EY helps clients create long-term value for all stakeholders. Enabled by data and technology, our services and solutions provide trust through assurance and help clients transform, grow and operate.
At EY, our purpose is building a better working world. The insights and services we provide help to create long-term value for clients, people and society, and to build trust in the capital markets.
Jubilant Ingrevia’s CFO shares how the finance function uses data and AI to improve pricing, forecasting and decision-making in a regulated, tech-driven environment.
The discussion covers the foundation needed to unlock GenAI, including unified data platforms and disciplined processes. The speakers outline early use cases such as commodity price prediction, scenario planning and S&OP, along with improvements in forecasting and P&L prediction.
Key takeaways
Integrated data systems are important for meaningful GenAI adoption and reliable predictive models.
Practical AI use cases emerging in finance and specialty chemicals include price forecasting, scenario modeling and sales and operations planning.
Effective AI deployment requires strong governance, cybersecurity preparedness and continued human oversight.
CFOs should start with focused pilots, invest in people capability, monitor ROI strictly and scale AI initiatives with discipline.
The finance function has to bring real‑time visibility — predicting price movements, modeling sensitivities and guiding decisions that directly shape enterprise value.
Varun Gupta
Chief Financial Officer, Jubilant Ingrevia
CFOs who make a real impact are those moving from performance reporting to strategy execution and becoming strong champions of technology adoption.
Abhinav Johri
Partner, Technology Consulting, EY India
Host
Sardul Seth
Partner and CHS Consulting leader, EY India
Varun, you work in a regulated industry where there are a lot of things that are driven both by regulation, the government, as well as shareholders and stakeholders. I have seen that in such industries finance play a role much beyond typical account keeping, bookkeeping, standard processes and more into strategic levers.
What do you think — how has your role expanded since working in a multinational setup to a regulatory driven environment?
Varun
Finance has evolved from traditional stewardship and bookkeeping, or oversight of the business, to a more insight led business, where you have to be an active partner in driving the strategy and getting the results.
What has changed is that business partnering is on steroids. The kind of VUCA world we are in — like the dollar movement or the commodity movement — means the decision making has to be very apt. You cannot wait for the month end results to finalize, to look into the rearview and decide the forward view. That is not the case right now.
We have to decide, and that is where finance leads the way in bringing visibility to the business on what they are going to see in the future, based on current price movements, or by doing the modeling on what sensitivities can happen.
From partnering impact — short term and long term — especially from the product portfolio decisions, and the resource allocation, the risk profiles of every capital allocation are very different. The return today might not be the same in the future. If you see some returns are high today but low tomorrow, when the capital is really allocated, you have to take that hard course now.
These drive the core enterprise value — product portfolio, pricing and capital allocation discipline.
From an oversight to an insight, while controllership, stewardship and bookkeeping are the table stakes now, this is what makes a real difference. That is where the bulk of the time goes in for the finance folks.
Sardul
That is very powerful, Abhinav. The theme of oversight to insight as a journey. What are you seeing with a lot of our clients? Are they following the same trajectory?
Abhinav
I concur with what Varun mentioned. This gives me a flavor of the CFOs who think very transformatively and very progressively. I would agree that CFOs need to move to strategy execution rather than just focusing on performance reporting. Performance reporting is pretty much passé. We also see that CFOs who really tend to make a dent into the progressive story of their organization are also great proponents of technology adoption.
Sardul
You are talking about insights, and traditionally that is more for business owners or business functions to kind of ask for within their teams. How is the finance function proactively doing it? What levers do you have? What are you trying to do in your organization and in your setup with your teams? How are you moving in that direction?
Varun
To give you an example, what should be my pricing decision when the dollar is at 90, 92, or 94? Rather than taking a pricing decision based on the last quarter’s average, I do not think that is the right way to do it when, from a forward view, your dollar can move to any X number.
Similarly, for commodities like acetic acid — three years back it was US$800 and today it is US$350. Crude volatility — these are commodities which control roughly 60% of your value chain.
In business partnering, the finance folks work with the sales team or with the product development team, saying: what should be your pricing for the next quarter? What are the contracts which are still under negotiation? What should be your contract negotiation strategy?
The second one is, how do we really invest in technology which can cut the decision making time, or the insights time, from days or weeks to hours, so that people have enough time to build a strategy on the models that can be created?
The second example is capital allocation. There are a number of projects where you can invest. Every business wants their project to be at the top of the table. Then you have to partner with them to understand what the value-maximization proposition is and what the basic IRRs are. That is where you partner with them and decide what is right for the organization.
Sardul
In the world of GenAI, and in the world of all the hype that GenAI is creating across the globe, where do you see finance? Do you see any tangible use case that you have initiated that is working in the organization and that you believe is delivering value — not only to the business but to yourself? Is your workload going down? Is your team becoming more efficient? If you can share some views on that.
Varun
So let me be very candid, Sardul. GenAI is a very shiny word. For it to really work, we need the data systems to be correlated across the organization.
Three or four years back, they were all data lakes which were not integrated, and at the month end it used to be integrated, where the output of one used to be the input of others. For GenAI to really work and make a dent in the real world, they all need to be on the same platform.
We are working on GenAI in predicting the prices for the future, which will help us in having contract negotiations, or understanding how my next quarter will look, especially for key commodity prices.
What used to take a long time and used to be a manual decision, GenAI gives me a range of ethanol prices or acetic acid prices that are not on any platform. But with GenAI, I have a graph of how this might be in the future. With our industry knowledge, we know this is the range because there is seasonality to it.
Second, GenAI will help in terms of your currency, where you leverage the banking networks. With their knowledge and your insights, you know what the impact will be in the future.
Third is sales and operations planning (S&OP) processes. What is my demand and supply? It changes from industry to industry. I have seen one end in consumer led goods, where this can be very helpful, to a stable B2B business where it is more accurate — we know the contracts for the future. But in the FMCG business, GenAI can do wonders for the S&OP process for the future.
Apart from that, there are operational benefits which have cut down the workload of the finance team. The time that has been saved can be redeployed into doing something much more meaningful and more strategic.
In a nutshell, I am seeing the ROI coming out of it now.
Sardul
Well said.
Abhinav, since we are working with a lot of companies and finance functions around this area, are they also echoing what Varun is saying around areas of importance that are P&L impactful or more strategic? Or are they going more tactical in day to day operations because this is new, upcoming, or emerging? Where do you see the pendulum?
Abhinav
The maturity in the use cases — if I were to speak about finance as a function alone, the focus is on better reporting and insights, that too in real time. Also, the areas that directly give insights into how the P&L can be predicted.
Some of the use cases we are seeing in finance are: am I able to predict the position of the position of the P&L four quarters ahead so that I have a standing position and I am understanding the risk exposure to my investors and to my board as well?
While finance continues to transform because of GenAI, there is an uptake in the ancillary functions as well. At EY, the way we see it is how much of the adoption and impact is on the functions which are revenue centric — sales and marketing, R&D, manufacturing — or how much of the impact is on the cost side, which is the enterprise value function like finance, HR and so on.
The adaptability and applicability of GenAI — I will not limit myself to GenAI; I would rather say the possibility because of Agentic AI — is far higher now.
Some of the use cases we are seeing, especially in the specialty chemicals sector, are around R&D and formulation. The second is around operation and yield optimization, which is much closer to plant operations. The third is customer and commercial intelligence.
These are the three areas where we continue to see work progressing from POCs to live products, with a direct impact on the P&L. They are revenue centric, very close to the business and matter to the CFO agenda.
Sardul
As companies progress further on this journey — which is inevitable, as many people will deploy these models — what, as a CFO, would be your guardrails or safeguards as you implement these in your organization?
Varun
I will break it into two buckets.
The first is financial risk. Any AI model comes with an underlying algorithm; it cannot be opaque. We need to understand the logic behind it. As long as that is understood before implementation, the output can be much more reliable.
Second, it cannot be a decision maker. It needs human handling. AI can give insights and recommendations, but it needs to be human approved.
Sardul
What is our view? What are we seeing in the market and what is the general view around AI governance?
Abhinav
As AI evolves, the lens needs to move from functional risk to enterprise risk. That is the first thing we promote and tell our clients to expect.
In addition to that, there are inherent risks that will continue to mature. Cyber exposure is a major risk associated with any digital technology. AI not only makes it more severe but also expands the attack surface. We have seen cases of sophisticated phishing and deepfake personalization of senior executives.
These are strategic risks associated with AI that CFOs and executives need to discuss with security leadership.
In addition, data becomes the base for AI and GenAI. Model lifecycle management, which is at the heart of every GenAI/AI utility tool, is also a real risk. What worked six months ago may not work today if the data context has changed.
Are organizations mature enough to continuously monitor what is being built from a security perspective?
Lastly, not everyone builds everything. Organizations also buy from the market, which increases reliance on third parties. Are we conscious of contractual risks? Who owns the data? Who has liability if the model hallucinates or drifts? Who is liable for the outcomes?
These are some of the top questions we raise with our clients, asking whether they have thought about this holistically rather than only from a technology-risk lens.
Sardul
Well said. What is your message to your fellow CFOs who are just starting or thinking about this journey? And what is your message to those investing dollars and scaling this journey?
Varun
For those just starting, do not boil the ocean. Start with a specific area. Get yourself and your team comfortable with it. That will be a much faster way to roll it out.
Second, in any AI transformation, it is 20% technology and 80% people. Be mindful of that.
Measure ROI very rigorously. Every area you scale — procurement, operations — comes at a cost and consumes bandwidth. The discipline around ROI needs to be very clear.
Abhinav
One important thing to consider is having genuine excitement about the art of the possible. CFOs are naturally strong in financial discipline and rigor. If that discipline can be combined with excitement and pragmatism, organizations can become frontier firms rather than laggards who are catching up.
Sardul
Thank you, everyone, for listening in. I thoroughly enjoyed my conversation with both Varun and Abhinav. Thank you for tuning in again. Stay connected. It was good to interact with you, and I look forward to more such conversations.
Thank you.
If you would like to listen to our podcasts on the go:
Drive business growth with technology transformation solutions at EY - integrating tech, operations & architecture to build agile, data-driven organizations
