India and Singapore show strong enterprise AI momentum, and some reported measures put them above global benchmarks. But the available surveys do not establish a like-for-like agentic AI adoption rate for both countries. They measure different things—from exploring autonomous agents to using AI tools and redesigning end-to-end workflows—so the evidence supports a qualified comparison, not a definitive ranking.
What do the latest surveys actually show?
The figures below indicate activity and gaps, but they are not directly comparable adoption rates: the countries, survey years, respondent groups and definitions differ.
| Source and year | Geography and respondent group | Reported result | What it measures |
|---|---|---|---|
| ServiceNow, 2026 Enterprise AI Maturity Index | Singapore; 200 senior leaders. The survey covered 4,500 senior leaders across 19 countries. | 51% reported adopting agentic AI tools, up from 22% in 2025. 10% reported using AI for autonomous end-to-end workflows. | Tool adoption and, separately, end-to-end workflow use. |
| Deloitte, 2026 India report | India respondents; sample size and respondent details are not stated in the cited findings (Deloitte, 2026). | 40% reported significant or full AI usage, compared with an approximately 28% global average. | Broad AI use across enterprise activity, not agentic AI alone. |
| Deloitte, April 2025 India perspective | Indian organisations; sample size and respondent details are not stated in the cited finding (Deloitte, April 2025). | More than 80% were exploring autonomous agents. | Exploration, not confirmed production deployment. |
| PwC India survey, 2025 | Indian domestic organisations and India-based global capability centres; sample size is not stated in the cited findings (PwC India, 2025). | 55% were building and testing early prototypes; 14% had progressed beyond early validation. | Stages in an adoption journey, not a nationwide measure of all Indian businesses. |
| Deloitte Singapore survey, 2025 | Singapore leaders; sample size and respondent details are not stated in the cited finding (Deloitte, 2025). | 14% reported mature agentic AI governance, versus a 21% global average. | Governance maturity, not adoption. |
Does this prove India and Singapore are ahead of the world?
Not on a single, consistent measure. Deloitte’s India comparison places reported significant or full AI usage above its global average, while ServiceNow reports rapid growth in Singapore respondents’ use of agentic AI tools. Those are meaningful signals, but they do not answer the same question. Broad AI use is not synonymous with agentic AI use, and using tools is not the same as deploying autonomous agents in production.
The specific India-versus-Singapore comparison behind the headline is attributed to Thoughtworks in Computer Weekly’s reporting. The underlying primary Thoughtworks report and comparable country-level figures are not available in the cited material, so that particular ranking should be treated as a reported claim rather than an independently verified head-to-head result. Computer Weekly quoted Thoughtworks chief technology officer Rachel Laycock saying, “The organisations moving fastest are integrating AI into the core of how they operate.”
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How much of the reported activity is in production?
Singapore: tools are more common than end-to-end redesign
ServiceNow’s results separate the use of agentic AI tools from applying AI to autonomous, end-to-end workflows. That distinction matters: a tool can assist an employee with a task without an organisation having redesigned the process around AI. ServiceNow APJ Innovation Officer CK Tan put it this way: “But adoption and transformation are not the same thing. Helping individuals work faster has value. Redesigning how work moves across the enterprise is where AI starts to change business outcomes.”
India: exploration and prototypes are not scaled deployment
Deloitte’s exploration finding and PwC’s prototype-stage results describe earlier points in an adoption journey. Neither establishes that the organisations concerned have put autonomous agents into routine production at scale. Deloitte’s 2026 measure is broader still: it records significant or full AI use, not agentic AI specifically.
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Deloitte India Partner Moumita Sarker noted in the 2025 perspective that many Indian organisations prefer buying AI solutions to developing them in-house, adding that “ensuring adaptability to evolving needs is a challenge.” Buying a tool may speed initial adoption, but organisations still have to determine how well it fits their systems, data and changing processes.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What should businesses watch beyond adoption rates?
For leaders, employees and anyone assessing claims about AI-led business change, a useful comparison should identify the adoption stage, survey year, respondent population, whether the measure concerns agentic AI or AI generally, and the organisation’s readiness to manage the technology. A high tool-use figure alone cannot establish durable operational change.
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- Governance: Establish who can approve, monitor and intervene in automated decisions. The Singapore governance result shows that reported adoption and mature oversight are not interchangeable.
- Data and security: Check whether systems have reliable access to the information they need and whether permissions, privacy and security controls match the intended use.
- Workforce capability: Prepare people to supervise AI-supported work, understand its limits and handle exceptions.
For consumers and workers, adoption headlines are best read as evidence of experimentation and tool uptake, not as proof that whole companies—or particular industries—have been transformed. The cited findings do not isolate financial-services adoption or establish effects on prices, jobs, investment returns or customer outcomes.
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