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Probizbeacon > Money Management > Relying Too Much On AI Is Backfiring For Businesses
Money Management

Relying Too Much On AI Is Backfiring For Businesses

July 7, 2025 5 Min Read
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5 Min Read
Relying Too Much On AI Is Backfiring For Businesses
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As more companies race to adopt generative AI tools, some are learning a hard lesson: when used without oversight or expertise, these tools can cause more problems than they solve.

From broken websites to ineffective marketing copy, the hidden costs of AI mistakes are adding up, forcing businesses to bring in professionals to clean up the mess.

AI Delivers Mediocrity Without Supervision

Sarah Skidd, a product marketing manager and freelance writer, was hired to revise the website copy generated by an AI tool for a hospitality company, according to a report by the BBC.

Instead of the time- and cost-savings the client expected, the result was 20 hours of billable rewrites.

Skidd told the BBC:

“[The copy] was supposed to sell and intrigue but instead it was very vanilla.”

This isn’t an isolated case. Skidd said other writers have shared similar stories. One told her that 90% of their workload now consists of editing AI-generated text that falls flat.

The issue isn’t just quality. According to a study by researchers Anders Humlum and Emilie Vestergaard, real-world productivity gains from AI chatbots are far below expectations.

Although controlled experiments show improvements of over 15%, most users report time savings of just 2.8% of their work hours on average.

Cutting Corners Can Lead To Problems

The risks go beyond boring copy. Sophie, co-owner of Create Designs, a UK-based digital agency, says she’s seen a wave of clients suffer avoidable problems after trying to use AI tools like ChatGPT for quick fixes.

Warner tells the BBC:

“Now they are going to ChatGPT first.”

And that’s often when things go wrong.

See also  ChatGPT Expands Memory Capabilities, Remembers Past Chats

In one case, a client used AI-generated code to update an event page. The shortcut crashed their entire website, causing three days of downtime and a $485 repair bill.

Warner says even larger clients encounter similar issues but hesitate to admit AI was involved, making diagnosis harder and more expensive.

Warner added:

“The process of correcting these mistakes takes much longer than if professionals had been consulted from the beginning.”

Training & Infrastructure Matter More Than Tools

The Danish research paper by Humlum and Vestergaard finds businesses that offer AI training and establish internal guidelines see better (if still modest) results.

Workers with employer support saved slightly more time, about 3.6% of work hours compared to 2.2% without guidance.

Even then, the productivity benefits don’t seem to trickle down. The study found no measurable changes in earnings, hours worked, or job satisfaction for 97% of AI users surveyed.

Prof. Feng Li, associate dean for research and innovation at Bayes Business School, told the BBC:

“Human oversight is essential. Poor implementation can lead to reputational damage, unexpected costs—and even significant liabilities.”

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The Gap Between AI Speed & Human Standards

Kashish Barot, a copywriter based in Gujarat, India, told the BBC she spends her time editing AI-generated content for U.S. clients.

She says many underestimate what it takes to produce effective writing.

Barot says:

“AI really makes everyone think it’s a few minutes’ work. However, good copyediting, like writing, takes time because you need to think and not just curate like AI.”

The research backs this up: marketers and software developers report slightly higher time savings when employers support AI use, but gains for teachers and accountants are negligible.

See also  Most In-Demand Marketing Jobs & Skills

While AI tools may speed up certain tasks, they still require human judgment to meet brand standards and audience needs.

Related: This Is Why AI Won’t Take Your Job (Yet)

Key Takeaways

The takeaway for businesses? AI isn’t a shortcut to quality. Without proper training, strategy, and infrastructure, even the most powerful tools fall short.

What many companies overlook is that AI’s success depends less on the technology itself and more on the people using it, and whether they’ve been equipped to use it well.

Rushed adoption may save time upfront, but it leads to more expensive problems down the line. Whether it’s broken code, off-brand messaging, or public-facing content that lacks nuance, the cost of fixing AI mistakes can quickly outweigh the perceived savings.

For marketers, developers, and business leaders, the lesson is: AI can help, but only when human expertise stays in the loop.


Featured Image: Roman Samborskyi/Shutterstock

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