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AI adoption driven by hype, not strategy
Businesses and governments are increasingly mandating the use of generative AI, often without clear objectives or measurable benefits, industry insiders say. The trend has left employees skeptical about leadership's ability to manage the transition effectively.
The cost of chasing AI trends
Malcolm, an AI engineer at a data analysis firm (name withheld for confidentiality), advised against using generative AI to categorize customer personas. He argued that traditional machine learning models would deliver more consistent, cost-effective results. Executives overruled him, prioritizing the ability to claim AI adoption over efficiency.
"They still went ahead with Gen AI," Malcolm said. "It was less accurate, far more expensive, but it let them say they were 'embracing AI.'"
Corporate mandates and employee skepticism
Consulting giants like Accenture and KPMG have tied AI tool usage to career advancement. Accenture reportedly requires "regular adoption of AI tooling" for promotions to senior roles, while KPMG tracks U.S. employees' compliance with a 75% usage target via a dashboard. KPMG describes this as part of a broader effort to "move people up the AI maturity curve."
The UK government is similarly banking on AI to "rewire" the state and boost Whitehall efficiency. However, a survey by the FDA, the union representing civil servants, revealed deep skepticism. Fewer than a third of respondents had been consulted on AI rollout plans, and many doubted management's ability to lead the change.
"Change is being done to workers, not with them,"
Dave Penman, FDA General Secretary
Misaligned priorities and wasted investments
Dan Boyles, CEO of consultancy Hello AI Collective, said many organizations adopt AI without clear goals. During a meeting with an oil and gas company's leadership, he found no consensus on why AI was needed. The CEO cited competition, the sales team wanted higher profits, and marketing aimed to reduce contractor reliance.
"This sort of confusion at the top can mean AI investments fail to deliver," said an anonymous senior consultant at a major firm. While employees had access to multiple AI tools, engagement remained low, and returns on investment often fell short of expectations.
Culture and training as critical factors
The consultant noted generational and gender differences in AI confidence, emphasizing the need for mandatory training on ethics, bias, and tool limitations. "AI can be sycophantic and hallucinate," he added, warning of potential pitfalls without proper oversight.
Caroline Rawlinson, CEO of employee feedback firm Culture Amp, stressed that organizational culture determines AI success. "If you layer AI on a fragmented or fear-based culture, it won't work," she said. While 90% of HR professionals expect to expand generative AI use, a third reported no clear ownership of AI strategy.
For the oil and gas company Boyles advised, clarity finally emerged when the president revealed his goal: increasing operating earnings to facilitate a future sale. With that focus, Boyles' team could identify bottlenecks and target AI solutions effectively.
Key takeaways for organizations
- AI adoption should be driven by specific, measurable goals-not just trend-chasing.
- Employee consultation and training are critical to successful implementation.
- Pre-existing workplace culture can accelerate or undermine AI initiatives.
- Without clear leadership and strategy, AI investments risk underdelivering.
