Future Proofing a Learning Strategy for Organizations with Inna Horvath

With the advent of AI, everyone’s anticipating changes. L&D leaders in charge of building a learning strategy for organizations are also looking forward to changes. But, most teams are stuck when it comes to really applying AI into their workflows, remaining limited to content creation at best.

In this conversation with Inna, a learning strategist, Ashish explores the future of learning and development strategies, while primarily focusing on:

• Are L&D teams effectively meeting the needs of end users in the current work environment, considering remote and hybrid work, generational diversity, and cross-functional collaboration?
• What are the core areas where L&D teams should focus to bridge gaps in learning strategies, particularly when looking 5 to 10 years into the future?
• How can technology, particularly AI, play a role in creating future-proof L&D strategies?

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How to Make a Learning Strategy for Organizations with AI in Mind?

• The need for alignment between organizational goals and learners’ needs is crucial. There is work to do to ensure this alignment, especially with the rapid changes in the work environment.
• Upskilling and reskilling are essential for the workforce. It’s predicted that 50% of the workforce will need to upskill or reskill by 2025, which requires a change in the approach to L&D strategy.
• Personalized learning is key to effective learning. Generic training programs do not address the specific needs and challenges of individual learners, so technology and AI are needed to provide personalized learning experiences.
• Learning should be integrated into the flow of work. Learning should be immediately applicable and accessible when needed, rather than being a separate activity with delayed application.
• Technology, especially AI, can significantly enhance L&D. AI can assist with content creation, curation, data analysis, and evaluation, enabling L&D professionals to focus on strategic aspects. AI can also provide personalized learning paths and update courses more efficiently.
• ROI in L&D is a critical consideration. It’s important to measure the tangible outcomes of learning initiatives, such as retention rates, performance metrics, and employee engagement scores. The learning must also be relevant to the current challenges of the learners.
• The goal of adopting AI is not to replace humans, but to support them. AI should be seen as a thought partner to upgrade learning initiatives, allowing L&D professionals to do their jobs better and more efficiently

How can AI integrate into L&D strategies?

Technological advancements, particularly the integration of AI, significantly enhance L&D effectiveness in several key areas. In the conversation, Ashish and Inna primarily spoke about:

• Content Creation and Curation: AI can aid in the creation and curation of learning content. Instead of relying on generic, lengthy materials, AI can help you generate more focused and relevant content. For instance, rather than a 10-page document, AI can pinpoint the specific page or section that addresses a learner’s immediate need. AI can also help update courses more efficiently.
• Personalized Learning Paths: Technology, especially AI, lets you make personalized learning plans for the people on your team. AI can assess a learner’s profile, experience, and challenges to tailor learning journeys specific to their needs. This level of personalization is crucial because a generic training program cannot address the diverse needs of a large group of learners. For example, Risely’s AI coach for leadership, Merlin, can speak to hundreds of managers for their specific problems in a hyper-personalized way that would be hard to recreate with human coaches at scale.

• Data Analysis and Evaluation: AI can process large amounts of data to provide insights into learning effectiveness. This data analysis can help L&D professionals understand what’s working and where improvements are needed. For instance, AI can analyze data to identify gaps in learning programs or highlight areas where learners struggle.
• Learning in the Flow of Work: Technology facilitates learning within the flow of work, providing immediate access to relevant information. For instance, Inna speaks of QR codes next to tools can provide on-the-spot video tutorials. This approach ensures that learning is practical and applicable when needed, making it more effective.
• Simulations and Interactive Learning: AI can create simulations and interactive learning experiences that allow learners to practice and apply their skills in a risk-free environment. This active approach, based on the principle of “learn by doing,” is more effective than passively consuming information.
• Communication and Engagement: AI can help personalize communications with learners, such as scheduling messages and providing personalized learning paths. This approach makes learners feel supported and valued. By adopting marketing strategies, L&D teams can effectively communicate the value of learning programs

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