India must move from consuming to creating talent: Accenture India head

What is your assessment of where we stand in the AI-driven technology evolution, and how is it translating into real-world impact?

 In my view, there are three phases in any technological evolution. The first one is invention. With Gen AI in 2022, the invention came… The next phase is innovation, which is what we are going through right now. Innovation means how industries adopt and personalize it for greater efficiency and gain. The third phase will be diffusion. When you’ve got your invention, and you know how you will use it at scale. That’s the internet moment! While we are still a few years away from that, we are working closely with our clients to identify strategic bets to drive competitiveness, reinvent their core business processes, enhance cost optimization, and identify innovative new growth models through AI-led reinvention. 

A lot of companies are yet to figure out what to do with AI. What are companies who are leading with AI doing differently?

Different companies are at different stages. We believe this is also a stage of evolution. You need to understand the product, and you need to get educated and you need to experiment. You may fail in some, but in the process, you also learn. Those who are leading the AI race right now are those who are taking a holistic approach.

What is the number one challenge for the IT industry?

Skilling at scale is the biggest challenge and an opportunity that we need to solve. Traditional academic pathways alone can no longer meet evolving needs of India. This requires the trifecta of government, industry and academia to collaborate for a scalable, inclusive skilling ecosystem.

As an industry, we really need to move away from being just consumers of talent and become creators of talent.

Is the industry doing enough to develop skillsets to take advantage of the AI opportunity?

In today’s AI environment, every company is looking to invest in building their people’s capabilities. For us, building relevant data and AI skills is a top priority. Almost 500,000 of our employees globally are trained to use Gen AI. We have also increased our data and AI workforce to approximately 75,000 against our goal of 80,000 by the end of FY 2026.

Additionally, employees today are more aspirational. It is no longer about one big bang skill. Rather, it is about having a constant learning loop to stay competitive in a dynamic environment. On the other hand, clients recognize that people are at the centre of data and AI-led reinvention. Through LearnVantage, our technology learning and training services, we are helping our clients reskill and upskill their people to reinvent their organization in an AI-led economy. We acquired Udacity and, more recently, TalentSprint to expand our LearnVantage capabilities to offer learning programs to emerging and experienced professionals in the industry. Our intent is to be a leading learning and skilling player in the industry.

How is Accenture looking at India now in terms of people and talent?

 India is a global talent and innovation hub for Accenture with over 350,000 people driving innovation for clients across multiple industries in India and across the world. The talent, creativity and passion of our people lies at the heart of our success. We take an intentional approach to skilling, combine their skills with new technologies and ways of working to create value and drive innovation at scale every day.

Are engineering institutes keeping pace in equipping students with the skills needed for AI-related jobs?

 For basic talent, yes, but for client readiness it needs to be more and relevant. And that’s where the trinity of government, industry, and academia needs to come together . My personal view on this is that we need more osmosis between industry and academia- where professors come and spend a few months with industry and industry leaders go and teach at the institutes to infuse ‘corporate’ readiness into academic learning.  

Will IT services companies like Accenture build their own LLM models?

As companies move beyond experimentation to scale, they are looking to adopt generative AI to reinvent their business and tap new avenues for growth. The rapid expansion of AI systems and large language models has created a complex landscape where each model presents unique tradeoffs in performance, cost, and speed. Our proprietary “switchboard” allows users to do just that by offering a combination of models – Small Language Model, Large Language Model, and classical AI models to address their business needs.  We believe that there is no one size fits all, and to fully harness the AI opportunity, customization and combination of LLM models will be required – one that addresses the unique needs of companies based on each of their business requirements or processes and other criteria such as cost, accuracy among other things.

Should India build its own LLM model?

 India, with its vast and diverse population, rich linguistic heritage, and growing digital economy, could certainly benefit from a large language model. But what we really need to be thinking about is a Cognitive Digital Brain...one that is far more comprehensive as it goes beyond just language processing.