Upskilling and reskilling are critical to successful gen AI implementation

Authored by Lindsay Falkov, Associate Partner, People Advisory

Harnessing the boundless potential of gen AI demands more than just deploying tools. It necessitates a holistic approach centered on human empowerment through upskilling and reskilling.

Tapping into the seemingly endless possibilities that generative artificial intelligence (gen AI) represents requires organizations to think bigger than simply rolling out new tools. Truly sustainable gen AI implementation begins with a holistic strategy — one that puts humans at the centre and supports them through the upskilling and reskilling needed to make the most of these emerging technologies. 

In 2023, gen AI proved to be one of the most rapidly adopted technologies the world has ever seen. It holds the potential to increase productivity, create economic impact, transform work, improve data governance and reshape workforce. Looking forward, more and more organizations will be seeking ways to unleash those upsides in pursuit of a competitive edge. What does that business case look like?

By the numbers, some estimates show as much as 7% of current US employment could ultimately be substituted by AI, while a further 63% could be complemented by it.¹ In Canada and around the world, workforces will need to work with, and alongside, gen AI for businesses and organizations to maximize its capabilities. Doing so will require a meaningful shift in how we structure, organize, guide and carry out work; a shift layered with implications, including organizational culture and operating models.

At EY, we’ve found that focusing on a core set of human factors can increase the probability of business transformation success to more than 70%. Putting humans at the centre of gen AI implementation necessitates a strategy that considers what values, behaviours and leadership styles will be needed to create an environment that’s receptive to adopting this technology and transforming in this way. With this insight, you’ll start to see ways the organizational structure must evolve for gen AI to really take off internally.

First things first: effectively optimizing operating models and organizational structures will mean clarifying how specific roles and responsibilities will evolve in light of gen AI adoption. This shift will also require governance to evolve accordingly; you’ll need the right oversight and expertise to manage potential risks or emerging threats posed by gen AI. All of these considerations will have implications for — and require engagement from — your people.

Tech tools make the greatest positive impact when people are empowered and trained to think about and to use them effectively. That’s especially true for gen AI, which will feel entirely new to much of the workforce. This technology represents a host of new opportunities and risks that must be considered in everyday use. Your people will need new skills that allow them to work iteratively in this transformational work pattern.

But that’s not all. Working with gen AI will also require a range of soft skills, fresh thinking and an inherent openness to continuous innovation. This could present an opportunity to refresh talent management overall through this lens, including a much tighter alignment of the new skills leaders and employees will need and the learning they receive.

Some of these skills include tactical capabilities: for instance, prompt engineering to ensure you’re getting the most accurate and impactful results from gen AI queries. Bias detection and handline will also be important. Employees will need to be able to spot biases that may exist, especially when the system is learning. While additional measures will be in place to manage risk, your people need to understand how to identify and address risk occurring in the results.

Moreover, your team must adopt a mindset rooted in flexibility and continuous learning to effectively engage with gen AI. This involves a readiness to adapt to evolving circumstances and swiftly acquire new skills. Employees should possess critical thinking skills to assess gen AI responses, emotional intelligence to understand the human context in applying those responses, a collaborative approach with the technology and, most important, resilience. Working with gen AI may yield results that don't perfectly align with expectations, and in such cases your workforce should respond with resilience — learning from experiences, iterating and improving their approach for better outcomes in the future.

If you’re going to double down anywhere, focus on that learning element now. To embed that people-first learning focus at the heart of your gen AI implementation strategy, start by asking key questions now. Doing so will surface critical insight about where your organization stands on the learning and development journey now, and gaps you can close through a strategic refresh. 

What questions should you consider as part of this process?

1. How will roles and skills evolve as we implement gen AI? A current and future state assessment helps clarify new tasks that will emerge as gen AI rolls out, outline related performance metrics and scope the skillsets employees will need to effectively work alongside gen AI. From there, you can build programming strategically.

2. Where are the biggest skill gaps in our current workforce? It’s critical to laser-focus learning budgets and investments on the areas that will require the most upskilling and reskilling. By mapping out the skills your people have, and the skills your workforce is missing to capitalize on gen AI, you can make learning plans targeted and impactful now and into the future.

3. Do we have clear learning pathways to move our people forward? Organizations — and the people who bring them to life — need learning to make meaningful progress and understand where they’re headed. When people feel their learning pathway is deliberate and strategic, they’re more likely to stay engaged and invest in a future they can be excited about; including one that incorporates gen AI.

4. How will leaders need to adapt their coaching styles? As employees build capabilities and confidence to work with gen AI and achieve results, the leadership supporting them must evolve, too. In this new paradigm, leaders have to adapt the way they lead, pay more attention to key areas and engage with people in different ways than they have in the past. Identifying those necessary shifts now can help further identify associated learning and development programs that proactively bolster these skillsets, strategies and styles.

5. Are we ready to shift away from process management? Gen AI will also bring new focus areas to the workforce. These could include engineering prompts and writing good questions that gen AI tools can effectively work, using gen AI data to shape better-quality outputs, advice and decisions, and drawing on gen AI’s analytics and creative results to design a better end product. All of these new focus areas will be relevant and important as gen AI gains traction across the organization. Employees and leaders alike will need training to understand these new areas and tackle them effectively in the course of their daily work. 

What’s the bottom line?

Anyone who’s gone through transformation before will likely know the importance of prioritizing people at the heart of the strategy. That said, gen AI is unique in terms of the risks it brings, the massive potential for productivity gains and the breadth of impact expected to touch two out of three people. These nuances require organizations to embrace this transformation thoughtfully. Start by experimenting in a safe way that considers all risks, conducting a change impact analysis and then using that intel as your foundation to start upskilling people and leaders today.