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The AI Advocate's Role in Unlocking Its Potential in Learning and Development

Updated: Oct 14, 2023

by Mike Vaughan, Brian Hackett, and Markus Bernhardt

Why are Learning and Development (L&D) professionals struggling to see the biggest opportunity in L&D? As one CLO recently shared, “I get it; people outside L&D teams already utilize AI to create training. Why wouldn't they? The tools are user-friendly and efficient… [it] is adequate for immediate business requirements. It seems like a significant opportunity to step up. Instead, L&D professionals are sitting on the bench. We need to get in the game!" Does this sentiment resonate with you?

For half a century, technological innovations have been shifting the learning landscape. Today, with the introduction of AI, we stand at a pivotal juncture in the journey as L&D professionals. AI is the unexpected Swiss Army knife revolutionizing the processes of creating, developing, and delivering training. It's akin to injecting nitrous into a race car, propelling it to newfound speed and excitement. From a business standpoint, this translates to substantial cost efficiencies, time savings, and better learning—an unequivocal win-win scenario.

What does it take to get into the game?

L&D needs AI advocates. No, we’re not saying grab your most enthusiastic technophile on the team to sing the praises of AI publicly. Imagine the strategic addition of an AI advocate who plays a crucial role in promoting the understanding, acceptance, and responsible integration of AI technologies while skillfully championing the adoption of these solutions. AI advocates can actively ensure L&D has a seat at the table. Put in direct terms, the sooner you get an AI advocate in place, the more L&D jobs you’ll save. AI will not replace jobs, but L&D will need to learn to work alongside AI to automate and accelerate the creation of training. We believe AI can be a unifying force across organizational ‘silos’, and L&D can be instrumental in making this happen.

What does an AI Advocate do?

An AI Advocate demonstrates how AI can significantly cut design and development costs, accelerate the time required to produce high-quality learning, and transform L&D into a data-driven culture.

Here is a summary of the key benefits the Advocate can demonstrate (not just talk about):

  1. Speed: From manual to automated. Many of the AI tools created this year can help L&D professionals cut costs by upwards of 90%. There are tools to create images, audio, videos, avatars, animations, and 3D graphics within minutes. Some tools rapidly create eLearning, microlearning, and simulations. Other tools are revolutionizing just-in-time and in-the-flow of working learning. There are even tools for securely ingesting previously created learning materials and converting them into experiential learning.

  2. Experience: From what-to-think to how-to-think learning. What-to-think learning entails teaching people the processes, procedures, and methodologies they need to perform their jobs. How-to-think learning entails applying what people know to new and emerging situations. AI is optimized for teaching the what while humans are great at teaching the how.

  3. Analytics: From smiles to insights. Many organizations still evaluate the efficacy of learning using smile sheets. There’s a good reason: most traditional technologies do not capture useful data, and making sense of what little data is available is challenging. With modern learning platforms and AI, behavioral analytics (how an individual’s thinking and behavior changes over time) is now possible and applicable.

What is your AI perspective?

Undoubtedly, AI is a game-changer, but it also raises new questions from stakeholders. Each organization has unique attributes, so we’ve posed the following questions to help you shape your perspective on AI’s transformative potential for your L&D team and organization. The lens in which we encapsulate our perspective is tied to one or more of the outcomes of speed, experience, and analytics. Most businesses are adopting AI to help them achieve a competitive advantage in getting products to market more quickly and providing higher-value services more effectively. So, if business leaders are thinking about speed, experience, and analytics, then L&D should be thinking about the same thing.

What advantages can we expect from AI in L&D?

Let's flip the script on this question and introduce a new concept: speed to performance. Rather than detailing a list of advantages, let’s focus on how AI accelerates speed to performance. The more quickly we can educate individuals and the more effectively they can apply their newfound knowledge, the better the organization will become. This reasoning will resonate with stakeholders, positioning L&D as a partner in helping the organization become more competitive.

Is reducing staff a viable option if AI can satisfy all our training requirements?

While some organizations might see this as an opportunity to ‘right-size,’ let’s consider it an opportunity for organizational growth and adaptation. Instead of cutting staff, consider reallocating resources to address a critical business imperative—upskilling and reskilling. Heavyweights like McKinsey, IBM, and the World Economic Forum agree that the world is on the brink of the most substantial training challenge in our history, with a staggering 1.4 billion people needing reskilling in the next five years. That's why it's vital to kickstart this process by upskilling instructional designers and turning them into experiential designers. While AI automates knowledge-level learning, L&D professionals can focus on crafting experiences that turbocharge skill development.

You mention cost savings; what are training costs today compared to what we anticipate they will be once we start to see the benefits of AI tools?

This is another budget-cutter question. Therefore, our recommendation is to frame the discussion regarding how L&D will accelerate the design and development of learning to meet the demand of upskilling and reskilling the workforce. Not to sound overly cliché, but the conversation needs to convey that learning can be done faster, better, cheaper, and at scale. Emphasize the better by talking about quality. This is critical because speed is often associated with a lack of quality. Many organizations, especially those focusing on heavily researched products, must emphasize quality. Here’s how: to achieve speed to performance–that is, to provide an individual with the skills they need to do their job better and faster- requires the content and learning experience to be high-quality. Thus, suggest using the savings from AI tools to enhance and elevate the quality of educational experiences to accelerate skill acquisition.

Can we get rid of certain tools to cut costs?

While this seems logical, costs for tools shift to newer and more advanced options rather than vanish. That’s why it’s prudent to concentrate efforts on enhancing the learner's experience. AI will soon outshine traditional tools for creating eLearning content, disseminating knowledge, facilitating just-in-time learning, and improving performance on the job. Since AI will become responsible for knowledge-level education, L&D professionals can shift their energy toward what they love doing: improving the skills of others to feel more confident and successful in their careers and their lives. This approach emphasizes AI's unique advantages and how it supercharges upskilling, making learning more efficient and effective.

How are organizations ensuring the successful integration of AI to cut costs and improve learning?

To establish credibility as an AI Advocate, you’ll want to consider drafting both an AI Manifesto and an AI Playbook.

AI Manifesto – This document outlines how L&D will use AI ethically and responsibly to help the organization gain a competitive advantage through the upskilling and reskilling of the workforce.

AI Playbook – If you’re playing to win, you’ll need a playbook that outlines various experiments to conduct to determine how to create scalable and better learning experiences faster and more cheaply.

The playbook will serve three purposes. It will be:

  1. Your plan of initiatives and objectives to lead L&D teams in their adoption and use of AI tools.

  2. Your roadmap to help stakeholders see how you intentionally explore how AI can improve L&D and the business.

  3. Your data strategy to measure the efficacy of learning, inform learners of what they need to improve, and guide the organizations on where to invest time and resources.

Tips: Embracing the concept of "fail fast and learn quickly" is crucial in today's rapidly evolving AI landscape. It's essential to act with urgency and adopt an experimental mindset. Avoid becoming overly dependent on any specific vendor's product as new tools frequently emerge and outpace older ones. Navigating this rapidly changing landscape can be challenging, but resources like The Thinking Effect can provide guidance.

How will we gauge Return on Investment (ROI), and what does this entail?

In L&D, we've traditionally relied heavily on smile sheets to gauge training success. It's high time we reframe our ROI conversations and focus on how learners' thoughts and behaviors align with organizational objectives. This is where Behavioral Analytics (BA) can help. BA can help determine efficacy, provide learners with more valuable and practical insights into their strengths and opportunities, and change conversations from “this is how people felt” to “this is what we recommend doing next.”

How can we ensure the security of our data and individual privacy? Here's reassuring news: major professional service firms have recently invested billions of dollars to instill confidence in their clients regarding AI and data security. Much like the transition to cloud computing or the emergence of Software as a Service (SaaS) companies, organizations are progressively becoming more comfortable with data protection. Soon, organizations will be ingesting content into their private AI models to provide guidance, answer questions, and create training at mind-blowing speed. As a result, we recommend advocating for how L&D can guide this transformation. For example, the AI manifesto should encompass statements addressing data privacy, data protection, the secure use of company data and intellectual property, and the cautious use of unsupported AI tools. In addition, it should set the expectation that learning and content experts will diligently review all AI-generated materials for accuracy, bias, and quality.

Finally, what can we anticipate the future of learning to be like?

Not surprisingly, this question is top-of-mind for many people and organizations. Though no one can predict the future, here are some key points we're highly confident about, which may aid you in shaping your perspective:

Personal AI training assistants: We foresee a future where each of us will have a personal AI training assistant and coach that will readily respond to commands like "create a 5-minute course on improving team performance," "craft a discussion guide with questions," or "schedule a team meeting for Friday morning."

Widespread use of chatbots: Chatbots will become commonplace, offering on-the-spot, just-in-time learning and performance support.

Integration of AI: AI will seamlessly integrate into various software tools, reducing the need for separate software training.

Shift from knowledge-level learning: Traditional knowledge-level learning, including microlearning and eLearning, will continue to evolve toward AI tools that require minimal human intervention.

Rise of Simulations and Games-Based Learning: Simulations and games-based learning will emerge as the dominant learning modalities, offering high levels of efficacy, cost-effectiveness, and scalability–through contextual learning and contextual practice.

Practical and Valuable Training Data: Increasingly useful training data will become valuable, providing actionable insights and turning learning from an event into a continuous cycle alongside or interwoven with job performance.

Focus on Learning New Skills: Learning initiatives will increasingly prioritize rapidly acquiring new skills and honing those distinctly human attributes.

Performance Support: Learning at the moment of need and verifying that the employee has the knowledge to do a task will be enhanced with AI.

User-Generated Content: Everyone throughout an organization will be able to research, innovate, solve problems, and collaborate with others to save time and money.

This evolving landscape signifies a profound shift in our approach to learning, one where AI takes center stage in driving knowledge-level learning, allowing L&D professionals to focus on creating high-quality learning experiences.

As we embark on this transformative path, it's vital to understand that AI doesn't replace human expertise; it enhances it. With an AI Advocate on board, you can fully leverage these advancements for more valuable, cost-effective learning.

Remember to prioritize speed, experience, and analytics as key business goals, and let them guide your L&D strategies. CLO and L&D leaders occupy a special position in the organization: you have a business viewpoint and deeply understand the needs of learning professionals. We recommend you take on the role of AI Advocate and find a few others within your team, preferably across borders and departments, to assist you. If you need help thinking this through, don't hesitate to contact us at The Thinking Effect or Learning Forum.

About the Authors

Mike Vaughan is the Chief Editor at The Thinking Effect, a platform dedicated to helping L&D professionals learn about and use AI tools to advance their careers. He is also the CEO of The Regis Company, which specializes in providing AI-driven tools to accelerate the design and development of business simulations.

Mike has been at the forefront of educational technology and adult learning for 25 years. He earned a master’s in cognitive neuroscience from Middlesex University, London, and degrees in psychology and computer science. In addition to speaking at TEDx on the power of questions, Mike authored The Thinking Effect, The End of Training, and Strategic Performance Learning.

Brian Hackett is the founder of The Learning Forum. After a career at what is now Willis Towers Watson, and The Conference Board, Brian saw a need for senior executives to be more innovative and active in their own learning and professional development. The Learning Forum is a member-driven learning organization for senior executives from F500 firms and key government agencies. Members learn directly with each other, face-to-face in candid and confidential forums.

The forums cover L&D, Talent Management, Workforce Analytics, HR Technology, HR Operations, Knowledge Management, Innovation, Foresight and Cyber Security.

Markus Bernhardt is a Fellow of the Learning Performance Institute (LPI). He is affiliated with organizations such as the Forbes Technology Council, the HBR Advisory Council, and the Learning Development Accelerator (LDA). Markus is a recognized authority, author, panelist, and global learning and HR community speaker. Recently serving as chief evangelist at OBRIZUM on the vendor side, Markus has been at the forefront of combining cognitive science with digital learning transformation and AI. Previously, Markus held the CEO position at two educational institutions in the UK, backed by an extensive leadership background serving in executive and non-executive board roles.

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