Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry?

Over the past 25 years, I’ve had the opportunity to build my expertise across a range of areas, including Managed Services, Transition & Transformation, Client Management, Change Management, Service Delivery, Quality & Risk Management, and setting up data- and analytics-driven Shared Services Centers (SSC). Today, as Vice President of Program Management, Transition & Transformation at Accenture in Bangalore, I lead large-scale programs focused on harnessing the power of data and analytics.

Throughout my career, I have been recognized for strong strategic planning and successful execution of digital transformation, driving operational excellence, scalability, and business growth in managed services environments. My track record demonstrates consistent contributions to both organizational and team objectives through data-led decision-making and AI-enabled transformation, resulting in enhanced overall performance.

I maintain a strongly customer-centric approach, collaborating effectively across all levels of the organization while driving end-to-end transition programs and delivering analytics-led service excellence.

Q2. Looking ahead, where do you see the largest pool of enterprise spending emerging across AI, automation and transformation services?

We’re seeing enterprise spending move away from simply building infrastructure and instead focus on AI services and software that deliver real value. That means more investment in things like advisory, integration, process re-engineering, and managing AI-powered operations.

Agentic AI is leading the way in terms of growth. Companies are no longer just experimenting with copilots or pilots—they’re embedding AI agents into the core of their everyday business workflows.

But the real key to unlocking value is getting the basics right: data readiness, governance, and AI security. Many large-scale programs hit roadblocks here, so it’s no surprise that organizations are investing heavily to address these challenges.

A lot of the demand is coming from highly regulated, complex sectors—think banking, insurance, healthcare, and finance & accounting—where transformation needs a strong partner who understands compliance and process intricacies.

Overall, the market is moving on from trial runs to large-scale, ROI-focused deployments. Buyers now want to see real results before they commit, so funding is tied to outcomes, not just ideas.

Q3. Which business processes are currently delivering the most measurable ROI from AI, RPA and intelligent automation?

Document-heavy processes 

When it comes to processes like invoices, claims, contracts, KYC, and onboarding, intelligent document processing stands out for delivering fast and tangible results.

Customer service and service desk 

Using AI to triage and resolve customer issues not only lowers the cost per interaction but also helps customers get answers faster.

F&A and HR shared services 

Processes like AP/AR, reconciliations, close and reporting, payroll, and hire-to-retire continue to deliver the biggest savings when it comes to high-volume work.

Engineering, testing, and compliance monitoring 

These are now some of the highest-return areas, thanks to AI, which makes it possible to check almost everything instead of relying on just a few samples.

What really drives these returns isn’t just the technology itself, but a combination of thoughtful process redesign and having clean data. In fact, it’s the high-volume, rule-based processes with few exceptions that deliver results the quickest.

Q4. How are AI investments affecting outsourcing, shared services and managed services models across banking and F&A?

Shift to outcome- and consumption-based constructs

Commercial models are moving from FTE and input-based pricing to outcome- and consumption-based constructs, as AI breaks the link between volume and headcount.

Partner Selection based on Data Capabilities

Demand is not shrinking – it is re-shaping. Clients now select partners on AI and data capability rather than labor arbitrage alone.

Evolution of Shared services and GBS centers

Shared services and GBS centers are evolving from transaction factories into AI, analytics, and control hubs that own end-to-end process performance.

Emphasis on Governance and Regulatory Control

In banking and F&A, the focus is on end-to-end process redesign with strong governance – model risk, data ownership, auditability, and regulatory control are now contract-level topics.

Transformation of the Talent Pyramid

The talent pyramid is changing – fewer transaction processors, more domain, data, AI orchestration, and exception-management roles.

Q5. As a final takeaway, what is the one AI or automation trend you believe investors should watch most closely over the next 2–3 years, and why?

The one trend to watch is agentic AI moving from assistance to autonomous, end-to-end execution of business workflows. It matters because it de-links cost from volume and resets the economics of software, services, and shared services pricing.

Ambition is currently running ahead of readiness – most agent programs are still sub-scale, and many will stall on weak data, governance, and unclear ROI. The winners will be those with proprietary data, orchestration and governance layers, and domain depth – not those with the most pilots.

For investors, the test is simple – measurable business outcomes and repeatable, at-scale deployment, backed by trust, security, and responsible AI.