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Pallavi: Hello, this is Pallavi, welcoming you to a new episode of the EY India Insights Podcast where we look at the role of Generative AI in shaping the workforce of the future. We have Alpana Dutta from EY India joining me. Alpana is a PAS (People Advisory Services) Partner at EY India with over 20 years of experience. She is also the EMEIA leader of culture, leadership and people experience, and is deeply involved in shaping the latest thinking in this space for clients across the globe. She works with clients across industries and sectors to enable them in deriving maximum value through their people strategy.

Hi Alpana, welcome to our podcast.

Alpana: Thank you Pallavi, very glad to be here. 

Pallavi: Alpana, technology adoption is typically seen as a phenomenon that improves efficiency, but also reduces jobs. With AI, earlier programs could spot patterns, but still needed humans for the eventual output. Generative AI, with its power to create content, can actually take over that function too. So, what kind of jobs are now under threat as Generative AI evolves further? We already see coders and writers being threatened.

Alpana: Absolutely, we can see the potential impact of Generative AI on a wide variety of jobs across functions and industries. Let me give a few examples. Tech roles are not limited to the tech industry; they are now an integral part of every sector. Jobs in the information processing industry, if I may say, are very exposed. Jobs that use programming and writing skills are quite closely related to Generative AI’s capability. Roles such as (that of) software developers, especially for code generation, testing and optimization; jobs like QA testers for regression, integration and load testing; blockchain engineers; IT support and network administrators… all of these are susceptible.

Similarly, if we were to look at financial services, AI could potentially monitor transactions to give detailed financial advice on saving and spending. So, jobs like financial or quantitative analysts, tax preparers, investment analysts, credit analysts, compliance officers, even customer care and communication managers, accountants, risk and compliance officers, marketing executives, all of these could get impacted.

In legal services, AI bots have the potential to address what we call ‘access to justice’ questions and make legal services available to a much larger mass. They can read and interpret contracts faster and more accurately, thereby looking at jobs of, say, documentary viewers, legal researchers, contract drafters, due diligence analysts, compliance officers.

If I were to give one more example of a very different industry, I would say think about media and marketing. News can be written by machines. Publishers could translate into a digital-only business with Generative AI, and they could rely on it to personalize content or enhance quizzes so jobs of news writers, content writers, public relations specialists, interpreters and translators could get significantly impacted.

One could pick any industry and do this analysis, which means that organizations are at a stage where if they are not thinking about the potential impact of Generative AI on jobs, they could be putting themselves at a very massive risk.

Pallavi: Thank you for those insights, Alpana. Now, technology adoption also creates new jobs. We see that Generative AI will be no different. But what kind of jobs would Generative AI create?

Alpana: Just as some jobs are at a threat, like we just discussed, a lot of new jobs are also getting created and no prizes for guessing that a lot of them are in and around new tech. Some examples would include jobs like prompt engineering – professionals who can design and refine prompts to interact with language models like Chat GPT effectively; AI trainers and explainers to be able to explain the use of Generative AI in business; AI ethics specialists and AI auditors – professionals who will need to focus on addressing ethical considerations related to AI to enable more fairness, transparency and privacy; AI UX designers will be responsible for designing intuitive and user-friendly interfaces that enable effective interaction and collaboration between humans and Generative AI systems, because that is really a new field altogether.

Jobs such as data curators, AI security specialists, digital twin engineers, which I thought were really interesting – (they are) engineers who will be responsible for creating and maintaining digital twin models for various applications. These could be in manufacturing, logistics, healthcare. Jobs which would require AI policy and governance-related matters; experts in that field who will develop legal frameworks, standards and guidelines for ethical use and governance of Generative AI across industry. Jobs such as AI augmented creatives. We know that Generative AI can be used to augment creativity in various fields such as art, music, or writing, so AI augmented creatives will need to possess both artistic and technical skills to leverage AI tools to enhance their work.

Other jobs could be those such as research scientists in Generative AI, machine managers, human-AI collaboration, and interaction designers. I would say it is a whole new segment of jobs that are getting created, which are a combination of the creatives and of the sciences, which could be really interesting to a lot of the next gen.

But I also do want to say that all of this is one side of the story. With this change in roles and skills and jobs, there will also be a need to change leadership and behavioral skills. And we are already seeing organizations focusing on building leaders who will demonstrate more change and disruption readiness, more ambidexterity, mindfulness, empathy, and the ability to work with global teams, which could be a combination of virtual and physical workers. All of these will also have an impact on the kind of roles that would become very important for success in the future.

Pallavi: That is really interesting. One of the things that have excited people is Generative AI’s ability to train students and others. How will this change the workforce?

Alpana: Yes, of course, students are the largest supply pool for our workforce, but when you think of the word ‘student’, I would encourage everybody not to be confused and think only about the 18- or the 20-year-olds. We are also seeing so many executives going back to learn at various points in time in their career. If I was to think about the term ‘student’ more broadly, Generative AI has a huge role to play in improving both the quantity and the quality of well-educated students. These could be students who are just about starting their career, or executives who have become students for certain parts of their career in order to refresh their learning and come back into the corporate world.

You would also be aware that some ed-tech organizations and some schools are already well ahead on this path. But if I was to throw some light on how, we see them using AI to create enhanced learning material, content, and personalized learning that caters to individual student’s needs and interests.

They are using Generative AI for improved training, intelligent tutoring systems, focused and personalized guidance and instant feedback. This means I really do not need to wait to get feedback on what I am understanding or not understanding; it just helps the student better understand complex concepts, which improves their learning experience.

Some are getting into adaptive learning platforms and creating learning pathways that work for each student so that their pace and their interests are really taken care of. They are using Generative AI for more collaboration and creativity, which can help in better ideation and brainstorming.

In my view, the other very big use case where Generative AI is being used is for effective translation, which means that students can learn without any language barrier. Imagine what that could do to rural India or to under-represented parts of the world. One could even stretch this to say that it will create a much more equitable and inclusive environment for students.

Now, if we were to think about this from the employer’s perspective, the implication is that they need to think about a few things. Employers need to play an active role in creating the supply pool through industry plus academia partnership. And we are already seeing some organizations creating very niche collaboration courses in universities to make sure that the supply is as needed. Otherwise, there just might be a huge demand-supply gap that only keeps increasing with time.

The other thing that employers need to do is to enable more awareness and continuous learning for their existing workforce. This is so that the workforce does not become outdated and also actively works through proofs of concept (PoCs) to apply the potential of generating AI into their domain of work and create use cases that they can leverage. So, more exploration, experimentation and active learning so that the workforce is also constantly rejuvenating itself and is able to rise to the potential of Generative AI in organizations.

Pallavi: Thank you, Alpana. We see that Generative AI has huge potential. People have already started using it to write better résumés and cover letters and even prepare for interviews. How are your HR managers dealing with this?

Alpana: That is true, but I would say writing résumés is only one part of the game. When we test or interview a candidate, if we do a good job of deep diving to discover the true experiences, I think we should be fine. But of course, employers need to constantly be at it to remain at the top of the game.

I would also think of this in another way. Just as employees are getting smarter by using Generative AI, employers also need to and can get much smarter by using Generative AI to discover better candidates, to create more nuanced success profiles, and to separate the wheat from the chaff. Better search and match; better due diligence on CVs using information that may be widely available on each person through their digital footprint; better pre-employment assessments, better interview assessment and assistance.

We could also look at employers getting into predictive analytics. I also firmly believe that if used correctly – and that is a very big if, because we have to also make sure that Generative AI is not trusted blindly till it matures more – it could have the potential of improving diversity, equity and inclusion (DEI). We could look at removing human biases and focusing on more objective criteria.

AI algorithms can actually help identify better candidates based on their skills and qualifications, which would then promote more unbiased hiring practices. It (Generative AI) is as available to employers as it is to employees, and hence, there would become a level playing field shortly.

Pallavi: That is great to hear and thank you for all those valuable insights. I hope our listeners have got a complete and detailed analysis of Generative AI.

With this, we come to the end of this episode. Visit our website www.ey.com/in to know more about Generative AI in the workforce and do leave us comments on other such topics on Generative AI that you would like us to deep dive into. Signing off now. Thanks for listening in.

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