Enterprise AI focus shifts from coding productivity to business execution: Report

NEW DELHI: Enterprises are increasingly shifting their focus from improving developer productivity to accelerating overall business execution, as organisations recognise that faster coding alone does not necessarily translate into better business outcomes, according to a report by Sonata Software.

The report said the next phase of enterprise AI adoption will be driven by how effectively organisations integrate governance, enterprise knowledge and operational workflows into AI-enabled software delivery rather than by code generation alone.

According to the report, software delivery in large enterprises is rarely constrained by coding alone. Instead, governance, architecture, security, compliance, domain knowledge and organisational complexity often determine how quickly businesses can execute technology projects. It noted that while enterprises are widely adopting AI coding assistants, many continue to struggle to translate experimentation into measurable business value.

Citing McKinsey’s 2025 State of AI survey, the report said AI adoption is widespread, but many organisations still face challenges in scaling business value from AI initiatives. It also referred to DORA’s 2025 research, which found that AI amplifies existing organisational systems, accelerating workflow in high-performing organisations while magnifying inefficiencies in fragmented ones.

The report added that enterprises may deploy AI coding assistants across thousands of developers and still fail to improve delivery cycles, reduce costs or enhance business responsiveness if workflows are not redesigned. As code generation becomes increasingly common across technology platforms, competitive advantage is shifting towards an organisation’s ability to govern, contextualise, orchestrate and operationalise AI across the software delivery lifecycle.

It said the next generation of AI delivery platforms will evolve from “prompt-to-code” systems to “context-to-code” systems, where enterprise knowledge —including customer standards, regulatory controls, project knowledge, architectural patterns, reusable assets and delivery workflows — is available at the point of execution, enabling AI to improve enterprise-wide delivery rather than individual productivity.

The report identified three foundations for AI-enabled enterprise delivery–secure context, reusable intelligence and governed execution. It said AI systems need to be grounded in organisational policies and business processes, continuously reuse enterprise knowledge across projects and deliver compliant, auditable outcomes with built-in governance, security validation and human oversight.

Commenting on the shift in enterprise AI, Sundaralata A, vice-president at Sonata Software, said, “For the last two years, the enterprise AI conversation has been dominated by one question: how much more productive can we make the developer? The more important question for business leaders is no longer, ‘Can AI help a developer code faster?’ It is, ‘Can AI help the enterprise move faster?’ That distinction matters”.

The report also cited Stack Overflow’s 2025 Developer Survey, which found that while AI adoption among developers is high, trust in AI-generated output remains a significant challenge. It said organisations should increasingly measure AI success through broader business indicators such as idea-to-production time, compliance cycle time, onboarding speed, knowledge reuse and business outcome realisation rather than relying only on developer productivity metrics.

Concluding the report, Sundaralata A said, “AI will undoubtedly make coding faster. But the greater opportunity lies in making the enterprise faster. Organizations that succeed will be those that can transform enterprise context into executable intelligence–making knowledge reusable, governance intrinsic and delivery scalable. In doing so, AI evolves from a productivity tool into a strategic engine for enterprise transformation”. (ANI)