Gartner’s latest prediction is already gaining traction: by 2027, half of organisations that cut customer service staff due to AI will need to rehire people into similar roles under different job titles. In my view, this is an important signal, not because AI is failing, but because many organisations are applying it with the wrong intent and success measures.
What Gartner is describing in the above article reflects, in my opinion, the consequences of treating AI as a workforce replacement strategy rather than an operating model change. Headcount reduction has become an easy, visible way for organisations to prove AI success to boards, investors and markets. That visibility is often prioritised over long-term operational performance.
At Sabio, we deliberately take a different stance (you’ll learn more about this during our upcoming Disrupt programme of events taking place across Europe, and this strongly shapes how I believe AI should be applied. We help organisations adopt AI through what we describe as a zero human impact lens. This is not a claim about what the market has done to date. It is a conscious choice in how we guide clients through AI transformation.
Instead of building ROI on forced redundancies, we align AI deployment to reality. We, as a contact centre industry, already face sustained attrition, recruitment challenges and a year-on-year demand growth. AI is applied to absorb that demand, reduce the need to backfill roles and stabilise operations over time. In this model, organisations effectively recruit AI agents alongside their human workforce, evolving the make-up of their capacity.
Where I believe many strategies fall down is in how value is defined. ROI models built purely on FTE reduction ignore the additional capacity and value AI creates. That capacity can be reinvested to improve experience quality, increase resilience, extend service coverage and shift organisations away from reactive, failure-driven contact towards proactive engagement that adds measurable business and customer value. When AI is applied this way, rehiring is not an inevitable outcome, it is a symptom of poor design choices.
The organisations Gartner is pointing to did not fail because AI lacked capability. Because, it simply doesn’t. In my view, they failed because automation was confused with transformation. AI was introduced without sufficient consideration of workforce dynamics, customer complexity or change management.
This is why Sabio positions itself as an expert services partner rather than a technology-first vendor. The technology is rarely the hard part. The challenge is designing an AI strategy that balances efficiency, experience and people in a way that holds up beyond the next earnings call.
For me, Gartner’s prediction should prompt a simple question for every service leader: is your AI strategy designed to deliver sustainable change, or short-term proof points? The answer will determine whether you are building a future-ready operating model or quietly preparing to rehire the roles you removed under a different name.
