Perform an AI skills gap analysis and talent audit

- Implementing AI solutions without capable and enthusiastic employees and supporters across your organization is a non-starter. Unfortunately, many leaders discover skill gaps too late, and this undermines initiatives after they have already made significant investment. In this video, I'll demonstrate how to systematically analyze your talent landscape to help pinpoint existing capabilities, identify skill shortages, and inform decisions on hiring and re-skilling. All of which are vital for AI success. So how do we perform an AI skills gap analysis? Well, it starts with understanding the specific competencies required for AI implementation in your business. This builds on your technical requirements document that we covered in the previous video. Start by identifying these roles and skills across technical, non-technical and leadership positions. Then compare these requirements against your current team's capabilities. Assess not only their technical skills, but their readiness to adapt to AI. Are there team members who with additional training could fill these roles, or do you need to consider hiring externally? Remember, re-skilling your existing team can be as crucial as hiring new talent. It's not just about filling gaps, but also about fostering a culture of continuous learning and adaptability in the face of technology that is advancing this quickly. There are two primary skill gaps that you should focus on. Those across technical teams that design and build AI solutions and those across business teams that apply AI in their operations. Technical skill gaps often revolve around specialized AI tasks, such as fine tuning models and managing data. Business skill gaps, on the other hand, are about understanding AI's role and capabilities within a business context. To address these gaps, start by looking internally. Identify AI thought leaders within your organization and empower them as AI evangelists. Focus on retraining and upskilling existing employees, emphasizing not just technical skills, but also interpretive and cognitive abilities like creativity and strategic thinking. Consider setting up innovation labs and internal conferences to foster an AI-centric culture and collaborative learning environment. If internal resources are insufficient, you must look externally. This may involve hiring AI experts, tapping into young talent through internships, or partnering with consulting firms with an experienced talent pool. Such external hiring should be strategic, focusing on areas where your organization lacks expertise. Performing an AI skills gap analysis and conducting a talent audit are critical steps towards successful AI adoption. By understanding and addressing these gaps, you can ensure that your organization not only adopts AI technology effectively, but also remains competitive in a rapidly evolving digital landscape.