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“The fact that AI is a transformational and disruptive technology, and has the power to change the working of enterprise fundamentally, is no news.
To reap the benefits of AI, the talent management practices and HR practices need to transform first, fast, and drastically, says Tapati Bandopadhyay, Vice President – Research, HFS Research.
Which industries do you see as the biggest beneficiaries of AI adoption?
Most of the surveys including our own on AI-ML and intelligent automation adoption [applied AI- Analytics-Automation: The HFS Triple-A Trifecta] show that –
▸ Banking, Financial Services, Insurance;
▸ Media, Telecommunications & High-tech Industries;
▸ Retail & CPG
▸ Healthcare Sectors
are seeing scaling up of investments in AI given the early adopters showing good RoI as well as disruptive and transformational business impact and competitive advantages. Next in line is new age manufacturing esp. ones that leverage IoT and industry 4.0 technologies and practices.
On the contrary, public sector and education are the two sectors where adoption has been late, slow, and conservative.
With AI and automation in the disruptor’s seat, do you feel this disruption bump free?
No disruption is bump-free, and in case of AI and automation, the bumps are often unanticipated, unseen, uncertain, and under-estimated. The biggest bump, for example, is a technology-first approach towards adoption of AI & automation whereas, the real issues on ground are much more to do with firstly, people, organizational change management & culture shifts than technical finesse or marvelous algorithms, and secondly, lack of an end-to-end process view while adopting AI and automation, given most of the early efforts have gone into focusing on specific technology stacks and isolated tasks, thereby creating siloes and consequently & often inadvertently creating new performance bottlenecks & resource constraints across the process chains.
AI comes with its challenges – including lack of skills as fast as they are needed. How do you think enterprises can meet the topmost challenges that technology poses?
The talent management practices and HR practices need to transform first, fast, and drastically. HFS has a lot of published research on how to handle this AI talent crunch.
Key ideas are:
▸To look at unusual places for AI talent, e.g. not assuming everyone has to be coding experts and appreciating the needs and importance of business and functional domain knowledge and skills especially for low-code/ no-code AI -analytics-automation implementations, e.g., application of AutoML.
▸To change an organization’s view on sourcing talents, e.g. instead of expecting these high-demand to come to the company, the company goes to the common talent pools like crowdsourcing platforms.
▸To create massive but simple reskilling modules which can make AI palatable for business users, and granting ubiquitous access to those modules and incentivizing anyone who shows the willingness as well as awareness of staying relevant with these skills.
“No disruption is bump-free, and in case of AI and automation, the bumps are often unanticipated, unseen, uncertain, and under-estimated.”
Tapati Bandopadhyay, Vice President – Research, HFS Research.
Tapati Bandopadhyay is Vice President, Research at HFS, with over 20 years’ experience in technology strategy, consulting, and advisory on Artificial Intelligence, Analytics, Automation, DevOps, and services management. She is based out of the HFS India office in Bangalore.
A PhD in AI, gold medallist in engineering and a DFID scholar at Strathclyde, she started her career with Tata Motors and then at GEC Glasgow, where she built their first Expert System.