Can Infosys Topaz challenge Accenture and IBM in enterprise AI transformation at global scale?

Infosys Limited (NSE: INFY) has positioned its Topaz platform as the cornerstone of its generative AI strategy in 2025, aiming to transform enterprise operations through copilots, reusable assets, and domain-specific automation. With 12,000+ AI assets and over 100 client engagements under its belt, Infosys is now aggressively scaling delivery capabilities through GenAI studios in Dallas, London, and Bengaluru.

This surge in Topaz adoption places Infosys in direct competition with enterprise AI offerings from Accenture plc (NYSE: ACN) and International Business Machines Corporation (NYSE: IBM), raising the question: Can Infosys rival these global incumbents in AI-enabled transformation across industries?

What is Infosys Topaz and how is it positioned in the global enterprise AI services market?

Infosys launched Topaz in May 2023 as an integrated generative AI platform embedded within its broader digital services framework. Described by the Indian IT services firm as a “comprehensive AI-first suite,” Topaz blends proprietary and open-source large language models with domain-specific copilots, business APIs, and accelerators tailored for industries like banking, telecom, and manufacturing.

Topaz is differentiated by its extensive library of 12,000+ reusable AI assets, which include function-specific copilots for supply chain, HR, finance, and customer experience. These assets are designed to be rapidly deployed across client environments, with minimal customization and high interoperability with existing enterprise systems.

Institutional investors have taken note of Topaz’s role in accelerating time-to-value for AI deployments—particularly in mid-sized digital transformation projects where speed and cost-efficiency matter more than full-stack control.

How is Infosys scaling Topaz delivery through GenAI studios in key global hubs?

A key part of Infosys’s Topaz rollout strategy involves physical co-creation hubs called GenAI studios. Located in Dallas, London, and Bengaluru, these studios serve as client-facing innovation centers where AI solutions are developed, tested, and iterated in close collaboration with end users.

Each GenAI studio is equipped with capabilities for prompt testing, LLM fine-tuning, and risk-mitigation scenario planning. They are staffed by cross-functional teams including AI researchers, delivery engineers, prompt architects, and business domain experts. Clients are invited to co-create use cases—from customer onboarding copilots to fraud detection assistants—ensuring higher adoption and contextual relevance.

These hubs have also become talent magnets for Infosys, helping the Indian IT services firm retain AI-literate talent and build localized delivery credibility in North America, Europe, and India.

How does Infosys’s AI training and workforce strategy compare to Accenture and IBM in 2025?

Infosys has trained more than 55,000 employees in Topaz-related capabilities since 2023. The firm offers role-based certifications covering generative AI concepts, prompt engineering, model tuning, and responsible AI practices. These programs are delivered via internal learning academies and partnerships with cloud providers and academic institutions.

By contrast, Accenture has reported over 50,000 professionals trained in generative AI across its global workforce and plans to scale to 80,000 by the end of FY26. Its AI Navigator certification program integrates with delivery platforms like myWizard and SynOps to standardize usage across verticals.

IBM has oriented its workforce training more tightly around its Watsonx platform, with a particular emphasis on governance, explainability, and compliance in regulated environments. Watsonx certifications are offered alongside training for Red Hat and hybrid cloud infrastructure.

Analysts observe that Infosys’s certification depth may be narrower than Accenture’s but is purpose-built for rapid deployment in repeatable use cases, making it well-suited for function-specific automation at scale.

What types of enterprise AI programs is Infosys delivering through Topaz in 2025?

Infosys has delivered over 100 enterprise programs using Topaz across a range of business scenarios.

Infosys has implemented Topaz-powered generative AI programs across a diverse set of geographies and industries. In Europe, the Indian IT services firm has deployed customer service copilots for telecom clients, streamlining call center operations and enabling intelligent response generation across multiple languages.

In the United States, Topaz has been used to automate onboarding workflows for financial services institutions, reducing manual documentation cycles and improving compliance turnaround. In Southeast Asia, Infosys is delivering predictive maintenance assistants for large-scale manufacturing clients, integrating sensor data with LLM-driven diagnostics to anticipate equipment failures. Meanwhile, in Canada, Topaz underpins fraud detection engines for insurance companies, helping identify anomalous claims using real-time behavioral analytics combined with historical policy data.

Most of these solutions integrate Topaz with cloud platforms such as Microsoft Azure, Google Cloud, and AWS. The firm’s multi-cloud readiness, coupled with its investments in industry accelerators, allows Infosys to implement AI in weeks rather than quarters—an increasingly valuable proposition amid rising transformation fatigue.

Institutional sentiment suggests Topaz’s modular architecture and Infosys’s disciplined cost base give it a strong edge in cost-conscious procurement environments—especially compared to firms with more layered operating structures.

How does Infosys Topaz compare with Accenture Navigator and IBM Watsonx in generative AI delivery?

While Infosys, Accenture, and IBM all offer generative AI services at scale, their delivery strategies differ significantly.

Accenture Navigator is embedded within a multi-platform operating model that includes AI copilots, delivery automation (myWizard), and integration with ERP, CX, and data lake architectures. Accenture also partners with all three major hyperscalers and delivers AI through a globally federated team model.

IBM’s Watsonx is positioned as a full-stack AI platform, with proprietary governance, model training, and RAG infrastructure. It is particularly strong in compliance-heavy sectors like healthcare, finance, and public services, but is seen as more vertically integrated and less cloud-agnostic.

Infosys’s Topaz stands out for speed, modularity, and industry alignment. Its GenAI studios provide physical proofing environments that neither Accenture nor IBM has replicated at the same scale. However, its challenge will be expanding Topaz into more complex, end-to-end transformation mandates—a space where Accenture and IBM continue to dominate due to delivery history and global enterprise account control.

Can Infosys scale Topaz into a full-stack transformation platform to match global rivals?

As Infosys expands its ambitions in the global enterprise AI market, a central question facing institutional investors is whether the Indian IT services provider can evolve Topaz from a modular AI enablement suite into a comprehensive, full-stack digital transformation platform. While Infosys has demonstrated clear success with Topaz in delivering domain-specific copilots and reusable AI components, long-term leadership in the AI services market will require greater maturity across architecture, governance, and strategic advisory.

Analysts suggest that Topaz’s future competitiveness will hinge on Infosys’s ability to integrate generative AI not just at the function level, but across enterprise-wide IT and data estates. This includes the capability to re-architect core systems around AI-native design principles, implement hybrid and multi-cloud LLM orchestration frameworks, and deliver governance models that meet the emerging standards of AI regulatory regimes in the U.S., Europe, and Asia. In this regard, Infosys will need to show it can handle cross-functional transformation mandates that span multiple business units, geographies, and regulatory jurisdictions.

To compete with Accenture’s Navigator-led engagements and IBM’s Watsonx platform deployments, Infosys may also have to strengthen its presence at the strategic advisory layer. Both Accenture and IBM have entrenched relationships at the board and C-suite levels, allowing them to shape long-term digital transformation agendas. Infosys’s ability to influence enterprise-wide AI roadmaps may depend on expanding its global consulting bench, hiring domain-focused AI advisors, and building IP-led transformation methodologies tailored to vertical-specific reinvention.

However, Infosys does hold significant structural advantages that could allow it to close this gap. Its asset-light delivery model, combined with its GenAI studio infrastructure, offers high scalability and customization without the overhead of multi-tiered operating hierarchies. This enables faster client onboarding and lower implementation friction, particularly in cost-sensitive markets. Infosys’s tight integration with hyperscalers like Microsoft, Google Cloud, and AWS also gives it the flexibility to support diverse client environments while maintaining platform neutrality.

Moreover, growing client fatigue from proof-of-concept overload is shifting enterprise preferences toward providers who can offer rapid, repeatable AI deployments that are operational from day one. This plays directly to Topaz’s strengths in modular copilots, composable APIs, and industry accelerators. Rather than building monolithic AI stacks from scratch, clients increasingly want plug-and-play generative AI capabilities that integrate with existing systems and workflows.

Infosys’s challenge will be to capitalize on this opportunity without compromising on platform ambition. To become a full-stack AI transformation partner, it will need to extend Topaz beyond workflow copilots and embed it into end-to-end modernization journeys—ranging from legacy platform rationalization and data strategy development to talent reskilling and outcome-based managed services. In this respect, further expansion into strategic consulting and systems integration will be crucial.

Still, the momentum behind Topaz is real, and its expanding portfolio of global AI deployments suggests that Infosys is no longer viewed as a fast follower in the generative AI space. If the Indian IT services firm can deepen its consulting footprint while continuing to scale its asset-based delivery model, Topaz could emerge as a serious contender in the race for AI-first enterprise transformation—challenging traditional assumptions about who leads the future of intelligent services.