How to Upskill in AI Through Training, Mentoring, and Continuous Learning

Artificial intelligence (AI) is transforming the way we approach business. More and more people need to develop some level of AI skills, even if they aren’t in a technical role. The answer is also not as simple as hiring AI specialists or building job roles specifically around AI mastery. Instead, we need to ensure our people have access to training and knowledge to help upskill our teams.

Data from LinkedIn suggests that by 2030, 70% of the skills we use in most jobs will have changed, and AI is considered to be a major catalyst for this. Meanwhile, research from SHRM tells us that 35% of US workers are very or extremely concerned that AI will displace their current job in the next five years.

Despite these concerns, many HR professionals recognize that AI might not displace workers, but instead transform the way they work. The same research from SHRM found that HR professionals at organizations that use AI are 16x more likely to say that AI is transforming the existing jobs within their company (32%), rather than displacing them (2%).

We’re all still trying to work out where AI sits within our organizations. Everyone will have their personal levels of acceptance, with some workers choosing to only interact with AI in certain scenarios or for selected tasks compared to other colleagues who may be heavier users. For this reason, we can’t really send people on a ‘one-size-fits-all’ training day.

If you are considering how best to upskill your team in AI, we’ve got a few tips to help you build out meaningful training that is tailored to your workers. With any shiny new toy, we can get distracted by its capabilities and what it can do. Take a step back and consider the human who will actually be using it. Through mentoring and the right support, can you set them up for success with upskilling?

Why AI Upskilling Matters for Your Workforce

The practice of upskilling allows us to keep our skills sharp and ready to manage the changes that come to our job landscapes. AI is changing existing workflows across sectors, not just tech development. An AI upskilling program will then look to ensure workers can develop the knowledge, practical skills, and, perhaps most importantly, judgment needed in order to effectively work with these new and emerging tools and expectations.

One important thing to bear in mind: AI upskilling isn’t purely technical development.

Say you work for a healthcare provider, or for a nonprofit supporting education for minorities. Sure, there might be reasons to develop AI tools in your sector, but that will not be a task for your office workers. So, how can we reframe AI skill development in a way that actually supports them?

This can include:

• Promoting AI literacy: Understanding what AI can and cannot do.
• Developing practical AI skills: Using relevant AI tools effectively.
• Determining role-specific AI capability: Knowing where AI can support someone’s job.
• Championing human skills: Critical thinking, judgement, communication, creativity, problem-solving, and ethical decision-making.

These can all serve the average business and its workers far more than trying to force everyone to become prompt engineers for tech development they should never be working on.

Regardless of the department you work in, from sales and marketing to operations and finance, there are already ways to integrate AI current capabilities into your working practices, if such a shift is not already underway. We don’t have to make the conversation about finding new ways to insert AI into your organisation; we can instead look at it in the context of skill building to help you retain and develop your existing talent.

How to Upskill Your Team in AI

Upskilling is a process that isn’t as simple as sending everyone on the same course. With AI innovation taking many forms beyond the tools already at our disposal, business leaders need to be a bit more discerning when deciding how they wish to include it in their teams’ workloads. Let’s walk through some smart steps for AI adoption and upskilling programs within your company.

1. Start With the Work, Not the Technology

With access to AI training and new tools, it can be really tempting to dive in and explore the options out there. However, you need to take a step back and instead work out how you can use AI to solve problems and support business objectives without disrupting people’s work.

Anything you introduce should be tied to an actual task within your workers’ task loads. Do you know which teams are already using AI tools? Which tasks could involve AI assistance? Would introducing AI be a reasonable pathway, or would it significantly alter someone’s role in a way that doesn’t fit with their own career map?

2. Assess Your Current AI Skills

Start with a skills gap analysis, whether through employee self-assessments, manager evaluations, practical assessments, or a combination of all three.

Whatever you undertake could potentially uncover a wide spectrum of use. One employee may already be regularly using AI to help them with their repetitive tasks, another may never have used a tool at all, and a third occasionally uses generative AI to help them create drafts and outlines for their projects.

3. Establish the Training and Support Each Employee Needs

Everyone is at various starting points, and therefore you need to ensure you have differentiated development in place. Some employees might not have much interest in using AI in their everyday work. However, they still need a good foundation in AI literacy and responsible use, as they do with any other workplace policy. Others might be more interested in how to integrate AI in their workflows and other practical applications.

Formal learning through courses and workshops may be appropriate here, but it can be balanced with sandbox environments and training with real-world scenarios and projects. Don’t limit learning to the classroom. Complement it with hands-on practice. Give your workers the space and grace to learn from AI and build their confidence with it as you would with any other new tool.

4. Use Mentoring to Turn AI Knowledge Into Practical Capability

Mentoring gives us an opportunity to pair people together to learn from one another. In the context of AI upskilling, this could take the form of someone with stronger AI skills being paired with a colleague who is still developing theirs. This could be a good opportunity for reverse mentoring, with a worker with more technical AI expertise being paired with a senior leader.

Even if you want to explore AI within a single project, bringing everyone in the project into a mentoring circle can create a structure for feedback and support that can then be expanded if general AI use is also rolled out across the company.

Remember, a mentor doesn’t need to be an AI expert. However, they should be further along the journey exploring AI uses, and therefore able to pass knowledge or insights to their mentee. One-off courses can quickly become outdated. An ongoing support and continuous learning environment that everyone feeds into will stand the test of time more confidently.

5. Keep an Emphasis on Human Skills

Digital transformation and AI rollout shouldn’t exclude the development of an employee’s human-led skills. Soft skills like critical thinking, creativity, and adaptability will only become ever more important as AI tools potentially occupy new roles within our workplaces.

It is in the development of these human skills that mentoring really shines. Being able to work alongside someone, seeing how they interact with and overcome challenges, gives us so many opportunities to learn. Even if AI takes over routine tasks or more technical aspects of someone’s job, that doesn’t mean skills like critical thinking and communication become less important.

6. Give Employees Clear AI Guardrails

Don’t let yourselves get caught off guard by innocent experimentation. If people don’t know where their boundaries are, they can’t be expected to confidently explore this new horizon. AI guardrails and governance policies should outline important things like approved tools, human review protocols, and IP considerations. They should also include guidelines and rules around the data that is given to the AI tools, including customer data and confidential company information.

We appreciate that this isn’t the fun part of AI upskilling, but it is a conversation you need to have. Better to have a policy in place first than rush to put out a fire from someone’s unknowing mistake.

7. Measure Whether AI Upskilling Is Changing How People Work

As with any initiative to improve and upskill employees, you need to have some form of metric to help you measure success. This needs to go beyond course completion rates or tool usage; neither of these really gives you insightful data.

Instead, consider measuring employee confidence, progression against mentoring or personal development goals, and overall productivity or AI adoption in specific challenges where measurable.

A Few Extra Considerations to Include

We’ve already covered the importance of not giving everyone the same training, and not treating AI upskilling as a one-off checkbox that you never have to revisit rather than part of a wider continuous learning program. However, there are a few extra things we’d like to see you include in discussions around AI upskilling.

Primarily, don’t just assume that younger employees will automatically understand AI and its applications. Gen Z’s native tech skills have their role to play in the workplace, but that doesn’t mean that they are best placed to lead training and rollout.

On top of this, make sure that the focus is kept on job outcomes, not the tools themselves. Course completion isn’t the same as competency, and it is also not reason enough to expect employees to immediately produce good results in their AI projects if they have not had the chance to safely experiment and practice with their tools.

And, because it is that important, please make sure you have an acceptable AI use policy!

Build AI Skills Through Continuous Learning and Mentored Support

AI tools are constantly evolving. Employers can’t focus their energy on training employees in one batch, only to then consider the skills gap closed and solved. Development will have already moved on, and employees can be left feeling frustrated as nothing really changes.

When discussing AI, our first thought is often to the tools, but it should be to the people who will be using them. Upskilling doesn’t necessarily mean training someone to use a specific tool. It can be more about giving them the confidence and support through other skills to take on the challenge of an evolving part of their workplace.

Companies need to focus on creating a continuous learning environment where knowledge is always being brought in, shared, and updated in step with external and changing elements.

Mentoring will play a key role in this infrastructure. Having a good mentoring program at the heart of your upskilling efforts gives you the power to match employees with the right mentor, structure and track their development, and find support with others across your organization.

MentorcliQ’s award-winning mentoring software gives you everything you need to manage your mentoring relationships, whether they have the specific goal of upskilling your employees or not.

Want to know more? Book a demo today and find out how our platform can overhaul your approach to connection and learning in the workplace.