ADP surveys 39,000 workers globally each year. Their 2026 People at Work report landed with a finding that every mid-market leader deploying AI needs to sit with. One in five workers are engaged. A similar number feel their jobs are secure. Speaking of an AI anxious workforce… Those numbers are not specific to AI. They…
The AI governance framework is complete. The policies are documented. The decision rights are assigned. The production readiness checklist exists. The compliance requirements are mapped. The risk categories are defined. And the deployment is still stalling. CEOs I work with encounter this pattern more often than the governance conversation prepares them for. The framework is…
The AI development pace that keeps mid-market CEOs up at night isn’t a technology problem. It’s a listening problem. Every week brings new capabilities, new tools, new regulatory developments, new vendor announcements, new customer expectations shaped by AI experiences elsewhere. Most mid-market organizations are trying to track all of it through one person — someone…
The AI governance conversation in most mid-market organizations focuses on the technology layer. Data quality. Model accuracy. Security protocols. Compliance frameworks. Production readiness criteria. All of it necessary. None of it sufficient. The AI initiatives that stall in production — the ones that pass every technical test and then quietly fail to deliver their projected…
The AI pilot was a success. The model performed. The accuracy metrics exceeded the threshold. The business case held. The stakeholders who saw the demonstration were impressed. Everyone agreed: this is ready to move forward. That was fourteen months ago. The AI is still not in production. CEOs I work with encounter this pattern more…
AI initiatives that stall don’t fail suddenly. They slow down gradually — losing momentum across weeks and months until the energy behind them quietly dissipates and the project joins the list of things the organization is still planning to do. The stall is almost always visible in advance. Not in the technology. In the answers…
The leadership meetings about AI in most mid-market organizations cover the same ground. Deployment timelines. Budget approvals. Vendor selections. Pilot results. Governance frameworks. The AI conversation that determines whether any of those decisions land well almost never makes the agenda. It’s the conversation with your people about what AI means for them. Not the technology…
RSM’s 2025 Middle Market AI Survey found that 91% of mid-market organizations are using generative AI. It also found that 92% reported challenges during implementation. The gap between adoption and success is nearly universal. And when you look at where implementations go wrong, the pattern is consistent: it’s rarely the technology. The models work. The…
There is a mid-market opportunity hiding inside Deloitte’s most recent AI governance research. Most people reading the survey missed it entirely — because the headline number looks like a problem. 70% of organizations have AI governance policies in place. Only 16% are satisfied with their AI adoption pace. The conventional reading: governance isn’t working. Organizations…
A manufacturing company deployed AI for quality control inspection. The technology worked flawlessly. Defect detection improved 40%. Cost savings: $800K annually. Six months later, HR flagged unusual turnover in the inspection department. Exit interviews revealed why: Inspectors felt their expertise was devalued. Their jobs had become “babysitting the AI’s mistakes.” Their career path disappeared —…
