Exclusive Industry Insights 2026

Many organisations are stalling as pilots fail to scale, blocked by fragmented data, unclear ownership, outdated operating models, and slow adoption. And the risk is rising: up to 40% of agentic AI initiatives could fail by 2028 amid unclear value, rising costs, weak governance, and tightening regulation like the EU AI Act.

An easy infographic that covers all of the governance-based sessions at the Agentic Transformation Summit.

In this exclusive interview, Ramsundar Subramanian, AI Lead – Internal Controls over Financial Reporting at Equinor, shares how organisations can balance AI-driven innovation with the controls needed to maintain trust, compliance, and financial integrity. He explains why governance must be designed into agentic AI from the start, and how organisations can enable experimentation without losing oversight.

As agentic AI becomes increasingly autonomous, Ramsundar also explores the importance of clear accountability, robust data foundations, and governance frameworks that support sustainable adoption at scale.

Download to learn more about:

• Governance by Design: Embed risk management, human review, and audit requirements before development begins
• Accountability at Scale: Maintain clear decision rights and human ownership in AI-assisted workflows
• Balancing Innovation & Control: Enable experimentation while preventing governance gaps and unmanaged risk
• Auditability & Trust: Ensure AI outputs are transparent, traceable, and defensible under scrutiny
• Data Foundations for Agentic AI: Understand why clean, connected data is critical for successful deployment

Agentic AI is not just about autonomy, it's about operating confidently in environments where every decision must be explainable, accountable, and trusted. Download the interview to learn how to scale agentic AI responsibly while maintaining control, compliance, and business value.

Scaling Agentic AI from experimentation to enterprise impact requires more than innovation, it demands strong governance, clear decision rights, and new ways of measuring value.

In this exclusive interview, Phani Kaligotla, Vice President, Global Product AI & Data Strategy, Mastercard, shares how to balance decentralised experimentation with centralised control, enabling innovation at the edges while maintaining enterprise-wide standards.

As agentic AI evolves into autonomous decision-making, Phani also explores how organisations can move beyond efficiency metrics to focus on outcome-driven value, trust, and real business impact.

Download to learn more about:

• Governance at Scale: Enable grassroots experimentation within clear guardrails, with reusable frameworks that make the safe path the fastest path
• Measuring True Value: Move beyond efficiency to outcome-based metrics like decision quality, customer impact, and business performance
• Decision Rights & Accountability: Define what agents can decide, what must be escalated, and how humans retain control over critical outcomes
• Trust & Control by Design: Embed auditability, traceability, and policy enforcement directly into AI workflows from day one
• From Pilot to Enterprise: Learn how to transition agentic AI from isolated use cases to scalable, organisation-wide capability

Agentic AI is not just about automation, it's about transforming how decisions are made, how value is created, and how organisations operate at scale. Download the interview to learn how to govern confidently, measure what matters, and unlock real enterprise impact with AI that acts.

While organisations are accelerating Agentic AI deployment, most leadership teams are still operating without the governance structures, accountability models, and regulatory readiness required to scale autonomous systems safely.

The challenge is no longer whether to adopt agentic AI. It is whether your organisation can maintain control, demonstrate accountability, satisfy regulators, and scale business value fast enough to stay competitive.

With the EU AI Act now in force, alongside the EU Data Act and emerging CEN/CENELEC standards, governance has become one of the defining leadership challenges of the next decade. This fact sheet is designed specifically for AI, transformation, data, technology, and risk leaders navigating that shift.

With expert commentary from Elena Maran, Committee Member, External Expert Advisor, CEN WG4, she sheds a practical light and gives exclusive advice on the steps leaders need to take to prepare for upcoming challenges regarding regulations, governance, and Agentic AI deployment.

Download to learn more about:

• What the EU AI Act, EU Data Act, and emerging European standards mean in practice for agentic AI deployment and governance
• Where organisations are most exposed today, from accountability gaps and auditability failures to behavioural drift and fragmented oversight
• The practical governance, target operating model, and control frameworks required to scale agentic AI confidently across the enterprise

The organisations that lead in the agentic era will not be those that deploy fastest. They will be the organisations that build trusted, regulator-ready, enterprise-grade agentic systems before everyone else.

Download the fact sheet to benchmark your readiness, identify governance gaps, and build a 12-month roadmap for scaling agentic AI with confidence.

As Agentic AI becomes embedded across enterprise workflows, the challenge for leaders has fundamentally shifted. It's no longer about if you use AI; it's about how you stay in control of systems that can act on your behalf.

But here's the real challenge: Most governance models were built for static systems, not autonomous agents that learn, adapt, and make decisions in real time. This report gives you clear and actionable insights for governing Agentic AI in the real world, helping you shift from reactive compliance to confident, scalable control.

Download to learn more about:

• How to navigate complex, fast-evolving AI regulations: Understand what global frameworks like the EU AI Act and U.S. policies mean in practice and how to align your organisation before enforcement catches up
• How to design governance for autonomous systems, not just models: Learn how to implement real-time controls, human oversight, and auditability for AI agents that act, interact, and make decisions independently
• How to reduce risk while still scaling innovation: Discover practical frameworks that help you balance compliance, accountability, and performance without slowing down transformation

In the Agentic Age, governance isn't just a compliance exercise; it's a strategic capability. Download the report now to gain the clarity, frameworks, and confidence you need to lead in a world where AI doesn't just support decisions – it makes them.