Organisations face a false choice between reach and relevance when it comes to AI training – Josh Wöhle reveals why this challenge extends beyond business efficiency to broader societal impact
AI is the new Microsoft Office in the workplace. It’s a must-have. The World Economic Forum predicts that 75% of companies plan to adopt AI technologies by 2027. But – and it’s a big but – there’s a significant gap between what people learn about AI in theory and how they actually use it in the real world.
Bigger doesn’t always equate to better. Scaling, done wrong, can be a problem too
In my discussions with enterprises, I see a common theme. There’s a scramble to become AI-ready. However, these large-scale businesses face a critical challenge: how do they make AI training personal (critical to ensure that employees get what they need to do their job more effectively) and scalable (can it be rolled out to everyone, from the C-suite to the newest intern)?
The personalisation paradox
Unfortunately, basic AI skills don’t transfer across roles and individuals as well as we’d hope. Otherwise, there would be no problem. I’ve seen this time and time again – one team has mastered the art of using AI to fully automate their sales emails, but another team doesn’t know how to apply that very same tool to draft agendas for an upcoming strategy session. AI isn’t like maths. It’s not a cookie-cutter skill that everyone can readily apply to their specific role. AI requires a more nuanced, individual-specific approach.
This is where personalisation comes into play. Real personalisation. I’m not talking about the “personalisation” which sees you create an avatar and then get presented with a blog article that matches a few keywords you put in. Real personalisation – in AI upskilling, at least – is providing actual use cases linked to an employee’s daily tasks. It’s about bridging the gap between theoretical knowledge and practical application.
Scaling up is hard to do
Bigger doesn’t always equate to better. Scaling, done wrong, can be a problem too. I’ve seen big companies throw money at platforms like Udemy or Udacity, thinking that a plug-and-play solution addresses the needs of a 10,000+ person company. It’s a tempting approach when you’ve got thousands of employees to train. But, while these platforms excel at reaching large numbers, they often fall flat on their face when it comes to, you guessed it, personalisation.
The result is companies are now forced to choose between reach and relevance. It’s a false dichotomy that’s holding back true AI adoption across enterprises.
A problem bigger than efficiency
There is a problem of lost efficiency, but I’m seeing much broader issues that extend beyond individual companies to society as a whole. At a company level, when the AI skills gap isn’t addressed, businesses lose the ability to pursue top-line-enhancing strategies. Instead, they’re forced to lean into cost-cutting measures.
Tech and product teams are figuring out how to leverage AI to automate processes. That’s great. But if the rest of the company can’t keep up, we’re heading for a scenario where leaders face a stark choice: reduce headcount in less AI-savvy departments, or miss out on the productivity gains AI promises. This isn’t just a company problem—it’s a societal one. When companies focus on cost-cutting, people lose their jobs. But when they can drive top-line growth through effective AI use, it often means more jobs and opportunities. The stakes are high, and they extend far beyond the bottom line of any single organisation.
AI competency comes before AI transformation. This isn’t just about efficiency. It’s about maintaining a balanced, innovative workforce. When only part of your organisation can effectively use AI, you lose the diverse perspectives that drive true innovation.
The path to scalable, personalised training
The solution lies in finding a way to deliver AI training that’s both deeply personalised and broadly scalable. It’s about creating learning experiences that are directly applicable to each employee’s role, while still being deliverable at an enterprise scale.
Companies that do this well will have a significant competitive advantage. They’ll be able to leverage AI across all departments, driving productivity throughout their organisation.
As business leaders, it’s time to take a hard look at your AI training strategy. Are you truly personalising the learning experience for each role? Can you deliver this personalisation at scale? These are the questions that will determine whether your organisation thrives or struggles in the AI-driven future of work.
That’s the kind of edge that separates the leaders from the followers. Don’t get left behind.
Joshua Wöhle is CEO and Co-founder of Mindstone
