The market is pricing in a dramatic AI-driven reset for tech services companies. Investors increasingly expect AI will fundamentally compress the labor required to deliver services, enabling the same output with a fraction of the headcount. The drop in share prices reflects investor concerns that these companies will not adapt quickly enough to operating models that depend on fewer employees (see Figure 1).

Figure 1

Customers are already factoring in productivity gains before they arrive, demanding as much as 20% efficiency improvements at renewal negotiations and awarding new work on assumptions of at least 30% (and in some cases as much as 50%) lower delivery costs. With many contracts spanning three to five years, service providers are committing to productivity they have yet to achieve.

AI is already improving productivity in tech services, which is expected to be between 15% to 45% across various service lines, but no one has cracked AI delivery at scale (see Figure 2). Many providers have built AI platforms to deliver their offerings, but few have built a repeatable commercial model. Even when well developed, bringing these platforms to market remains a challenge: Frontline teams lack the confidence and capabilities necessary to deliver AI transformations for customers, making it difficult to convert offerings into funded programs.

Figure 2

The market is still growing despite this readiness challenge: Firms such as Coforge, EXL, and Persistent delivered growth as high as 30% in 2025. But the market still cannot distinguish future winners and losers; that opportunity remains open.

Sustaining double-digit growth

Delivering double-digit growth in this environment requires more than an AI offering; the firms pulling ahead are changing how they compete and how they operate. While no company has perfected the model, a clear set of winning moves is emerging.

• Win in specific segments, not across the board. Generic AI capabilities are now table stakes. Leaders are focusing their investments on high-priority micro-verticals and defining specific battlegrounds at the intersection of spending priorities, micro-vertical, and geography. They then build offerings for that precise context. That depth makes a firm the obvious choice rather than one of five that can do something similar. A sustained Net Promoter Score® of 50 or higher is a strong signal that the differentiation is real. Coforge, for example, grew 29% over its last fiscal year by combining deep domain expertise with more than 150 AI engagements focused on four industries: banking and financial services, insurance, travel, and healthcare.
• Become a reinvention partner, not just a delivery partner. Incumbent providers already possess an advantage that new entrants struggle to replicate: intimate knowledge of their customers’ applications, data flows, integrations, business rules, exceptions, and technical debt. The firms that win will use those insights to identify and unlock value rather than waiting for a defined scope of work.
• Build a go-to-market engine that sells AI transformation. Traditional sales motions can produce interesting conversations about AI while gaining limited commercial traction. Leading firms are building frontline teams that combine knowledge about the customer and workflow with AI and technology capabilities to develop a winning sales proposition.
• Make platform differentiation real. Platform delivery no longer differentiates providers: Every firm now points to an orchestration layer, guardrails, and an agent library. In some industries, customers require service providers to join their platform rather than introducing another. True differentiation is more about depth and quality: the breadth and maturity of the agent library, how well it maps to real offerings, and whether it holds up at enterprise grade beyond the demo.
• Evolve the commercial model. Time and materials pricing is structurally misaligned with a platform delivery model. It rewards inputs, not outcomes. There is no single winning model yet, but outcome-based and gain-sharing structures are on the rise because they align better with incentives. The goal of any model must be to deliver real savings to the client and better margins for the provider.
• Win with partners, don’t just manage them. Winners will need to rewire their partner model to be much broader than before, with partnerships that fit customers’ varied AI journeys and priorities. The next era of partnerships with hyperscalers and frontier models will require both parties to work together to generate new opportunities rather than just fulfilling existing demand.
• Transform talent and leadership. AI is changing the talent model in many ways, including amplifying the productivity of entry-level work. New roles such as AI- and technology-proficient forward deployed engineers will become the delivery unit of record. Leadership needs to sell transformation outcomes, not technical capacity, which implies a fundamentally different talent strategy: career paths based on capabilities, pricing based on a collection of skills rather than roles, and hiring profiles that prioritize creative thinking and domain expertise over technical credentials.

Turning AI into competitive advantage

The market has already decided that AI will reshape the economics of tech services, but it hasn’t determined the winners yet; that window is still open. Winning providers won’t be those with just the best technology; they’ll be the ones that can differentiate themselves with an AI-first operating model that delivers new business value for customers. Leaders are beginning to emerge, but the window to be one of them is narrowing. Several priorities stand out.

• Focus where you can win. Winning firms aren’t spreading investment across every opportunity; they’re concentrating resources on a few high-potential markets and building the capabilities and expertise to thrive in each. Good candidates identify their ideal client, develop proprietary offerings, and build a delivery model priced on outcomes.
• Design the toolchain and the client experience together. Most providers have built a few AI features, but few have created the full technical system that actually delivers results and a clear path for clients that moves them from their current way of working to the new one. The client’s journey matters just as much as the technical tools that support it.
• Reinvention means rebuilding delivery. Leaders are redesigning how work gets done, including team structures, global delivery models, and pricing models, from the ground up; they’re not wrapping AI tools around an existing time and materials model. The benchmark has moved, and productivity is already expected to improve by 20% to 35% compared with the current baseline. Firms still optimizing around the current model are solving the wrong problem.
• Build a repeatable commercial model. Focus on one high-potential opportunity, build it properly, and show that it delivers client savings and margin improvements. Use that as the template. Firms that try to scale up before proving the formula end up with neither.

AI is creating entirely new service categories, and the providers that establish credibility in these new markets are poised to lead them. Incumbents already have trusted client relationships, giving them a head start. The firms that move now have an opportunity not just to adapt to the next era of tech services but to define it.