Earning Trust in the Age of AI: From Employees to the Boardroom

This November will mark three years since ChatGPT entered the mainstream. In that short time, for many organizations, Generative AI has shifted from an experimental phase into a boardroom agenda. More companies are disclosing board oversight of AI, treating it as a governance topic, and elevating it as a strategic initiative.

For many boards and executives, the real question isn't simply whether to engage with AI, but whether stakeholders will trust the way you do it.

That challenge touches every level of the enterprise: employees must trust leadership's vision, clients and partners must trust the safeguards behind AI-enabled offerings, and boards must trust that adoption is being guided with clarity and accountability. In the age of AI, it is the foundation on which adoption and long-term impact will rest.

As the World Economic Forum observes in its piece, Rebuilding trust in the Intelligence Age, it's essential for leadership to prioritize building trust across all levels of their organization...or risk undermining transformation.

Building Employee Trust in AI Adoption

Trust is a two-way exchange. Employees need confidence in leadership's plan for integrating AI and to believe there are structures in place such as policies, training and safeguards that enable them to use it responsibly. At the same time, leadership depends on employees to adapt workflows, experiment, and apply judgement in ways that align with the broader strategy.

Change management is critical here. As I noted in What AI is Really Asking of Business Leaders: From Talent to Trust to Transformation, AI adoption isn't simply about adding new tools, it requires new ways of working and supporting teams through transition. Organizations that fail to invest in this will find employees hesitant or resistant, putting AI initiatives at risk of being underused, or misapplied, likely resulting in missed opportunities, attrition, process inefficiencies, and competitive decline as peers accelerate ahead. Trust isn't built through pressure, but through preparation, consistent communication and meaningful support.

At Yale's Responsible AI in Global Business 2025 conference, which I attended last April, one theme came through across panels, ranging from workforce adoption to governance discussions: trust cannot be an afterthought. Workforce leaders cautioned that employees are often left out of AI strategy conversations until late in the process, undermining both value and trust. Speakers reinforced that leadership must treat trust as a core design principle, woven into both strategy and oversight.

Without transparency, accountability and oversight, AI risks eroding rather than building trust.

Earning Client and Customer Trust in Responsible AI

Clients and customers, whether B2B or B2C, have grown wary of shiny tools and overhyped numbers. They want evidence that your teams are equipped to navigate AI responsibly, and that your offerings balance innovation with safeguards for privacy, security, and accountability, especially in highly regulated spaces.

As the KPMG Global Trust in AI report makes clear, trust in AI influences adoption at every level. And, Pew research's survey shows Americans remain cautious about AI's impact on people and society. For businesses, this means trust must be actively earned through transparency, responsible governance, clear communication and demonstration of value.

From our own experience over the past three years, we've seen that dynamic play out, not only in how organizations consider moving from experimentation to adoption, but in some cases, whether experimentation is allowed at all. Trust becomes the deciding factor in creating the conditions for responsible exploration.

Partner and Vendor Trust in AI Ecosystems

No company can advance AI in isolation. Partners, vendors, and platforms must also be part of the trust equation.

Leaders need confidence that their ecosystem is anticipating AI's impacts, adapting business models responsibly, and safeguarding data and operations.

Trust here is twofold: confidence that partners are aligned strategically and confidence that technology providers have embedded resilience, compliance, and security. Without this, even the most sophisticated internal strategies can fail.

Leadership Trust and AI Governance

Leadership plays a defining role in shaping trust. Boards and executives are being asked to make AI decisions that will shape business models, competitive positioning, and risk exposure for years to come. In the article, The Enduring Power of Professional Relationships: A 35 year Perspective, my business partner emphasized that trust sustains organizations across cycles of change. That truth has never been more critical than it is today.

Yet, hype can distort trust. The often repeated claim that 95% of AI pilots fail has taken a life of its own, often cited without nuance. As Wharton professor Ethan Mollick has pointed out, and others remind us, that figure is based on a small sample with vague definitions of success.

Pilots by design, involve trial and error and some will fail, that is the point. What matters is whether leadership creates the conditions to learn from those pilots, apply governance rigor, and build pathways to adoption where it makes sense. This is where governance frameworks and oversight become not just procedural, but trust-building mechanisms.

Embedding Trust in AI Capabilities for Long-Term Impact

As we've seen through our own work, trust cannot be treated as an afterthought. By embedding governance frameworks, aligning adoption with strategy, and focusing on measurable outcomes, organizations can build capabilities that stakeholders can believe in. These principles are at the core of our AI Strategic Suite.

AI is not a single product or tool, it is a capability to cultivate. For some organizations, that journey has already begun; for others, it is still taking shape. What will define success is not the speed of the adoption, but the degree of trust earned along the way.

And in the Age of AI, cultivating trust may be the most important responsibility of all.

~Lynda Koster

Cofounder & Managing Partner at Growthential

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The content in this article reflects our professional experience, application, and research. AI tools supported development primarily through research, editing, and summarization, while insights, and recommendations are grounded in our own expertise.