The Thesis :

The markets delivered a clear signal this year - shareholders appear to be questioning whether traditional business models can sustain value in an AI-driven era. Shares of major enterprise software providers and system integrators (Accenture, Capgemini, SAP, Salesforce) have fallen more than 30 percent on average over the past year. Shareholders are sending a message: the services industry is failing to deliver measurable value.

The narrative is now undeniable. Enterprise transformation as we know it has reached an inflection point.

What Enterprise Leaders Are Actually Saying: WEF Davos 2026

As our Founder Kabir Nagrecha discussed at USA House in Davos, AI's value is visible but only at the margins. Productivity gains remain confined to individual and team level wins rather than enterprise wide impact.

The dominant question has shifted from "Can AI help?" to "Can AI execute safely inside real workflows?" Companies face mounting pressure to deploy AI as a vehicle for genuine transformation. Yet enterprise confidence remains low. Reliability, governance, and cross system execution are still immature. Large system integrators and enterprise technology platforms continue to push the AI message, but their execution lacks credibility with both customers and investors.

Why Services Led Transformation Has Reached Its Limit

The current enterprise transformation model is optimized for staffing and coordination. It does not compound capability within the enterprise.

The pattern is predictable: A platform shift triggers a multiyear program. Delivery scales through large external teams and layered governance. Knowledge accumulates in slide decks, ticket queues, and vendor owned expertise, none of which transfers into lasting enterprise capability. The system goes live, but any future evolution depends entirely on external resources.

The result: timelines stretch because the real work (exceptions, data debt, process gaps, adoption) consumes disproportionate effort. Plans look elegant, but execution is messy, leaving the persistent gap between transformation spend and business outcomes to widen.

Enterprise IT Budgets at an Inflection Point

A disproportionate share of IT spend goes to maintenance, legacy complexity, and external delivery. Enterprises face a structural trap: modernization crowds out innovation because so much capital flows toward maintaining aging systems with accumulated data and process debt.

C suite leaders want transformation velocity. Budgets remain committed to keeping current systems viable rather than building future capabilities. The opportunity is not incremental cost cutting. It is reallocating spend from nonvalue work to compounding execution.

AI at the Margin vs. AI That Transforms the Enterprise

Most enterprise AI today lives at the margin—copilots, faster content creation, improved search, and localized optimization. These tools boost individual productivity but rarely change end-to-end cycle times for initiatives that matter at the enterprise level.

Transformation begins when AI is embedded directly into workflows with governance, auditability, and clear outcomes. The model shifts from AI assisting humans to AI orchestrating work across systems, with human oversight.

SI to AI means scaling delivery by converting repeatable work into governed, learning workflows. Agentic AI becomes the execution layer—reducing handoffs, compressing coordination, and accelerating change through continuous improvement.

What Must Be True for AI to Drive Enterprise Transformation

Enterprises remain concerned about trust and governance. Rightly so. These cannot be afterthoughts bolted onto existing programs. They must be foundational to how transformation is designed and delivered.

Workflows must be explicit: permissions, approvals, and rollback paths for high stakes actions. Outcomes must be measurable: error rates, rework, adoption, and retention of institutional knowledge. Execution must stay disciplined. Most critically, enterprises need operating rhythms that treat AI as integral to delivery, not as isolated experiments. AI must be embedded into core operations for real transformation to occur.

Transformation Is No Longer a CIO Mandate

Transformation now shapes competitiveness, capital allocation, strategic agility, and investor confidence. The CIO role has expanded from delivery oversight to building enterprise execution capability and adoption readiness. The CFO role has evolved from cost management to redeploying savings into productivity levers: M&A, R&D, divestitures, and growth initiatives.

Business leaders (CEO, CFO, CIO) must co-own workflow redesign and enterprise transformation. AI changes how work gets done at the core, not just what tools exist. That is how productivity compounds across the organization.

At Tessera, our view is straightforward: to realize AI's potential at enterprise scale, we must embed it into the core workflows that drive business outcomes. AI is not the destination. It is the catalyst that changes how transformation gets delivered.

What This Means for the Future of Enterprise Transformation

McKinsey’s research(1) confirms what we see in the market: organizations with the most ambitious AI agendas capture the greatest value. Companies attributing 5% or more of EBIT impact to AI don’t treat it as a feature—they embed it into transformation. They redesign workflows, scale faster, and compound value through disciplined execution.

As AI becomes governed and operationalized, delivery models will shift. Leaders will buy outcomes measured in throughput and time to value, not team size or expertise. Competitive advantage will move from services intensity to execution capability.

The winners will be those who turn transformation into a compounding internal capability rather than a recurring external expense. AI’s real power is not automation—it is restructuring how change gets delivered. Learning and execution compound. Spending does not.

1. McKinsey: The State of AI: How Organizations Are Rewiring to Capture Value — https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-how-organizations-are-rewiring-to-capture-value