How to protect customer trust when using AI

The launch of OpenAI’s text-to-video tool Sora highlights a broader AI problem that too many marketers ignore: With so much AI-generated content out there, customers don’t know what’s authentic.

This might not seem like a big issue.

Still, your company’s reputation plays an increasingly important role in influencing consumer decisions and any missteps with AI can damage it.

This type of uncertainty isn’t just a B2C problem. Executives now find their content mixed in alongside AI-generated LinkedIn posts (often with little to no substance). As readers, we scrutinize every post more closely to see if the publisher actually included their own perspective or if they’re just churning out AI-generated junk.

Suddenly, even the insights of industry leaders are suspect. This change is making lots of people uneasy. They’re asking themselves questions like: 

• How can I trust this business or build a working relationship if I don’t even know who’s talking to me? 
• Will my interactions with them leave me feeling misled, too?

When the speaker’s credibility matters more than the content they share, it’s time to be more proactive about how you build trust with customers across every channel.

What customers think when encountering AI in your business

A business’s track record and reputation will play an increasingly important role in customer trust. Efficiency gains from AI are great, but be careful you don’t start cutting corners when it comes to quality of output — that’s not just your product or service quality, but the content you publish, which will form the early stages of your relationship with most customers.

Consider these ways customers often react at different touchpoints when AI is involved.

1. ‘Does this company actually care about me?’

Customers want to feel valued, not treated like just another transaction. Navigating a lengthy automated customer service line without problem resolution can be incredibly frustrating, leaving you feeling neglected by the business.

Delivering a high-quality product or service is the minimum. Whether it’s their first interaction with you or the 500th, one bad experience is enough to sour months or years of relationship-building with a customer.

How to get it right

Be very deliberate about where you deploy AI and how you do it. Instead of just efficiency, focus on helpfulness, anticipating customer needs and providing proactive communication. It never hurts to go the extra mile to show you value their time and business.

Fair practices, customer-centric policies and sometimes even commitment to ethical causes can all demonstrate good intentions. Still, you’ll also want to make sure any conversation or content they engage with is a positive experience.

Dig deeper: How to transform customer experience with AI

2. ‘Is this content authentic, or just AI-generated fluff?’

It’s a little test we’re all starting to do when reading content these days: wondering if the author actually wrote it. This one’s tricky because there’s sometimes a fine line between “AI helped me organize my thoughts into a post” and “I let ChatGPT do all my thinking for me.”

Getting a little writing help from AI isn’t the problem. The problem is when business leaders write posts without the originality or unique perspective required to make the content valuable. Whether it’s a blog or a LinkedIn post, you should respect your audience enough to give them something worth reading rather than posting for the sake of posting.

How to get it right

Engaging content should have your own thoughts and a point of view. If you’re using generative AI like ChatGPT for content marketing tasks such as writing your social posts, the AI isn’t going to tell you what to think (or when it does, it’s going to sound bland, unoriginal and entry-level). 

For CEOs and other business leaders, it matters even more to share in-the-moment reactions to current events or relevant industry news, demonstrating genuine engagement and insight that AI will have difficulty replicating.

This human element of thought leadership is precisely what’s missing from much of the AI-driven content out there. That’s why audiences still crave the connection found in face-to-face interactions: in-person events provide that authenticity and immediacy — you can’t fake being truly present.

Dig deeper: How generative AI is improving customer experience and service calls

3. ‘Is my data safe with this company?’

If you’re using customer data to improve your products or services, where does this risk data leakage? Do customers have control over how their data is used?

How to get it right

Between public breaches and controversies and the increasing reliance on customer data for AI and automation, safeguarding this data is incredibly important. This means implementing stronger cybersecurity measures for sensitive data, following regulations like GDPR and transparently communicating these practices to customers. 

For example, a B2B SaaS company leveraging AI for personalized marketing should outline how customer data is encrypted, stored and processed and how they ensure compliance with data privacy laws.

Dig deeper: How to build customer trust through data privacy and security

4. ‘Am I really getting help from a human?’

It’s getting harder to tell when a chatbot is really just a chatbot, but that doesn’t mean you should disguise the fact. Similarly, if you’re using AI to make decisions or recommendations, how should a customer know if the “thought process” behind those is worth trusting?

This problem comes partly because we know from experience that programs have limitations — and some are much more sophisticated than others — so we need to take their recommendations with a grain of salt. 

For example, consider those instances where Netflix keeps telling you you have a “98% match” for a new movie they’re promoting, but it looks boring. You might start ignoring their recommendations completely because their “algorithm” clearly has a different agenda than maximizing your enjoyment. 

How to get it right

Be transparent from the earliest interactions your leads might have with a chatbot on your website — nobody wants to wonder whether they’re talking to a human. Early moments like these set the tone for the rest of their interactions with your business.

Your business should not only disclose the use of AI and automation in your operations but should also explain how these technologies help you make decisions or influence customer outcomes.

For instance, if an AI system is recommending financial products or optimizing healthcare plans, you should communicate the basis of its recommendations, like the data you’re using, which factors play a role, or the AI’s learning process. 

This approach demystifies AI operations, allowing customers to understand and trust the logic behind AI-driven decisions rather than viewing them as opaque or arbitrary.

5. ‘Can I escalate this to a real person if needed?’

Even if they’re comfortable using your AI, the more important or complex a problem or decision, the more a customer will want to talk it out with a person. Chatbots and automated tools might cut down on labor, but without a human in the loop, some problems end up unsolved and customers are left frustrated

How to get it right

AI-powered chatbots can provide quick answers and self-service options but should always allow for a smooth transition to a human when complex issues arise.

On the product and service end, even when you’ve got AI doing the heavy lifting for routine tasks like processing data, a person should have the final say when you’re acting on its output or making recommendations.

How much in time savings is your brand’s reputation worth?

While it helps to move fast, the main takeaway is to avoid getting too distracted by AI when it means having less control over how customers experience you or your company.

To paraphrase Jim Collins, successful companies will thoughtfully and strategically use new technology to amplify their preexisting strengths — they don’t just adopt new tech for the sake of keeping up.

If you find yourself diving right into AI tech without a clear idea why you’re doing it and what you’re risking, you may want to take a step back and ask yourself some of these questions first:

• How can our team use automation or generative AI to enhance the things that my team does well already? What tools are best suited for what we already do well?
• How should the AI solution[s] fit into our existing tech stack and workflows?
• Will this AI technology genuinely improve the customer experience and build trust, or does it risk alienating customers?
• How will this specific AI solution directly contribute to our key business objectives (increased revenue, improved lead quality, cost savings, etc.)?
• How will we ensure the protection of customer data in compliance with industry regulations and ethical standards?
• What processes will be in place to maintain “a human in the loop,” ensuring that AI decisions are reviewed and can be overridden when necessary?

While we’re in the midst of a crisis of trust with so much driven by AI, savvy leaders will recognize the parts of their business that need to stay human and how to manage the parts that don’t. It all comes back to putting your customer first, which thankfully, isn’t such a new idea.