When customers read “About us” or “Contact us” on your website, they probably associate the word “us” with you and your team. Increasingly, however, they’re less likely to be greeted with an “us” than an “it.”

A chatbot might have already popped up the moment they landed on your home page and offered to help answer any immediate questions.  

The customer might appreciate this and explain what they’re looking for, to which the chatbot responds with links to a knowledge base full of AI-generated help content.

Perhaps afterwards, the customer will get a follow-up message via e-mail or text, all thanks to AI-powered automation.

You can forgive the customer for wondering at this point if there are any actual people working at your company behind the scenes. The cumulative effect feels impersonal, even if each touchpoint is “efficient.”

This explains why WordPress VIP’s Future of the Web report found consumers hit “bot fatigue” after about 40 minutes of AI interaction. Bot fatigue is the point at which repeated AI interactions feel impersonal enough to erode brand trust.

Why bad bot experiences get deployed by good enterprise brands

AI tools like chatbots are often employed with good intentions. They allow you to serve your customers much faster than keeping them on hold for a contact center rep, and offer support 24/7. Employees are also freed up from triaging the same common issues.

The problem comes when a basic conversation begins to feel like you’re dealing with a robot in a dystopian sci-fi film:

• A sense of toxic positivity when an AI chatbot constantly uses “Great!” or “Awesome!”, even when you’re reaching out with a serious product or service issue.
• The repeated “Can you rephrase that?” despite the fact that any live person could have understood the sentence the first time around.
• The “Thanks for your patience!” in response to a comment that shows you are not, in fact, feeling very patient.
• Conversely, “I’m sorry you feel that way” isn’t convincing from a chatbot that has no emotions of its own.

The business case for AI automation is real. Faster response times, lower support costs, and the ability to scale content across dozens of markets without hiring proportionally — these are legitimate advantages: The question isn’t whether to use AI; it’s whether the efficiency gains are worth the trust you’re spending to achieve them. A chatbot that deflects 80% of tier-one support tickets is a win… until customers start associating your brand with the frustration of the other 20%. Automation compounds. So does the impression it leaves.

Senior leadership teams want to ensure they’re not left behind competitors who adopt AI and gain the benefits quickly, but those executing those mandates are increasingly aware of the risks. The Future of the Web report gathered responses from both consumers and those working in enterprises, and 91% agreed a human tone is critical in any AI-assisted processes.

It makes good business sense to develop an AI strategy based on speed, cost efficiency and scaling. Without also aiming to preserve a sense of humanity, though, customers may sour on the end result. This is where “trust debt” quickly accumulates.

From tech debt to trust debt

Trust debt is similar to tech debt, otherwise known as the legacy technologies organizations hang onto for too long. The lack of interoperability and maintenance expenses associated with older platforms means you pay more than you should, while limiting your ability to bring on innovations like AI.

The impact of tech debt sneaks up on you over time, just as a few negative experiences can make customers trust your brand less and less. Whereas you can upgrade or modernize your technology, trust debt may be impossible to overcome before a customer switches to a competitor.

The bottom line: Even if AI assists in the customer journey, marketers are fundamentally trying to woo people. You need to ask yourself if the experience you’re delivering via AI feels robotic, and if it will require significant effort to rebuild credibility in the event of negative feedback.

What human-centered AI content workflows look like

Rather than a bottleneck, having employees review and approve content (and sometimes make critical changes), is an act of trust-building.

Treating human-in-the-loop activity as overhead creates over-reliance on AI-assisted processes that directly impact customer relationships.

Whether it’s a bot that sounds more human or copy that carries your brand’s distinct voice, keeping humans at the center of what you say (and how you say it) matters: It tells customers you care about them, you’re accountable for what you publish (and what bots use to chat with them), and that you’re authentic in the promise you’re making about the customer experience.

What the people behind the bots should do

Most organizations have already rolled out AI in some areas by now, but you can still address the human factor as you continue to transform. Here’s how:

1. Evaluate where AI is customer-facing vs. behind-the-scenes

Chatbots are a critical area because they have become the de facto brand ambassador for many different companies. The initial testing may have focused on whether the information presented was accurate and could align with common customer questions.

Now is the time to refine the language the bot uses, which may require a conversation with your provider (or dev team to embed your brand tone and voice guidelines).

It’s always a good idea to have your team routinely act as “mystery shoppers” where they roleplay your ICP as they engage with the chatbot to ensure it’s not only helpful, but comes across as human as possible.  

2. Look for areas where human review has been reduced

AI should let employees focus on their highest-value work, which should also now include monitoring and assessing its outputs.

Map out typical customer journeys and where AI plays an active role. Now layer on where humans intervene. If they’re not involved at a critical step, ask why. Then, think about developing policies that require content to remain in draft mode until a human approves it.

3. Use a CMS that streamlines AI-assisted content workflows

Having people review, approve and publish content might seem time-consuming and onerous, especially in a large enterprise that operates dozens or even hundreds of websites. A CMS like WordPress VIP solves for that by offering content team members tools to ease those processes.

Working with WordPress VIP makes it easy to enforce editorial oversight, maintain consistency in tone and voice and leverage AI to recommend additional content to your audience. This allows your employees to invest their time in exercising human judgement, not toggling across applications to get a single piece of content to go live.

An approach to AI content operations that puts people first

Bots are conversational tools, but they should never be the only way you use AI to communicate with your customers. 

Balance further investment in live chat with continued investment in content that supports omnichannel digital experiences such as newsletters, blog posts, downloadable guides and others still to come.

Round it out by pairing analytics (how content performs) with surveys and direct feedback that reveal how human your brand feels online, and where it comes across as automated.