A Big Win for HR Collaborations: 5 Practical Steps for Building Your AI Training Program By Stacey Young Rivers, Ph.D., of Warner Bros. Discovery and Robert Joseph, Ph.D., of Team MindShift Have you heard the saying, “We’re all in this together”? If not, then the logical interpretation of the saying conveys that circumstances affect every individual in some way. Hence, a favorable outcome should be the focus for everyone involved. The adage “we’re all in” explains how leaders should approach building AI skills for business value. Organizations must invest in structured training to integrate AI effectively, which empowers employees with the right knowledge and skills. However, building an AI training program requires support from various functional roles for effective communication, careful planning and solid execution. Starting at the Top For any training initiative to succeed, an executive sponsor must champion action and accountability. The executive sponsor provides insights into the purpose, scope, expected outcomes and, of course, the budget. As an HR or L&D lead, your role supports driving value by helping to define a clear, measurable return on investment. This will require a discussion for how the leader will communicate the business goals that the training supports. With strategic information from the leader, the team executing the training can take action to bring the program to life while providing feedback to those accountable for achieving the goals. The executive sponsor can also help secure internal subject matter experts to support the selection of qualified trainers, appropriate tools and job aids for workflow integration. As a result, HR and L&D leads should expect the partnership of key stakeholders who have the expertise to help create and implement a successful plan. Now that you have the input from the executive sponsor, let’s review five practical steps to foster collaboration with key stakeholders. 1. Conduct a Needs Assessment - A comprehensive needs assessment identifies the skill gaps and determines how AI training aligns with expected outcomes. While you may have some of the information from the executive sponsor, you will also need to partner with your subject matter experts to conduct surveys and interviews with employees to understand their AI knowledge levels. You should identify the specific AI tools and technologies that have been approved and are available for usage. To effectively assess the impact of the training, it’s imperative to define measurable learning objectives, such as improving automation skills or enhancing data analysis capabilities. Ultimately, the needs analysis should ensure that the training’s purpose is targeted, relevant, and valuable to employees and the organization based on the measurable business goals that have been agreed upon. 2. Select Qualified AI Trainers - Your project's success heavily depends on the expertise of the trainers. As the HR or L&D lead, you must select trainers with deep AI knowledge who can translate complex concepts into practical applications. Use your subject matter experts to engage other internal AI experts, external consultants or academic professionals. The objective is to validate that trainers have experience in both AI technology and effective teaching methods. For a blended learning experience, you should also consider online platforms and AI training providers with strong credentials. NOTE: A training initiative in essence is a change management strategy, so the trainer should include methods to prepare the participants to become change agents. Knowing how to positively effect behavioral change, along with developing technical skills, can either make or break a project. This is why you need to understand the expected outcomes, so that you can lead the training to achieve the desired outcomes. For example, if one of the outcomes is to retain employees by upskilling or reskilling, then ensure they can access the tools they have been trained on at completion. Nothing is more frustrating for an employee than to use their time to gain new knowledge and have no way to use the knowledge they just acquired.   3. Design the Learning Initiative - Structured learning provides employees with a clear roadmap for acquiring AI knowledge. The training should cater to different experience levels and be designed in progressive stages, from foundational concepts to advanced applications. Using a blended learning approach, develop beginner, intermediate, and advanced training modules that offer a mix of self-paced online courses, live workshops and mentorship opportunities. To keep learners engaged, be sure to incorporate interactive elements such as quizzes, case studies and group discussions. 4. Utilize Relevant Use Cases and Hands-On Tools - AI training should be more than theoretical and must provide employees with hands-on experience. Strive for real business scenarios where learners can improve their critical thinking skills using AI to inform decision-making, integrate automation, or gain customer insights. Provide access to AI tools such as machine learning platforms, data analytics software and automation tools. Encourage employees to work on AI projects relevant to their roles that support the value the project is seeking to achieve. This will help to solidify their knowledge and build confidence. Ensure that employees can utilize the tools in the day-to-day workflow; otherwise, the value for the training will be diminished. 5. Measure Outcomes - Tracking progress and measuring outcomes will showcase the value of the training. Capturing data and analyzing the insights will help refine the program and ensure continuous learning. Key actions include conducting pre- and post-training assessments to evaluate knowledge retention. Be sure to measure employee engagement and feedback on training effectiveness. And finally, track business impact by assessing how AI skills are delivering the return on investment identified at the start of the project. Also, assess what other ROI may exist as a result of the training that you may not have considered. Conclusion Building an AI training program is a strategic requirement for the future of your workforce and organization. HR and L&D leads should engage key stakeholders to help create a compelling and sustainable AI learning environment. By starting with an executive sponsor who can define a clear purpose, you and your project team will have a clear, measurable plan to select the right trainers, design the learning plan and produce outcomes tied back to company value. AI is evolving rapidly, and keeping your employees trained and prepared will be a big win for driving innovation and success. About the Authors: Stacey Young Rivers, Ph.D. is Head of Global Learning and Development at Warner Bros. Discovery. CDO Magazine has recognized her as one of the "Top 50 Data Training & Talent Champions in HR" in the U.S. (2025). The Technology Association of Georgia awarded her the Data Science & AI Innovator of the Year (2024) for the Telco, Media & Ent. sector. She is a mom, researcher, author, speaker and blogger with 18,000+ subscribers to her "Level Up on Learning" blog on LinkedIn. Robert Joseph, Ph.D. is a Data Scientist and Educator specializing in workforce development. As Co-Founder of Team MindShift, he leads transformational tech training. A former Director at Stanley Black & Decker, Robert has 19+ years as a University Professor, teaching over 5,000 students. He authored the LinkedIn Learning course "Causal AI Primer" and teaches other courses at Georgia State University, Atlanta Technical College, and Emory University. With degrees from MIT (B.S., M.S.) and Carnegie Mellon (M.S., Ph.D.), he has built 100+ apps and holds a patent for an internet DJ system. His proudest role is being a father to two adult sons. RELATED RESOURCES For more information on Artificial Intelligence and L&D, please visit the HR Knowledge Center. Also, the HR Learning Series offers an on-demand webinar exploring the Future of L&D.   SHARE THIS ARTICLE