Key takeaways
- Nine in ten retailers are now actively using or piloting AI, but organizations taking a technology-first approach are 1.6 times more likely to miss their investment returns than those that design human-AI collaboration with genuine intent.
- As of 2024, 45% of boards had AI entirely off their governance agenda. By 2027, Gartner projects half of all business decisions will be augmented or automated by AI agents. The gap between those two facts is where retail’s accountability problem lives.
- AI is eroding trust in both directions inside retail organizations. In fact, 80% of executives are concerned colleagues are using AI to appear more productive than they are, while employer trust has fallen to 75% globally, with AI-driven transformation named as a primary driver of that decline.
Retail CEOs have made AI a strategic priority. Budgets are increasing, tools are being deployed across pricing, customer service, merchandising, and hiring, and what began as cautious experimentation has become standard operating procedure. The sector has moved fast, and deliberately so.
What most boards have not moved on is the accountability question. Not whether AI in retail is delivering value — many operations would say it is — but who is responsible when it goes wrong. When an automated pricing system makes a decision that damages a customer relationship. When a hiring tool filters out candidates it should not. When a customer service bot makes a commitment the company has no intention of honoring.
Leadership needs to be honest with itself. The question at this point is not whether AI is working, but who is responsible when it doesn’t.
Is your AI adoption an AI strategy?
Nine in ten retailers are now actively using or piloting AI. Budgets are rising, and what began as cautious experimentation two years ago, has become, today, operational infrastructure. By the measure of AI adoption in retail, the sector has moved decisively.
But investment and returns are not moving at the same pace. The gap between investment and outcome is not primarily a technology problem. According to Deloitte’s 2026 Global Human Capital Trends report, 59% of organizations are taking a technology-first approach, adding AI onto existing operations rather than redesigning how their people work alongside it. Those organizations are 1.6 times more likely to miss their AI investment returns than those that approach deployment with genuine intent around human-AI collaboration.
The difference shows up in operational outcomes. A European telecommunications company deployed an AI tool into its customer service operation without changing how staff worked with it and recorded a 5% productivity lift. When it redesigned the collaboration — new workflows, defined trust thresholds, clear escalation paths — productivity rose to 30%. Same technology but different design choices.
Who is responsible when AI goes wrong?
This is the question most retail boards have not yet structurally answered.
As of 2024, 45% of boards had AI entirely off their governance agenda. Only 14% discussed it at every meeting. Research firm Gartner projects that by 2027, half of all business decisions will be augmented or automated by AI agents.
When those decisions produce discriminatory outcomes, unauthorized commitments, commercially damaging errors, or reputational failures, accountability does not assign itself. AI systems make decisions through processes that are often impossible to trace after the fact. They operate at speeds that outpace human oversight. And board members who have not developed sufficient AI literacy cannot meaningfully govern what they cannot interrogate.
The EU AI Act now requires organizations to establish AI oversight mechanisms and maintain auditable evidence trails ahead of enforcement deadlines. Retail boards across European markets that have not built these structures are accumulating regulatory and reputational exposure simultaneously in a sector where consumer trust is the primary commercial asset.
What governance of AI in retail requires is the same discipline boards have always applied to consequential decisions: defined accountability, clear escalation paths when AI systems fail, and regular evaluation of AI’s impact on consumers, on workers, and on the brand itself.
What AI is doing to your workforce
AI is changing the relationship between employers and workers, as well as between employees themselves.
According to Deloitte, 80% of executives, managers, and workers are concerned that colleagues are using AI to appear more productive than they really are. More than a third of workers admit using AI to embellish their professional profiles. 42% say their organization rarely evaluates the impact of AI on people at all.
The result is a workplace where trust is eroding in both directions simultaneously. Leadership is losing confidence in whether it has an accurate picture of workforce performance. Workers are losing confidence in whether leadership’s AI decisions are being made with their interests in mind. The 2025 Edelman Trust Barometer found that employer trust has fallen to 75% globally, with AI-driven transformation named as a primary driver of that decline.
Retail runs on frontline human performance; on the quality of interactions between staff and customers that no algorithm can fully replicate. When workers are uncertain about their roles, their value, and whether AI is coming for their jobs, that uncertainty reaches the shop floor, the customer relationship, and ultimately the brand.
Organizations need to be explicit about where AI is being used and why, what it means for roles, and what the company’s actual position is on the relationship between human work and machine work. And leaders need to be accountable for the decisions AI is making on their behalf.
The leadership question
The retail sector is not lacking in ambition on AI adoption. The investment is real, the tools are deployed, and the momentum is not slowing.
What has not kept pace is the accountability. Who designed the relationship between your people and your machines? Who answers when an AI-driven decision causes harm|? Can the data your organization runs on be trusted? What is AI in retail doing to the people doing the work?
These are questions that cannot be deferred. Retail has never had the luxury of waiting for problems to become visible before addressing them. AI is not a different kind of challenge. It is the same one, moving faster.
