Enterprise AI needs custom fit

San Francisco: Will the next wave of AI tools displace IT services firms? The argument seems intuitive. If AI models are becoming increasingly powerful and more accessible, why do companies need intermediaries to build and run technology? Yet, this debate is focused on the wrong question.

The more important question: why do so many companies continue to struggle to translate unprecedented AI investment into measurable business outcomes? A June 2026 Cognizant-Pearson study, 'The AI workforce pulse: The adaptability imperative', found that 63% of enterprises report a moderate-to-large gap between their AI ambitions and current capabilities, even though more than half already spend $10 mn or more annually on AI.

Enterprise AI is no longer constrained by access to tech. Frontier AI capabilities are becoming more available by the day. What remains scarce is the harness that converts frontier model capability into measurable business value.


Also read: Off with offset training wheels

The idea that a business can deploy an AI model or tool off the shelf to deliver those results overlooks the complexity of enterprise transformation. Large enterprises operate within intricate legacy systems, fragmented data environments, regulatory requirements, operational dependencies, and deeply embedded ways of working. Most struggle because scaling AI exposes weaknesses in those systems rather than resolving them.

AI readiness requires shaping the technology around the operating realities of the enterprise: its systems, data, processes, risk posture, workforce and performance expectations. Real work begins when AI is engineered into the operating core of the enterprise: customer service operations, supply chain decisions, software delivery and other business-critical workflows.

This is where AI moves from promise to performance - helping reduce unplanned downtime on a factory floor, enabling banks to resolve customer requests faster and more accurately, and accelerating the design and launch of new products and services.

Also read: Nepal’s deadly flood is a warning no one is listening to

AI strategy is ultimately about more than selecting technologies. It's about creating conditions that allow AI to scale across the enterprise and deliver business results. The differentiator is readiness, which must be built.

An AI builder's role is to help enterprises industrialise AI by designing and orchestrating the harness that makes AI productive across the business. This is how enterprises move beyond isolated experiments to AI at scale, and toward agentic operating models where humans and AI work together seamlessly. That shift is underway.

Global enterprises scaling AI share a common denominator: they design for enterprise-wide adoption by building this harness from day one. They create technical, operational and organisational foundations that allow AI to scale across the enterprise and deliver sustained value. This includes data, integration, governance and workforce readiness, enabling employees to not only use AI but also trust it, challenge it and improve it over time.

India offers a compelling proving ground for enterprise AI. Companies operate across diverse languages, markets, regulatory environments, data and customer segments. This complexity is evident across financial services, public services and distributed manufacturing, where organisations have often leapfrogged legacy constraints by rapidly adopting cloud-first and AI-native architectures. As a result, India is uniquely positioned to become a global template for AI-at-scale innovation.

37% of entry-level tasks in India are already performed by AI, ahead of the 33% global average, and 96% of HR leaders expect entry-level roles to evolve toward supervising AI.

Indian companies are leaning into this shift: 63% have already allocated dedicated time for AI training, compared with 49% in the US. Increasingly, Indian enterprises are moving beyond adoption to co-creation, building the models, platforms and workflows that can set global standards for how AI is deployed at scale.

The current moment marks a true inflection point for enterprise AI. Moving beyond experimentation, embedding AI into the way a business operates is now a strategic imperative. The future of enterprise AI will not be determined by the best models alone but by the enterprise harness around them.

This is why the real question is not whether AI will replace IT services firms. It's who can close the gap between AI's potential and enterprise outcomes. So, the future will belong to AI builders.

The writer is president, Americas, Cognizant.