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AI in Workplace Learning (2019 DevLearn AI + Learning Summit)


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Artificial Intelligence (AI) is shaping the future of work and changing almost every industry, including learning and development.

At the AI & Learning Summit at DevLearn 2019, we explored the emerging world of AI, including what it is, how it works, and most importantly, how it will transform what learning and development looks like in the future. JD from LearnGeek presented on the realities of AI in workplace learning as well as tactics for leveraging AI to build an impactful recommendation tool.

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AI in Workplace Learning (2019 DevLearn AI + Learning Summit)

  1. 1. PRACTICAL AI The Reality of in Workplace Learning
  2. 2. JD Dillon Chief Learning Architect Founder + Principal
  3. 3. Which option would you choose? Pixabay Traffic signals use AI to dynamically adjust traffic flow in congested areas. Self-driving cars have the potential to fundamentally change the personal transportation experience.
  4. 4. 80% of CEOs see AI as a critical component of their digital transformation strategy Forbes
  5. 5. Pixabay Looking back to past tech adoption challenges can help inform how we build a vision for AI within L&D.
  6. 6. eLearning social learning gamification mobile learning L&D has historically struggled to find unique value within large-scale technology trends.
  7. 7. Completely realized technology should help us evolve beyond our course mindset.
  8. 8. AI AIAI may seem like a distant prospect for many L&D teams today, but workplace technology (including learning) is rapidly exploring and adoption AI-based capabilities right now.
  9. 9.
  10. 10. Pixabay Functional AI Transformative AI
  11. 11. The Steps Every L&D Team Must Take in Order to Achieve Transformative AI Pixabay
  12. 12. 1 | comprehend the future of work Pixabay L&D must understand how the workplace is changing to properly plan for how to best support people in the near future (AI or otherwise).
  13. 13. 2 | do your AI homework L&D pros can leverage a variety of educational resources to improve their understanding of AI and help them have more informed conversations.
  14. 14. 3| explore how AI will be applied across the organization Pixabay Most organizations are already applying improved data and AI practices. L&D pros can leverage internal expertise and potentially align with the organization’s evolving AI vision.
  15. 15. Pixabay 4| establish a vision for AI within your renewed L&D strategy Once L&D understands how their workplace and employee needs are changing AND how the organization is leveraging data and AI, they can shape an improved strategy (potentially with AI-enabled tactics).
  16. 16. VALUE ADOPTION Personalization Content Authoring End User Administrator Chatbots Content Recommend Content Tagging NLP Search Impact Analysis System Administration Gap Identification Smart Coaching Expertise Match Translation
  17. 17. Pixabay 5| fix your data practices AI requires A LOT of data for most high-impact use cases. L&D must expand beyond traditional “learning data” and leverage available “business data” that relates to performance.
  18. 18. 6| partner with experts + solution providers Pixabay L&D may have the resources to add data scientists and AI experts to their team … but many will not. L&D pros can leverage their tech partners to understand what’s possible and how to begin exploring AI-enabled tactics.
  19. 19. Pixabay 7| experiment Stakeholders may not recognize the value of AI-enabled learning until they experience it. While moving towards a larger vision, L&D can experiment with high-value use cases.
  20. 20. Pixabay 8| measure, iterate, socialize L&D must socialize how AI-enabled technology can transform their practices … before wide-scale implementation. Early experiments can provide quick wins through measurable results.
  21. 21. Pixabay 1 | comprehend the future of work 2 | do your AI homework 3 | explore organizational AI 4 | establish a vision for AI in learning 5 | fix your data practices 6 | partner w/ experts + providers 7 | experiment 8 | measure, iterate, socialize
  22. 22. AI is not an L&D concept. It’s an established field with tons of research and deep expertise. L&D must find ways to leverage this expertise and apply it to address modern workplace performance challenges.
  23. 23. eLearning social learning gamification mobile learning AI This will help L&D rapidly adopt AI and avoid the missteps of our technology past.
  24. 24. Follow the AI discussion with our curated LearnGeek online magazine filled with that latest articles and resources.
  25. 25. PRACTICAL AI The Reality of in Workplace Learning
  26. 26. What is the role of RECOMMENDATION in workplace learning?
  27. 27. Netflix Why is L&D obsessed with the idea of creating a “Netflix for learning” experience? Is this what people really need to improve their performance and accomplish their goals?
  28. 28. What PROBLEM are you trying to solve?
  29. 29. How do we keep people watching? How do we get a person to their destination as quickly and safely as possible?
  30. 30. Every employee is UNIQUE. iStock
  31. 31. TIME CAPABILITY How people THINK learning happens
  32. 32. TIME CAPABILITY What ACTUALLY happens as people develop
  33. 33. ServiceSafetyProductsBrand 20% 75% 55% 60% ServiceSafetyProductsBrand 65% 75% 5% 20% SUSTAINED CAPABILITY People don’t just arrive with different levels of ability. They also progress at their own paces.
  34. 34. ServiceSafetyProductsBrand ServiceSafetyProductsBrand SUSTAINED CAPABILITY The goal is to enable AND sustain mastery for the duration of the person’s time in the role.
  35. 35. Individual Scale iStock L&D is historically challenged with balancing the needs of the individual with the scale of a modern business.
  36. 36. Pixabay PERSONALIZED LEARNING How do we provide the right support at the right time to help an individual employee improve their workplace performance?
  37. 37. L&D can leverage a variety of tools and tactics to personalize support. AI is a powerful foundation that can strengthen many of these concepts.
  38. 38. Netflix The Current State of Recommendation in Personalized Learning
  39. 39. Demographics Consumption Interests Shared Attributes Machine Learning Model?
  40. 40. What PROBLEM are you trying to solve? Provide an individual employee with the right support at the right time to improve a specific behavior within their workplace performance.
  41. 41. assumes content is the solution reduces discoverability applies very limited data rarely validates the impact of a recommended solution help users sort through extremely large content catalogs improve the perceived value of workplace learning THE GOOD THE LIMITATIONS
  42. 42. 4 components of an impactful learning recommendation engine DATA ENGAGEMENT SOLUTION OPTIONS AI
  43. 43. Multi-Dimensional DATA Profile Who is this person? Demographic What has this person reviewed? Consumption What does this person know right now? Knowledge What is this person doing on the job? Behavior What impact is this person having on the business? Results What else is happening around this person? Context What does this person say they want/need? Feedback How does this person engage with the org? Connections
  44. 44. A great recommendation engine will not matter if people are not engaged in a continuous learning experience.
  45. 45. Reinforcement Analytics Motivation Practice Shared Experience Shared Knowledge Events Online Content Experiences Messaging Knowledge Growth Business Results Coaching continuous learning experience
  46. 46. The right-fit solution may be digital content … … or it may be another type of support activity.
  47. 47. Pixabay proactively identify performance challenges validate the effectiveness of a available activities associate potential solutions with support needs (without direct instruction) “push” potential high-value activities based on individual performance challenges and context The Role of AI in Recommendation
  48. 48. People are always learning. Learning is always personal. L&D must enable continuous personalized learning.
  49. 49. Netflix This is NOT the right model for impactful personalized learning!
  50. 50. Make it OK to personalize Build audience trust Improve your data practices Challenge your vendor partners Shift to a continuous learning model Recommended Next Steps
  51. 51. @JD_Dillon JD Dillon
  52. 52. What is the role of RECOMMENDATION in workplace learning?