Infosys Topaz Automates 30% of IT Operations

Infosys, one of the world's largest IT services companies, has announced that its Topaz AI platform now automates approximately 30 percent of IT operations across its client engagements. The milestone marks a significant leap in enterprise AI adoption and raises fresh questions about how generative AI is reshaping the $1.3 trillion global IT services industry.

The Bangalore-headquartered giant, which employs over 300,000 people worldwide and serves major clients including Goldman Sachs, Verizon, and Daimler, has positioned Topaz as its flagship AI-first offering since launching the platform in early 2023. With this latest achievement, Infosys joins a growing cohort of IT services firms — including Accenture, TCS, and Wipro — racing to embed AI deeply into their delivery models.

Key Facts at a Glance

• 30% automation milestone: Infosys Topaz now automates roughly one-third of routine IT operations tasks for enterprise clients
• Built on generative AI: The platform leverages large language models, computer vision, and proprietary AI assets trained on Infosys' decades of domain expertise
• 12,000+ AI use cases: Infosys claims to have cataloged over 12,000 potential AI use cases across industries including banking, healthcare, retail, and manufacturing
• $2 billion+ in AI revenue: Industry analysts estimate Infosys' AI-related services could generate more than $2 billion annually by FY2026
• 150+ enterprise clients: Topaz is reportedly deployed across more than 150 major enterprise accounts globally
• Cost reduction target: Clients using Topaz have reported operational cost savings ranging from 20% to 40% in automated workflows

How Topaz Transforms Traditional IT Operations

Infosys Topaz is not a single tool but rather an integrated suite of AI capabilities layered across the company's entire service delivery stack. At its core, the platform combines generative AI, machine learning, and knowledge graph technologies to automate tasks that previously required significant human intervention.

The platform handles a wide range of IT operations functions. These include incident management, code generation and testing, infrastructure monitoring, and service desk automation. Unlike earlier rule-based automation tools like UiPath or Automation Anywhere, Topaz uses contextual understanding powered by large language models to handle ambiguous, unstructured scenarios.

For example, when a client's server experiences an anomaly, Topaz can analyze log files, correlate patterns across systems, identify the root cause, and recommend — or even execute — a fix. This kind of autonomous remediation previously required a team of skilled engineers working through manual runbooks.

The Technical Architecture Behind the Platform

Infosys has built Topaz on a modular architecture that integrates with major cloud platforms including Microsoft Azure, AWS, and Google Cloud. The platform utilizes a combination of open-source and proprietary models, including fine-tuned versions of models from OpenAI and Meta's Llama family.

Key technical components include:

• Topaz Responsible AI: A governance layer that ensures AI outputs meet ethical standards and comply with regulations like the EU AI Act
• Infosys Nia: The company's legacy AI engine, now integrated as a data analytics backbone within Topaz
• Connected Intelligence: A knowledge graph system that maps enterprise data relationships across siloed systems
• AI Amplifier Kits: Pre-built solution accelerators for specific industries, reducing deployment time from months to weeks

The platform's ability to learn from each client engagement creates a compounding advantage. Every resolved incident, every automated workflow, and every code review adds to the system's collective intelligence — a concept Infosys calls 'living AI.'

Industry Context: The AI Arms Race in IT Services

The IT services sector is undergoing its most dramatic transformation since the shift to cloud computing. Every major player is making aggressive AI bets, and the 30% automation figure from Infosys puts it in a competitive position against rivals.

Accenture has committed $3 billion to AI investments and recently acquired multiple AI-focused firms. Tata Consultancy Services (TCS) launched its own generative AI platform and reports AI-related deal wins worth over $900 million. Wipro has partnered extensively with Microsoft and Google to embed copilot-style AI into its services.

Compared to these competitors, Infosys' 30% automation claim is among the most concrete metrics any major IT services firm has publicly shared. While Accenture speaks broadly about AI transformation and TCS focuses on deal pipeline numbers, Infosys has tied its narrative directly to measurable operational outcomes.

The broader market validates this direction. According to Gartner, by 2027, approximately 70% of IT service management tasks will be partially or fully automated using AI — up from roughly 25% in 2023. Infosys appears to be tracking ahead of this industry curve.

What This Means for Enterprise Clients

For businesses that rely on IT services providers, the implications are substantial. The 30% automation figure translates directly into faster incident resolution, fewer human errors, and significantly lower operational costs.

However, the shift also demands a new kind of client-vendor relationship. Enterprises must be willing to share more data, grant AI systems deeper access to production environments, and trust automated decision-making in critical workflows. This requires robust governance frameworks and clear accountability structures.

Practical impacts for enterprise decision-makers include:

• Reduced headcount dependency: Companies can scale IT operations without proportionally scaling teams
• Faster time to resolution: Automated incident handling cuts mean-time-to-repair (MTTR) by an estimated 40-60%
• Predictive maintenance: AI-driven monitoring identifies issues before they cause outages
• Compliance automation: Regulatory reporting and audit trail generation become largely automated
• Skill shift requirements: Internal IT teams need upskilling to manage and oversee AI-driven operations rather than perform manual tasks

For CIOs and CTOs, the message is clear: the value proposition of IT outsourcing is fundamentally changing from labor arbitrage to intelligence arbitrage.

The Workforce Question Looms Large

The elephant in the room remains workforce impact. If 30% of IT operations are already automated, what happens to the engineers who previously performed those tasks? Infosys CEO Salil Parekh has repeatedly stated that the company views AI as an augmentation tool rather than a replacement mechanism.

Infosys reports it has retrained over 250,000 employees on AI-related skills through its internal learning platform. The company argues that automation frees up human talent for higher-value activities such as solution architecture, client advisory, and innovation work.

Yet industry analysts remain cautious. Forrester Research projects that AI automation could displace up to 30% of IT services jobs globally by 2030, even as it creates new roles in AI engineering, prompt design, and model governance. The net effect on employment remains hotly debated.

Looking Ahead: The Road to 50% Automation

Infosys has signaled that its next target is 50% automation of IT operations by the end of fiscal year 2027. Achieving this will require advances in several areas, including multi-agent AI systems that can coordinate complex workflows autonomously and improved reasoning capabilities in foundation models.

The company is also investing heavily in agentic AI — autonomous AI agents that can plan, execute, and iterate on multi-step tasks without human oversight. This represents the next frontier beyond simple automation and could fundamentally alter how IT services are delivered.

Several key developments to watch in the coming months:

• Expansion of Topaz into business process outsourcing (BPO), extending automation beyond IT into finance, HR, and procurement functions
• Deeper integration with enterprise copilots from Microsoft, Google, and Salesforce
• Launch of industry-specific AI models fine-tuned for banking compliance, healthcare diagnostics, and supply chain optimization
• Potential strategic acquisitions of AI startups to accelerate capability building

The 30% milestone is significant, but it is also just the beginning. As large language models become more capable and enterprise data infrastructure matures, the ceiling for AI-driven automation will continue to rise. For Infosys and its competitors, the race is no longer about whether to adopt AI — it is about how fast they can scale it across every client engagement.

In an industry historically built on human capital, the company that cracks intelligent automation at scale will define the next era of enterprise IT. With Topaz, Infosys is making a credible bid for that position.