The GenAI Skills Gap Seems Real: Are most people just getting started?

Am I living in a GenAI echo chamber? While my LinkedIn feed overflows with the latest AI breakthroughs and ‘must-try’ features, my experience in the trenches tells a different story. As a volunteer leading GenAI projects, delivering prompt engineering training and talking about GenAI in the non-profit sector, I’ve witnessed a gulf between the breathless pace of AI innovation and how most people actually use these tools day-to-day. (I have to say that I have not noticed resistance, concern – yes, but not resistance and in all cases I see the ‘wow’ moment happen when people realise the possibilities and practical applications.)

What is it?

It seems to me that we have a GenAI training gap which is real and growing wider by the day. While ChatGPT has millions of users, I suspect most people are still using it at a basic level – asking simple questions, getting quick translations, or writing basic emails. Through my volunteer training sessions, conversations and talks I’ve given, I have noticed that only a small percentage of users have developed the skills to leverage GenAI’s more advanced capabilities, like Tree of Thought to improve the grant writing process.

This isn’t surprising – we’re asking people to develop an entirely new skill set while the technology itself is evolving at such a pace. It’s like trying to learn to drive while the car keeps changing underneath you. The result? A growing chasm between what GenAI can theoretically do and what most people can actually accomplish with it.

What does it mean from a business perspective?

This skills gap has real implications for businesses betting on an AI transformation:

Unrealized ROI: Companies may be investing heavily in GenAI tools, but if employees can’t use them effectively, they’re leaving significant value on the table.
Competitive Disadvantage: Organizations with GenAI-savvy employees will pull ahead, while those organizations with a basic understanding will struggle to keep pace. The gap could widen dramatically.
Resistance to Change: When people don’t feel confident using AI tools, they’re more likely to resist adoption, leading to slower digital transformation. (Like I said above though – I see concern, not resistance once people wee the opportunity.)
Missed Opportunities: Without advanced AI skills, employees might miss crucial opportunities to innovate or improve processes, limiting your organization’s potential for growth and efficiency.

What do I do with it?

To address this challenge, consider taking these concrete steps:

Assess the Current State: Conduct an honest evaluation of your organization’s AI literacy. Don’t assume everyone is up to speed just because they have access to the tools.
Develop a Structured Learning Path: Create a clear progression from basic to advanced GenAI usage. Start with fundamentals and gradually introduce more sophisticated concepts and techniques.
Make Learning Contextual: Instead of generic GenAI training, focus on specific use cases relevant to your employees’ daily work. Show them how to use AI to solve real problems they face.
Build Communities of Practice: Foster internal networks where GenAI-savvy employees can share knowledge and help others grow. Consider implementing a mentorship program.
Set Realistic Expectations: Recognize that developing advanced AI skills takes time. Create a sustainable long-term learning strategy rather than expecting overnight transformation.

Remember, the goal isn’t to turn everyone into an GenAI expert. It’s about helping people move beyond basic usage to a level where they can meaningfully leverage GenAI to enhance their work. Start small, focus on practical applications, and build momentum gradually.

By acknowledging and actively addressing the GenAI skills gap, organizations can ensure they’re not just acquiring cutting-edge technology, but actually building the human capabilities needed to use it effectively.

What is it?

What does it mean from a business perspective?

What do I do with it?

Further Reading