As AI systems become more autonomous, experts highlight the importance of tailored governance frameworks and transparency to ensure safety and trust, with Gartner warning of potential enterprise failures from uniform controls.
Trust, governance and clearly defined safeguards are becoming central to the next phase of artificial intelligence as businesses move towards agentic systems that can act with limited human oversight, an Axis Max Life Insurance executive said at the 3rd India International Fintech Festival in New Delhi. Sanjay Thawakar, the insurer’s head of AI, data, innovation and BIIG, said the conversation has shifted from conventional automation to AI agents and agentic commerce, where the key question is whether consumers and companies can safely rely on software to make decisions and carry them out.
Thawakar said that confidence in such systems will depend on how much authority they are given, how transparent their decision-making is and what kinds of transactions they are allowed to complete. He argued that the governance layer around AI will matter as much as the technology itself, with checks and balances needed to make autonomous systems accountable before they are deployed at scale.
His comments echo a warning from Gartner, which said in May that applying the same governance model to every AI agent can cause enterprise failures. The research firm predicted that by 2027, 40% of enterprises will demote or shut down autonomous AI agents after governance gaps emerge only once the systems are already in production. Gartner said companies need a proportional approach that matches controls to each agent’s autonomy level and trust boundary.
Thawakar also framed cybersecurity as one part of a broader risk-and-governance structure, particularly as agents begin interacting with the open web. Beyond technical controls, he said organisations will need to manage how humans and AI systems work alongside one another, train staff for new workflows and accept that routine tasks will increasingly be handled by machines, leaving workers to focus on higher-value work.
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