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CEOs once believed they had struck gold with AI, but the technology has often proved to be a money-draining black hole. Algorithms can process data, yet they lack human intuition—an element that many businesses say is essential for understanding customers and delivering service quality.
Recent examples illustrate the risk of replacing people with AI. After laying off an SEO team, a company saw a freefall in Google Analytics metrics. Klarna, meanwhile, has had to recruit real people again after prioritizing an AI chatbot for customer support.
Gartner’s latest research, covering 350 companies with annual revenue of at least $1 billion, found that up to 80% of firms using automation tools have cut staff. The primary motive is often pressure from shareholders and the desire to show a quick return on investment from AI spending.
Gartner analyst Helen Poitevin said that cutting the workforce may create budget gaps, but it does not generate profits. The report also highlights a cost trap: the projected cost of investing in AI agents is expected to rise from $86.4 billion in 2025 to more than $376 billion the following year, while returns have not yet materialized.
Poitevin’s view is that the biggest mistake is treating AI as a replacement rather than an amplification. Firms that achieve real ROI are those that invest in skills and operating models that allow humans to lead and scale automated systems, rather than firing them.
Klarna, the Swedish fintech, previously claimed that an AI chatbot could replace the work of 700 customer-support staff. After a year of prioritizing AI to handle inquiries, the company reversed course. CEO Sebastian Siemiatkowski acknowledged that service quality deteriorated and no longer met Klarna’s standards.
Klarna is now rehireing human customer support staff. The company’s reasoning is that in finance, trust and the ability to manage nuanced situations that require empathy remain areas where AI is weak. In this context, human support is no longer viewed as a cost center but as a core competitive advantage.
The broader lesson for firms driven by FOMO is that higher volume does not automatically translate into better outcomes. AI can handle 2–3 million conversations per month, but if many interactions simply funnel customers toward frustration because issues are not fully resolved, the quantity of conversations loses value.
AI often falls short in fully replacing functions like SEO or customer service because of one key factor: intuition. Data can show what customers are doing, but intuition and the experience of seasoned professionals explain why customers act that way and what they are likely to want next.
AI relies on probabilities drawn from past data, while markets and human psychology continue to evolve. In SEO, a skilled editor does more than write for search engines—they aim to resonate with readers’ emotions. In support, a strong agent does more than follow a script—they can calm an angry customer with sincerity.
Many experts believe that by 2028, automated business tools will be a net job creator. They argue that AI will create new types of jobs that it cannot absorb itself.
However, tasks involving high trust and strategic decisions grounded in cultural and social context are expected to continue requiring human involvement.
Some observers say that labeling AI as a “job thief” can be a way for companies to mask management mistakes or earlier overhiring. Sam Altman, OpenAI’s CEO, has also used the term “AI washing” to describe situations where companies blame technology when layoffs are driven by other financial reasons.
The Gartner and Klarna examples point to a consistent conclusion: businesses should not rush to discard human intuition in favor of algorithmic decision-making. In the digital age, the firms that endure are not necessarily those that use AI the most, but those that use it to free people to focus on what machines cannot replicate—creativity, empathy, and decisions grounded in human intuition.
Source: The Verge, ITPro.
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