Handling AI disruption and failure to deliver | Computer Weekly

Surveys indicate many businesses fail to achieve measurable returns from AI spending. A key issue is that AI providers often overlook human and enterprise factors. Employees commonly fear job loss, and worker participation is recommended at every stage of AI deployment, from strategy and problem definition to tendering, application design, and rollout. Change management becomes more difficult with generative AI because it is accessible and often begins as a boardroom priority. Leaders may assume HR or business teams will manage change, but job displacement and role changes increase employee fear. Implementers also experience disruption, and work relations and enterprise technology constraints are frequently not addressed.

"“They completely ignored the human factor, and also the enterprise factor,” he told Computer Weekly during the CamundaCon 2026 conference in Amsterdam."

"“CEOs immediately understand the potential, so they have been pushing it even harder into their organisations,” he said. In his experience, CEOs assume that people down the line who are in charge of change management, such as the human resources team, or the people in the business who are driving these transformation programmes, will handle change management."

"“Since there is a direct implication on jobs, with job roles changing and people being displaced, the fear and concerns among employees increases exponentially.” According to Schaffrik, not only are employees afraid and confused, those people who are supposed to implement the AI are also being impacted."

"The Trade Union Congress recommended that employers build a meaningful worker participation at every stage of the deployment of new AI technology to drive effectiveness of technology - from strategy development to problem definition, through to tender, application design and deployment."

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