The Future of L&D - Ellen Parker

Ellen Parker

The Future of Learning and development

From The Learning Survey 2024 conducted by LPI

Data Analysis

Marketing and Communications

Content production and design

Artificial intelligence

Skills gaps in L&D

Using the data to create effective learning journeys

Better advertising learning and raising engagement

Creating effective and impactful learning

How will this affect our learning landscapes?

AIAnd L&D

• Personalising the learner experience
• Data mining
• Generating content

L&D Leaders and Managers most closely align on how AI can benefit their learning offer.

The Learning Survey 2024 - LPI

The potential of AI in L&D

The skills-based organization: A new operating model for work and the workforce; Deloitte Insights, 2022A global survey of 1,021 workers

66% are struggling to keep up with constantly changing skill requirements

Improving content quality

AI takes the admin out of updating or maintaining courses. It can assess when content is out of date to keep content fresh and relevant

Curating the learning feed

Much like a social media platform, AI can recommend training to the learner based on previous content accessed

Bridging the skills gaps

Given the right data, AI can be used to analyse a learner's skillset and goals and pinpoint where they need to develop to achieve and thrive

Advanced gamification

Creating immersive and playable scenarios for learners to work through. Chatbots to interact with, badges and leaderboards to compete with colleagues.

Continuous learning at speed

By tracking skill development, teams stay up-to-date with the latest industry trends through on-demand training content at their fingertips.

Content is accessible globally

With Natural Language Processing, content is easily adapted by reigon to help businesses scale effectively.

Personalising the learner experience

Improving content quality

AI still needs that human touch to check if the data it has used is correct, and if the content it created matches the needs of the learner appropriately.

Curating the learning feed

AI doesn't always get the recommendations right and the learner will need to curtate their feed, or flag content to an admin

Bridging the skills gaps

The data out is only as good as the data in. AI needs lots and lots of data to properly analyse and compare where a learner is, and where they need to be.

Advanced gamification

This is an expensive way to create learning that can still take up a lot of time. It would require heavy investment in tools and technology, perhaps beyond the team's budget

Continuous learning at speed

Learners could feel overwhelmed or pressurised to stay up to date with the recommendations, having an impact on their mental health

Content is accessible globally

The accuracy of the translation would need to be checked by a human to avoid any cultural or language issues.

Personalising the learner experience

Cons

Pros

• Lack of originality
• Needs to be manually checked
• It's only as good as its data sources
• A lack of emotional intelligence
• Expensive to implement
• High cost to the environment

• Summarizing text
• Generating writing pieces or content on well-known topics
• Determining the appropriate writing style for a specific task and spelling/grammar checks
• Creating photos and videos from text

• Generating assessments for learning
• Editing scripts
• NLP

Should AI be used for content creation?

Generating Content

The cost of running the servers for content to be created is having an unimaginable effect on the planet

Environmental Impact

It can assess the data coming back from learners to improve the effectiveness of training and measure implementation

AI can spot skills gaps, and areas for development and cut out the admin behind drawing insights from learning needs analyses continually.

Using AI to assess the data coming from learning gives L&D teams access to top-level insights to plan and implement an effective strategy.

Engagement and completion insights

Instant skills mapping

Make strategic decisions

Using AI to mine Learning Data

AI at its current stage is a tool to be used by L&D to improve their learning offer, not to replace it entirely.

With innovation and creativity, comes refinement

AI and its limitations

Lack of transparency

Sometimes it can be hard to understand how AI arrived at the conclusion it has drawn. This can make it difficult for someone to explain this and use it in decision-making.

Privacy and consent for data

For learning teams to use AI to mine the data of their staff, consent would need to be given and strict guidelines followed on how that data is being used

You can't replace a human

AI makes mistakes or doesn't sound human. Although Gemini comes close to replicating a person, it isn't perfect, and you need the human touch.

Bias and fairness in the content

If there are biases in your data, or cultural elements missing, these will show through in your creations. AI still needs to be sense-checked before content is launched.

Inital data clean up

The data out is only as good as the data in. By using this in your L&D offer with bad data, your strategy or change of learning intervention could be way off.

Lack of accessibility for some users

Not all content created by AI will be easily understood by those with disabilities or who are neurodivergent. Screen readers may struggle to adapt.

Risks of introducing AI to your L&D offer

Yes. With caution, research and applying the human element before and after the AI processing is completed.

Is AI worth the risk?

thank you