Executives who use AI in their daily work are 3.6 times more likely to report a significant productivity increase compared to employees who do the same. This finding, from the 2024 Gartner Digital Worker Survey, doesn't describe a difference in technology access. It describes a difference in how AI is integrated into work at different organizational levels.
The gap nobody is closing
Fewer than one-third of employees say they use generative AI for any work task. Only 12% of those who use it say they've applied it to significantly reduce effort on a critical task. The most telling data point: only 18% have received support from their organization on how to integrate GenAI into daily work. 82% of workers have never received any guidance on AI use.
Executive expectations around AI-driven productivity are high. The operational reality of the workforce is far removed from those expectations. This misalignment complicates ROI assessment and puts human capital investment return objectives at risk.
Why workers aren't leveraging AI
Gartner identifies three specific risks in organizations in the early stages of LLM and GenAI adoption. The first is the inability to recognize hallucinations in outputs. The second is the difficulty of building prompts with enough domain context to produce outputs with real business value. The third is low overall technological competence that leads to using a model not optimized for the specific use case.
On top of this, there's a habit problem: many workers treat GenAI like a search engine, transferring an established behavior to a tool that works in a completely different way. Generative AI requires active dialogue, not passive queries.
Three quick wins to close the gap
Gartner identifies three high-impact, rapid-implementation interventions for digital workplace leaders. The first is connecting workers to the most effective use cases through hands-on activities: working sessions on real business problems, live demonstrations, and collaborative projects that let people apply AI to concrete tasks. The average time savings already measurable with the simplest use cases, such as information retrieval, email generation, and document summarization, is 25 minutes per worker per day.
The second intervention is distributing a structured framework for prompt writing. The third is building and distributing an internal prompt library. These three interventions don't require new technology: they require organization, training, and an investment in operational guidance that most companies haven't made yet.
The opportunity for digital workplace leaders
The AI productivity gap is a problem, but also an opportunity. Those who manage digital workplaces now have a chance to increase their influence and value by demonstrating tangible progress on workforce-level AI ROI. Combining immediate quick wins with a long-term enablement strategy ensures that workers realize the benefits of GenAI in the short term while building a sustainable foundation for future productivity.
The takeaway
AI productivity doesn't automatically distribute across an organization when you purchase a license. It's built through guidance, training, and concrete operational tools. Companies investing in these three elements are achieving real results. Those waiting for employees to figure out how to use AI on their own keep seeing the gap their executives can't explain.
