Generative artificial intelligence (genAI) is reshaping work across industries, and leaders must ensure their organizations have the skills to keep up.
Yet, a recent Accenture report (https://www.accenture.com/us-en/insights/consulting/genai-talent) highlights a concerning gap: Some 94 percent of workers are eager to build genAI skills, yet just 5 percent of organizations are actively up-skilling their workforce. The report paints a stark picture—workers are eager for genAI skills but lack organizational support. This is where Learning professionals, closely partnering with business leaders, can play a critical role.
Learning teams must help leaders envision relevant genAI use cases, engage in hands-on experimentation, and cascade the learning to their teams.
Generic market overviews do not suffice; programs must be highly customized and co-created, with highly practical, hands-on application.
Increasing Impact
Here are some ways to make these programs more impactful and drive long-term upskilling and culture change:
- Make AI a leadership imperative. Work with sponsors to embed AI fluency as a core pillar of leadership development programs. Accenture, for instance, mandates all senior leaders to complete genAI training through a series of executive briefings and digital learning courses. The requirement ensures they have personally upskilled themselves and are equipped to spread the learnings to their teams.
- Leverage leaders as teachers. Amid all the hype, it is critical to show practical examples of how, used responsibly, genAI can truly transform internal workflows and customer-facing experiences. Inviting power users (at any level) of genAI tools to share their use cases and workflows adds much more relevance than theoretical, “art of the possible” scenarios. A global defense company, for instance, recently implemented an AI-powered knowledge bot and has worked with its Learning team to showcase it with hands-on tutorials during training sessions.
- Encourage innovation around workflows. Embed innovation sessions and hackathons as part of development programs to help leaders reflect on their area of the business and identify where genAI can optimize decision-making, resource allocation, and strategic insight, freeing up time for higher-level work. Ideally, these sessions should be run with their teams, as well as external technology partners, for maximum impact and relevance. Starting with internal genAI use cases (vs. customer-facing options) can provide a low-risk way to start experimenting and learning.
- Remap skills. Once genAI use cases are identified, Learning teams can help determine newly needed skills to implement them. These insights should, in turn, feed into target capabilities for future development, as well as broader talent shifts across the organization. Apple, for instance, recently recognized a need for stronger AI capabilities and redeployed most of its autonomous car team toward AI.
- Empower ongoing learning. The rapid pace of genAI evolution means leaders need continuous learning support beyond formal training. Facilitate collaborative networks where leaders can share their successes, troubleshoot challenges, and learn from emerging best practices. This ongoing, peer-driven learning accelerates adoption and builds a sense of shared purpose as leaders navigate this uncharted terrain together.
A Competitive Edge Starts with Learning
Learning teams that prioritize AI fluency in their leadership development programs have a direct impact on their organization’s success. By equipping leaders with AI knowledge and ways to innovate with their teams, they ignite upskilling across the broader workforce.
In a landscape where AI is continuously evolving, their commitment to leadership upskilling builds a future-ready talent pool, keeping the organization agile and ready to thrive in the age of AI.
