Many organizations are increasingly embracing skills-based strategic workforce planning (SWP). Nevertheless, transitioning to skills-based SWP can be a lengthy endeavor, particularly as numerous organizations lack a shared language for discussing and organizing skills. And in instances where a common language does exist, tracking skills and their fluctuations can prove to be a formidable task. However, as highlighted in this article, skills intelligence technology offers a solution by enabling organizations to automate the compilation and integration of skills data from internal and external sources, making it easier to update databases as employee skills evolve. This article provides an overview of skills-based technology platforms and explores how one company, Unum, leveraged such a platform to implement a scalable, real-time SWP approach. Implementing skills intelligence platforms is not as simple as “flipping a switch” and will require organizations to carefully consider their specific needs and goals in this process. Key questions arise, such as: 1) What internal and external data sources will the AI engines of these skill platforms utilize to infer employees’ skills? 2) How will skills be verified? Will employees self-assess their skills and rate their proficiency, or will managers and others be involved in assessing the skills of their colleagues? Answering these and other questions can increase the likelihood of successful implementation and adoption of skills-based talent platforms. To help you navigate these and other considerations as you transition to skill-based talent practices and tap the potential of skills platforms, here is my playlist of 6 resources from Deloitte.