BEYOND VIRTUAL

While businesses are eager to adopt AI to personalize, predict, and perform, customers are growing more cautious. They’re asking tougher questions: Where is my data going? Who decides what I see? Can I trust a machine to make fair choices?

And they’re right to ask.

A recent study shows that 64% of customers would prefer companies not to use AI in customer service, and 53% say they’d consider switching to a competitor that doesn’t rely on AI. It’s an interesting dilemma because customers want quick responses and 24/7 availability, yet they’re uneasy about bots making decisions or handling sensitive data.

So how do companies find a balance between delivering the speed customers want and maintaining the trust they expect?

The answer lies in transparency and thoughtful integration. Some experts say that businesses that communicate when and how AI is being used and give customers the option to connect with a human when needed tend to build stronger trust. 

Feature Story

Customer Trust Is the New Currency

Trust has quietly become the most valuable currency in business. You can have the most advanced AI tools on the planet, but if your customers do not feel comfortable with how you are using them, you are already losing ground.

Take McDonald’s, for example. In 2024, the company ended its AI-driven drive-thru pilot with IBM after months of mixed customer reviews. The idea was smart on paper: use voice-activated AI to speed up service and personalize orders. But in practice, it did not quite land.

Customers began posting videos of the AI getting orders wrong, sometimes hilariously wrong. Fries added instead of shakes. Ten nuggets when they wanted two. It became a social media moment, but not the kind brands hope for. Instead of feeling impressed by innovation, people felt unheard. They did not want to argue with a robot over a burger. They wanted a quick, accurate, human interaction.

McDonald’s eventually paused the program and acknowledged that maybe the tech was not quite ready, or maybe the customers were not ready to trust it yet.

Companies that push AI without listening to feedback risk creating technology that feels cold and transactional. But when they slow down, communicate openly, and involve customers in the process, trust builds naturally.

Customers do not expect perfection. They expect honesty. And in the AI era, that is what separates the brands people love from the ones they leave.

Visionary Voices

Explainability Builds Trust

Arvind Krishna, CEO of IBM, has often emphasized that AI must be explainable to be trustworthy.

Businesses wanted faster models, better predictions, and more automation. But as the technology spread, so did the need for something deeper - understanding and transparency

Explainability means being able to say, “Here is how this AI reached that conclusion,” in plain language. When businesses can do that, they move from asking customers for blind trust to earning it. Transparency goes hand in hand with explainability. It means being able to talk openly about how AI is being used and how client data is handled, so customers are not left in the dark. When people understand what is happening behind the technology, they feel safer engaging with it.

For companies like IBM, explainable AI is not just a talking point. It is a design principle. Tools such as Watson OpenScale were created to help organizations see how their AI systems make decisions, spot bias, and correct it in real time

The Trend

Rise of Responsible AI

The conversation around AI is shifting. For years, the focus was on speed, automation, and scale. But as AI touches more parts of our lives, the new focus is on responsibility. Companies are realizing that how they use AI matters just as much as how well it performs.

This shift did not happen in a vacuum. Over the past few years, several brands have faced backlash from customers who felt that AI-driven decisions were biased or poorly communicated. Some companies rolled out AI features designed to predict behavior or personalize ads, only to discover that customers found them creepy or unfair. The result was a loss of trust and, in some cases, business.

Responsible AI is rising because trust is now a measurable business metric. Customers want to know that the technology working behind the scenes is being used ethically and transparently. IBM has been one of the leaders in this space. Its Watson OpenScale platform was created to bring visibility and fairness into AI decision-making. It helps businesses detect bias, explain AI outputs in plain language, and monitor model performance in real time. Instead of treating AI like a black box, Watson OpenScale makes it possible to show how and why decisions are made. For companies, that transparency is becoming a competitive advantage.

Other global brands are taking similar steps. L’Oréal, for instance, has been open about how it uses AI to improve customer experience from virtual try-on tools to skin diagnostics. What sets L’Oréal apart is its communication. The company clearly explains what data is being used, how it protects privacy, and what role human experts still play. By being transparent, it turns AI from something mysterious into something empowering. Customers know the technology is there to help, not to manipulate.

But responsible AI is not just a big-company conversation. Smaller businesses and service providers have a critical role to play, too. Ethical AI does not require massive budgets. It starts with mindset and intention.

Here are a few ways smaller teams can apply responsible AI thinking in practical ways:

1. Communicate clearly. Tell customers when AI is part of the experience and why it is being used. Transparency builds confidence and helps customers feel in control.

2. Review your data sources. Make sure the information feeding your systems reflects the diversity of the people you serve. Biased training data brings out biased results.

3. Keep humans involved. AI should support human judgment, not replace it. Always give customers the option to reach a person when the issue is complex or personal.

4. Listen and adapt. Treat customer feedback about AI experiences as valuable insight. Every concern is a chance to improve.

By applying these simple but intentional practices, smaller organizations can build the same kind of trust that global brands are striving for. This way, you can enjoy the benefits of AI without sacrificing your customers’ trust and have the best of both worlds.

A Final Note

Customers never forget how a brand makes them feel. That truth still matters, even in the age of AI.

As a business owner, take time to listen to how your clients respond to the technology you use. Their comfort and trust should matter more than how quickly you can automate.

Be intentional about building their confidence in your business - that’s what makes all the difference.

Until next time,

Your technology shouldn’t just be powerful, it should be trusted.

We’ve helped COUNTLESS BUSINESS OWNERS find that sweet spot between smart automation and genuine connection.

Ready to see what ethical AI can do for your business? Let’s explore it together.