(26 August 2026 – Global) As AI continues to evolve, leaders are now asking difficult questions: Where should AI make decisions? What are the governing criteria when AI goes wrong? Agentic AI is the next step in that journey.
Enterprise investment reflects this shift. Tech Mahindra’s Bank of Tomorrow report shows that 81 percent of banks now have dedicated AI budgets. That figure is projected to reach 17 percent of total IT spending by 2028. Beyond banking, 44 percent of finance teams expect to use agentic AI in 2026, 600 percent up from the prior year.
This also shows that organisations are preparing for AI systems with greater operational responsibility. They are redefining leadership, governance, and culture to support responsible autonomy across the enterprise.
“To better understand these realities, Tech Mahindra commissioned East & Partners to directly interview 150 senior banking executives across APAC, the Americas, Europe, and the Nordics. The analysis reveals how banks are currently approaching agentic AI adoption, where they are directing their investments and, most importantly, what truly separates the leaders from the laggards” stated Tech Mahindra Practice Head-Banking & Financial Services, Saurabh Agrawal.
“Despite the clear potential of agentic AI, banks face several significant hurdles in adoption. The most common barriers include uncertain ROI and high upfront investments, a shortage of responsible AI implementation expertise, ambiguous data availability and quality, inadequate security, and a lack of talent and skill sets required for AI adoption, all of which hinder rapid technological advancement in banks” commented Tech Mahindra Head, AI and Digital Transformation, Financial Services, Gopal Parasnis.
“The convergence of agentic AI, sustainable quantum computing, and real-time data architectures will shape the next decade. Organizations will need clear principles for how autonomous systems participate in their business. In our experience, these questions are easier to answer when governance is built before the first agent goes into production. Define decision boundaries, accountability, escalation paths, and traceability before adding controls to systems already running. The price is far less than rebuilding trust after an operational failure would cost.”
Enterprises that approach agentic AI on platforms like AWS with clarity, responsibility, and conviction will architect the next era of learning, adaptation, and competition. They’ll write the rules that everyone else will follow.