At Infosys we were building AI platform 10 years ago, now it is all in past: Vishal Sikka
Infosys, once a pioneer in building an artificial‑intelligence platform a decade ago, has now shifted its focus away from that early effort, according to former chief executive Vishal Sikka. The change highlights how quickly technology strategies evolve and why firms must constantly adapt to stay relevant in a competitive market.
Around 2013, Infosys launched an internal AI platform designed to automate routine processes, enhance data analytics, and offer predictive insights to its enterprise clients. The initiative was part of a broader push by Indian IT services firms to move up the value chain and transition from traditional outsourcing to higher‑margin digital services. At the time, the platform was promoted as a differentiator that could help Infosys win large contracts in banking, healthcare, and manufacturing.
Why the platform stalled
Several factors contributed to the platform’s decline. First, the pace of AI research accelerated faster than the company could integrate cutting‑edge models into a production‑ready product. While research labs worldwide released new architectures every few months, Infosys’ engineering teams struggled with legacy code, limited data pipelines, and the need to meet strict compliance standards for global clients.
Second, the market shifted toward cloud‑native AI services offered by a handful of large cloud providers. Companies such as Amazon, Microsoft, and Google began bundling AI tools with their infrastructure, making it easier for businesses to adopt machine‑learning capabilities without building them from scratch. This created a pricing and convenience advantage that was difficult for an on‑premises platform to match.
Finally, internal priorities changed after Sikka left the company in 2017. Successive leadership emphasized cost efficiency and scaling existing consulting services rather than investing heavily in a single, capital‑intensive AI product. Resources were redirected to newer offerings like automation bots, data‑analytics consulting, and partnerships with cloud vendors.
Infosys’ experience mirrors a broader trend across the technology sector. Many firms that invested early in AI platforms discovered that the rapid evolution of the field made it hard to maintain a competitive edge without continuous, large‑scale investment. The shift toward platform‑as‑a‑service models has lowered entry barriers for smaller players while concentrating market power among a few cloud giants.
For emerging economies, the story offers a cautionary note. Governments and companies that aim to build national AI capabilities must balance long‑term research ambitions with the practicalities of deployment, data governance, and ecosystem partnerships. The cost of keeping a proprietary platform up to date can be prohibitive, especially when open‑source tools and public cloud services provide comparable functionality at lower expense.
What the change means for Infosys
Infosys is now positioning itself as a strategic integrator rather than a platform creator. The company has deepened collaborations with leading cloud providers, offering implementation services, industry‑specific templates, and managed AI operations. This approach leverages Infosys’ strength in large‑scale project delivery while avoiding the heavy R&D burden of maintaining a proprietary AI stack.
Clients benefit from faster access to the latest AI models, as the cloud partners continuously update their services. At the same time, Infosys can focus on customizing solutions, ensuring data security, and providing domain expertise—areas where its consulting background adds clear value.
Potential future directions
While the original platform is considered a thing of the past, the knowledge gained during its development remains valuable. Experts suggest three possible paths for Infosys moving forward:
1. AI‑enabled consulting – Embedding machine‑learning insights directly into advisory projects, helping clients make data‑driven decisions without building separate AI systems. 2. Industry‑specific AI accelerators – Creating reusable modules for sectors like finance or healthcare that can be quickly deployed on top of cloud services. 3. AI governance and ethics services – Offering frameworks and audits to ensure responsible AI use, a growing concern for regulators worldwide.
Each path aligns with the company’s core competencies and the market’s demand for trustworthy, scalable AI solutions.
Broader industry impact
Infosys’ pivot underscores a larger shift in the IT services landscape. As AI becomes a commodity, differentiation increasingly relies on how firms integrate, manage, and govern these technologies rather than on owning the underlying algorithms. This trend encourages a more collaborative ecosystem where specialists, cloud providers, and system integrators co‑create value.
The move also raises questions about talent allocation. Engineers who once focused on building proprietary AI stacks are now likely to work on integration, data engineering, and client‑facing roles. Training programs and hiring strategies will need to reflect this change, emphasizing hybrid skill sets that blend technical depth with business acumen.
The AI platform that Infosys built a decade ago may no longer be a centerpiece of its strategy, but the experience has shaped the company’s outlook. By acknowledging the platform’s limitations and embracing a partnership‑driven model, Infosys aims to stay relevant in a fast‑moving digital economy.
For the global tech community, the episode serves as a reminder that early innovation does not guarantee long‑term dominance. Success now depends on agility, strategic alliances, and the ability to translate AI advances into tangible business outcomes. As more organizations adopt AI through cloud services, the role of integrators like Infosys will become increasingly important, shaping how technology is applied across industries worldwide.