According to a new study by Tata Consultancy Services (TCS), only 10% of enterprises surveyed allow AI agents to make decisions without human approval across multiple functions or business areas, while 9% report that their agents can securely coordinate workflows across enterprise applications.
It found that 84% ranked productivity improvement as the leading benefit of AI investments, highlighting a gap between the value organisations report from AI-assisted work and their readiness to give AI systems greater autonomy.
Security and governance shape enterprise AI deployment
Security, risk and governance were identified as the leading factors influencing where and how enterprises develop and deploy AI, ahead of cost, speed and ease of deployment.
The findings come as organisations consider giving AI agents greater access to enterprise applications, workflows and decision-making processes. TCS said the next phase of adoption will depend on controls that determine where human oversight is required and where AI can be given greater authority.
Enterprises assess AI costs and resilience
The study found that 39% of enterprises are still assessing whether AI initiatives deliver sufficient value relative to token and compute costs. It also found that 90% of respondents consider model independence important in AI investment decisions.
However, only 7% reported having organisation-wide plans to maintain continuity when switching AI providers. Meanwhile, 34% identified AI sovereignty-related requirements, including control over data location, model choice and compliance, as a high or very high organisational risk.
The concern was more pronounced in Europe, where 43% of respondents cited AI sovereignty as a high or very high risk.
Fragmented knowledge remains a barrier
The survey found that 44% of respondents said important business knowledge remained embedded in employees or fragmented documentation, potentially limiting AI systems’ access to consistent enterprise context.
Open-source AI is also being adopted for selected use cases, with 46% of respondents reporting targeted deployment. The study additionally found that the share of leaders who said it was too early to determine AI’s effect on jobs rose from 4% in 2024 to 19% in 2026.
Productivity was the most commonly cited source of AI value, followed by improvements in customer experience and the development of new products or services.
Regional priorities differ
The study identified differences in enterprise AI priorities across regions. In North America, 15% of respondents said AI was treated as a strategic enterprise capability. Europe reported a stronger focus on AI sovereignty, while the UK and Ireland showed comparatively higher levels of AI continuity planning and governance integration.
TCS said the findings point to a shift from AI systems that assist employees towards systems that can take on more autonomous actions, with security and governance becoming central to that transition.