A roadmap for upskilling your workforce on AI
Now is the time for HR leaders to design an AI workforce skills strategy.
The window for HR leaders to build their competitive edge in AI skilling for the jobs of tomorrow is shorter than you might realize.
Take the example of the “digital transformation” movement of the 2010s, when the majority of HR leaders took a position that the “business” should answer the question of what digital upskilling would entail (and exactly what “digital” meant). In the years of change that followed, those who sat on the sidelines and deferred to others were largely left behind.
To avoid a similar fate around AI, HR professionals should be ready to dig in and use their expertise to set their organizations on the right path.
So, where to begin? Below, I lay out the context of our current moment and a set of steps to follow as you get your organization started with AI. You’ll gain ideas and resources to take back to your teams to help with the following:
- Understanding the initial considerations for your AI journey
- Preparation through AI self-skilling and experimentation
- Building out personas for AI upskilling
- Defining AI programs your employees need
Let's get started!
1. A narrow window of opportunity
Gartner’s “Hype Cycle” popularized the idea that all the noise around new technology can lead to a “trough of disillusionment.” It’s the moment when a new technology loses its initial excitement, and the combination of over saturation, early failures, and complexity causes a loss of energy and enthusiasm for the work.
“And while the ‘trough’ may feel like a chance to catch up on your other priorities, it’s actually a critical moment for reskilling and upskilling on new technology to make it a strategic advantage for your company.”
Matthew J. Daniel, Senior Principal, Talent Strategy, Guild
For now, there's still a window of opportunity in which to act without falling behind. Here are the questions I recommend HR leaders explore as they build their AI skilling strategy:
- Which companies are leading the way with AI adoption, and who are the thought leaders I should engage with?
- How do I get connected to existing internal tests and stakeholders to accelerate our learning without introducing new risks?
- Who are the internal partners that will build with me, and how do I identify the most significant needs we can work to address together?
- Which AI tools should my teams and I start experimenting with to build credibility and better understanding?
2. Learn from "digital transformation" and take an active role
“It can be tempting to lean on technical teams to dictate your business needs around AI, but let me be blunt: Deferring to the rest of the business to pull together the first rounds of AI skilling is a recipe for missed opportunities and HR irrelevance.”
Matthew J. Daniel, Senior Principal, Talent Strategy, Guild
As I mentioned at the start, the HR leaders who made it through the years of “digital transformation” were those who embraced “digital,” defined it, created upskilling programs, and realigned staff accordingly. In the case of AI, now is the time to choose your path and decide if you will define the skilling agenda or leave it to the business.
To be clear, HR should absolutely partner with other functions to drive the learning agenda and ensure the most essential needs of your organization are being addressed. My caution to HR leaders is simple: Lean in and stay connected to the decisions around how, what, when, and where AI learning happens.
3. Building a persona-based framework
Part of the challenge of knowing where to start with AI upskilling is addressing the fact that many employees already use AI at work — whether they are telling their managers or not. One survey of primarily office workers found that more than half are using generative AI for job tasks, but only 26% said their organization has a policy governing the use of generative AI. To add to the complexity, another study found that just 14% of frontline employees say they’ve received AI training.
At Guild, I have the opportunity to talk with our Fortune 500 employer partners about the challenge of reskilling the workforce once again. They have shared that they feel unqualified to decide who gets access to what AI skills and when — and that they might even defer to the business in the ways described above.
Looking at the experiences faced by these companies, we recognized that AI skilling isn’t a one-size-fits-all or even a one-size-fits-most proposition. As a result, we developed a persona-based framework for approaching AI upskilling.
4. Investing in foundational skills for AI
Once you’ve identified the segments of learners in your organization, it’s critical to define the categories of AI skilling that you want to emphasize. This is especially important when you recognize that employees are hungry for AI content and are likely already seeking it out on their own.
Case in point: At Guild, we found that where AI programs were available, 1 in 10 learners who already had a degree were enrolling in AI certificate programs. In a survey of our users, we also found that 15% of financial services employees and 12% of retail employees said that AI had already impacted their career direction or the types of roles they were considering.
While the categories of relevant skills will undoubtedly evolve over the next few years, we’ve focused on what we believe are the most foundational skills that will continue to serve employees well even when new and increasingly innovative technologies are released.
Here are the four categories we started with, in case they are helpful in designing your own skilling approach:
- AI Fundamentals: Building literacy and ethics around the use of AI and developing the ability to consider the implications of AI on your work.
- AI in Practice: Understanding the landscape of AI tools available and identifying when and how to practice using those tools in their roles.
- AI Expertise: More technical skills that offer learners the ability to build and scale AI in their area of business.
- AI in Leadership: Empowering leaders to incorporate AI into their business strategy and eventually evolving to an AI-driven strategy.
5. Charting a path forward
With your goals, personas, and skilling programs mapped out, it’s important to put the work into practice while the timing for upskilling is in your favor.
Below are my suggestions for what to keep in mind as you move forward:
- Continue to view skilling investments through an equity lens. Guild’s research has shown that the groups most likely to use AI tools are those with more education and higher incomes and are younger, white, and male. As decision outcomes regarding AI will be infused through nearly every part of the business, it’s critical to approach skills development such that your entire workforce — including frontline employees — can grow and succeed.
- Experiment and stay open to how AI can shape your workforce. The next phases of Gartner’s “Hype Cycle,” after the “trough of disillusionment,” involve rapid expansions and increased energy. Especially if your AI upskilling is on track, you can maintain an open mind toward AI innovation and its potential value for your employees and business. For inspiration, look at the vision Peter Schwartz, Chief Futures Officer at Salesforce, offered at last year’s Guild Opportunity Summit.
- Remember that people are the real key to your AI strategy. As Guild’s Dean Carter explained, HR is critical in creating a cultural environment that embraces the coming change and helps employees get excited about their role in their organization’s future. Just like we’ve seen time and again over the last several years, HR leaders will have a big opportunity and responsibility to step up and help create the future of work.
Want AI updates for HR leaders? Sign up for the Compass newsletter ->
About Matthew J. Daniel
Matthew is Senior Principal, Talent Strategy and Mobility at Guild.
