Learning agility has become an essential workplace skill. With generative AI reshaping the way work gets done, as well as continued economic uncertainty, both individuals and organizations have a stake in building a learning culture. For organizations, learning agility means building a resilient and adaptable organization that can weather change. For individuals, it means refreshing old skills and learning new ones to stay current. Charter’s new playbook, “The AI Educator,” offers a roadmap for using new AI tools to power learning across organizations.
In April, Charter fielded a survey about workplace learning and AI tools, with a targeted sample of 152 L&D professionals (individuals whose roles include learning and development, leadership development, and/or learning and enablement) and other managers across the US.
Here’s how respondents said that they learned new skills for their work over the past year:
Increasingly, workers are turning to generative AI chatbots like ChatGPT to develop learning plans, receive coaching and tutoring, and practice skills through role-playing scenarios. Ethan Mollick, a Wharton associate professor and author of a popular newsletter about AI, points to a recent research experiment that gave Kenyan entrepreneurs access to AI coaching through ChatGPT. Among the best performers, the intervention boosted profitability by 20%. Mollick notes that AI coaches can be effective in helping individuals gain many workplace skills, including how to “be good managers, how to communicate with people, how to run sessions like pre-mortems where you imagine how a project might fail in advance and then you go through it.”
Now, alongside individuals’ own exploration, many organizations are introducing institutional approaches to AI-based training. Through our conversations with experts and practitioners, we identified five of the most promising use cases: curriculum development, skills practice, AI tutor and content enhancement, mentorship and connection, and skills assessment.
Curriculum development
At organizations that already have a built-up library of professional development content, AI assistants can be a helpful partner in summarizing and synthesizing existing content into a personalized syllabus, organized by skill level or themes. It can also help L&D leaders mix and match existing content and repackage it as a new course for a specific audience or learning goal.
Learning platform Coursera recently used its Course Builder tool, an AI-powered platform that allows users to specify their learning goals and generate custom courses from existing content, to create a two-hour training session during a company leadership summit. Without it, Trena Minudri, Coursera’s chief learning officer, says the process would have taken eight weeks. Using AI, it took just two days.
Skills practice
Helen Edwards, co-founder of AI research and services firm Artificiality, points out that AI chatbots can be a low-stakes platform to practice skills like having difficult conversations, giving feedback, or crisis management. “You can role play,” she says. “You can have it test things. You don’t have to go out into the wild and make mistakes in real contexts.” (See our recent piece, “Five ‘aha’ ways AI can unlock solutions to our biggest work problems,” for tips one of how to do this.)
For example, a manager might want to practice having a tough performance conversation with an employee. With generative AI, they could practice giving feedback in a safe, low-stakes environment, whether using chatbots like ChatGPT and Anthropic’s Claude or tailor-built platforms for AI coaching, including Valence (the sponsor of Charter’s playbook). These platforms can help individual users identify relevant skill gaps or problem areas, model best practices, encourage reflection and practice through right-sized challenges, and follow through on these conversations with additional nudges and prompts.
AI tutor and content enhancement
While new AI-powered tools are allowing many L&D teams to move away from their traditional reliance on content libraries, they can also help existing courses, videos, and learning materials come alive. AI can help make recommendations for course material based on a user’s learning goals, as well as serve as a live tutor during the lesson or after the fact.
Infosys, a digital services and consulting company, provides employees an internal version of the company’s learning platform, which recommends courses similar to how Netflix recommends shows and features an AI tutor that can answer employee questions during lessons.
Mentorship and connection
Experts we spoke with, while optimistic about the potential for AI-based learning, highlight that there is no replacement for human connection. While 47% of professionals and other managers who Charter surveyed indicated that AI-powered coaching would make a meaningful difference to their work quality, 22% indicated that person-to-person coaching would also generate improvement, suggesting that these types of coaching should co-exist. AI tools, rather than replacing human mentorship, can make these relationships more meaningful by helping workers identify potential mentors and generate transcripts and takeaways from mentoring sessions.
Egle Vinauskaite, co-founder of AI learning consultancy Nodes, shares a case study from a US-based telecommunications company that used AI to build on an in–person development session with senior leaders. After the event, an AI assistant generated summaries of the discussions, with major themes and action items, allowing leaders to easily take insights generated during the session into their daily work.
Skills assessment
There’s a unique advantage to using AI to assess managers’ skills, argues Kian Katanforoosh, CEO and founder at skills platform Workera. “Because of the half-life of skill getting shorter and shorter, we need to update our assessments more frequently because skills change,” he explains. “AI helps us author and calibrate assessments faster so that whenever something comes out in the market, we can turn it into a validated assessment and serve it to the community as fast as possible.”
(It’s worth noting that historically, workers are more likely to reject rather than adopt new technology when “AI is managing or assessing individuals’ performance, rather than coaching them,” as we explained in our research playbook on AI and worker dignity. Employers can build trust in these tools by implementing guardrails against bias in assessment and maintaining human judgment in any decisions about hiring, promotions, and dismissal.)
For more on our survey data, tactical implementation strategies, and case studies and examples for each item of the L&D menu, download the full playbook.
Thank you to Valence, the sponsor of this playbook, for making this work possible.