Short-term savings on AI generated work are backfiring, as companies quietly spend thousands fixing errors with old-fashioned human skill.
Businesses that replaced human workers with AI are now paying top rates to fix the resulting errors. Writers, developers and marketers report being hired to re-do or repair flawed AI-generated work. Experts warn that brand identity, code integrity and audience targeting often suffer when humans are left out.
It was supposed to be a triumph of modern efficiency: replacing costly human talent with nimble, generative AI. But across Asia and beyond, firms are learning an expensive truth, the cost of fixing a machine’s mistakes can far exceed the price of doing it right the first time. In the rush to automate, many businesses have inadvertently created a lucrative cottage industry: highly-paid professionals now mopping up after poorly executed AI work.
The False Economy of AI
Overdependence AI generated copy, designs and code promise convenience. But when the results fall short, the price of rework mounts quickly. Sarah Skidd, a product marketing manager, recently charged $2,000 to rewrite dull, ineffective chatbot generated copy. The original content, she explained, was "vanilla" and lacked the persuasive punch needed to sell.
This isn't an isolated case. Firms keen to trim costs by using chatbots for content creation are discovering that salvaging subpar output requires more than light editing. As Skidd noted, what should have been a quick polish turned into a 20-hour rewrite from scratch. For more on the limitations of AI, see our article on When AI Slop Needs a Human Polish.
A Booming Business in AI Clean-Up
In the UK, Sophie Warner of Create Designs says her agency is now busier than ever; not with new builds, but with repairs. Clients initially experiment with ChatGPT for small website changes. But when things break, they return sheepishly, often incurring investigation fees and delays.
In one such case, a minor code tweak supplied by an AI model disabled a client's website for three days. What would have been a 15-minute job ballooned into a US$500 recovery mission. "Correcting these mistakes takes much longer than if professionals had been consulted from the beginning," Warner observed.
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Asia's Parallel Reality
The Rush to Automate Across Asia, the same pattern is emerging. From Singapore’s SME rich tech corridors to India’s outsourcing hubs, firms are turning to AI for fast fixes only to realise that one-size-to-all solutions rarely work in the region’s culturally nuanced markets.
In Bangkok and Jakarta, digital agencies report similar complaints: AI generated campaigns that misinterpret tone, bungle translations, or ignore market specific behaviours. As one Singapore-based strategist put it:
"AI speaks, but it doesn’t listen."
The Value of Human Nuance
What makes human work still indispensable? Context. As Warner points out, AI overlooks brand identity, target demographics and conversion design. These are not just minor details they're the heart of effective marketing and digital strategy. For more insights into how AI recalibrates business value, read our piece on How AI Recalibrated the Value of Data.
While generative models can churn out text or code, they lack the instinct to know what matters and why. Humans don’t just execute; they interpret. And that interpretation is exactly what clients are paying for often at premium rates after AI has failed. This highlights the ongoing debate about Is AI Cognitive Colonialism? in AI applications.
The antitrust angle
Chrome’s data‑collection role has placed Google under antitrust scrutiny. The US Department of Justice is pushing for its divestiture after a judge found it held an unlawful search monopoly. OpenAI once hinted it might be interested in acquiring Chrome if forced by regulations. But its current path is clearer: create a browser from the ground up to sidestep Chrome while taking advantage of open‑source Chromium. This mirrors discussions around Perplexity: Amazon's "Bullying Tactics" Won't Stop Comet.
Job Security for the Skilled For professionals like Skidd, the AI boom hasn’t been a threat but a boon.
"Maybe I’m being naive," she says, "but I think if you are very good, you won’t have trouble."
This sentiment echoes across many creative and technical industries. Those with deep domain expertise are not just surviving the AI shift they're profiting from it. But they also share a note of caution: AI can augment, but it rarely replaces seasoned judgement. This brings to mind the concept of What Every Worker Needs to Answer: What Is Your Non-Machine Premium?.
As more firms in Asia grapple with the hidden costs of AI misfires, the question is no longer whether to use AI, but when and how to do so wisely. Are you investing in speed, or paying for it later in lost nuance and costly clean-ups?
Latest Comments (2)
This really resonates, yaar. Just last month, my cousin, who runs a small e-commerce site, was tearing his hair out over product descriptions AI generated. Had to hire a freelance copywriter to fix the clunky phrasing and factual errors. He reckoned he spent more correcting it than he would have on a human from the start. Definitely a false economy, isn't it?
This is a really insightful piece. It makes you wonder, doesn't it? We're always chasing the "next big thing" without truly evaluating the full lifecycle cost. Like, when we see companies here in the Philippines touting their AI tools for customer service or content creation, I always think about the potential for errors. My question is, how do businesses then account for these unseen remediation costs in their initial ROI projections for AI implementation? Is there a better framework they could use to avoid this backward step? It feels like we're learning the hard way, again.
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