With fears of automation disrupting traditional outsourcing work weighing heavily on market sentiment, industry executives and analysts say IT and software services firms have a small window to pivot business models and delivery processes to ride the AI wave rather than be buried under it.
Experts called for a fundamental redesign of operating models, instead of an incremental change, while flagging the challenges in executing this pivot.
Enterprise AI scales slowly; ROI delayed: CP Gurnani
“Enterprise AI does not scale up the way earlier technology waves did. It requires clean and contextual data, deep domain integration, strong governance, and sustained change management within client organisations. This leads to longer incubation cycles and delayed ROI, an uncomfortable fit for an industry historically optimised for linear growth and predictable margins,” CP Gurnani, co-founder and vice-chairman of AIONOS and former chief executive at Tech Mahindra, said.
He added that Indian IT companies must stop treating AI as a horizontal capability to be showcased and start treating it as infrastructure that must earn its right to scale. This entails focusing on fewer, high-impact use cases where AI materially changes cost structures, productivity or decision-making, rather than spreading investments across pilots that never industrialise.
“Further, AI cannot be forced into quarterly business models. Firms need to ring-fence capital, platforms, and talent, accepting that returns will be asymmetric and back-loaded. This is not a headcount-replacement story, but a delivery-model redesign driven by smaller, high-quality teams with deep domain understanding and AI fluency,” he said.
Analysts and industry experts said the recent rout in IT stocks may partly reflect a knee-jerk reaction to new AI tool launches and their perceived impact on the future of IT services and SaaS providers. However, they added that the correction also signals growing investor recognition that AI-led automation could structurally alter traditional outsourcing economics.
In an interview to CNBCTV18, former Infosys head Vishal Sikka explained that while the disruption on account of AI is already underway, its impact on business will vary across service lines. Some segments may see immediate transformation, while others could take longer to evolve.
“We need to switch from being operators and executors of what is known to being creators and innovators of what is not yet known. The fundamental question is — are we able to do that? Are we going to able to make that switch from doing repetitive things that are well prescribed to creating a large culture of innovation,” Sikka said during the interview.
While the markets present a cautious outlook, experts said the industry is far from being structurally threatened. Instead, they believe the next few years could determine which firms successfully reposition themselves for AI-driven transformation.
“Humans have an implicit knowledge of processes when we’re working that an AI Agent doesn’t have. To train an Agent on the institutional knowledge is a very slow drawn-out process. The reason why Agentic AI adoption has been slow is that there is a lot of process, data and tech debt so there’s barely 10-15 % of enterprises that have been able to deploy Agentic AI,” Ashvin V, executive research leader (IT services) at global tech advisory HFS Research, said.
Agentic AI boosts productivity, could squeeze IT margins
Agentic AI is already offering alternatives to labour-intensive software development, with clients increasingly demanding productivity and efficiency gains. This, in turn, could compress margins for IT services firms and software vendors.
“The ambiguity related to AI is what is causing the fear and consequent stock falls. So, the best way is to embrace the advancements slowly and with thorough planning. Since markets do not wait or reward experiments, it is up to the IT industry to convince through revenue stability proof…through case studies, productivity improvement announcements,” said Rinku Prakash, manager – digital marketing at Rayblaze Global, a software solutions provider. The time required to scale up enterprise AI deployments may provide IT firms an opportunity to realign their strategies.
The reset may prove difficult to execute as IT firms continue to carry the burden of legacy revenue streams and delivery frameworks that could slow transformation. AI-led revenues remain at a nascent stage, even as investments required to scale the technology are rising sharply. In addition to workforce realignment challenges, firms must balance long-term transformation bets with near-term business viability — a trade-off that could define the sector’s competitive landscape in the AI era.