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

    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): 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. 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. 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: Your plan of initiatives and objectives to lead L&D teams in their adoption and use of AI tools. Your roadmap to help stakeholders see how you intentionally explore how AI can improve L&D and the business. 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.

  • The Future of Learning: Experience

    A 1997 report from Idaho claimed that thousands of Americans have died from accidental ingestion of dihydrogen monoxide (DHMO), a chemical compound that can cause severe burns and other unpleasant side effects. Asking what can be done about this dangerous substance, a 14-year-old student distributed the report to classmates, prompting a vote which resulted in overwhelming agreement to ban DHMO. The punch line? None of the students stopped to consider what dihydrogen monoxide was. Ironically enough, they chose to ban something that is critical to our survival! Turns out, DHMO is simply two molecules of hydrogen to one molecule of oxygen, also known as H2O or water (which can, of course, cause death from drowning, dehydration, or scalds!) The lesson? Trust, but verify. In the age of misinformation, social media overload, and an onslaught of endless news, people need more time, space, and increasingly sophisticated ‘thinking’ capabilities to critically consider the information they’re consuming. And, with AI bots generating content, creating deep fakes, and learning people’s behavior patterns, the noise we experience is only going to get louder. What can be done to help? Develop higher cognitive skills. The World Economic Forum (WEF) recognizes these skills as the most important for individuals to learn. L&Ds can play a crucial role in the essential upskilling of workers by prioritizing capability development and enabling individuals to better navigate the complexities of the future. And let's face it, the pressure to keep up with the latest skills and deliver value is not going away anytime soon. In today’s environment, focusing on developing higher cognitive skills is vital for two reasons. First, reasoning and decision-making are currently the least automated workplace tasks, accounting for just 26% of task automation. Second, higher cognitive skills help individuals cut through the noise of information overload. Noise refers to the constant influx of information and distractions that can cloud our judgment and hinder our ability to think and communicate clearly. In both our personal and professional lives, this can be observed in countless situations, whether it be overwhelm by choice at a supermarket, being bombarded by Slack messages, or mindlessly scrolling social media. By developing higher cognitive skills, we can be more discriminating, elevate decision-making, and better navigate this noisy world. Here comes the harsh reality…As AI advancement intensifies, so does the noise, stress, and pressure. Did you know that according to Nobel laureate Daniel Kahneman, our brain operates using two distinct systems? System 1 is like a fast and automatic brain, responsible for making quick judgments and decisions, while System 2 is like a slower and more analytical brain, which analyzes information and considers solutions. We tend to rely more on System 1 thinking, which can lead us to accept information at face value without much critical thinking. It's important to be aware of this tendency and to consciously engage, develop, and enhance our System 2 thinking so that we are prepared to make important decisions or evaluate information critically. Here comes a glimmer of hope. Decades of research in mental models have shown that the most effective way to cultivate higher cognitive skills is through practice and reflection. We can enhance our innate System 2 thinking abilities by practicing in a practical context that allows us to apply what we have learned. This helps craft new neural pathways and refine our abilities. Plus, it exposes us to different scenarios and challenges, enabling us to adapt and improve our problem-solving skills. And, when we take the time to reflect on our experiences, we gain valuable insights into what worked well and what needs improvement. Reflection enables us to analyze our performance, identify patterns, and recognize opportunities to enhance our understanding or approach, but it also helps us connect the dots, integrate new information, and extract meaningful lessons from our experiences. And, here comes the great news! Experiential learning provides an ideal framework for the practice and reflection individuals need to stay ahead of the game. By engaging directly in real-world experiences, learners apply their knowledge and skills, receive immediate feedback, and reflect on their actions. The combination of hands-on experience with thoughtful reflection maximizes the effectiveness of the learning process, promotes more profound understanding, and enhances the transferability of knowledge and skills to real-life situations. With experiential learning, education’s future is bright, and the key to giving individuals the skills they need to quiet the noise. And you, my L&D friends, play a vital role in making practice and reflection an everyday reality.

  • The AI Advocate for Learning and Development

    AI is quickly becoming commonplace, and its pervasiveness will only grow. Boosted by AI, stores, transportation, and homes will become smarter, and most apps and applications will employ AI to some degree. It’s only a matter of time before kids' toys join the AI bandwagon and begin teaching us a thing or two. Resistance to AI in organizations prohibiting its use is temporary, as giants like Microsoft and Google lead the way in integrating AI into everyday productivity suites and tools. Following suit, every app and application developer is furiously looking for ways to integrate AI into their products and offerings - making its ubiquitous integration inevitable. Enter the need for an AI Advocate - the champion who supports and promotes AI’s responsible and productive use of AI technology throughout an organization. These AI ambassadors inspire and educate on AI's potential while keeping ethics and data privacy firmly in mind. Their mission is to harness the power of AI to elevate organizational performance and decision-making without compromising on standards, policies, and regulations. What does this role of the AI Advocate in Learning and Development? As an AI Advocate, key responsibilities include: Education: One primary responsibility is to clearly communicate the benefits, risks, ethics, and potential applications of AI technologies to a diverse range of stakeholders. AI Opportunity Identification and Support: Stay up-to-date with the latest trends and developments in AI technology in order to collaborate with various teams to identify opportunities for AI implementation, fostering innovation and problem-solving. Monitoring AI technology: Regularly monitor and assess the functionality and effectiveness of deployed AI systems, recommending any necessary improvements. Cross-Functional Collaboration: Work closely with departments such as IT, legal, and data privacy to ensure AI initiatives align with the organization's goals, policies, and values. Training and support: Facilitate AI-related training for teams across the organization on responsible and effective use of AI tools. Offer ongoing support and address inquiries or concerns that arise. Why is this role essential now? The IBM AI Adoption Index increased from around 31% in 2021 to 35% in 2022 and is expected to reach 52% in 2023. The global AI market is predicted to exceed $1.5 trillion by 2030, with a Compound Annual Growth Rate (CAGR) of 38.1% from 2022 to 2030 (SnapLogic). This growth is largely a result of organizations striving for a competitive edge, with productivity being a primary driver. By offloading tedious, repetitive, and routine tasks to AI, employees can focus on higher-value tasks, leading to higher satisfaction rates, with 68% wanting more AI-based technology in the workplace. AI is also being explored to enhance customer experience, drive sales growth, replace knowledge-level training, optimize supply chains, and reduce staff costs. Consequently, the urgent need for a dedicated AI advocate is critical to empowering organizations to harness the power of AI and maintain a competitive position in the market. Where does this role sit within the organization? The AI advocate role should report to a senior leader within the organization, such as the Chief Technology Officer (CTO) or Chief Information Officer (CIO), to ensure strategic alignment and access to comprehensive support and guidance. Key reasons for this reporting structure include: Technical expertise: Working closely with a senior leader with technical expertise, such as the CTO or CIO, will provide the AI Advocate with technical support and resources, aiding in the effectiveness of their role. Strategic alignment: Aligning the AI Advocate's responsibilities with the organization's strategic goals is crucial. Reporting to a senior leader guarantees that their work remains consistent with the company's vision and mission. Cross-functional collaboration: The implementation of AI technology calls for cooperation among various departments, such as IT, legal, and data privacy. The AI Advocate will benefit from the senior leader's oversight, fostering collaboration across these diverse functions. Budgetary support: Deploying AI technology can entail significant costs. Reporting to a high-level executive will help the AI Advocate secure the necessary budgetary support to effectively execute their role. Why is the AI advocate essential to L&D? An AI advocate is crucial for L&D teams, as they can lead the way in utilizing the vast, sophisticated AI tools at their disposal to accelerate the design and development of training programs, minimize costs connected to subject matter experts, elevate the learner's experience and efficacy, and transform L&D into a data-driven entity. In essence, the AI advocate can establish L&D as a beacon that directs the organization toward ethical AI usage, while simultaneously maintaining a competitive edge in the market. Here are some additional resources: Fast Company: Why every Fortune 500 business needs a chief AI officer: . Worklife: The rise of the chief AI officer . Venture Beat: How to choose the right Chief AI Officer.

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  • Write Me A Cover Letter

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