We had an exhilarating two days with L&D and HR leaders from a variety of industries at the GP Strategies Client Forum. Both days were full of keynote presentations, workshops, success stories, demonstrations, and lively discussions on how and where to apply artificial intelligence (AI) strategies and technologies for the greatest effect.
Here are four takeaways we identified for AI in learning and development.
#1: AI Is Evolving Enterprise Skilling
AI is reshaping how many HR leaders view job roles and skills, and how to deploy them within an organization. In addition to optimizing job tasks of individuals themselves, some enterprise AI integrations are creating new ways to identify, analyze, and deploy skills.
AI excels at analyzing and organizing large sets of data. AI can make skills models and structures more dynamic, such as analyzing and making faster connections in clustered skill structures and skill marketplaces.
However, AI is only as good as the data it has to work with. It is critical for organizations to prepare their data for these types of integrations. The following chart highlights how the full continuum of how skills are expressed in an organization from competency models to the specific work outputs the employee generates on the job.
#2: Reprioritizing Leadership Soft Skills in an AI-Enhanced World
Large-scale and fast-paced changes, as the result of AI technologies, inevitably create fear and uncertainty. The media is full of headlines about jobs going away and how remaining jobs will evolve. Unfortunately, humans often fear the unknown and are resistant to change.
A recent poll from the American Psychology Association highlights the fear and uncertainty related to AI and its effect on jobs.
Percentage of workers intending to look for a new job in the next year by worry about AI making some or all job duties obsolete.
- 33% overall
- 25% not worried about AI
- 46% worried about AI
These number are worse among younger workers.
How Do Leaders Help Alleviate Fear and Drive Adoption?
Leaders can help their employees overcome the fears and unknowns surrounding AI by refocusing on uniquely human soft skills, gaining knowledge of AI, and communicating the benefits of AI to employees.
The following chart from Leah Clark outlines an approach leaders can take to help their employees embrace AI and enable efficiencies.
| What | How | Why |
| Audit your thinking Go first Integrate AI into team’s efforts Understand reskilling implications and opportunities | Training Shared experimentation Team assignments AI learning discussions Involvement | Reduce the fear factor Stay relevant Gain efficiencies Gain knowledge of AI capabilities and possibilities |
A key human differentiator in an AI-enhanced world are soft skills such as empathy. When leaders develop both soft skills and learn AI tools and capabilities, they will be able to help reduce the fear and unknowns of these technologies.
Understanding will help leaders alleviate fear among their teams with support and communication. As teams learn to embrace AI and upskill for it, they will realize new opportunities.
#3: AI Can Be an Expensive Investment: How and Where Should Organizations Get Started?
Developing and implementing AI, such as LLMs with company data and within protected company environments, can be costly projects. Many industries are split between taking a “wait and see” approach and implementing pilot AI projects within their organizations. However, it can be challenging to sit back and get left behind.
Getting Started with Individual AI Technologies
Employees and their teams should at least experiment with available AI tools and learn about short term productivity gains at a minimum. There are many AI technologies available and more emerge every day, but here is a quick list of tools to get started:
- ChatGPT, Microsoft Copilot, or Google Gemini. These tools can help write, generate ideas, summarize text, conduct research, and more.
- ElevenLabs. This tool has a limited free version where users can choose from a variety of AI voices and create text to voice audio. Human voices can also be cloned to create AI audio versions of real people.
- 7Taps. This platform includes multiple templates and features to quickly create microlearning courses. Features include quizzes, audio, video, and more. There is a free version to get started.
Getting Started with Enterprise AI: An Integrated LLM for Learning Content Libraries
Many organizations have challenges managing their learning content libraries and their components, such as eLearning, microlearning, videos, job aids, and more. It can be a daunting and tedious task to keep these resources updated, publish new resources, maintain records, and keep everything organized and easy to administer.
In a similar fashion to the evolution of skilling we mentioned earlier, AI excels at consuming, analyzing, and organizing vast amounts of data. Integrating AI technologies like an LLM within your learning content libraries and related platforms can solve many of these issues in an incredibly accelerated timeline.
The following chart outlines the challenges a recent customer was experiencing with their learning library of over 3,000 eLearning courses.
As a commercial learning provider, it is critical for this company’s users to quickly find courses they need to take via search or from recommendations. By integrating an LLM, the company solved these issues and continues to discover new capabilities, such as generating organization-specific quizzes, outlines, and more.
The benefits of integrating AI into their system can be organized into three key areas:
| Usability | Increased Revenue | Future Proof |
| Reduce time to access content Improve discoverability of new content Blend different modalities Non-L&D stakeholders and customers | Improved licensing New bundles and packaging of content Speed of deployment | The way people want to learn is changing Generative AI Skills Mobility |
#4: Measurement is a Continuing Challenge
The learning and development industry has always had a challenge in measuring and proving the impact of learning. This challenge persists in the L&D and HR industries even with AI, where measuring and quantifying the impact of AI is not a structured process.
Establishing a measurement strategy along with baseline metrics to monitor and improve at the beginning of an implementation is critical to demonstrate the impact.
The following chart can help outline key criteria to set up a measurement plan.
The Human+AI Future Is Now
With adoption and technological advancement happening quickly, L&D and HR professionals need to respond, and fast. AI can offer capabilities that were not possible before, however, they need to be implemented carefully to be effective.
It is critical to not lose sight of the human component and human differentiators in the process. With careful considerations, organizations will be able to develop their AI-enhanced workforce and excel.
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