Artificial Intelligence (AI) is not something that only tech guys or IT departments use. People in HR, marketing, logistics, and compliance are finding uses for this game-changing tool. But the misconception of being replaced by a bot often seeps into our minds. AI is reshaping how organisations operate and, if employees are ready, they will enjoy the many benefits that come with incorporating this tool into their job functions.
According to recent research, over one-third of companies want to retrain or reskill their teams within the next three years. This is to ensure that they are meeting the growing demand for AI competence. For L&D (Learning and Development), this presents both a challenge and a great opportunity: how can you build scalable, future-forward AI skills within your company?
Assessing Your Organisation’s AI Readiness
Before designing learning pathways or selecting tools, it is of paramount importance to understand exactly where your business stands.
1. Identify Current Skills and Gaps
Start with a skills check. Who already has experience in fields like data science, machine learning, or automation? Next, you need to identify the critical skill gaps. Include both technical roles (such as developers and analysts) and non-technical ones (such as project managers, HR professionals, and marketing teams).
2. Understand New Roles and Competencies
AI is not just creating new tools; it is also creating new roles. Think about jobs like AI Product Managers and Predictive Analytics Specialists, which didn’t exist 10 years ago. Or consider existing roles that are evolving, requiring a better, stronger grasp, like AI Project Management and Digital Transformation Principles.
Designing Effective AI Learning Pathways
L&D leaders need to build learning journeys that are engaging, relevant, and flexible enough to meet the varied needs of different team members.
1. Blend Learning Methods
Use a mix of:
- Formal courses: These courses cover core knowledge, such as Artificial Intelligence Fundamentals and State Space Search, or AI and Future Trends.
- Microlearning: These are short, focused lessons that are ideal for busy professionals, such as ChatGPT for Viral Social Media Content Generation or AI for Educators.
- Hands-on projects: Real-world problem-solving that reinforces learning and supports experiential learning.
2. Encourage Cross-functional Learning
Develop a culture of trying new things by encouraging employees from different departments to collaborate on AI-related projects. This will give them an idea of what they can do with AI and how it can be incorporated into different job functions. For example, HR and IT could work together to implement AI in Human Resource Management, while marketing teams test out AI-Driven Digital Marketing Strategies.
Leveraging Your LMS
Your Learning Management System (LMS) is more than just a content host. It is a strategic enabler of your AI training goals.
1. Build Customisable AI Learning Paths
Offer well-crafted and designed learning journeys for different teams at the point of their need. For instance, logistics teams might benefit from Artificial Intelligence for Supply Chains and Logistics, while compliance teams could explore AI in Compliance – Enhanced Regulatory Reporting & Workflows.
2. Track Progress and Measure ROI
Use built-in analytics tools to track learner progress, completion rates, and engagement metrics. This helps in adjusting content delivery and demonstrating the impact of training on performance.
3. Cater to Both Technical and Non-Technical Staff
Not everyone needs or wants to become a deep learning expert, and that’s okay. While your data science team may dig into Machine Learning and Advance AI Techniques, non-tech teams can start with Introduction to Responsible AI Use and Design or AI for Task Management and Productivity.
A Success Story Using AI Tools
A mid-sized law firm, VWV, based in the UK launched an AI innovation programme into everyday L&D tasks in 2023. They began using these tools for contract review, note-taking, drafting and prompt-engineering.
AI tools significantly helped them measure efficiency gains, and reduce time spent on common tasks like drafting and note-taking.
AI was positioned as an enhancer and not a replacer.
The above example shows that AI in L&D can be used even in non-enterprise organisations.
In your company, you can also implement AI tools in some of the following ways:
- Help with repetitive tasks
- Measure efficiency
- Maintain human oversight, but use AI for relevant information
- Use AI tools for training new employees
Conclusion: AI Learning is a Continuous Journey
AI is advancing faster than most companies are prepared to handle. This means that continuous learning is the most important strategy for staying competitive in the market. As a learning leader, your role is pivotal in driving AI readiness across your teams.
By focusing on experiential learning, cross-functional collaboration, and customised learning plans, you can create a workforce that’s not just prepared for change but confident in becoming a leader in your field.
