ServiceNow Launches AI Workflow Factory in India as Enterprises Struggle to Move Beyond AI Pilots

ServiceNow has launched two new products in India aimed at helping large companies move artificial intelligence out of pilot projects and into day-to-day operations, as the US enterprise software group deepens its bet on one of its fastest-growing markets.

Announced at the company's World Forum in Mumbai, AI Workflow Factory combines process mining, autonomous engineering and application development into what ServiceNow describes as a continuous loop for finding, building and improving AI-powered workflows. A second product, Autonomous Engineer, brings agent-based automation to the software development cycle itself, from planning through to building and testing.

Both sit alongside AI Control Tower, an existing ServiceNow offering that gives enterprises a central place to discover, monitor and govern the AI agents and workflows running across their technology estate. AI Workflow Factory is available globally, while Autonomous Engineer is in early access.

The pilot problem

The launches are aimed squarely at a problem that has become familiar in boardrooms worldwide: enterprises have run hundreds of generative AI experiments, but relatively few have turned into systems that change how work is done at scale. Fragmented legacy infrastructure, unclear ownership and concerns about risk often stall projects after the proof-of-concept stage.

ServiceNow's pitch is that the bottleneck lies less in AI models than in the process and governance layers around them. Process mining identifies where work actually flows and where it gets stuck; the Workflow Factory then helps teams design and deploy AI-driven fixes; and the Control Tower provides oversight of what the resulting agents are doing. The company says the approach can help enterprises scale operations in days rather than months.

Indian data from the company suggests the governance gap is real. Only 22 per cent of Indian enterprises have AI testing, auditing and risk-assessment processes in place, according to a ServiceNow AI maturity assessment, even as enterprise AI investment in the country grew 119 per cent in a year, according to its 2026 Enterprise AI Maturity Index.

Autonomous Engineer addresses a related bottleneck. Many AI projects stall not because the idea is weak but because the engineering work of integrating with old systems, writing tests and deploying changes takes too long. By applying agents to the planning, building and testing steps of software development, ServiceNow aims to shorten the time between identifying an improvement and putting it into production, while keeping a record of what the agents changed and why.

That combination, rapidly rising spending alongside immature controls, is precisely the environment in which vendors that sell governance and orchestration see an opening. It is also one that regulators are watching, as financial-services and healthcare supervisors in several countries have begun to set expectations for how companies test and monitor AI systems.

Why India matters to ServiceNow

India plays a dual role for ServiceNow: it is both a growing market and a large part of its engineering base. Sumeet Mathur leads the company's India technology and business centre, which contributes to product development for its global platform.

The country is also home to more than 2,100 global capability centres (GCCs) employing about 2.35 million people, according to industry estimates cited by the company. These captive technology and operations hubs, run by multinational banks, retailers, pharmaceutical groups and manufacturers, are among the heaviest users of enterprise workflow software and are increasingly being asked by their parent companies to lead AI adoption.

ServiceNow also relies on a large partner ecosystem in India. Around 30,000 engineers work on its platform across major systems integrators including Accenture, Deloitte, KPMG and EY, implementing and customising ServiceNow products for clients worldwide.

Financial services remains the company's strongest vertical in India, while healthcare and life sciences, consumer and retail businesses and the public sector are other priorities. In July, ServiceNow invested $40 million in BUSINESSNEXT, a Delhi NCR-based software company serving banks and financial institutions, deepening its presence in that sector.

GCCs are particularly important to the AI story. Many began life as cost-saving back offices but have evolved into centres that own products, platforms and transformation programmes for their parent companies. When a global bank or retailer decides to automate a process with AI agents, the engineering and operations teams doing that work are frequently in Bengaluru, Hyderabad, Pune or Chennai. Selling to those teams, and training them on its platform, gives ServiceNow influence over decisions taken far beyond India.

Amit Zavery, ServiceNow's president, chief operating officer and chief product officer, has positioned the company's AI strategy around the idea that enterprises need a single platform to coordinate agents built by different vendors, rather than a proliferation of disconnected tools.

Security, identity and the agent era

The India launch also reflects how security and identity have become central to enterprise AI. As companies deploy autonomous agents that can take actions inside business systems, they need to know which agents exist, what they can access and what they are doing. ServiceNow's security business already generates more than $1 billion in annual contract value globally, and the company has acquired identity-security start-up Veza, co-founded by Tarun Thakur, to strengthen its capabilities in managing access across human and machine identities.

Recent incidents have highlighted the stakes. Reports in recent weeks of AI agents operating beyond their intended boundaries on public internet services have sharpened questions about oversight, and enterprise buyers are increasingly asking vendors how they prevent automated systems from causing unintended damage.

ServiceNow faces competition on several fronts, from hyperscale cloud providers building agent platforms into their infrastructure to enterprise software rivals embedding AI into their own applications, and from a fast-growing crop of start-ups. Its argument is that workflow and governance, the plumbing of how work moves through an organisation, will matter as much as model capability as AI becomes embedded in operations.

Pricing and measurable return on investment will be the deciding factors for many buyers. Enterprise AI budgets are rising, but chief financial officers are increasingly asking for evidence that pilots produce savings or revenue before approving wider deployments. Vendors that can show clear before-and-after metrics on processes such as IT service management, customer service or employee onboarding will be best placed to convert interest into contracts.

For Indian enterprises and GCCs, the launches add to a growing set of tools for scaling AI responsibly. Whether they translate into measurable productivity gains will depend less on the software than on how organisations redesign their processes, train their people and decide which decisions they are prepared to hand to machines.