Cutting through the AI noise

Diageo, the $20B powerhouse behind iconic brands like Johnnie Walker and Tanqueray, faces the same question echoing across boardrooms today: to AI or not to AI?

Sayantan Datta, who heads the Order to Cash Process at Diageo, and brings over a decade of experience driving automation projects at SIs, is a (cautious) optimist. We talk to him about his philosophy and practical approach to automation projects.

Watch the full interview

Cutting through the AI Noise | Sayantan Datta, Transformation Leader @ Diageo - YouTube

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Featuring

Sayantan Datta (Global process leader, Diageo)

Anirudh Patri (Growth, Nanonets AI Agents)

Watch time: 43:00

Highlights

Avoiding the AI theatre

With the pace of progress in AI and all the marketing hype, there's a rush to find problems for solutions. We don’t need a Ferrari to buy groceries. Start conversations with outcomes, not features.

Data is the key

What needs to be true for the solution to work? The answer is almost always clean data, so that you avoid a stack of half-finished innovations. Understand what data you have and what outcomes are possible based on that, and in the meantime invest in data improvement continuously.

Mindset shift

Many people get bogged down by the belief that “my business is unique”. However 70% of business processes are roughly the same across businesses, and there shouldn’t be an aversion to off-the-shelf tools that are already in the market.

Transcript

Anirudh: Hi, everyone. Welcome to the Nanonets Podcast. Nanonets is an AI platform transforming how enterprises reimagine their processes. I'm Anirudh Patri, a GTM leader at Nanonets and an AI enthusiast.

Today I have with me Sayantan Datta, SVP Global Process Leader at Diageo, a company that owns familiar brands like Guinness, Tanqueray, and Captain Morgan. Sayantan is responsible for transforming a multitude of business processes at Diageo and brings a wealth of knowledge around automation.

What automation means to me

Anirudh: To set the stage, what is automation to you? How do you see it evolving? How has it changed the world over the past few years?

Sayantan: Automation has gone through several generations. Early in my career, it meant simple things like building Excel macros or mainframe screen scraping. It's come a long way in the last 15–17 years to a point where we now have conversations that would've seemed sci-fi even 10 years ago, around immersive technologies and the capabilities of AI.

To me, automation is about doing things better and creating better experiences, not just automating tasks for the sake of it. If something doesn't make sense to do, I'd rather eliminate it than automate it.

Outcome first vs Feature first

Anirudh: A lot of people are struggling with new offerings from legacy players like UiPath or Blue Prism, and from startups, all claiming to automate processes end to end. How do you cut through the noise? With new tools launching every day, how do you focus on what's actually important?

Sayantan: The way AI is marketed today, it’s like we have the solution already painted and now we’re looking for a problem. The organisations that succeed start with the problem. What do I really need to get done? What outcome do I want? That clarity makes it easy to cut through the noise. Start with needs and outcomes, then move to features, and from there to benefits.

Data is the key

Anirudh: Data seems to be one of the biggest challenges in automating any process. How do you overcome that, especially in large enterprises with multiple brands and acquisitions?

Sayantan: Data is a living problem. We’ve been trying to solve it as a finite task, but it evolves as businesses evolve. The goal is to understand the gaps and use what you have to deliver the needed outcomes.

Zero-based approach

Anirudh: If there are 50 things to fix in one part of the business, that part needs a redesign. Let’s take accounts payable or receivable. If you can list 50 things to change, something fundamental is broken. Go back to the basics: what do I need this process to deliver?

Sayantan: If your business has too much low-value work to automate, your foundation is weak. Fix the foundation first.

The culture shift

Anirudh: If you had a magic wand to redesign a company for AI and automation adoption, what would you change?

Sayantan: I’d change the culture and the way people look at AI. AI should enable solutions, not be the solution.

Skills for the Future

Anirudh: Since we’re talking about humans making decisions and work being automated, what skills should someone build to stay relevant?

Sayantan: Adaptability. Change is scary because we fear what we don’t understand. But adaptability, being able to learn and apply new things, is crucial.

Future of AI and Human Roles

Sayantan: In the future, the focus will shift toward experiences rather than just transactions. Future individuals will spend more time creating hyper-customised experiences.