Guest post by Cathy Mauzaize, President, Europe, Middle East and Africa (EMEA) at ServiceNow

As businesses shift from AI experimentation to full-scale implementation, bridging the AI trust gap has never been more urgent. While AI-driven innovations drive productivity, they also introduce new uncertainties. Executives across the C-suite must take the lead, embracing change and continuous learning.

In EMEA, we are at a pivotal moment. Governments and business leaders alike are looking to ensure the benefits of agentic AI are maximised responsibly. As intelligent agents become embedded across front and back-offices, trust and accountability remain top priorities. Governance isn't just IT's responsibility - it requires active leadership from the entire C-suite.

As global AI regulations tighten, clear governance can ensure AI is deployed transparently, ethically, and securely. AI decision-making must be explainable and fair to earn trust from employees, customers, and stakeholders. This trust doesn't just happen - it's built by active commitment, which business leaders must champion from the top down.

Attitudes towards AI are shifting

The dramatic rise in the use of generative AI and agentic AI has raised valid concerns around security, data privacy, regulatory compliance, and even the risk of employee over-reliance on AI, at the expense of human judgment. The key is balance: pairing the speed of AI with the empathy of human insight.

ServiceNow's 2025 Consumer Voice Report shows how attitudes are evolving. Today, only a fraction of consumers in EMEA trust AI to handle a suspicious transaction. Yet, in the next three years, 33% say they would trust AI in the same scenario. Growing confidence signals greater comfort with AI handling critical tasks. Crucially, increased trust doesn't remove the need for human oversight. This isn't a choice of one over the other. AI and humans thrive when working together seamlessly, with leaders setting the direction for integrating AI effectively into workflows.

Trust in AI starts with data

For AI to be effective and trusted, it must be built on a solid foundation of clean, reliable data. I've seen this happen time and again over the past two years with proof-of-concept projects. Without strong data management that ensures accuracy, fairness, and relevance, AI will deliver weak outcomes - and take longer to deliver value.

Meanwhile, users trust AI more when they understand how data is used and how decisions are made. However, biased data can lead to biased results, eroding confidence. By taking the lead in identifying bias and maintaining oversight, leaders ensure AI operates responsibly across both teams and data flows.

Transparency shouldn't stop at internal audiences. Communicating clearly with customers about how AI processes data helps foster long-term trust and ensures that business impact is fully understood. Innovative leaders put governance and orchestration at the heart of AI adoption, establishing transparency as a core component of their business transformation.

Leadership-led AI

AI has the power to transform businesses, offering new ways to solve real-world challenges. This isn't some future promise. AI agents are already delivering tangible results today. One utility provider I recently met in the Middle East is a great example - they're exploring how to leverage AI agents to automate billing dispute resolution by analysing historical consumption data, recommending solutions, and triggering downstream actions. The result: faster resolution times, higher customer satisfaction, and reduced operational costs. Given the tangible value, it's no surprise that IDC projects that, by 2025, 50% of organisations will use enterprise AI agents configured for specific business tasks.

Yet, the difference between unlocking AI's full value and falling short comes down to leadership.

The path to success starts with leadership buy-in and investment in innovations that enable centralised, transparent, a...