How do we design learning experiences that remain meaningful in a world where AI is rapidly transforming the way we work? As organisations navigate this evolving landscape, balancing human-centred learning with cutting-edge AI technologies has become a central challenge.
In a recent LinkedIn Live session hosted by Cheshta Dora, Head of Research, Content, and Community at People Matters, the conversation titled “Designing the Future of Learning: A Human-Centred Approach with AI” took a deep dive into this pressing question.
This session, attended by a global audience, featured two prominent industry leaders—Nick Shackleton-Jones, CEO & Founder of Shackleton Consulting, and Neelmani Singh, Group Head at Aditya Birla Global Centre for Leadership, Learning ‘Gyanodaya,’ Aditya Birla Group. They shared their insights on how organisations can balance the rapid advancements in AI technology with the imperative to create more human-centred, empathetic, and context-driven learning experiences.
A Human-Centred Learning Mindset
Cheshta Dora set the context by addressing a critical question in today’s learning landscape—how can we ensure that learning remains meaningful and relevant in a world increasingly dominated by technological advancements?
Nick Shackleton Jones pointed out that mindset is a key barrier to progress. He highlighted how many organisations still prioritise content over context, focusing on delivering information rather than addressing learners’ real-world tasks and challenges.
Reflecting on the evolution of e-learning, he noted that while technology holds immense potential to transform learning, outdated approaches to content delivery have limited its impact. He argued that AI should not merely be a tool for delivering more content but should instead be leveraged to reshape learning based on the specific needs and contexts of learners.
Neelmani Singh supported this view, emphasising that the transformation in learning goes beyond the shift from computer-based training to AI-based learning. It requires a foundational change in both the way AI is utilised and how learning experiences are designed.
Neelmani cited McKinsey’s estimate that AI could contribute between $2.6 to $4.4 trillion to the global economy but stressed that its role in learning should be focused on “meaning-making.” He believes AI can enable learners to transition from merely absorbing information to creating knowledge and gaining wisdom.
AI’s Role in Personalised Learning
A central theme in the discussion was how AI can drive personalisation in learning programs. Nick underscored that learning experiences should be closely connected to learners’ personal interests, tasks, and challenges. He introduced the concept of AI-generated personas, which simulate real-life scenarios, allowing learners to practise skills such as emotional intelligence while receiving personalised feedback in leadership training. This form of AI-driven personalization bridges the gap between scalable technology and real-world application.
Neelmani reinforced this perspective, noting that while AI can provide cognitive empathy by responding to data with understanding, it lacks the human element of compassion. Feedback from learners is crucial in allowing AI to adapt and improve. Without continuous input, AI may struggle to tailor experiences effectively.
The session also highlighted the importance of prompt engineering in guiding AI’s role in learning. While AI can accelerate course and content creation, the key challenge lies in training it effectively to create meaningful and contextually relevant learning experiences.
Striking a Balance: AI and Human Empathy in Learning
Cheshta raised an important question—how can we ensure that AI-driven learning remains human-centred? Both Nick and Neelmani discussed the delicate balance between leveraging AI’s efficiency and retaining the human touch, particularly in learning programs designed for senior leadership. AI can offer scalable solutions for onboarding and training, but it is crucial to maintain human interaction to foster a sense of belonging.
Nick provided an example from onboarding programs, where new hires often experience a rollercoaster of emotions. While assigning a human buddy may not always be feasible, AI chatbots can serve as virtual buddies, offering an always-available, personalised experience. However, he emphasised that AI should complement, not replace, human interaction.
Measuring Success and Managing AI Risks
When discussing how to measure the success of AI-driven learning programs, Neelmani pointed to the continued relevance of traditional models like Kirkpatrick’s, which assess learning outcomes at different levels, including return on investment (ROI).
However, he stressed that measuring success should be as streamlined and efficient as the learning interventions themselves. AI has the potential to automate data collection and enhance feedback efficiency, but it must be employed thoughtfully.
Nick added to this by encouraging organisations to move beyond superficial feedback mechanisms such as “happy sheets.” Instead, they should focus on engaging business stakeholders to design programs that target specific behavioural changes tied to business outcomes, rather than simply delivering content.
Both speakers also touched on the potential risks associated with AI, particularly in terms of data security and algorithmic errors. Neelmani reminded the audience that AI itself is not dangerous—it is the algorithms and lack of oversight that need careful management. AI should be applied strategically, handling logistical tasks while maintaining a human-centred focus in learning design.
Balancing AI Innovation with Human-Centred Learning: A Path Forward
The session concluded with a strong message for organisations aiming to integrate AI into their learning strategies. It emphasised the need for a shift in mindset from content-focused to context-driven, learner-centred approaches. AI can provide powerful tools for personalising learning experiences and simulating real-world challenges, but it must be paired with thoughtful feedback and context.
Striking a balance between AI efficiency and human empathy is essential, particularly in fostering meaningful connections and engagement in learning. Moreover, measuring success must go beyond traditional methods, leveraging AI to streamline data collection and focusing on outcomes that drive performance improvements. AI should be used strategically to enhance, rather than replace, the human aspects of learning.
This insightful session served as a powerful precursor to the upcoming People Matters L&D Conference, where the theme “Undo, Redo, Outdo: Drive Transformation Through Action” will further explore how AI can revolutionise learning and drive tangible business impact. As technology continues to evolve, it is clear that AI will play a pivotal role in shaping the future of learning, guided by empathy, context, and a commitment to continuous improvement.
To gain deeper insights from the experts, you can watch the full LinkedIn Live session here!
To dive deeper into these insights and explore how AI can drive transformation in learning and development, join us at the People Matters L&D Conference 2024 . Register here!