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The true cost of AI cost-cutting: why businesses must consider the human impact

The Mercury

|

October 28, 2025

IT'S A CATCH-22: AI adoption among businesses of most, if not all kinds, is now a competitive must - yet it's not a panacea and the human cost can be considerable.

- Julia Ahlfeldt from Julia Ahlfeldt Consulting. The views expressed here do not necessarily represent those of Independent Media or IOL.

This is both in terms of job displacement due to the adoption of fast-changing technology that can drive efficiencies (read: head count) but requires a new breed of skills, as well as the impact on consumers who continue to seek human-based support and customer care in response to over-digitised and automated path to purchase channels that lack sentience and person-to-person understanding and empathy.

This is a key insight of the 7th annual South African Customer Experience Report, which I coauthored and which has just been released.

While AI in all its forms - from Gen AI, AI assistants and Agentic AI, among many more - must, no doubt, be integrated into a business's operations and ways of working, asap, it needs to be done strategically and with a long term vision for AI transformation.

This is so that ethics are not compromised, employees - from manual task operators right up to the C-Suite - are upskilled swiftly (or risk becoming irrelevant and unemployable), and customers are assisted or can review brands and products quickly, digitally, through an increasing use of AI tools like LLMs (Large Language Models e.g. ChatGPT), while also having the option of physical, people-based support when needed.

This may seem like a paradox, but over-digitisation can land up being more costly, and costing businesses customer loyalty, as in the case of Swedish Fin-tech Klarna, a company that integrated AI chatbots too hastily, and then had to pivot back to human agents, due to the disappointing performance of the AI tools.

Of course, not upping the AI ante is a major business risk as first-mover competitors speed up efficiencies, data analysis and operations, at scale, putting them ahead of the purchasing pack - for now.

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