Recently, we interviewed
Artificial Intelligence: “Up-placement” of Jobs instead of “Replacements”
What's to come should be a brilliant spot where robot butlers take into account our each need and the four-hour work day is a reality. Be that as it may, the genuine picture could be much bleaker. Top researchers have cautioned that the ascent of AI and robots in the work spot could bring about mass unemployment and dislocated economies, rather than unlocking productivity gains and liberating every one of us up to sit in front of the TV and play sports.
But that could be just a hype, Kalyan said, “It would be more of an up-placement of jobs than replacements. Organizations may need to redesign tasks, jobs, management practices, and performance goals when they implement AI technologies. These technologies may be used to upskill jobs or curtail growth in staffing levels. They may also be used to automate specific tasks, changing how workers allocate their time and require them to interact with systems in new ways.”
He further added, “Workers may spend less time performing routine tasks, handling only exceptional cases and spending more time focusing on work that requires high-end involvement. For all these reasons, we believe AI technology deployments are different from traditional IT deployments and their impact on organizations requires greater thought. We see the whole approach as evolutionary.”
Induction of AI in companies
Many companies are adapting Artificial intelligence in their processes (both internal and external) and facing a hell lot of problems. When asked, Kalyan said “Highly customized or innovative applications, such as automating the screening of patients for clinical trials or the provision of financial and legal advice, are closer to research projects and are evolving than large scale systems integration projects. These will involve unpredictable efforts.”
He wasn’t wrong when he pointed one of the biggest needs of the hour “Shortage of technical talent.” He stated that demand for knowledge in some AI technologies, such as machine learning, computer vision, natural language processing, speech recognition, image analysis, etc. has seen an upsurge in contemporary years. Knowledge of quickly altering landscape of cognitive technology vendors is likely to be in short supply. Organizations may tussle to staff teams with the talent required to pilot and build systems using these technologies
Recently HCL introduced
What is it all about?
DRYiCE Autonomics platform is made up of 40+ components, it consists of a well-proven Monitoring layer (MTaaS), Machine learning components (on proven supercomputing systems), Automation Modules, Orchestration components, Knowledge Management and a Reporting layer - all tied together in a real pragmatic IT service management (ITSM) based framework - the