Consumer trust in AI: Achievable or out of reach?

For marketing leaders, the merits of experimenting with AI to support campaigns are numerous. However, AI is not only changing the way we execute campaigns but the foundations of consumer relationships.

Edelman’s recent Trust Barometer Flash Poll, suggests that nonacceptance of AI outweighs enthusiasm, with 46% of UK respondents rejecting it and 71% of those who distrust AI feel it’s being ‘forced upon them’. Our own research into UK workers’ attitudes towards AI found that overwhelm persists even as optimism grows, with 61% still feeling unable to keep pace. Dependency on AI tools was the top concern, cited by 42% of respondents. PwC’s Trust in AI studies also show that many consumers are concerned about AI’s influence on their decisions while continuing to use AI-powered systems daily.

These findings are both a warning and an opportunity for marketers. Those organisations that actively cultivate trust through transparency, fairness and respect for autonomy will strengthen consumer relationships and gain long-term advantage. Those that don’t, will face disengagement, scrutiny and reputational harm.

Why trust must come first

Consumers no longer evaluate the tangible product or service alone when making a decision. The use of AI to deliver differentiation has led consumers to question everything: from whether the associated recommendations are genuine through to the reliability of rankings and prices.

Rather than starting from a default position of trust, consumers are sceptical and just as likely to consider an organisation’s motives as well as the value of the recommendation. And this scepticism is not misplaced. When people perceive AI outputs as biased or unfair, their willingness to rely on those systems declines and brand engagement may suffer.

As well as converting browsers into buyers, building trust has additional benefits. Consumers who feel fairly treated are more willing to share data. That data improves the performance of marketing models, which in turn enhances the experience and strengthens loyalty. But the impact of bad experiences can cascade just as quickly. A single high-profile incident can undo years of careful brand building in seconds as well as invite regulatory attention.

Practical actions for marketing leaders to gain consumer trust

Building and maintaining consumer trust in AI requires more than technical capability. It calls for a strategic approach while preserving consumer integrity. To support this shift, there are some fundamental actions for marketing leaders to consider.

• Establish visible governance with authority

Set up AI governance structures that include external voices, clear responsibilities and escalation powers. Publish the remit and membership to demonstrate seriousness and strengthen stakeholder confidence.

• Position AI as a human-in-the-loop

Make it clear that AI is designed to augment, not replace, expert judgment. Indicate where and how human review takes place, especially for consequential decisions. This will help consumers benefit from AI efficiency while maintaining their connection to the decision process.

• Provide consumer-facing model cards

The concept of ‘model cards’, as used by Google to provide simple, structured information overviews, can help translate the tech into plain language. Summarise what the system does, what data it uses, its limitations, how it is monitored and how consumers can challenge a decision.

• Redesign consent mechanisms

Move beyond static terms and conditions to dynamic, granular consent. Provide clear choices about how data is used for training, prediction and sharing. Show the difference that opting in or out makes to the experience.

• Implement comprehensive trust measurement

Traditional metrics such as Net Promoter Score do not capture AI-specific drivers of trust. Add measures for perceived fairness, clarity of explanations and preservation of autonomy. Track how quickly incidents are acknowledged and resolved.

• Communicate limits alongside benefits

Be transparent about what the system can and cannot do, and how errors are mitigated to strengthen trust. Including limitation statements in customer communications helps set expectations and demonstrates maturity.

• Build in decision reversibility

Ensure consumers can easily undo, modify or override AI recommendations to help maintain confidence and a sense of control.

AI is reshaping consumer trust and decision-making in profound ways. For organisations to thrive, they must understand that trust is not a simple asset to maximise, but a nuanced relationship to cultivate and maintain. This means building systems that empower consumers through AI's capabilities while preserving their sense of ownership over choices.