AI-enhanced products and skills-based organizations are two of this decade’s defining HR trends—and the combination of the two promises to be a transformative one. PeopleFluent’s VP of Product, Gavin Beddow, explores how AI (both free and paid options) can support your organization’s skills-based development plans. What does the future look like utilizing these strategies, and what can you do right now with AI to enhance your existing talent development strategy?

How Can AI Support Skills-Based Development?

According to LinkedIn’s Economic Graph Research Institute, the average role’s core skills are expected to change by up to 65% by 2030, and AI tools are a significant factor behind both the pace and scale of this change. Meanwhile, Deloitte reports that 89% of executives believe skills are becoming more important in how they define work, deploy talent, manage careers, and value employees. While AI tools contribute to this phenomenon by introducing a whole range of new skillsets that the workforce needs to reckon with, the technology itself has an exciting role to play in how organizations address their skills requirements.

AI makes building a robust skill enablement strategy more viable in organizations of all sizes, but its ability to reduce the difficulty, time commitment, and cost of such a strategy in larger organizations is particularly profound. There are four key areas that HR professionals deal with every day where AI can already offer a helping hand. These areas are:

• Skills mapping and skills gap analysis
• Content creation
• Workforce agility
• Knowledge retention and practice

Understanding how AI can help in each of these areas, as well as the current progress of the market for AI-enabled skills tools, will help you better work with your vendors. It will also help you positively impact the efficiency and effectiveness of your teams.

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1) AI-Assisted Skills Mapping and Skills Gap Analysis

The skills mapping process, which involves identifying a taxonomy of skills that matter to your organization and mapping those to the skills you have and want available to you, has traditionally been a time-consuming one. If you’ve been part of a larger organization working on a skills project in the past, there’s a high probability that the size of the problem has stopped you in your tracks.

When the traditional, manual approach to skills mapping is taken, large enterprises often find that they’ve got several stakeholders all with different skills taxonomies they can’t agree on. Manually reviewing skills and trying to reconcile them is time-intensive, and organizations rarely manage to make every stakeholder happy. Projects often get hung up on the need to “get it right first time” and spend months, if not years, getting nowhere.

Thankfully, an appropriately trained AI allows us to be far more flexible and, of course, many times quicker. An AI-assisted tool can simplify your existing taxonomies and map them to your roles and resources. Point it at a large database of job profiles, and it can automatically surface the skills required by each position.

You can try this for yourself with Lightcast’s skill parser demo. Lightcast uses its existing taxonomy to produce an AI-generated review of the skills in the content you provide it with. Feed a job or employee profile into the public demo, for an idea of how this technology works—it’s definitely something worth experimenting with (within the confines of your organization’s data privacy policies!)

PeopleFluent’s own AI-enabled Skills platform, Stories, uses AI-assisted skills APIs to deliver its unique skills mapping functionality. The power of Stories is that it connects to a wider pool of data, both third-party as well as your own organization’s tech stack, to assist in your skills-mapping process. It provides a far more comprehensive understanding of your organization’s skills profile that, once mapped, will provide detailed insights into strengths and potential business strategy-related skills gaps.

READ MORE ABOUT PEOPLEFLUENT STORIES | ‘Introducing Stories Skill Enablement’

2) Using AI for Content Creation

Once an organization understands the skills it has, and the skills it needs, it can start building or sourcing training content specific to the unique organizational requirements it has uncovered. AI has a role to play here too. The traditional content creation approach has been to manually build content in eLearning authoring tools, with the support and input of subject matter experts. And while manual content creation isn’t going away—and modern collaborative, web-based authoring tools have refined the learning creation process—supporting designers and SMEs with AI promises further significant improvements to the time-intensive production processes we’re all used to.

An AI-assisted authoring solution can leverage your organization’s existing materials to accelerate content creation and target specific skills. For example, some large organizations are using AI to dynamically update onboarding courses when teams make process changes. The AI springs into action when organizational knowledge in the company wiki, intranet, or another internal resource is altered, removing the need for a learning designer to manually implement the change.

Then, there's the possibility of using Generative AI to assist and accelerate content design. An SME can provide the AI tool with their knowledge and ask AI to lay it out as a piece of eLearning. This could be transformative in areas where specialist knowledge needs to be deployed quickly—where organizations have previously had to choose between getting the content late but properly designed for easy understanding, or on time but in whatever inefficient format the SME knows how to throw together.

Translation is also another strong suit for generative AI, with AI-assisted translation capable of taking the content you design and quickly translating it into multiple different languages.

In all of these use cases, the accuracy of what you create won’t always be 100%. All of these outputs require human validation once generated. They will be limited in how creative they can be in terms of design. The advantage AI offers is getting you to a refinable first draft more quickly. We encourage you to explore the AI-assisted authoring features of your content authoring tools, or directly with a generative AI tool such as ChatGPT.

3) Deploying AI in Your Knowledge Retention Efforts

Helping learners maintain the knowledge they gain from learning, and proving that your learning strategy is working, is a key part of any robust skills and talent development approach. Knowledge retention checks are already commonly used for topics such as security compliance training: high-stakes, repetitious training that needs to be easy to roll out to a wider audience.

Though important, such training is made available on rigid schedules and is untargeted. This is fine for this form of large training program, but the concept of providing knowledge retention and practice opportunities for a wider range of courses is an exciting one.

In fact, we’re starting to see AI-assisted approaches that quiz individual learners on specific skills they’re developing, and doing so within the flow of work. For example, some organizations are using Slack bots that will, a week after a learning event, message a learner with a quick quiz to complete. This creates an unobtrusive but timely feedback moment, and helps create better and more specific learning outcomes.

Most excitingly, AI’s ability to process large datasets and use resources beyond their initial purpose promises to open up limitless opportunities for practice. In conjunction with Skill Mapping, Generative AI can be used to generate new supplementary experiences to assist in knowledge retention based on subject matter, skills, and skill proficiency levels. The fact that it can do this at a scale that simply wouldn’t be practical without AI, while simultaneously delivering these experiences down to a personalized level, is particularly inspiring.

AI-generated practice quizzes and an AI coach are key features of Stories by PeopleFluent. Another way you can leverage AI for your knowledge retention efforts is to ask Claude.ai or another generative AI chat agent to take the content you provide and generate a role-play scenario for practice purposes, or create questions and a release plan for a knowledge retention exam.

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4) Achieving Workforce Agility With AI

Finally, and in culmination of the preceding strategies, there’s AI’s potential to enable new forms of workforce agility. Organizations need to create plans for how they will fill roles and address their skills gaps, and they must anticipate how those gaps will evolve in the future based on succession and attrition trends. They need to know their skills and their people, to develop the right content, and to have the organization at large buy into the plan.

Once again, this is a process that’s currently achieved manually. Larger organizations will have huge, complicated systems dedicated to this purpose, but the scale and complexity of succession means they’ll only be doing it for particular cohorts. It’s simply too costly and time-consuming to do on an individual basis.

AI-driven systems with this capability are in their infancy, but an AI-driven workforce agility approach will:

• Reduce time to implement changes by utilizing AI skills mapping across profiles and content
• Rapidly identify strategic skill gaps and existing training, practice, shadowing, or mentorship recommendations to address them
• Support faster creation of new training materials via AI-assisted content creation
• Quickly identify suitable employees with the potential to fill skills gaps and succession requirements
• Enhance identification of emerging needs through integration with external market data

All that’s needed to make this possible is sophisticated software and an organization that’s committed to planning its future. While there aren’t currently a lot of organizations using AI with sufficient forward-looking workforce agility to help predict outcomes down the road, we can see this use case coming. Senior stakeholders are asking for it and it’s an obvious add-on to some of the succession planning tools that already exist in the market.

And there are also already some ways you can leverage generative AI for workforce agility-adjacent tasks. For example, you could try using Microsoft Copilot to perform a skills gap analysis between two roles, and to suggest activities to fill the gaps it finds. There are also a number of talent marketplace platforms using AI and skills mapping to deliver personalized development paths and growth opportunities.

DISCOVER MORE | ‘Leveraging AI for Talent and Skill Development Strategies in Regulated Industries’

Conclusion

HR and L&D professionals are being asked to do more with less. AI offers a unique opportunity for these leaders to quickly and effectively drive impactful talent development strategies. Successfully integrating AI into both your skills development strategy and your tech stack requires careful planning and alignment to business goals.

You’ll also need to take steps to protect your organization from potential security risks. Nonetheless, AI can supercharge your workforce agility by speeding up content development, aligning disparate systems, and uncovering crucial gaps in your workforce.