Every company now has access to the same large language models, the same cloud platforms and the same AI vendor ecosystem. When the technology itself becomes a commodity, what separates the winners from the rest? The answer is trust. 

For boards and senior leadership teams, trust in AI – how it is governed, how it is deployed and how it is communicated – is rapidly becoming the most measurable competitive advantage available. Companies that treat trust as a strategic asset are seeing faster adoption, stronger customer loyalty and higher returns on their AI investments. Those that ignore it are burning capital on tools nobody uses.

Trust Is No Longer a “Nice to Have” — It’s a Balance Sheet Issue

There is a growing body of evidence that trust directly impacts the commercial performance of AI investments. According to PwC’s 2025 Responsible AI survey, 60% of executives said responsible AI practices boosted ROI and efficiency, with 55% reporting improved customer experience and innovation. 

In its 2026 predictions, PwC also noted that only a small number of companies are currently achieving extraordinary value from AI. They also highlight that those pulling ahead are the ones who combine AI capability with robust governance and trust frameworks.

Meanwhile, the 2026 State of AI in IT report found that trust in AI increased for 62% of surveyed IT professionals year-on-year, while only 5% reported a decline. Yet just 16% of organisations fully trust AI to make and execute operational decisions autonomously. That gap between growing comfort and actual delegation of decision-making is where competitive advantage lives. Boards that close this gap faster will scale AI further and faster than their peers.

For leaders with fiduciary responsibility, this is a clear signal. Trust is not a soft metric. It is a leading indicator of adoption speed, employee engagement, and ultimately, the return on AI-related CapEx (Capital Expenditure)and OpEx (Operational Expenditure).

The Trust Gap Is a Global Challenge and a Local Opportunity

The Edelman Trust Barometer Flash Poll on AI, conducted across five major markets in late 2025, laid bare a dramatic trust divide. Trust in AI stood at 87% in China and 67% in Brazil, but dropped to just 36% in the UK and 32% in the United States. In the US, nearly three times as many people rejected the growing use of AI as embraced it.

However, what Edelman also found is that hands-on experience transforms perception. Among people who reported that AI had improved their understanding of complex ideas, trust levels rose dramatically. The takeaway for boards is straightforward: the fastest path to building trust in AI is not a policy document,  it is structured, guided exposure to the technology in a safe environment.

This is especially relevant for Irish and European businesses. In a market where regulatory scrutiny is high and public scepticism is real, companies that invest in responsible AI adoption and communicate that investment clearly can turn a perceived disadvantage into a genuine competitive moat. Trust, in this context, becomes a form of brand equity.

Why “Trustworthy AI” Must Be a Board-Level Priority

The era when AI governance was the sole concern of the CTO or data science team is over. In 2025, 72% of S&P 500 companies disclosed AI-related risks to investors, up from just 12% in 2023. That tenfold increase tells boards everything they need to know: AI risk is now a material issue for shareholders, regulators and customers alike.

The OneTrust 2025 AI-Ready Governance Report found that 90% of advanced AI adopters said AI exposed the limits of their existing governance processes. Even among organisations still experimenting, 63% reported the same strain. More than two-thirds of technology leaders admitted that governance capabilities consistently lag behind AI project timelines.

For directors and C-suite leaders, this presents both a risk and an opportunity. The risk is clear: ungoverned AI creates legal exposure, reputational damage and employee disengagement. The opportunity is equally clear: organisations that build governance into the design of their AI systems, rather than bolting it on afterwards, create a trust infrastructure that allows them to move faster, not slower.

Think of it like brakes on a racing car. The brakes do not exist to slow the car down. They exist so the driver can go faster with confidence. AI governance works the same way.

Trust as a Revenue Driver: The Commercial Case

The commercial impact of trust extends well beyond internal adoption metrics. The 2025 Edelman Trust Barometer Special Report on Brands found that 80% of consumers trust brands they use – more than they trust business, media, government, NGOs or even their employer. Trust, the report concluded, is as much of a purchase consideration as quality and price.

When applied to AI, this insight has serious implications. Customers increasingly want to know how their data is being used, whether AI is making decisions about them and what safeguards are in place. Companies that answer these questions proactively with transparency, explainability and clear accountability will win customer confidence and market share.

Google’s 2025 ROI of AI Report reinforced this point. Among executives whose organisations had deployed AI agents in production, 74% reported achieving ROI within the first year. However, the report also made clear that the organisations scaling most effectively were those that had secured executive sponsorship, built systematic deployment frameworks, and invested in the governance and trust structures that allow AI to operate at scale.

In short: AI without trust delivers pilots. AI with trust delivers transformation.