This session explores the transition from traditional skill-set based training to a proactive, application-based learning ecosystem that ensures human employability. It highlights how the L&D function can stay relevant by moving beyond general transactional tasks to focus on high level human intelligence and effective AI collaboration. Talkpoints include:

• Moving L&D from a traditional reactive mindset to championing change and driving organisational performance.
• Building a robust system that can cope with the changing environment by shifting from knowledge-based delivery to impact-based application.
• Training the workforce to collaborate with AI with an emphasis on preserving critical human skills such as resilience and ethical decision making.

As machines get better in crunching numbers, the human differentiator is the ability to turn numbers into stories which move people.

This session highlights the importance of L&D leaders as storytellers in a data-saturated world. It will also address the critical need to bridge the gap between analytical insights and human decision making. This helps to ensure that professionals can translate complex information into compelling stories that drive organisational change and maintain relevance in an automated landscape.

• Shifting from static data delivery to narrative-driven communication that captures attention and influences senior leadership.
• Using storytelling to preserve the essential human element in analysis by providing context and meaning that AI cannot replicate.
• Developing the communication skills to turn technical findings into a resonant and memorable story for stakeholders.

In the fast-evolving AI-driven era where markets shift quickly and expectations keep rising, learning leaders must think business when thinking of learning. This session explores how to design learning that moves at the speed of change, while keeping learning governance and SOPs front and centre, especially in large, distributed organisations.

We will also look at how to manage privacy, data use, and learner responsibility when building a robust learning ecosystem.

Get set to discuss:

• Designing a learning governance framework that balances consistency with flexibility and responds quickly to shifting business priorities.
• Embedding technology across the 70/20/10 model to sharpen skill gap identification and deliver targeted, in-the-flow learning.
• Setting clear guardrails on data privacy and learner responsibilities, while using workforce insights to match real skill gaps to the right learning.

With content becoming so easily accessible, questions have been raised around the relevance of the L&D function, and if it is evolving faster than the workforce it supports.

In this session, we put out a message to all L&D teams to continuously upskill themselves to remain credible, strategic partners and true ambassadors of next-generation learning.

On this session, we will come up with ideas on:

• Importance of anticipating future talent shifts, such as reduced entry-level opportunities, and proactively designing interventions.
• How L&D professionals can stay anchored to critical business priorities that directly impact performance.
• Real-life experience sharing for L&D leaders to broaden their perspectives, and position themselves as forward-thinking business partners.

This presentation provides a practical roadmap for integrating AI into the L&D workflow to achieve mass customisation. Our speaker moves beyond a simplistic understanding of AI applications to the specific steps required to build a performance-led framework.

By anchoring AI in established human performance models, we look at how L&D practitioners can transition to strategic architects who deliver personalised development at scale.

This session covers:

• The performance-first audit: Ensuring AI is activated to solve systemic performance gaps rather than just delivering more training content.
• Expertise driven AI literacy: Upskilling interventions for high precision prompts to generate rapid, contextual solutions.
• Scaling the learning loop: Using AI as a real-time partner to bridge formal training and on-the-job challenges for the workforce.

As Singapore accelerates AI adoption, learning must go beyond skills development to build workforce readiness and business performance. Beyond the formation of the National AI Council, organisational adoption will require an intentional approach to help employees thrive in an AI-driven workplace.  

This keynote explores how organisations can design learning strategies that help employees keep pace with evolving business needs and turn AI ambition into real impact. 

In this session, delegates will learn: 

• Preparing the workforce for AI-driven change: How learning strategies can help employees build the skills and confidence needed for a changing world of work. 
• Balancing execution and trust: Strategies to keep a human in the loop for critical tasks requiring strategic judgement and intervention.
• Redefining learning, performance and accountability: Creating a safe practice environment, parameters and boundaries.

In a world where knowledge is abundant and instantly accessible, traditional content-heavy learning is losing its edge. This session explores how L&D heads can shift towards application-based learning, design engaging formats for shorter attention spans, and embed development into new ways of working. We will focus on turning information into real capability, real performance, and real change.

Get set to discuss:

• Shifting from knowledge download to application-first learning that starts with real work challenges.
• Designing shorter, modular, and engaging learning experiences that respect shrinking attention spans.
• Embedding learning into everyday work through projects, practice, and feedback, rather than standalone events.
• Reinventing the classroom and digital learning spaces as hubs for experimentation, problem solving, and tangible outcomes.

The potential for AI to impact how learning is designed and delivered is being held back by its risks. While technology enables scale and speed, leaders have expressed worries about culture and empathy being eroded if the human element is taken away.

In this session, we explore how to humanise AI usage to support L&D initiatives, with the intention to not only build capability, but also character.

Talkpoints include:

• The approach for leveraging AI to maximise human productivity as well as potential.
• How to embed human traits like humility, learning from failure, and empathy into AI-driven learning for holistic development.
• Guardrails to prevent over-surveillance and preserve trust in AI-powered learning experiences.