Here’s an ironic twist in the age of artificial intelligence (AI): To navigate the vast potential of generative AI (genAI), we need distinctly human expertise. It’s like an advanced spacecraft that can explore new frontiers, but without skilled human navigators, it can’t leave the launchpad. This paradox underscores the critical challenge facing leaders today: equipping our workforce with the skills to work with AI.
Yet, despite the clear need for upskilling, many companies are falling short. The numbers tell a striking story: While 94 percent of employees are eager to learn new skills, only 5 percent of organizations are implementing reskilling at scale, according to Accenture. This gap presents a significant challenge for Learning leaders, who often struggle to determine where to begin.
A 3-TIERED APPROACH
In our experience, successful genAI upskilling typically starts with one of three key groups: senior leaders (including boards), technical experts, or the broader workforce. Each has distinct learning needs and plays a crucial role in AI adoption across the enterprise.
1. Executive Leaders: Shaping the genAI strategy. Executive leaders are pivotal in driving the generative AI strategy, so their understanding and buy-in are critical for success. Yet, Accenture has found that 65 percent of executives feel unprepared to lead AI transformations.
For this audience, high-touch, and ideally in-person, learning experiences are highly effective. Such experiences include strategic roundtables, executive briefings, and immersive demo sessions. Leaders can explore genAI opportunities and top use cases for their organization, as well as responsible and ethical usage.
Some executive teams, however, have moved beyond introductory discussions and are already driving multiple genAI use cases across the organization. In this case, upskilling technical teams becomes even more critical, as they are essential for building and scaling these initiatives.
2. Technical Leaders: Turning genAI strategy into scalable solutions. Technical leaders are essential in bridging the gap between strategy and execution, whether in smaller experiments or enterprise-wide deployments. Sandbox environments are particularly effective for helping technical teams apply their learning in real-world scenarios, moving from theory to practice.
By upskilling software engineers into machine learning experts or technical roles into data architects, for instance, Learning leaders can help ensure the organization has the capacity to scale genAI efforts.
3. The Broader Workforce: Making AI use practical and responsible. For the broader workforce, genAI must be made relevant to their daily tasks to help them actively support the organization’s genAI strategy. Two common training needs we hear are around responsible AI to ensure the ethical use of new tools, as well as Microsoft Copilot upskilling to boost productivity. Alongside culture and change management efforts, these programs enable employees to personally keep their skills sharp while helping the organization remain on the leading edge of AI.
A CONTINUOUS LEARNING CULTURE
As genAI becomes more integral to organizations, the skills gap is likely to widen without proactive measures. This tiered approach to upskilling not only bridges the current gap, it creates a culture of continuous learning and adaptation. By driving genAI adoption from the boardroom to the frontline, companies can unlock new levels of innovation, efficiency, and growth in the AI-driven future.