chief executive for consulting at Accenture. "Related to that is a massive amount of reskilling and training that's going to need to happen to make sure nobody's left behind on this journey."In this article, discover what each board member told us about their workplace priorities.The following has been edited for length and clarity.<h2>'We're trying to understand a more holistic view of worker well-being'</h2>Shane Koller, senior vice president and chief people officer, AncestryThe two topics we're most focused on are worker well-being and DEI.We transitioned to a hybrid-flexible work environment a couple of years back, and we've been trying to understand both the positives and the negatives from that shift. We've been a very culture-centric company in the past.Now having more people distributed throughout the world, there's a question coming up more often about whether or not people feel too disconnected from their colleagues, so we're trying to understand a more holistic view of worker well-being.The other is diversity, equity, and inclusion. We are looking to build products that bring more people in from across the globe. We believe our workforce needs to represent the diversity of the world in order to build great products.<h2>'The key to unlocking the potential of AI is to make sure that our employees are embracing it and are excited about the value'</h2>Lucrecia Borgonovo, chief talent and organizational-effectiveness officer, MastercardTop of mind is C-suite innovation, but it's more around organizational transformation.Earlier this year, Mastercard announced changes in our organizational structure in support of the new vision and strategic priorities that our CEO has laid out: How do we make sure that we're structuring to unlock the potential and growth of the organization?Related to that is AI. As part of this new organizational structure, we announced our chief AI and data officer, one individual who would help bring together a cohesive strategy and vision for the organization's AI.The key to unlocking the potential of AI is to make sure that our employees are embracing it and are excited about the value these new technologies can have on their well-being and the quality of their work.We're making a lot of different resources available for employees, whether they're on demand or self-paced, depending on where they are in their AI journey and the type of work that they do.<h2>'The intersection of AI and C-suite transformation is pervasive'</h2>Jack Azagury, group chief executive for consulting, AccentureIn terms of the work that I do with clients, the intersection of AI and C-suite transformation is pervasive. In over 400 client discussions in the last nine months, only three did not include the topic of AI.A lot of our clients have dozens of AI pilots everywhere. Very few have a coherent business case and a true reinvention and transformation.So at that intersection, how do you take a few areas of the company and look at them end to end with a business case that could include revenue uplift, or cost, or employee engagement — but a real business case and a real talent strategy. How do you retrain your employees and reskill? What new jobs do you need? What jobs will go away? What superpowers will employees get? And then having the right tech stack, the right data, the right responsible AI framework.So how do you have a holistic C-suite transformation powered by a move away from a lot of AI pilots that are just plugged into existing processes — which are interesting but not having a fundamental impact on the performance of the company?<h2>'C-suite transformation is harder and more interesting than ever'</h2>Alicia Pittman, global people-team chair, BCGI'm responsible for driving generative-AI usage across BCG. We want our people to be at that cutting edge in terms of responsible AI and understanding all the risks of it, to use it creatively, and to be able to live in our clients' shoes about what it takes to make this amazing technology have high impact.AI is driving better, higher-quality impact and insights for us, which is most important. It is driving areas of productivity. But the other thing that lights me up the most is that it's really improving what I would call joy.One of the quotes I love is from focus groups where someone said, "The thing I love about AI is that it saves me at the ugliest hours of the day." That time when you're sitting at a blank screen toward the end of the day and you don't know what to do, that's when AI really is a friend.C-suite transformation is harder and more interesting than ever. The markets are volatile. The half-life of market leadership keeps getting shorter and shorter. We have C-suite executives and the clients that we serve wrestling — needing to both save costs but also invest in AI and change the way they lead and manage their workforce.<h2>'AI is not about cost takeout. It's about the ability to do more and amplify the potential of our employees.'</h2>Anant Adya, executive vice president, service-offering head, and head of Americas delivery, InfosysDEI, and within that, gender diversity, is something that we are very passionate about.At the company level, we are at 39.3% women, but as you go up the value chain, the gender diversity actually drops. So we are deliberately trying to see what we can do to improve that percentage at senior levels.The second is, of course, AI. And the way we look at AI is it's not about cost takeout or cost savings, but it is about how we use AI and amplify the potential of our employees to do more.Most think that with AI, you can take cost out, you can save money. But AI, and especially generative AI, is not about cost takeout. It's about the ability to do more and amplify the potential of our employees.<h2>'Studies have shown that employees want managers who are engaged, who are coaches versus supervisors'</h2>Marjorie Powell, chief human-resource officer and senior vice president, AARPThe topics we've been focusing on are workplace well-being and artificial intelligence and emerging tech. We have to reach our 38 million members, and now with the use of this technology, we can meet them where they are and personalize their experience.In order for us to do this, we're allowing our staff to use AI within their jobs and to create innovative ways to amplify their work and meet their goals and objectives. We've always been very excited about adopting technologies, particularly as it pertains to making people's lives better as they age.I also spend a lot of time on worker well-being because of the new hybrid work environment, and this goes to our people-leader effectiveness. Studies have shown that employees want managers who are engaged, who are coaches versus supervisors.So we are transforming that leadership quotient for our people leaders within the company to be able to adjust to that and make sure that we have a very robust work environment, no matter where the person sits or where they work from.<h2>'We've had to move upstream from being focused on workplace to the very nature of work and the workforce itself'</h2>Neil Murray, CEO, Work Dynamics at JLLMy day job is working with the biggest corporations in the world and helping them with their workplace strategy, which obviously has changed quite dramatically over the last number of years.We've had to move upstream from being focused on workplace to the very nature of work and the workforce itself, hence worker well-being being at the center of what we do and our thinking. The second thing would be C-suite transformation. For me, that incorporates both AI and DEI.Sitting on the executive board of a global Fortune 200 business, the world has changed quite dramatically for us in how we organize ourselves in terms of operating model. The skills required have changed quite dramatically. The notion of empathetic leaders who deeply understand people but also have the skills to leverage platforms at scale, to deal with ongoing geopolitical tensions and macro challenges that seem to have become the norm in leadership.What doesn't serve us well is the notion of the rise of nationalism and protectionism — how do we deal with that? How do we find the balance between global vertical expertise with the local knowledge and execution required to operate in this world around us?<h2>'We have made significant commitments to responsible AI'</h2>Maggie Hulce, chief revenue officer, IndeedEvery three seconds, somebody gets a job on Indeed. We come at this with a focus on how we help our employees but also how we're helping the world of work.For AI, we're thinking a lot about how to improve how we work, fraud detection, next best action marketing copy, many things like that. We also have a commitment to help 30 million people facing bias get hired. And so we have made significant commitments to responsible AI and have published our responsible-AI principles.A big focus for us is worker well-being. We have a work-happiness score, which is the largest dataset in the world of what makes workers happy in their roles. It includes lots of different dimensions, like fair pay, flexibility, inclusion, learning, and how your manager works with you.We think a lot about how to use this dataset to help advocate for better work for people, given research that shows many people don't love their jobs and are not totally thriving at work. We also study it for ourselves, and there are things we're working on ourselves as an employer to make our workplace a place where people want to stay and grow their careers.<h2>'There's a constant discussion around not only whether AI is going to replace my role but also how to stay relevant'</h2>Kenon Chen, executive vice president of strategy and growth, Clear CapitalThere's been a lot of attention on the property-appraisal industry over the past few years from an equity standpoint.We've seen ourselves as a company that wants to bring accuracy, fairness, and modernization to the process of valuing properties. That's why AI is an important topic for us because it's not so much about just creating efficiencies; it's about creating more accurate outcomes and results.We see a really strong tie between AI and worker well-being because a lot of the solutions that AI could be appropriate for have an impact on the way that people work and how their jobs might look.Because we work directly with real-estate professionals — appraisers, real-estate brokers, and agents — there's a constant discussion around not only whether AI is going to replace my role but also how to stay relevant to the process and bring what's needed in terms of human expertise.<h2>'The hybrid work environment has really changed how our leaders show up'</h2>Sharawn Tipton, chief people and culture officer, LiveRampC-suite transformation is a very intentional focus for us, and there's certainly opportunity.So it's about developing those leaders, holding them accountable — not just to our objectives but also to their behaviors — and grooming the next level of leadership as well. The hybrid work environment has really changed how our leaders show up and how we develop them in various areas.The other area that is extremely important around product is artificial intelligence. AI will fuel data collaboration, which is what we do, so we are infusing that into our products. I'm also thinking about how we infuse that into our employees' day-to-day work. There's a lot of complexity there.There's also a conversation that needs to be had around how AI will impact underrepresented groups and do they have the skills necessary to operate in that space.

AI and worker well-being are top of mind for business leaders, according to execs from Accenture, Mastercard, Ancestry, and more

<keyword id="6355315" type="General" weightage="100" keywordseo="elon-musk" source="Orion">Elon Musk</keyword> on Monday revealed he is going to develop his own version of an artificial intelligence chatbot, 'TruthGPT' during an interview with <keyword id="1100092" type="General" weightage="50" keywordseo="tucker-carlson" source="Orion">Tucker Carlson</keyword> on Fox News. During an interaction with <keyword id="370591" type="General" weightage="80" keywordseo="carlson" source="Orion">Carlson</keyword>, the Twitter CEO shared why he wants an alternative to ChatGPT, an AI app developed by progressive programmers that he initially helped fund. Musk said, "I'm going to start something which I call TruthGPT, or a maximum truth-seeking AI that tries to understand the nature of the universe. And I think this might be the best path to safety in the sense that an AI that cares about understanding the universe is unlikely to annihilate humans because we are an interesting part of the universe," He further said, "AI is more dangerous than, say, mismanaged aircraft design or production maintenance or bad car production in the sense that it has the potential, however, small one may regard that probability, but it is not trivial; it has the potential of civilizational destruction," the <keyword id="107096" type="General" weightage="80" keywordseo="tesla" source="Orion">Tesla</keyword> CEO stated. A few days ago, he also tweeted about meeting with former US President Barack Obama to warn of the dangers surrounding the software's capabilities, and to encourage AI regulation. The Tweet read, "I saw it happening from well before GPT-1, which is why I tried to warn the public for years. The only one on one meeting I ever had with Obama as President I used not to promote Tesla or SpaceX, but to encourage AI regulation." SEE ALSO: <a href="https://www.businessinsider.in/business/corporates/news/sbi-hul-tcs-kotak-bank-and-hdfc-and-other-big-companies-ceo-will-change-in-next-12-months/articleshow/99574790.cms">Companies with $465 billion in combined market cap to see a CEO change in the next 12 months: Here’s what investors should do</a> <a href="https://www.businessinsider.in/finance/banks/news/hdfc-hdfc-bank-merger-to-bring-inflows-of-up-to-3-billion-all-eyes-now-on-the-merger/articleshow/99557243.cms">HDFC-HDFC Bank merger to bring foreign inflows of up to $3 billion</a> <a href="https://www.businessinsider.in/stock-market/news/infosys-shares-tank-after-a-disappointing-q4-fy23-performance/articleshow/99548980.cms">Infosys shares tank over 9% post a disappointing Q4, analysts caution demand moderation ahead</a>

Elon Musk to launch AI platform 'TruthGPT'

<ul><li>We have always spoken about democracy in the context of politics, but here’s a new way to look at the concept – <keyword id="18872395" type="General" weightage="20" keywordseo="ai-democratisation" source="Orion">AI democratisation</keyword>.</li><li>In the digital setting, democratisation of resources can prove to be beneficial for individuals and organisations.</li><li>We explore the various levels of <keyword id="6355999" type="General" weightage="20" keywordseo="ai" source="Orion">AI</keyword> democratisation and how they can add value for the end user.</li></ul>The concept of ‘democracy’ carries several interpretations. While the most popular one is a government representing all people, it also extends to things/resources that can be democratised and made available to the masses. The notion applies equally in the realm of digital technology. AI democratisation is a framework aimed at making the benefits of <keyword id="107950" type="General" weightage="100" keywordseo="artificial-intelligence" source="Orion">artificial intelligence</keyword> accessible to all, even to those who do not have any knowledge of it. <cmsannotation type="cmsannotation" annotationid="What is AI democratisation? Why democratise?" comment="subhead" text="What is AI democratisation? Why democratise?"><keyword id="18872394" type="General" weightage="20" keywordseo="what-is-ai-democratisation" source="Orion">What is AI democratisation</keyword>? Why democratise?</cmsannotation> The 20th century witnessed a surge in technological advancements and techies. This century, however, is all about data and intelligence and using them to recognise trends, make decisions, forecast, learn, improve, and above all, make data accessible to everyone in the organisation. But the catch is that <a href="https://www.infosysbpm.com/offerings/functions/sourcing-procurement-outsourcing/insights/documents/generative-ai-in-procurement-who-is-ahead-of-the-curve.pdf">AI development </a>demands a lot - resources, expertise, computing power, and money. In short, it is a technology that is limited in its reach for the rich and/or the tech-savvy population. Others find themselves lagging - a situation that firms up the need for democratising AI. The three main benefits of doing so are: <ul><li>Reduced entry barriers for individuals and organisations: With little investment, they can both enter the world of AI and experiment with building AI models by accessing publicly available datasets.</li><li>Accelerated adoption in the fields of business and academics: The use of NLP (Natural Language Processing) in businesses, ML (Machine Learning) and deep learning to augment human decision-making enables businesses to be more agile and hyper-productive.</li><li>Lower overall cost of building AI solutions: Since data and many algorithms are available for free, developers can start extending them to build more powerful solutions.</li></ul><cmsannotation type="cmsannotation" annotationid="Levels of democratisation" comment="subhead" text="Levels of democratisation">Levels of democratisation</cmsannotation> Which aspect(s) of the AI product adds the most value for the end user? This question must be answered by technology vendors before they release their products in the market. The gamut of AI democratisation includes data, algorithms (pre-trained models), data computing and storage, and the marketplace. Data: It is the raw input for ML from which insights are generated, decisions made, and outcomes predicted. This level is easy to democratise, enables basic analysis of datasets and also helps in training AI models quickly. Algorithms: At this level, data gets engaged. Democratising algorithms, though more complex than data democratisation, is still easy. However, it needs a basic understanding of computer science, statistics, and mathematics to make sense of the algorithm. Platforms like GitHub and Hugging Face boast of hundreds of AI code repositories and pre-trained models which provide a jumpstart and overall acceleration to the AI journey. Data Computing and Storage: At this point, democratisation starts to become more complicated. With major AI/ML providers like Amazon Web Services (AWS), Google Compute Platform, Microsoft Azure, and IBM Cloud, transitioning to cloud-based platforms, access to essential hardware components like central processing units (CPUs) and graphics processing units (GPUs) has been simplified. Additionally, advanced storage solutions like Google Cloud Storage and Amazon S3 facilitate easy and secure data storage and management. Marketplace: The democratisation of the marketplace is still in its early stages, indicating untapped opportunities awaiting exploration. Platforms such as Hugging Face Leaderboard, Kaggle, Algorithmia, and AI Hub are thriving AI communities of ML practitioners. These communities regularly conduct open challenges that promote the creation and enhancement of Large Language Models (LLMs). Much like the printing press democratised information and the internet democratised knowledge – AI and Generative AI, representing the present and future of technology, are on this path now. The full potential of AI is yet to be realised and democratising it is the path forward to unlocking its true capabilities. As Kay Firth-Butterfield, the head of AI and ML of the World Economic Forum aptly noted, “The long-term success in the development of AI will depend on the agility of the collaboration, the diversity and integrity of the data, and the accuracy of the risk assessments.” Disclaimer: This article is authored by Santosh Unni, Head of Digital Transformation for EMEA and APAC and Head of AI CoE, Infosys BPM. The opinions expressed are those of the author and do not necessarily reflect the views of Business Insider India.

AI for all: The power and potential of democratising artificial intelligence

<ul><li>TCS and HCL Tech said that they have over a 100 <keyword id="17930214" type="General" weightage="20" keywordseo="genai" source="Orion">genAI</keyword> opportunities in the pipeline.</li><li>They also won a few projects, most of which are in the proof-of-concept or pilot stages.</li><li>Tech companies said they built large-scale genAI capabilities, and are ready to take on projects. </li></ul>Less than a year after ChatGPT was launched, Indian tech majors have started bagging generative AI projects. Even in times when demand is slow, discretionary spends are elusive, the new-age technology is bringing work as well as excitement into the IT outsourcing market. Although the size of the deals is small at the moment, genAI has ‘captured the imagination’ of clients, say top executives of Indian IT companies. TCS and HCL Tech said that most of their <keyword id="19151325" type="General" weightage="20" keywordseo="genai-projects" source="Orion">genAI projects</keyword> are proof-of-concept or pilot stages. “Deal sizes are small and are mostly under $1 million where clients are trying them out. But there is potential to convert a part of our Jaguar Land Rover with AI and ML capabilities,” said N Ganapathy Subramaniam, COO of TCS at the company’s Q2 earnings press conference. HCL Tech’s MD C Vijayakumar too shared that most of the genAI deals they are bagging are either half a million or sub-$1 million deals. But they are currently working on a hundred such opportunities. “We have been selected as a partner by this very large software major for their product testing and sustenance efforts. We are providing GenAI on a private language model to improve resolution rate and speed efficiency,” said Vijayakumar. Infosys CEO Salil Parekh also shared that they are working on some proprietary large language models (LLMs). “AI is a part of almost every deal we do. And, GenAI is getting there. As it expands and more and larger enterprises get into it, it will be very exciting,” he added. A catalog of AI opportunities A few months back, all tech majors announced big moves in the generative AI space. Wipro announced that it will spend as much as $1 billion over three years to build capabilities. TCS, HCL Tech partnered with software major NVIDIA to skill their employees. As of September end, TCS said that they have 100,000-strong GenAI-ready workforce. They said they also have as many as 250 Gen AI opportunities in the pipeline. “When we started generative AI, they were all about knowledge discovery. As clients understand more, the genAI is getting more complicated. We are now working for a co-pilot for a financial advisor on what advice to give clients, help underwriting policies,” explaining K Krithivasan, CEO of TCS. TCS said that it has identified opportunities across various verticals, identified use cases and cataloged them per vertical. With that it says that it’s planning to go and engage with clients and have conversations on the same. “With this, we can have conversations with our clients – be in CRM or payments space and wealth advisory and other use cases,” explained Ganapathy. HCL Tech too is working on use cases related to banking and financial sector. “We signed a generative AI deal with a to improve their risk and compliance efforts – which is a very big effort in financial services. There are a lot of transactions happening on this front, and we have discussed how we can help,” said Vijayakumar. The buzz for cost optimization and automation deals has gone up in the last few months. Clients are looking to ramp down their expenses and intend to use tech to help with their overall cost reduction efforts. As automation gains ground, AI and ML will find more use cases – and most tech companies are confident that a little of it can spill into the new and emerging area of GenAI as well.

Beyond just chats: Indian tech majors start bagging deals in GenAI space

<ul class="summary-list"><li>I attended attended the World Economic Forum in Davos, Switzerland. </li><li>I had more than 20 conversations about AI over the span of four days.</li></ul>The annual <a target="_blank" href="https://www.businessinsider.com/davos-switzerland-world-economic-forum-spectacular-winter-scenery-alps-2024-1">World Economic Forum</a> just wrapped up in Davos, Switzerland, and talk of <a target="_blank" href="https://www.businessinsider.com/generative-ai-future-will-not-be-free-2024-1">artificial intelligence</a> was just about everywhere.The annual event brings together world leaders, billionaire founders, CEOs, academics, and nonprofit types to discuss the biggest topics of the day. The official WEF theme this year was rebuilding trust. And while there was plenty of discussion around changes to the global order, increasing geopolitical risk, and it being a huge election year, this was unquestionably the first <a target="_blank" href="https://www.businessinsider.com/everyone-talking-about-ai-plenty-clearly-dont-understand-davos-wef-2024-1">Davos</a> of a new AI era. Tech companies dominated the Davos Promenade, with AWS, C3.ai, Infosys, IBM, Builder.ai, Cisco, Qualcomm, Salesforce, and more paying for prominent spaces on the main street. OpenAI CEO <a target="_blank" href="https://www.businessinsider.in/tech/news/openai-ceo-sam-altman-unveils-vision-for-ais-impact-on-economy-and-society-at-wef-davos/articleshow/106978990.cms">Sam Altman</a> spoke at the event.<div type="image" title="Tata AI poster at Davos" height="1152" width="1536" msid="106999877" hostid="261"></div>I had more than 20 conversations about AI over the span of four days. Here are my takeaways:<h2>Copilots everywhere</h2><a target="_blank" href="https://www.businessinsider.com/blackrock-larry-fink-succession-boys-club-weidman-goldstein-2024-1">BlackRock</a> COO Rob Goldstein said the investing giant is rolling out AI copilots to staff, anticipating that AI will be able to produce first drafts of content such as meeting docs or primers. Jason Girzadas, the CEO of Deloitte US, said he'd just gotten trained on <a target="_blank" href="https://www.businessinsider.com/microsoft-copilot-everyday-ai-companion-paid-subscription-2024-1">Microsoft 365</a> Copilot. And the consulting firm Oliver Wyman Group created a generative-AI tool called LenAI that some users said saved them eight hours a week.<h2>Tasks versus jobs</h2>Amid lots of concern about how AI will impact the workforce (scroll down for more on that), several of those I spoke to drew a distinction between tasks, which have a narrowly defined process and outcome, and jobs, which are a collection of tasks. AI won't generally replace jobs, these people said, but it will absolutely automate tasks. Take someone who works in recruitment. Maybe their job involves paperwork, identifying and meeting with candidates, and providing strategic counsel to employers and prospective employees. The paperwork can most likely be heavily automated, potentially freeing up that recruiter for more human-to-human interactions. <h2>Big savings</h2>Deb Cupp, the president of Microsoft Americas, said in a panel discussion that the software giant saved $100 million in its customer-service operation by implementing AI. Similarly, Mihir Shukla, the CEO of Automation Anywhere, said the company cut customer-service costs by 40% while seeing improved performance since introducing AI.<h2>Workforce concerns </h2>Of course, whenever there's talk of cost savings and increased productivity, there's understandable concern that this is code for job losses. "There is an equal measure of excitement and wanting to engage with it and nervousness about what it's going to do for them and their jobs," Tanuj Kapilashrami, the chief human resources officer at Standard Chartered, said of employees and AI on one panel.A recent survey found that 51% of global executives, 50% of global CEOs, and 52% of US CEOs said <a target="_blank" href="https://www.businessinsider.com/will-ai-replace-jobs-generative-artificial-intelligence-tools-training-ceos-2024-1">job replacement</a> could be one of the effects of adopting AI in their businesses.Ana Kreacic, the chief knowledge officer at Oliver Wyman, said that in some cases, productivity was actually declining because workers were paralyzed by their fear of the technology. <h2>Reskilling</h2>That means it will be crucial to find ways to retrain workers for the human tasks that are still necessary in the AI era. At Automation Anywhere, which, as its name suggests, works on automating work, the customer-service team shrank when AI was implemented. But some of those customer-service agents found new roles at the company, either in customer success or in technical roles, based on their transferable skills. Shukla said the business world had defined roles increasingly narrowly as companies looked to industrialize their operations and scale. In the age of AI, the workforce will be more fluid, he said.Becky Frankiewicz, the chief commercial officer at ManpowerGroup, echoed this, saying the age of the static job is over, and employees will have to continually upskill and reskill in the future. This means employers should look for potential hires who are adaptable and have the ability to learn quickly rather than focus on specific skills that could soon be redundant.<h2>From small to scale</h2>If 2023 was the year of the pilot study, then 2024 will be the year of operationalizing AI, Lareina Yee, a senior partner at McKinsey, told me. Others I spoke to agreed: Many businesses have small-scale AI experiments running, often with promising results so far. The challenge is in taking that pilot and specific-use case and scaling it.<h2>Different models</h2>While "<a target="_blank" href="https://www.businessinsider.com/how-to-create-ai-materials-resources-guide-2023-9">LLM</a>" (large language model) might have been up there with WEF as the acronym of Davos 2024, many of those I spoke to stressed the difficulties with multipurpose models trained on giant datasets like OpenAI's <a target="_blank" href="https://www.businessinsider.com/openai-gpt4-ai-model-got-lazier-dumber-chatgpt-2023-7">GPT-4</a>.In many cases, the most effective AI tools, particularly for corporate use, are those that have narrowly defined purposes and have been trained or fine-tuned on exclusive, bespoke datasets. For example, McKinsey built an AI tool that's trained on the consulting firm's rich archive of PowerPoint presentations, white papers, and Excel spreadsheets and helps consultants get up to speed on specific topics more quickly."There will be different classes of models for different contexts," said Satish H.C., an EVP and cohead of delivery at Infosys.<h2>Cost</h2>Then there's the <a target="_blank" href="https://www.businessinsider.com/mark-zuckerberg-ai-flex-meta-nvidia-gpus-2024-1">cost</a> involved. These AI projects are expensive, and not every company has the financial or human capital to pursue an ambitious AI strategy. Plus, not every AI project will generate a positive return on investment, especially when factoring in not just the cost of the tech itself but the costs of changing workflows and retraining staff.<h2>Augmentation … for now </h2>There are always a few buzzwords that emerge at every Davos, and augmentation was one of those this time around. The idea is simple: Rather than replacing humans, AI will superpower them, taking on some of the most boring and repetitive tasks and freeing them up for higher-level work. "As machines get better at being machines, humans can get better at being humans," said Kapilashram from Standard Chartered.That certainly seems to be supported by the research so far. But some questioned how long that could last. <a target="_blank" href="https://www.businessinsider.com/google-deepmind-ai-could-run-businesses-in-five-years-2024-1">Mustafa Suleyman</a>, the cofounder of the AI pioneer DeepMind who now runs the startup Inflection AI, predicted that AI will be so business savvy by 2030 that it may be capable of acting like an entrepreneur, mini project manager, or inventor by manufacturing, marketing, and selling products for profit."We are going to have not just those capabilities, but those capabilities widely available for very cheap," he said. "I think that completely changes the economy."At a panel where Kapilashram was speaking, Azeem Azhar, who writes the Exponential View newsletter, noted that when AI-powered game engines emerged, the hybrid of human players plus AI outperformed for about eight years. Now, though, the AI game player wins out.Dan Vahdat, the founder and CEO of Huma Therapeutics, said that while we might think of empathy as a distinctly human characteristic, <a target="_blank" href="https://jamanetwork.com/journals/jamainternalmedicine/article-abstract/2804309">research</a> published last year showed that patients found AI chatbots to be more empathetic in their communication than medical professionals. <h2>A few final words</h2>The computer scientist Roy <a target="_blank" href="https://www.businessinsider.com/ai-stocks-enter-correction-territory-chart-analysis-2023-8">Amara</a> is often credited with first saying that we overestimate the impact of a technology in the short term and underestimate its impact in the long term. AI will likely be no different.

What the global elite are saying about AI behind closed doors

<ul><li><keyword id="15777223" type="General" weightage="100" keywordseo="generative-ai" source="Orion">Generative AI</keyword> has found applications in various fields, and the arena of life insurance operations is no exception.</li><li>In this article, we examine the potential use-cases that generative <keyword id="6355999" type="General" weightage="20" keywordseo="ai" source="Orion">AI</keyword> can have in the life <keyword id="6512638" type="General" weightage="20" keywordseo="insurance-sector" source="Orion">insurance sector</keyword>.</li><li>We also explore the various challenges in successfully implementing this technology to maximise benefits and mitigate risks.</li></ul>Generative AI is a category of artificial-intelligence (AI) procedures that involves generating <a href="https://www.infosysbpm.com/offerings/functions/digital-business-services/service-offerings/marketing-operations/case-studies/documents/putting-content-back-on-the-throne.pdf">new content</a>, such as images, text, or audio using models and examples learned from existing data. One of the most widely known generative AI models is the Generative Adversarial Network (GAN), introduced in 2014 by Ian Goodfellow and his team. Another advanced type is Large language models (LLMs) that help in constructing pre-trained transformer platforms. LLMs are a game-changer for the insurance industry and have enormous possibilities. They can analyse extensive written material and information effectively. They can also help automate complex business processes that deal with natural language. <cmsannotation type="cmsannotation" annotationid="Reshaping life insurance operations" comment="subhead" text="Reshaping life insurance operations">Reshaping life insurance operations</cmsannotation> Generative AI has found applications in various fields. For example, it can be used to create realistic images, generate text or speech that mimics human language, enhance, and manipulate images, create virtual characters or environments, and even aid in drug discovery and molecule design. Nonetheless, it does raise ethical concerns, as it has the potential to generate realistic but fake content, such as deepfake videos or fabricated news articles. Ensuring responsible and ethical use of generative AI is a vital aspect that needs to be addressed as this technology continues to advance. Generative AI can have several potential use cases in life insurance operations. Here are a few examples: <ol><li>Synthetic customer data generation: Generative AI can be used to create synthetic customer data that resembles real policyholders. This data can be utilised for testing and training purposes without compromising the privacy and security of actual customer information. </li><li>Risk assessment: By analysing large volumes of historical data, generative AI models can learn patterns and generate simulated scenarios to assess risk. This can help insurers in predicting and quantifying potential risks associated with policyholders and their life situations. </li><li>Underwriting and policy generation: Generative AI can aid in automating the underwriting process by analysing customer information and generating policy terms and conditions based on predefined rules and regulations. This can streamline the policy generation process and reduce manual efforts. </li><li>Fraud detection: Generative AI models could be trained on a dataset of known fraudulent activities and generate synthetic fraud scenarios. These scenarios can help insurance companies in enhancing their fraud detection capabilities by identifying patterns and indicators of potential fraud. </li><li>Customer experience enhancement: Generative AI can be used to create personalised marketing materials, such as tailored policy offers and customer communications. By analysing customer preferences and historical data, generative AI can generate content that resonates with individual policyholders, improving their overall experience. </li><li>Predictive analytics: By generating synthetic data and simulating various scenarios, generative AI can assist insurers in predicting customer behaviours, such as lapse rates, premium payment patterns, and customer churn. These insights enable strategic decision-making and help in developing more effective retention and customer engagement strategies. </li></ol><cmsannotation type="cmsannotation" annotationid="Need to proceed with caution!" comment="subhead" text="Need to proceed with caution!">Need to proceed with caution!</cmsannotation> It is important to note that the implementation of generative AI in life insurance operations requires careful consideration of ethical and regulatory implications, as well as the protection of customer privacy. The responsible and transparent use of generative AI is indispensable to ensure its <a href="https://www.infosysbpm.com/dis/streamlined-digital-advertising-operations/documents/digital-interactive-services.pdf">benefits</a> are maximised while mitigating potential risks. Implementing generative AI in life insurance operations can pose several challenges such as: <ol><li>Data availability and quality: Generative AI models require large volumes of high-quality data for training. Obtaining relevant and representative data can be challenging, especially in the case of life insurance where sensitive and personal information is involved. Ensuring data privacy, compliance with regulations, and data quality can cause significant hurdles. </li><li>Ethical and legal implications: Generative AI can create synthetic data or content that closely resembles real individuals or situations. This raises ethical concerns and legal implications, especially in terms of privacy, consent, and potential misuse. Ensuring that the generated content is used responsibly and following legal and regulatory frameworks is vital. </li><li>Interpretability and clarity: Generative AI models are often complex and difficult to interpret. Understanding the decision-making process of these models and providing explanations for the generated outputs can be challenging. In the insurance industry, where transparency and clarity are important, ensuring that generative AI models can provide clear justifications for their outputs is crucial. </li><li>Bias and fairness: Generative AI models can inadvertently get influenced by biases present in the training data, which can lead to unfair/biased outcomes. It is essential to address and mitigate biases in the generative AI models to ensure equitable treatment of policyholders in life insurance, where fairness and non-discrimination are critical. </li><li>Regulatory compliance: Life insurance is subject to various regulatory frameworks, including data protection, privacy, and fairness regulations. Implementing generative AI while complying with these regulations can be complex. Insurers need to ensure that their generative AI systems meet the necessary compliance requirements and adhere to industry standards. </li><li>Integration and adoption: Integrating generative AI into existing life insurance operations can be challenging. It requires infrastructure and system updates, as well as training and upskilling employees to work effectively with generative AI technologies. Ensuring a smooth integration process and fostering organisational adoption can be a significant undertaking. </li><li>Continual model improvement: Generative AI models require continual monitoring and improvement to ensure their effectiveness and performance. Regular updates, retraining, and fine-tuning are necessary to adapt to evolving data patterns and business requirements. Establishing processes for ongoing model maintenance and improvement is essential. </li></ol>To tackle these obstacles, a collaborative approach involving data scientists, domain experts, legal professionals, and compliance officers is essential. It is imperative to prioritise ethical considerations, regulatory compliance, and transparency when implementing generative AI in life insurance operations. Disclaimer: This article is authored by Neeraj Kaushik, Principal Consultant, Infosys McCamish and Chuck Johnson, Principal Product Architect, Infosys McCamish. The opinions expressed are those of the author and do not necessarily reflect the views of Business Insider India.

Generative AI: The next big leap in transforming life insurance operations

<ul><li>Legal research helps determine the steps required to answer legal queries and helps to form a sound base for legal decision-making.</li><li>Many law firms and in-house legal teams are earning profits by opting for automated legal research solutions powered by modern technological solutions.</li><li>This article explores the key elements required to construct a solid foundation for any <keyword id="6137671" type="General" weightage="20" keywordseo="legal-practice" source="Orion">legal practice</keyword> and the important steps to conduct proper legal research.</li></ul>Building capabilities is essential for any organisation to thrive, and the legal sector is no exception. To achieve consistent performance, legal practices must integrate their people, processes and technology efficiently. One crucial aspect of this integration is legal research, which serves as the foundation for making informed legal decisions and providing valuable insights for cases. In a broad sense, any research is a methodical quest for the collection, categorisation, and analysis of the right information. This holds true particularly for legal research, as answering legal questions correctly helps to form a sound base for <a href="https://www.infosysbpm.com/offerings/functions/legal-process-outsourcing/case-studies/documents/winning-back-a-lost-cause.pdf">legal decision-making</a>. <h2 style="line-height:1.295;text-align: justify;margin-top:2pt;margin-bottom:0pt;">Understanding legal research</h2>As a legal professional, it is a lawyer’s duty to understand the distinctions within the law and have the capability to interpret legal precedents. Legal research is the method to first determine the steps required to answer the legal query and then follow the process to collect relevant data to answer those questions. This entire process makes legal research an integral part of the legal profession and an essential skill to have when working on any type of case. It may sound simple, but legal research is quite demanding and requires not only an in-depth knowledge of the law but also a good grasp of information analysis. Organisations are building this capability so that it can be leveraged as a managed service offering to make the legal research process more efficient, both in terms of time and cost. This way, many law firms and in-house legal teams are earning profits by opting for automated legal research solutions powered by predictive analytics to provide cutting-edge solutions and using their domain expertise to help lawyers. <h2 style="line-height:1.295;text-align: justify;margin-top:2pt;margin-bottom:0pt;">Constructing a solid foundation for your legal practice</h2>Legal research is not an optional or incidental part of the process but a necessity before starting work on any legal matter. Commonly, any legal practice will search for primary and secondary sources of legal information, irrespective of jurisdiction and subject matter. The two information sources of legal research — primary law (focusing on case law, status, and regulations) and secondary sources (explaining the legal theory, such as treaties, journals, and digests, etc.) — are the stepping stones in identifying key facts, legal arguments, and doctrines relevant to the issue at hand. In addition, legal research provides a comprehensive understanding of any legal issues using the following methods. <ul><li>Analysing the law by breaking it into separate elements, simplifies understanding and the interpretation of specific statutes and cases.</li><li>Forming coherent legal standards by blending distinct elements of different cases and statutes, justifying specific legal decisions which may be very useful in building an argument.</li><li>Breaking down doctrinal issues and advising legal professionals or clients about the application of legal theories in specific cases, or criticising judicial opinions and resolving conflicts based on legal doctrine.</li><li>Curating teaching material for legal professionals and students to help them understand legal theories, doctrine, statutes, and case laws.</li><li>Arguing for improvements in legal practices and examining crucial legal doctrines from the perspective of economics, sociology, politics, and other sciences.</li><li>Leveraging AI/automation to access, analyse and apply legal information and augment the process.</li></ul>And with these, legal research offers benefits to legal professionals as well through: <ul><li>Fact-finding: Providing comprehensive knowledge about cases, including all the facts and evidence of the case before the authority and the jury.</li><li>Understanding key issues: Simplifying issues by eliminating unnecessary or irrelevant data and allowing focus on core facts to argue the matter at hand.</li><li>Finding answers: Getting accurate answers to understand the whole issue with the concerned authority and developing a strategy to effectively counter any arguments.</li><li>Value add: Providing more value when presenting case evidence and other details in front of the concerned authority while interpreting the underlying legal theory and precedent that supports the argument.</li></ul>Fundamentally, legal research ensures better clarity on any issue and anticipates different arguments that may come up in court. <h2 style="line-height:1.295;text-align: justify;margin-top:2pt;margin-bottom:0pt;">Steps to successfully execute legal research</h2>Legal research is a comprehensive process; and here are a few things to consider while undertaking legal research: <ul><li>Understanding the issue: It is critical to be cognizant of the issue under consideration to better evaluate the core details and supporting information uncovered during legal research.</li><li>Recognising the primary and secondary sources: Primary and secondary sources of research must be correctly identified to generate a cohesive representation of the collected information.</li><li>Evaluating information: The knowledge of the issue at hand and the information collected from both sources must be aligned to evaluate accuracy.</li><li>Selecting core information: <a href="https://www.infosysbpm.com/offerings/functions/legal-process-outsourcing/case-studies/documents/beating-the-clock-and-securing-data.pdf">Data collected</a> is evaluated and the findings are used to build well-researched legal arguments and an informed strategy that incorporates core details with supporting background information.</li><li>Studying deviations: It is important to study deviations from the norm to understand potential counterpoints and prepare strong arguments to support the required issue. </li></ul>It is time-consuming to follow these steps manually and there may also be ancillary costs to accessing reliable data sources, which is one of the key reasons prompting modern law firms to consider outsourcing legal research. With the intervention of modern technological solutions such as automation, artificial intelligence, machine learning, and cloud-based services, legal research is now easier, faster, and cost-efficient, resulting in its emergence as a promising service line in the legal managed services space. By harnessing the power of technology and following best practices, legal professionals can conduct effective research, leading to better decision making and improved client representation. In this rapidly evolving legal landscape, organisations that prioritise legal research can thus gain advantage and stay ahead in delivering better services. Disclaimer: This article is authored by <keyword id="147098" type="General" weightage="80" keywordseo="sunil-nair" source="Orion">Sunil Nair</keyword>, Solution Design Head (Legal), <keyword id="6079860" type="General" weightage="80" keywordseo="infosys-bpm" source="Orion">Infosys BPM</keyword> and <keyword id="18151668" type="General" weightage="80" keywordseo="debshikha-dutta" source="Orion">Debshikha Dutta</keyword>, Sr. Practice Lead (Legal), Infosys BPM. The opinions expressed are those of the author and do not necessarily reflect the views of Business Insider India.

Strengthening your legal practice: How advanced research tools are changing the game

<ul><li>Robotic Process Automation (<keyword id="842249" type="General" weightage="20" keywordseo="RPA" source="Orion">RPA</keyword>) continues to have significant business relevance to automate repetitive daily tasks and boost efficiency and performance.</li><li>In the workplace of the future, RPA continues to evolve and adapt to meet the changing needs of businesses.</li><li>The deployment of RPA-based intelligent tools gives businesses access to crucial insights and allows them to focus on the end goal by simplifying business processes.</li></ul>There is no getting around the fact that future workplaces will witness an increase in the mix of humans and robots working side-by-side. We are, however, not talking about physical robots. The robots we are referring to here are robotic process automation (RPA) <a href="https://www.infosysbpm.com/offerings/functions/customer-service-outsourcing/case-studies/documents/when-the-going-got-tough-the-bots-got-going.pdf">bots</a> that can interact with computer systems, the same way human employees would, to complete certain tasks efficiently and swiftly without human intervention. The incorporation of RPA into an organisation’s standard operating procedures will continue to be a critical technology to boost productivity, reduce costs, and complete tedious, repetitive tasks accurately and rapidly. <h2>What exactly is RPA?</h2>In simplest terms, RPA is the use of modern technology and software to automate rule-based business processes. Process-centric organisations can benefit greatly from incorporating RPA to take over various tasks. <a href="https://www.infosysbpm.com/blogs/robotic-process-automation/how-robotic-process-automation-simplifies-processes-and-boosts-efficiency.html">RPA boosts overall efficiency</a>, improves workflows, and frees employees to take on higher-value tasks. Once a bot observes a human worker and records the process workflow, it completes rules-based tasks. It can mimic the way workers interact with their computer systems to take over these actions. Once implemented, these bots can log into systems, input or extract data as needed, navigate pages, and a lot more. Employees at most modern workplaces spend hours daily on repetitive computer tasks that can be easily automated. RPA can complete these tasks in a matter of seconds, saving a great deal of time and enabling these employees to be much more productive. And increasingly, RPA bots are integrating with AI and Machine Learning solutions, intelligent data extraction solutions, and other emerging digital solutions to drive greater efficiencies at the workplace by automating more complex tasks. These technologies aid in process simplification by allowing users to focus on the ultimate goal rather than the steps used to achieve it. Let’s take a look at some tasks that are perfectly suited to RPA in this context: <ul><li>Workload prioritisation: A considerable amount of time is spent on sorting workload and prioritising tasks based on importance and urgency to meet SLAs. RPA embedded in platforms or independently coupled with AI/ML can eliminate or significantly reduce effort in this time-consuming process by presenting workers with an organised workload, lining the important tasks in the order, and flagging the ones requiring immediate action on top. </li></ul> <ul><li>Report Generation: RPA can <a href="https://www.infosysbpm.com/offerings/industries/healthcare/case-studies/documents/dashing-towards-the-finishing-line-with-claims-automation.pdf">automate</a> a reporting function by compiling required data from multiple sources to generate reports in required formats. Compilation of reports can be performed using external as well as internal organisational data to provide real-time information to aid decision-making. It can also collate data in different formats into a single, standardised report. </li></ul> <ul><li>Data entry: The oldest use case of RPA is data entry and still relevant. As the technical landscape of organisations gets more complex, employees spend a lot of time extracting and compiling data from various sources in the interim-stage before large scale ERP or applications transformation takes place. RPA can effectively support data entry into systems, exchange of data between systems and when integrated with intelligent OCR solutions speeds up the process further by extracting data from scanned documents, images, or PDFs for entry into financial systems. </li></ul> <ul><li>Accounting duties: Automating simple financial duties can save a lot of time and effort for the accounts department while completely eliminating human error. RPA bots can create expense reports, match invoices to purchase orders, perform basic reconciliations of statements, and perform several other basic accounting processes. RPA benefits from integrating with AI/ML solutions in this area.</li></ul> <ul><li>HR duties: RPA can take over several time-consuming HR department duties, such as ordering business cards, acquiring security access, or assigning workspaces to new employees. It can also process employee benefit forms, make payroll updates, and handle employee exit procedures. With RPA handling these various back-office HR duties, HR staff can focus on more important tasks that demand critical thinking, human interaction, and faster decision-making. </li></ul> <ul><li>Customer service: RPA can streamline the customer service workflow in various ways, including scanning reviews, identifying complaints, updating customer details, chatbot integration for auto-response, and various other tasks that customer service representatives spend a lot of time on. RPA can also perform monitoring of customer service infrastructure by performing diagnostics and self-heal tasks.</li></ul>The incorporation of RPA into an organisation’s various processes will continue to revolutionise workplaces in the future. RPA bots take seconds to complete tasks that would take several man-hours and eliminate the possibility of errors in the process. This enables organisations to easily scale up or down to handle changing business needs and workloads, enabling businesses to be more responsive to market demands. Handing over tasks to RPA also allows employees to focus on duties that demand creativity, strategy, problem-solving, and other skills that software doesn’t possess. This helps improve data accuracy and security by reducing the <a href="https://www.infosysbpm.com/offerings/industries/financial-services/documents/customer-disputes-and-risks-robots-to-the-rescue.pdf">risk</a> of human error and ensuring compliance with data protection regulations. While RPA may not be the only technology being used for automation, it still has many advantages, including a relatively low cost of implementation, ease of use, and the ability to work with a wide variety of applications and systems. So, as RPA faces competition from other technologies in the market, it is still a valuable tool in the automation toolkit. RPA will continue to be relevant in the future, and the sooner businesses adopt this technology, the sooner they will see improved performance and ROI, ensuring long-term sustainability. Disclaimer: This article is authored by <keyword id="697772" type="General" weightage="50" keywordseo="vikramjit-singh" source="Orion">Vikramjit Singh</keyword>, Practice Engagement Manager, <keyword id="6744928" type="General" weightage="20" keywordseo="digital-transformation-solutions" source="Orion">Digital Transformation Solutions</keyword>, <keyword id="6079860" type="General" weightage="20" keywordseo="infosys-bpm" source="Orion">Infosys BPM</keyword>. The opinions expressed are those of the author and do not necessarily reflect the views of Business Insider India.

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