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The AI Value Paradox: Why TMT Leaders Struggle to Measure Gains

While 91% of TMT executives express confidence in their AI investments, only one-third can quantify the actual business value generated. This stark disconnect between optimism and measurable output defines a new report from Economist Enterprise and HCLTech, highlighting a critical struggle to move beyond experimentation toward scalable, industrial-grade implementation.

The AI Value Paradox: Why TMT Leaders Struggle to Measure Gains

The study, which surveyed over 200 C-suite leaders across the U.S. and Europe, suggests that artificial intelligence is rapidly dissolving traditional industry boundaries. As telecommunications, media, and technology sectors converge, companies are forced to seek new growth models. However, this shift is hampered by a significant execution gap. Although firms identify talent upskilling as their top priority, only 20% have a formal strategy in place for hiring or training staff. Furthermore, governance remains a weakness, with just 17% of organizations reporting that oversight actively shapes their AI system operations.

Charlotte Bullard Davies of Economist Enterprise notes that success will depend on combining disciplined governance with ecosystem collaboration. Anil Ganjoo, Chief Growth Officer at HCLTech, emphasizes that the next stage of competitive advantage belongs to those who shift from pilot projects to industrialization. Without the ability to consistently track returns, many organizations risk stalling in the experimentation phase, unable to unlock the full potential of their digital investments.

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