Enterprise adoption of generative AI tools has accelerated across industries. However, training practices have not kept pace.

According to a survey from OwlLabs and Pulse, while approximately 70% of organizations report incorporating AI into their workflows, only 38% have provided formal training to their employees. This imbalance highlights a growing execution gap in AI strategy, where technology investments exceed the organizational capacity to use them effectively.

The resulting gap poses operational risks.

Without a workforce equipped to use AI tools effectively and responsibly, companies face diminished returns on technology investments, exposure to compliance and data security issues, and stalled cultural transformation efforts. When executed properly, AI enablement demands a systematic shift in how employees interpret, engage with, and apply AI in context-specific environments.

Why It Matters: Organizations that fail to integrate structured AI training alongside technical deployment face limited returns on investment and elevated exposure to compliance and security risks. Equipping employees with the ability to confidently use AI ethically and within policy frameworks is essential for receiving strategic value from the technology.

• Adoption Is Outpacing Internal Preparedness: Employee use of generative AI has grown significantly without employers providing training or defined usage policies. This gap results in unsupervised experimentation and inconsistent outcomes that can erode trust in the tools as well as the processes they are meant to enhance.

• Effective Use Requires Cognitive and Cultural Shifts: AI tools function differently from traditional enterprise software and require a distinct approach to training. Programs should emphasize behavioral change and critical thinking. Effective training helps employees ensure accuracy and sound judgment.

• Policies Must Be Reinforced Through Training: Legal guidance emphasizes the need for employees to understand appropriate data handling and the risks of AI hallucinations. Policy adoption without implementation support leaves organizations vulnerable to avoidable errors and compliance breaches.

• Contextual Training Increases Engagement and Retention: Organizations that embed AI training within existing workflows tend to achieve stronger and more sustained adoption. When instruction is grounded in practical tasks and mirrors day-to-day responsibilities, it becomes more relevant and easier to apply. This approach supports the consistent use of AI tools across the organization.

• Leadership Alignment is Critical to Program Success: Training must be supported by clear endorsement from leadership and compliance teams. Without this alignment, employees may hesitate to fully engage with AI tools or lack the authorization to apply them meaningfully. Programs that incorporate executive perspectives are more likely to deliver consistent enterprise-wide outcomes.

Go Deeper -> Developing Skills in AI: The Importance of AI Training for Employees – Nutter