As artificial intelligence shifts from experimentation to enterprise-wide adoption, organisations are grappling with the challenge of scaling AI securely, efficiently, and sustainably. For professional services firms, this transformation demands not just new tools, but a fundamental rethink of delivery models, talent capabilities, and governance frameworks. In this conversation, Sudeepta Veerapaneni, Partner, Chief Innovation Officer, Technology & Transformation, Deloitte India shares how her organisation is responding to this shift, from building proprietary platforms like GenW.ai and driving large-scale AI upskilling, to fostering a culture of innovation and self-disruption. The focus, she explains, is on moving AI from pilot to production while embedding trust, resilience, and human oversight at every stage.
How is Deloitte modernising its core technology stack to support scale, resilience, and rapid adoption of emerging technologies?
We have made significant investments in building our own products and platforms. Today, about 500 professionals are focused on developing these solutions. Over the past two years, we have launched more than 30 products that are already being used internally to drive productivity gains and transform how we deliver client engagements. These tools are deployed across sectors and client types, enabling end-to-end transformation in the way our teams work.
A flagship example is GenW.ai, which we made available internally for six months before taking it to clients. We wanted it to be battle-tested and robust before external deployment. On top of GenW, we built solutions like Talk2Data, which connects to multiple databases, automatically populates schemas, and allows users to interact with data conversationally. Employees can ask questions in natural language and extract insights seamlessly.
How are you preparing your workforce for AI-led transformation?
Technology transformation must go hand in hand with people transformation. Out of our 45,000 India-facing professionals, more than 30,000 have completed our AI Con Academy, a rigorous AI upskilling initiative we’ve been running for two years. The objective is to make our teams ready for AI-driven client conversations and engagements.
We also run a program called A4Assets, where “A” stands for Assets. These are the platforms and products we build over time. Close to 20,000 professionals have been trained to understand and deploy these tools effectively in client engagements.
How are you building a culture of innovation within Deloitte?
When I took over this role in 2024, a key priority was building a strong innovation culture.
We launched initiatives like Green Dot Hustler, inspired by Deloitte’s green dot in its logo. It’s an internal ideation challenge encouraging employees to bring forward innovative ideas, many of which are now being executed successfully. Externally, we launched Hacksplosion, a campus hackathon initiative. We currently have close to 10,000 registrations from 60 colleges. Students are building use cases and solutions on top of the GenW platform. These programs help embed innovation and technology adoption deeply into our organisation.
What was the core technical objective behind launching GenW.ai, and how does it fit into Deloitte’s broader ecosystem?
Our annual State of AI report shows that many AI and agentic AI projects remain stuck in pilot stages. The issue isn’t AI capability, it’s productionising AI at scale.
GenW.ai was built to address this challenge. It enables scalable AI deployment while managing cost efficiency and enterprise-grade reliability.
From an ecosystem perspective, we work with hyperscalers like AWS and Google Cloud. Our platform is designed to integrate seamlessly across such environments, ensuring flexibility and scalability for clients.
Security is a major concern in AI adoption. How do you address it within your ecosystem?
Security is foundational for us. We have implemented strong data protection protocols, especially when solutions are deployed on client premises. There are guardrails governing agent-to-agent communications, and auditability is built into the platform.
One of the strengths of GenW.ai is that it is not a black box. There is a clear audit trail for outputs. For example, in our DocQA tool, outputs are source-referenced, users can see exactly where insights are drawn from.
Most importantly, we emphasise a human-in-the-loop approach. AI-generated results are reviewed before being used internally or delivered to clients.
What emerging innovations or architectural shifts will most impact professional services firms in the coming years?
AI is no longer part of the hype cycle, it is embedded in our everyday operations. It’s in our phones, laptops, and workflows. Professional services firms must treat AI as integral to how they operate.
We encouraged our top 50 leaders to go through a transformation program called Phoenix Encounter, which focuses on self-disruption, asking, “How can we disrupt ourselves before someone else does?”
That mindset is critical. AI must be reimagined as part and parcel of the way we work, not as an add-on.
This conversation highlights Deloitte India’s clear shift from AI experimentation to enterprise-scale execution. With proprietary platforms like GenW.ai, large-scale workforce upskilling, and structured innovation programs, the firm is embedding AI into its core operations rather than treating it as a side initiative.
Just as importantly, its focus on security, auditability, and human oversight reflects a balanced approach to responsible AI adoption. By prioritising self-disruption and scalable deployment, Deloitte India appears focused not just on leveraging AI, but on reshaping how professional services are delivered in an AI-first era.