Let’s face it: People are tired of hearing about how AI is going to change everything. A few months ago, I wrote about the very real phenomenon of AI fatigue. We know that AI-powered technology is everywhere, that it’s changing the way people work and that companies large and small are trumpeting their newest AI initiatives.

But how effective is all that trumpeting? Could it be hurting more than helping?

The Rise Of Consumer Skepticism

AI is proliferating more widely and becoming more inescapable in everyday transactions. According to McKinsey’s 2025 State of AI Report, 78% of businesses surveyed said they use AI in at least one business function. Your customers are, on some level, learning to accept AI out of necessity. But that doesn’t mean they want to hear about it.

A 2024 article from the Journal of Hospitality Marketing & Management found that marketing material using AI terminology actually decreases a customer’s purchasing intention. I’ve observed that more and more customers expect that businesses are using emergent AI technology. However, the Journal of Hospitality reports that using AI terminology in customer-facing marketing materials risks undermining the emotional trustworthiness that only humans can provide.

So what does all of this amount to for businesses that are using AI technology to improve their operations? Here’s what I’ve learned: It’s okay to mention it, but it shouldn’t be your value proposition. AI technology is a means to an end, and your responsibility is to deliver that end.

The Power Of Invisible AI

I’ve found the best AI solutions are typically those that do their job quietly by automating jobs too large and tedious for human beings. As a business, you can rely on these tools inasmuch as they can improve your operation. However, when it comes to customer-facing interactions, you may want to soft-pedal that reliance.

In my experience, customers want AI that provides:

• Invisible Safeguards

AI-powered firewalls have become something of a silent watchdog in industries like banking, lending, finance, trading and more. AI fraud detection technology has the capacity to scan billions of data points, identify anomalies, quantify risk and approve legitimate transactions in fractions of a second. If this technology is doing its job, your customers should experience enhanced speed, efficiency and data security without experiencing a direct engagement with your AI tech.

• Operational Efficiency

Businesses that use AI for internal processes like automated document review, data mining, data extraction and image annotation can save hours of human labor while providing faster service to consumers. According to a recent Forbes article, AI tools are saving the average employee up to five hours per work week. The result for your operation should be improved speed and efficiency. For your customers, however, the result should be an experience that feels “seamless” as opposed to “AI-powered.”

• Frictionless Experiences

AI technology can be used to verify customer identities online, help triage customers before passing them to the right human customer service agent, personalize online search results and more. This can result in a faster and more convenient consumer experience in which the role of AI is an unseen afterthought.

From Talking Point To Technical Advantage

We are in a period of rapid AI proliferation, but we are also seeing the first real wave of failures. According to a report from Heinz Marketing, 72% of all corporate AI investments are failing to deliver on their promises. The article also points out that 81% of enterprises have had an extremely difficult time quantifying the ROI from their investments in AI.

No wonder businesses are growing skeptical. In my experience, customers don’t want to hear about a multi-stage rollout of a new AI-powered back office system. They want to know how the heightened speed, efficiency and accuracy made possible by this system will cut costs, improve revenue or stimulate growth.

Your customers likely already expect that you’re using top technology to improve quality control, speed up product delivery and meet your service agreements. But most consumers are more interested in the outcomes than the details.

How To Prioritize Outcomes Over Adoption

There are several ways businesses can take a cue from their consumers and move the emphasis from experimental adoption to outcome-based implementation:

• Adopting Open-Source Tools

Many practical AI developments are widely available for use through open-source frameworks. Businesses have full and free access to these frameworks, which means you can tailor proven AI models to meet your specific business needs. In my experience, this approach can reduce exposure to risk by lowering your investment in costly technology. This can make open-source tools great options for businesses with strong in-house knowledge of popular open-source AI models.

• Piloting Modular Solutions

Avoid disruptive AI-driven technology overhauls. Instead, focus on a single high-impact area in your operation. Pilot targeted solutions like customer service chatbots or automated invoice matching. This measured approach can help you identify and address any issues before investing in a full-scale rollout. This cost-conscious approach may be a good fit for small businesses with a desire to leverage AI technology and a limited threshold for risk.

• Outsourcing

According to a Deloitte survey, 83% of surveyed executives are leveraging AI as part of their outsourced services strategies. Rather than investing in experimental technology, businesses are partnering with third-party providers that have already established proof of concept with their AI tech. (Full disclosure: My company offers these services, as do others.) If you decide to go this route, I recommend looking for vendors experienced with your market and who have a proven track record of providing invisible safeguards, unseen operational efficiency and frictionless consumer experiences.

We’re entering a new stage of AI adoption: a stage in which results matter more than the hype, where actions and outcomes mean more than words and marketing materials. It’s time we stop telling our customers how AI is going to make their lives better, so we can focus on simply making it happen.

See full article on Forbes here