How Reskilling the Workforce for AI Takes On a New Urgency
No matter how optimum an organization's artificial intelligence (AI) initiatives may be, there is always an ever growing need and concern for better retraining, up skilling and technocratic expertise development. This is done with an essential objective to significantly add value to the business.
In a recent global survey of more than 5,000 executives, IBM finds that skills deficiency is the number-one plaguing challenge to move forward with AI and its platform.
Yes we agree that AI will launch many new careers. But there are lacunas that need addressal in short term and long term basis. In fact IBM has been investing heavily in efforts to develop a skilled workforce ready to help employers embrace opportunities in AI, says Beth Smith, general manager of Watson Core.
We observed in a panel discussion in the recently concluded Bangalore Tech Summit 2018 on ‘Skilling Strategies for Emerging Economies’ that in general, 94% of companies actually see that AI can bring them competitive advantage.
But the interesting thing is that only 1 in 20 enterprises have extensively incorporated AI into their businesses on a day to day basis. Along with skills shortage the other elements are data trust, compliance and data quality which acts as chief barriers to the downfall of AI in an enterprise adds Joseph Jayakumar, Director Amstar Technologies and IT thought leader at the Bangalore Tech Summit 2018.
The need for updated AI skills and the contextual ability to redesign all types of jobs around it is being reshaped. It is an amazing scenario. However the “The Impetus for Reskilling for AI needs to happen now and not later in 2019." Else skill mapping and implementation will become a tedious process if not planned creating a hurdle for stakeholders and concerns across verticals.
Lastly the need for a skilled and trained workforce extends well beyond data science skills. It ultimately affects just about every job role in one way or another. "Everybody will be able to get involved with AI and there will be a spectrum of roles."
A conversational analyst, for example, would focus on analyzing the data generated through conversational exchanges between the virtual agents and their customers and this is where reskilling across platforms becomes necessary wherein we can offer our best assistance extensively.
AI is another pioneering advancement in automation. AI systems can easily be taught to do mundane tasks which can help professionals to focus their time better and expertise on innovation. Yes AI is a different kind of data with a different way of thinking. But it will also help to serve and liberate many other job roles. Not just this it will also open up further niche roles in innovation, research and development in the years to come.
Looking for a Complimentary AI Reskilling Audit? Get in touch with Amstar today
Sincere Thanks to Moderators and Panelists for an enriching talk on the topic.