It’s not an elephant but a zoo you’re trying to eat…
Eating the Whole Zoo: A Strategic Approach to AI Training
During the week, someone suggested that putting together an AI training plan was like eating an elephant — to be done one bit at a time. My pushback was that AI training isn’t a single animal; it’s the whole zoo. We’re seeing a lot of people rush to the gift shop to buy a shiny object often unconnected to their business goals.
As it’s Friday and the school run didn’t need doing, it was time to get AI to get inside my head and work something out there. There’s even the idea that we’re in danger of trying to preserve skills which should become extinct at the expense of those that haven’t yet been discovered.
Read on for a journey that explores skills, rethinking the future, the need to unlearn not just learn, and why we need to be more deliberate in our approach to AI training.
The Current State of AI
The landscape of AI is rapidly evolving, driven by the increasing integration of AI technologies across various industries. Research shows that AI has surpassed human performance in several benchmark tasks, such as image classification and visual reasoning. However, the adoption of AI within organizations often lacks a cohesive strategy, leading to fragmented learning experiences and missed opportunities.
Many organizations are currently approaching AI training with a focus on immediate needs rather than long-term strategic goals. This ad-hoc approach often results in training programs that are reactive rather than proactive, addressing skills gaps only after they become apparent. For example, employees frequently rely on free AI tools they find independently, leading to inconsistent skill levels and a lack of formal guidance.
Moreover, the rapid pace of AI development means that training programs must continuously evolve to keep up with new advancements. There has often been an emphasis on training people to do, or not do something, without the development of the skills they need to adapt to the future. AI tools like Microsoft’s Copilot for 365 aren’t static, yet training often focuses on using specific features in the way that we might have learned to use other productivity tools.
One of the biggest challenges we face in thinking about AI is that we’re often thinking of better versions of what humans do. The focus is on automating existing things, rather than rethinking how things are done when humans are no longer required to perform certain functions. The assumption that things will still need to be done, and done in the same way simply better, is limiting the opportunities for AI — and as a result, the training that is being delivered is focused on the wrong underlying skills.
The field of AI is evolving quickly — though adoption is much slower than we might perceive. This causes us a challenge — we want to respond, but to do so without strategic direction can leave us spending a lot and delivering little value. As we come on to think about a strategic approach, it is important to remember that strategy is about setting direction, agreeing on the things you will do, and most importantly the things that you won’t be doing.
The Importance of a Strategic Approach
A strategic approach to AI training is essential for organizations to fully realize the benefits of their investments in AI technologies. By aligning training programs with business objectives, organizations can ensure that their workforce is equipped with the skills needed to drive meaningful outcomes. This alignment helps in connecting the dots between the job to be done, the training provided, and the strategic business goals, thereby maximizing the return on investment in learning and development.
One of the key benefits of a strategic approach is the ability to foster a future-focused mindset among employees. This involves not only developing new skills but also unlearning outdated practices and embracing new ways of working. In understanding how to train the workforce in using Microsoft’s Copilot, it’s become apparent that unlearning and letting go of current practices is as important as building knowledge of new technologies. This shift from “just too late” training to anticipatory learning prepares employees to adapt to future challenges and opportunities.
Furthermore, a strategic approach to AI training emphasizes the importance of role-based learning pathways. Different roles within an organization have unique training needs, and a one-size-fits-all approach is often ineffective. By tailoring training programs to specific roles — such as technology providers, users, enablers, and leaders — organizations can ensure that each group receives the relevant skills and knowledge needed to excel in their respective areas.
Role-Based Training for Effective AI Adoption
Effective AI adoption requires role-based training. We’ve been working with customers to identify four key groups or ‘learning lenses’ to target training: providers (typically IT and data teams), users (internal customers and business units), enabler roles (policy, compliance, ethics), and leadership. Interestingly, most customers have identified three of those — but the enabler community is often missed. By identifying the roles in these broad groups, we can start to think about developing a consistent collaborative approach to learning underpinned by a shared language but recognizing the need for learning is different.
Skills Personas and Their Training Needs
Different AI skills personas have specific training needs:
- AI Workers: Need foundational AI literacy to enhance productivity.
- AI Professionals: Require advanced technical skills and interdisciplinary collaboration.
- AI Leaders: Need strategic oversight, governance, and change management skills.
Practical Steps to Effective AI Training
Here are some practical steps for effective AI training:
- Conduct a thorough needs analysis that considers the current and future skills needed to perform in the role.
- Develop role-based learning pathways.
- Foster a future-focused mindset that considers learning alongside unlearning.
- Implement continuous learning and adaptation programs.
- Use nudge-based interventions to support gradual adoption and continual learning, giving greater flexibility to skills application as the AI tools change.
The AI Zoo and the Skillset Ecosystem
The field of AI is vast and complex, much like a zoo with a diverse array of animals. Training the workforce on AI should not be akin to buying a random souvenir from the gift shop. Instead, organizations need to take a holistic view of the skillset ecosystem, identifying which skills need to become extinct and which new skills need to be developed. By adopting a strategic approach to AI training, organizations can prepare their workforce for the future, ensuring they have the right mix of skills to navigate the ever-evolving landscape of AI.
Ready to be your own zookeeper?
If you’re ready to take a strategic approach to AI training and develop a comprehensive learning strategy, I can help. Let’s work together to ensure your workforce is prepared for the future of AI. Contact me to discuss how we can create a tailored AI training program that aligns with your business goals and drives meaningful outcomes.
