AI is changing the world, and consumer trust is lagging behind. This is a problem, and if your company relies on AI, you need to address it head-on. AI can’t reach its full potential if people don’t trust it. That means businesses that build AI responsibly, communicate openly, and focus on security will win. Others? Well, they’ll have a harder time convincing customers to stick around.
AI adoption is soaring, but trust is crashing
Businesses are going all in on AI. Around 83% of executives see AI as critical to their strategy (Cisco), using it for everything from automation to fraud detection. It makes operations smoother, decisions smarter, and customer experiences better.
But the issue is that trust in AI has been sliding. In 2019, global AI trust was at 62%. By 2024, it had dropped to 54% (Edelman). The U.S. saw an even bigger dip—from 50% to 35%. That’s a warning sign. The more companies push AI, the more consumers hesitate. They worry about privacy, security, and whether AI actually has their best interests in mind.
For executives, this presents a challenge. AI delivers real business value, but if consumers don’t trust it, they’ll resist. Addressing this head-on is both an ethical move, and good business.
Trust is built on transparency, privacy, and ethics
Trust is simple—deliver on expectations, be honest, and don’t abuse people’s data. But when it comes to AI, trust gets complicated. Most consumers don’t fully understand AI, so they make judgments based on how companies use it. If an AI system is clear, reliable, and respectful of privacy, people will trust it. If it’s a black box making decisions with no explanation? Not so much.
Three key factors define AI trust:
- Transparency – People need to know how AI works, what it’s doing with their data, and why it makes certain decisions.
- Privacy – Customers don’t want their data used in ways they didn’t agree to. If a company can’t guarantee strong data protection, trust disappears fast.
- Ethics – AI can amplify biases if not designed carefully. Consumers want to know that companies are making responsible choices in how AI is trained and deployed.
“Companies that explain AI clearly and use it responsibly will build trust. Those that don’t will struggle to gain consumer confidence.”
AI can build or destroy trust depending on how you use it
AI isn’t inherently good or bad—it’s a tool. It can either create trust or destroy it, depending on how it’s applied.
Take Amazon. Its AI recommendation engine personalizes shopping experiences, making them more relevant and engaging. Customers get products they actually want, and trust in Amazon grows. The result? Amazon ranked #6 on Morning Consult’s Most Trusted Brands 2024 list.
Now, look at PayPal. Its AI monitors 430 million active accounts, analyzing every transaction with hundreds of security checks in real time. The result? Fraud losses dropped 25%. AI builds trust when it protects consumers from risk.
But AI can also erode trust—deepfakes, privacy breaches, and biased decision-making are all risks. The key is understanding that AI is a double-edged sword. Use it wisely, and it strengthens relationships with customers. Use it poorly, and you’ll lose them.
Companies must take action to restore AI trust
Trust isn’t automatic and has to be earned. For AI, that means putting the right strategies in place. Here’s what companies need to do:
- Data protection first – Make security airtight. Consumers need to know their data won’t be stolen, sold, or misused.
- Explain the AI – No black-box decisions. If AI makes an important call—whether in healthcare, finance, or hiring—there needs to be a clear explanation.
- Ethical AI development – Bias in AI isn’t just a tech problem—it’s a trust problem. Build fairness into the system from the start.
- Consumer education – People fear what they don’t understand. The more businesses teach consumers about how AI works, the more they’ll trust it.
None of this can be lip service. If a company says one thing and does another, it’ll do more damage than good.
Ethical development and transparency
AI is here to stay. The companies that earn trust will be the ones that develop AI responsibly, communicate clearly, and protect consumers. It’s that simple.
Here’s what the winners will focus on:
- Responsible AI development – Build AI with clear safeguards to avoid bias, errors, and unintended consequences.
- Transparent communication – Tell consumers what AI does, what data it collects, and why it makes the decisions it does.
- Positive customer experiences – AI should enhance user experiences, not create frustration or uncertainty.
- Data protection – Strong security and ethical data use aren’t just regulatory checkboxes—they’re essential for trust.
- Follow through – Consistency is key. If a company claims to be ethical with AI but cuts corners, consumers will notice—and they won’t forget.
AI trust is earned, not given. Companies that take trust seriously will see AI unlock massive business opportunities. Those that don’t? They’ll face pushback, regulation, and lost customers.
Key executive takeaways
- Balancing innovation with trust: Rapid AI adoption is driving business innovation, yet consumer trust is declining due to privacy and data security concerns. Leaders should invest in transparent, secure AI systems to bridge this growing trust gap.
- Prioritize transparency and data protection: Clear communication about AI processes and robust data protection measures are critical. Executives must ensure that customers understand how their data is used, thereby reducing skepticism and enhancing confidence.
- Leverage AI to enhance customer experience: When implemented correctly, AI can personalize customer experiences and improve security, as seen with Amazon’s recommendations and PayPal’s fraud prevention. Decision-makers should focus on using AI to deliver tangible benefits that build loyalty and trust.
- Commit to ethical AI development: Ethical guidelines and consistent governance are essential to prevent biases and maintain consumer confidence. Leaders should integrate ethical practices into AI development and ensure ongoing training and monitoring to align technology with customer expectations.
