Perth, May 21: Nearly half of major enterprise AI initiatives are expected to fail as businesses race to scale artificial intelligence while facing pressure to deliver faster returns.
A new HCLTech report, The AI Impact Imperatives, 2026, found 43 per cent of major AI initiatives may fail, despite widespread adoption across IT operations, software engineering and business functions.
The report, based on a global survey of 467 senior executives responsible for AI investments at enterprises with more than $1 billion in annual revenue, found organisations are struggling to turn AI ambition into consistent business outcomes.
In Australia, organisations cited legacy integration, data modernisation and governance gaps as key barriers to scaling AI successfully.
Nearly half of enterprise leaders expect measurable value from AI investments within 18 months, while 76 per cent of Australian organisations believe both legacy and already-modernised applications require major overhauls to properly support AI capabilities.
The report also found 89 per cent of Australian leaders believe competitors will be using autonomous AI systems for mission-critical work within the next 12 months.
HCLTech said many organisations were underestimating the coordination and decision-making clarity needed to successfully scale AI, with change management emerging as a major execution risk.
“AI has moved from being a technology initiative to becoming an enterprise operating reality,” said Vijay Guntur, CTO and Head of Ecosystems at HCLTech.
“What leaders are grappling with now is not whether AI can deliver value, but how organisations adapt their structures, decision rights and risk tolerance to keep pace with it. The pressure to move fast is real, but without the right investment in people, in helping them understand, trust and work effectively alongside AI, speed can just as easily amplify failure as success.”
The report also found 79 per cent of Australian organisations said governance and responsible AI considerations significantly influence deployment decisions.
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