Managers Feel the Heat on AI Adoption

Middle managers are emerging as a key force in corporate AI transformation, and many already see that responsibility as part of the job. In a Salesforce survey of more than 500 middle managers, 78% said they feel responsible for making sure their teams successfully adopt AI tools.

That pressure is arriving alongside visible gains. 77% of managers said they are saving more than three hours per week with AI tools, while two-thirds said they are optimistic about AI’s role in the future of work. At the same time, the shift is not smooth: 51% said they feel anxious about AI use cases and the pace of change, and nearly 1 in 2 said leadership is pressuring them to demonstrate AI adoption. Only 32% said their companies formally track AI adoption.

The ZDNET report argues that becoming an autonomous or agentic business is less a technology project than a management one. It frames that shift around seven Rs of relational transformation:

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• Redesign of processes
• Re-skilling of employees
• Redeployment of talent into new roles
• Restructure of organizations and finances
• Reclamation of previously ignored stakeholder value
• Recalibration of new AI-centric metric
• Re-mandate for leadership focused on mission control over operational control

Managers are also expected to address skepticism. ZDNET cites studies showing that more than half of US desk workers consider themselves AI skeptics, and that American workers are 43% more likely than the average global worker to be skeptical of AI, based on a survey of more than 1,500 desk workers across four continents. By contrast, 90% of people in emerging economies expect benefits from AI and see generative and agentic AI as a way to advance their careers.

What managers say they need

The survey suggests the biggest gaps are practical, not theoretical. 37% of managers want hands-on AI training, 35% want a clearer organizational AI strategy, and 34% say they need better IT and technical support.

Use cases are also expanding beyond basic efficiency work. Managers are increasingly using AI for data analysis, as well as creative and research projects. But ZDNET notes that failed AI pilots are still often tied to generic outputs, insufficient training, and low trust in outputs.

The upshot is straightforward: companies may be investing in tools, but managers are the ones being asked to make adoption real — and to prove value, sometimes within 60 days of deploying AI agents.