Market View
Navigating the AI transformation journey: How global service providers are reimagining value creation
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Produced by:
Vijay Raaghavan
Head of Enterprise Innovation at Fractal
About Vijay Raaghavan
Vijay Raaghavan is a Growth Architect with BxD at Fractal, where Behavior meets Design to make AI not just work, but stick. He leads with a decision-backward, design-forward mindset—anchoring every solution in the behaviors that drive business outcomes.
Vijay works across Fractal’s ecosystem of engineers, behavioral scientists, strategists, and designers to embed human-centered AI into enterprise workflows. His collaborations with leaders like Microsoft, Google, Merck, and Apple focus on one thing: trust through real adoption.
His signature approach?
Connect the dots → Frame the real problem → Align the right teams → Scale fast with actions. Not feature-first—decision-first, behavior-backed, and business-aligned. Because real growth isn't powered by more tools. It's built on systems people trust, use, and believe in.
How is AI beginning to reshape relationships between global service providers and their enterprise clients?
For enterprise clients, especially Fortune 100 companies, AI is fundamentally changing how we deliver value. Historically, these organisations would turn to service providers like us to build enterprise applications, develop insights, or optimise workflows. Take a banking client, for instance—they'd need help mining their existing customer data to drive analytics. Companies like Nestlé excel at consumer products but don't necessarily have robust IT or AI teams in-house. That's where vendors like us step in, not just to build internal capabilities but increasingly to help them develop monetisable digital assets.
The real transformation AI brings is scale, impact, and speed. In the past, we'd help clients with robotic process automation for tasks like call centre optimisation, which primarily saved time. Today, we're able to replace certain roles with agents or bots whilst elevating human workers to higher-order functions. This means for the same investment, clients can now have AI companions augmenting their teams, essentially providing a coach alongside their people. We're delivering more value per pound spent by enabling human-AI collaboration that enhances overall capability.
What value we are giving to enterprise is for the same dollars you're spending, we are able to help you build a companion who can augment a human being, and you can deliver more value to your client. So it's almost like having a coach by your side, and all of this at scale.
As you navigate this transformation, how are you evolving your service delivery model to blend AI capabilities with domain expertise?
We're fundamentally rewiring our teams and culture. Our founder, Srikanth, first talked about developing 'T-shaped' personalities—having deep expertise in one technology area overlaid with domain knowledge. Now he advocates for what we call 'Pi personalities', which is a more comprehensive approach encompassing three crucial dimensions.
The horizontal bar represents understanding AI itself—identifying problems that are AI-ready and determining appropriate use cases. The first vertical is engineering—knowing how to build solutions that can scale globally while adhering to responsible protocols. The second vertical is design—crafting experiences that humans can effectively consume and interact with, considering everything from language to incentives that drive adoption.
When a client approaches us about building a platform, we first establish the role AI should play—perhaps a bot providing advice or support. Then we address engineering challenges: How do we ensure global accessibility? How do we implement responsible data handling? Finally, we apply design thinking: How will humans interact with this system? What will motivate a user to engage with the platform?
How do you see the relationship between service delivery and value creation evolving?
The lines have completely blurred. In my recent client conversations, the technology itself has become almost secondary. Clients aren't particularly concerned about what technology we're using or how we're structuring the solution architecture. In the last quarter especially, almost every discussion about new initiatives starts with: "Tell me what economic value this creates for our business."
The conversations go straight to that point, and the means of achieving it becomes our responsibility. Whether it's a blended service model incorporating both human expertise and AI capabilities, or something entirely different, the focus remains squarely on measurable outcomes. This represents a significant shift—the technology, service delivery models, and implementation approaches are dissolving into the background while value creation takes centre stage as the single most important element.
The single most factor that will help us scale AI across jurisdictions is being responsible. Right? I mean, and it is not an afterthought. Unfortunately, responsible AI is globally thought of as an afterthought.
Where are you seeing the greatest potential for reimagining value creation through AI in service delivery?
For service providers, the greatest value lies in augmentation and validation. If I replace my £200-per-hour service with £160 of human expertise and £40 of AI capability, the AI becomes a validation engine that helps avoid mistakes and improves judgement. It's similar to how chess is played now—a chess bot improves a player's efficiency by reducing human error, which is precisely the value we're bringing to service delivery.
For clients, there's tremendous value in measurement and efficiency, though we're still developing frameworks to quantify this accurately. When we implemented AI in PepsiCo's manufacturing plant to detect imperfect potato chips, measuring the 30% improvement in detection rates was straightforward. However, measuring broader workforce productivity gains remains challenging. That's why AI conversations tend to be successful with CEOs but not with CFOs—we're still working on demonstrating concrete financial returns.
What's your approach to scaling AI capabilities across jurisdictions while ensuring consistent value delivery?
The single most important factor for scaling AI across jurisdictions is being responsible—and this must be a starting point, not an afterthought. Unlike the prevalent approach where technology comes first and regulations catch up later, we believe in building a strong responsible AI framework upfront and ensuring all applications pass through this governance structure.
Our philosophy is clear: if a solution can't pass through our responsibility framework, ethical AI standards, or governance protocols, we simply won't launch it. This approach sometimes creates tension, particularly in markets like the US where there's often pressure to move quickly. However, we maintain our position as trusted advisors, emphasising that bypassing proper governance inevitably carries consequences.
If the industry truly wants to scale AI and thrive long-term, regulations and clear governance frameworks must be the top priority. We're actively investing in developing robust artefacts to support this approach, as we believe it's the only sustainable path forward.
What I've found sensible is an audience of about 20 people - beyond that doesn't work. A small roundtable of six people where the mindset is, 'Look, we're getting together to make something'. That's the kind of audience I prefer.
About Fractal
Fractal is a global AI and analytics company that enables Fortune 500 organisations to make better decisions through data-driven insights. With over 5,000 professionals across 50 countries and annual revenue of approximately $350 million, Fractal provides enterprise-level AI solutions that help clients solve complex problems, optimise operations, and monetise digital assets. The company has established itself as a unicorn by focusing on delivering billion-dollar impacts to top-tier enterprises whilst incubating successful AI products like Qure.ai.
About Enate
Enate is the leading SaaS solution for business services. Enate orchestrates work from start to finish, giving clients the visibility and control needed to deliver better services. From email management and data analysis to intelligent document processing, Enate also offers a host of touch-button AI features designed to slash the time spent on manual work. Trusted by global service teams, Enate ensures smooth, consistent operations that help clients perform at their best.