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Across the two days, the focus was clear: less learning for learning’s sake, and more learning that helps people do their jobs better. Sarah Gideon reports.
AI is making knowledge easier and faster to access, and the value of learning is shifting from simply acquiring information, to knowing how to apply it, adapt to change, and use it to create value at work.
This shift is prompting L&D leaders to rethink what development should look like. Rather than relying on passive programmes and measures such as training hours or attendance, organisations are increasingly looking at how learning can translate into capability, confidence, collaboration, and business outcomes.
These questions took centre stage at the 12th edition of Learning & Development Asia, Singapore, which took place on 16-17 September 2026 at Hilton Singapore Orchard.
Across the two-day conference, L&D leaders explored how learning and skills strategies are evolving alongside AI and changing workforce expectations, and how organisations can make learning more contextual, practical, and relevant to the work people actually do.
Sarah Gideon reports the key lessons from the conference - scroll down for session-by-session insights, while the top five things that stood out for this journalist are below:
- AI may make knowledge easier to access, but it cannot replace human judgement: The skills that matter most are increasingly the ones AI cannot own, like making sense of context, asking better questions, building trust and taking responsibility for decisions.
- L&D needs to start with finding the problem, not the programme: When performance falls short, the answer is not automatically another course. It could be a process issue, a lack of manager support, unclear expectations or simply too little opportunity to practise.
- Learning has to live in the flow of work: The strongest development happens when people can test ideas, make mistakes safely, learn from others and apply new skills to real challenges, not just complete a module and move on.
- Trust will make or break AI adoption: People need to feel that AI is being introduced fairly, responsibly, and with their interests in mind. Leaders have a critical role in being transparent, listening to concerns and creating room to experiment.
- The real measure of learning is what changes afterwards: Attendance, completion rates and positive feedback only tell part of the story. The more meaningful question is whether people behave differently, work better together and deliver stronger results.
Day 1:
Powering the business
Why human relevance matters in an AI-driven workplace
Opening the conference with her AI avatar, Seet Teng Low, Head of Campus CoLab, Group Human Resources, OCBC, challenged L&D leaders to reconsider where their value lies in an age where AI can increasingly provide knowledge, content and skills on demand.
The biggest threat to L&D, she argued, is not AI itself, but what happens if the function fails to redefine its own value.
"The biggest threat to L&D today is not AI, but really, what happens if we ourselves are not able to redefine and reframe our value that we bring to the organisations, the ecosystem that we operate in?"
Drawing on OCBC’s approach, Low introduced five capitals of lifelong learning: human, seed, identity, cultural, and social capital.
- Human capital: The knowledge, skills and competencies employees bring to their work. While these remain important, AI is making access to knowledge and skills increasingly easy.
- Seed capital: The prior knowledge, experiences and foundational capabilities that allow people to build new skills. Low highlighted the importance of helping employees recognise what they already know and can build upon.
- Identity capital: The narratives people hold about who they are and what they are capable of. L&D can help employees see themselves as capable of change and move beyond being defined by their current roles or past experience.
- Cultural capital: The organisational environment and behaviours that determine what people feel comfortable doing. Even well-designed learning will struggle to create lasting change if the surrounding culture does not support experimentation, learning and new ways of working.
- Social capital: The relationships, networks and connections through which people learn. L&D can create opportunities for employees to learn from peers, leaders and people beyond their immediate teams.
A key shift, Low suggested, is that AI has effectively “re-priced” these capitals. And as AI makes knowledge easier to access, those less visible parts of development become more important.
For L&D, this means the role is no longer simply to deliver content. It is also about helping people build confidence, relationships, adaptability and a sense of identity as lifelong learners.
It also changes how impact should be measured. Instead of focusing mainly on training hours or completion rates, L&D can look at what happens afterwards: Are people applying what they learned? Are they building new capabilities? Are they collaborating differently?
In other words, AI may make learning easier to access, but it does not make human growth any less important.
Turning data into stories that drive action
The next session, led by Dominic Bohan, Co-Founder of StoryIQ, explored how professionals can turn data into stories that are easier to understand, more meaningful and ultimately more actionable.
The key learning was simple: Start with the takeaway, not the data.
Before choosing the chart, building the slide or pulling together more data, first decide what your audience needs to understand and what you want them to do with that information.
Bohan's storytelling framework centred on the audience, situation, complication and key takeaway, with the pyramid principle reinforcing the idea of leading with the most important message rather than making audiences work their way through a mountain of information.
The same principle applies to visualisation. Strip away what is unnecessary, make the important information easy to see, and use visual cues deliberately.
With AI making it easier to generate analysis and content, the human part of data storytelling becomes even more important: deciding what matters, why the audience should care and what should happen next.
The key highlights from the session were:
- Start with the takeaway. Define the one message your audience needs to understand and act on before getting into the data.
- Put the audience at the centre. Understand who you're speaking to, what they care about and why — then build the story around their needs.
- Give the data a storyline. Use a clear progression from situation and complication to key takeaway, supported by a small number of memorable arguments.
- Simplify the visual story. Choose the clearest way to display the data, strip away anything that doesn't serve the message, and use visual emphasis to direct attention.
- Let AI augment, not replace, human judgement. AI can help analyse data and create content at scale, but the storyteller still has to decide what matters, why the audience should care and what action should follow.
Building AI systems people can trust
After a short break, Kumar Veetrag, Co-founder and CTO, enParadigm, took the stage to highlight that the real challenge in the learning software space is not building impressive demos, but systems that organisations can actually trust and govern.
Veetrag shared that while it may take only weeks to build a polished prototype, turning that into a dependable product that measures and coaches real employees can take much longer. It could take months of engineering and iteration.
He distilled this journey into four key lessons:
- First, people practice when failing is free: Meaningful behaviour change happens only when learners can make mistakes without real-world consequences, repeat scenarios multiple times, and see tangible progress.
- Second, humanising AI is engineering, not decoration: Natural, trustworthy interactions come less from flashy avatars and more from handling difficult user behaviour, managing latency, and avoiding distractions that pull focus away from learning.
- Third, he emphasised that if AI measures people, it must be governed like a measurement instrument. That means treating model versions, prompts, scoring logic, and guardrails as calibrated components, with systems for detecting drift, recalibrating scores, aligning with human judgment, and transparently disclosing changes.
- Finally, Veetrag stressed the need to keep judgment with humans and give pattern work to AI, where machines should handle structured, repeatable analysis at scale, while humans retain responsibility for contextual, exceptional, and high-consequence decisions.
Taken together, these lessons aim to reframe AI in talent development as part of a broader governed ecosystem in which the real “product” is not just the model or the demo, but the sustained trust, stability, and shared responsibility between AI and human decision-makers.
Using humour as a strategic business tool
Humour might seem like a slightly unexpected topic at an L&D conference, but Paddy Rangappa, Co-Founder, Jest Business, made the case that it has a serious place at work.
His “funny formula” — Observation + Connection = Humour — frames humour as a learnable skill: noticing everyday realities and connecting them in unexpected ways.
Used thoughtfully, humour can help make leaders more approachable, lower defensiveness, encourage people to speak up, and strengthen relationships.
And the best part is:
“You don’t have to spend money to be funny.”
The ROI lies in making humour effectively “infinite” when used well.
To unlock this value, leaders and L&D teams are encouraged to:
- Champion humour as a positive force in existing programmes on psychological safety, engagement, communication, client relationships, and leadership.
- Adopt the mindset of not taking oneself too seriously, which makes it easier for humour and happiness to follow.
- Help employees understand their humour style (e.g., via a humour quiz) and build skill through simple observation habits and practical humour techniques.
- Humour, when executed thoughtfully, is not a distraction from serious work. Instead, it is a multiplier of clarity, safety, and connection in organisations.
Preparing people, not just systems, for an AI-driven workplace
Our first panel of the day explored what it really means to build an AI-ready workforce.
Taking the stage were:
- Jessica Choo, Founder & Chief Strategist, Integrated Learning Systems (ILS),
- Esther Liang, Principal, Global Front-End Organisation Development, Micron,
- Sean Lim, Chief Human Resource Officer, NTUC LearningHub
- Kevin Chua, Chief Human Resources Officer, United World, and College South East Asia (Moderator)
Together, the panel discussed:
- AI adoption ≠ AI readiness
- Simply giving employees access to AI tools or tracking usage does not mean they are ready for AI-enabled work. The panel stressed that readiness also depends on whether people have the skills to apply AI effectively, the confidence to experiment, and the willingness to continually learn, unlearn and relearn as their roles evolve.
- Expertise is shifting from answers to better questions
- As AI becomes increasingly capable of producing answers, recommendations and analysis, human value is moving towards judgement, discernment and sense-making. Employees need to be able to frame the right questions, challenge AI outputs, integrate different perspectives, and make decisions when the answer is not straightforward.
- AI learning works best when it is practical and social
- The panel highlighted approaches such as peer-to-peer learning, learn-apply-share cycles and differentiated AI learning pathways. Rather than relying on broad awareness training, organisations can build confidence by allowing employees to experiment with AI in their actual workflows, share relevant use cases and learn from both successful and unsuccessful attempts.
- Managers set the tone for responsible AI adoption
- AI adoption is not just an L&D or technology issue. Managers need to act as role models, coaches and change agents — openly sharing their own learning journeys, acknowledging mistakes, addressing concerns and creating an environment where employees feel safe to experiment. Trust and psychological safety therefore become important conditions for meaningful AI adoption.
- Measure behaviour and business impact, not training completion
- One of the strongest points from the session was the shift from measuring whether people completed training to whether training actually changes how they work. This means looking at indicators such as productivity, quality, decision-making, confidence, adaptability and ultimately business outcomes. As one panellist put it, the fundamental question is whether organisations are building an “AI-enabled workforce” or a “capable workforce enabled by AI.”
Accelerating capabilities
How to design learning that accelerates business capability
This themed experiential learning, hosted by Andrew Thomas, CEO at Eagles Flight Asia Pacific, considered behavioural science, practical models, and hands-on exercises, for all our participants to explore how to build communication, prioritisation, judgement, and collaboration skills under pressure.
The session highlighted eight pillars of high-performing teams:
- Think higher performance, not just high performance
- Trustworthiness is behaviour over time
- Everyone is a cultural architect
- Understand your own reality
- Make it clear what it means to be in a team
- Hold empathy and accountability together
- Build resilient systems, not just resilient people
- Under pressure, clarity matters.
A key takeaway was that organisations must create the confidence, support, feedback and ownership needed for people to apply new behaviours in practice.
As Thomas emphasised:
"It is about performance impact, and we as an industry need to talk about the performance impact that we need to bring about, and then reverse it back into some of these things.”
Building trust through AI-driven change
In her session, Dr Hwee Hoon Tan, Associate Professor of Organisational Behaviour & Human Resources, Lee Kong Chian School of Business, Singapore Management University, then shifted the conversation towards trust.
As AI reshapes jobs, breaks work into tasks and begins influencing decisions around hiring, performance and strategy, employees are also asking what those changes mean for their identity, competence and sense of fairness.
Tan described AI transformation as a “trust event”, highlighting three pillars of trust in leaders:
- Ability (competence),
- Benevolence (care for others’ interests), and
- Integrity (walking the talk).
Together, these pillars create the credibility needed to guide people through uncertainty. While AI can make organisations faster and more informed, Tan shared that it cannot make them more caring, empathetic, or trustworthy, as those remain uniquely human leadership responsibilities. These, she said, are the foundation for the psychological safety required for employees to speak up, challenge assumptions, and engage with change.
Making L&D a business partner
As Day 1 drew to a close, Elaine George, Executive Director, Learning & Talent Advisory Lead, APAC Tech & Ops, JPMorgan Chase & Co., and Chow Yong Ng, AGM, Learning & Talent Development, M1, took the stage to discuss how the L&D function can stay central to the success of the business.
Together, they discussed:
- L&D can’t just be about courses anymore: With AI and technology making information instantly available, the speakers argued that L&D’s real job is no longer to push out content. Instead, it’s to create environments where people feel safe, curious, and motivated to learn, to make sure those learning experiences are clearly tied to what the business is actually trying to achieve.
- Good feedback isn’t the same as real impact: “Happy sheets” and positive post‑training surveys don’t necessarily mean learning has changed anything. The session challenged L&D teams to ask tougher questions: What will people do differently after this? How will it show up in business results? The call was to move beyond counting attendance and satisfaction, and start focusing on whether learning is truly enabling transformation and performance.
- L&D needs to earn, and use, a seat at the table: Not every problem is a training problem. At times, it’s a communication or leadership issue. The speakers shared how honest, even light‑hearted conversations with senior leaders helped reframe “training failures” as broader business or messaging challenges. For L&D to play this role, they need strong relationships, a deep understanding of the business, and the courage to shift the discussion from “what course do you want?” to “where is the business heading, and how can we help you get there?”
- The “great equaliser” and the rise of human skills: With information no longer locked at the top of the organisation, early‑career employees are coming in more connected and informed than ever. This shift, described as a “great equaliser,” means L&D and HR must help organisations rethink how people build judgment, confidence, and institutional knowledge, especially as traditional entry‑level tasks disappear. Human skills like critical thinking, interpretation, relationship‑building, and trust are becoming the core differentiators L&D needs to nurture.
- Data‑driven skills intelligence is changing how we develop people: The session also highlighted how adaptive assessments and skills intelligence are opening up new possibilities for personalised development. Rather than offering one‑size‑fits‑all programmes, L&D can now use detailed skills data, be it at an individual, team, or company levels, to design targeted learning journeys, especially for high‑potential talent. This kind of evidence also gives L&D more credibility at the decision‑making table.
Learning by doing, capability by design
Wrapping up Day 1 of Learning and Development Asia 2026, Singapore, Julia Koh, Chief Human Resources Officer, Sunningdale Tech, shared how the company is bringing learning closer to everyday work.
Rather than relying primarily on short, classroom-based courses, Sunningdale Tech focuses on learning by doing, with structured on-the-job development built around the capabilities the organisation needs.
The initiative brings together learning across different functions, with a focus on strengthening capabilities in areas such as innovation, process improvement, automation and digitalisation. Technology and structured learning resources also help give employees and managers the tools to make development a more consistent part of the working day.
The idea is simple: learning should not sit separately from work.
Koh also emphasised that building this kind of learning culture is an ongoing process. Rather than waiting for the perfect approach, organisations need to start, learn from what works, and keep improving as their needs and capabilities evolve.
Day 2:
Driving change readiness
From training provider to solution architect
Opening Day 2, Jeslin Lim, Head of People and Culture, Cycle & Carriage Singapore, challenged L&D practitioners to rethink their role in what she described as the “superworker era.”
Rather than asking, “What training do people need?”, L&D should first ask where the gap is between expected capability and actual performance.
And the solution might not be training. It could be practice, management support, process changes, technology or AI.
“AI is not the hero, it is the enabler.”
That shift also means moving away from relying solely on familiar measures such as completion rates and learning hours. Lim encouraged L&D to become more like “solution architects”, diagnosing specific performance gaps and designing interventions around the moments that matter.
One way she is putting this into practice is through more application-focused learning, or what she calls, the "3P approach":
- Purpose: What are we trying to achieve — scale or precision?
- Possibilities: What could make it possible? This could include learning, practice, managers, processes, tools, technology or AI.
- Pragmatic: What can we realistically test with the resources we have?
Her advice was to start small: “Find the moment, diagnose the gap, run the smallest, useful experiment, and see what changes.”
For L&D, the opportunity of the “superworker era” may therefore be less about creating more forms of learning, but to just solve the right problem.
She left the audience with one, simple question: What can L&D make possible tomorrow?
Closing the digital capability gap
From there, Sabahat M., Global Head, Content and Learning & Chief Partnership Officer, Wordsburg, explored the human side of digital transformation.
Her central message was that organisations need to treat workforce capability as an ongoing part of transformation, not just something to address through training after a system goes live.
“We build the digital nervous system. But we often skip the digital muscle.”
Sabahat outlined four imperatives for closing the digital capability gap:
- Measure readiness before rollout to assess whether people have the confidence, clarity and capacity to use the technology, rather than relying on training completion or login rates as indicators of readiness.
- Architect behavioural change around roles as different users interact with technology differently, so a single learning curriculum may not address the needs of frontline operators, managers, occasional users and power users equally.
- Enable people in the context of their work as learning should reflect how employees actually perform their jobs, including the language, processes and situations they encounter on the frontline.
- Reinforce continuously through using feedback, workplace data and targeted interventions to identify where people are struggling, address those gaps and carry the learning forward beyond the initial transformation project.
The point was that adoption is a behaviour, not a completion metric. A system can have high login rates and strong training attendance while employees continue relying on old ways of working.
As Sabahat put it: “If the completion rate is still the headline number on your adoption dashboard, then your dashboard is measuring the wrong moment.”
Designing teams that can thrive through turbulence
The conversation then moved from digital adoption to a broader organisational question: how can organisations build teams that can adapt, collaborate and perform as conditions change?
In a panel moderated by Xingyan Chen, Talent & Learning Director, APAC, Campari, along with her panellists:
- Christina Yang, Managing Director, HR Executive Partner, Applied Materials,
- Karen Tay, VP of Core Services, Merz Aesthetics, and
- Gloria Chin, Group Director (Corporate Group), Ministry of Health (MOH), Singapore, tackled this issue.
A recurring message was to diagnose before designing.
When leaders come to HR asking for training or mentoring, the first step should be understanding what is actually happening. Is it a capability issue? A culture issue? A structural problem? A process problem?
The panel also stressed the importance of speaking the language of the business and connecting people initiatives to outcomes such as productivity, retention and business performance.
Culture came into the conversation too. Even positive cultural traits can have unintended consequences. A strong emphasis on harmony, for example, can sometimes make people less willing to challenge problems early.
For organisations navigating continued uncertainty, the panellists identified cultural capability, resilience, and collective accountability as important organisational capabilities for navigating continued turbulence.
How SATO is building a global learning ecosystem
After the morning break, Kazuhiro Aoyama, Group Leader, Learning & Development Group, Global HR, SATO Corporation, and Irene Goh, Talent Development, Global HR, SATO Global Business Services, took the stage to share their organisation's journey in building a global learning ecosystem.
As the speakers shared, SATO’s five-year journey to build a global learning management system (LMS) was less about finding the right technology and more about figuring out what would actually work for its people.
With employees across different countries, roles and cultures, SATO first needed to understand what people actually wanted from learning. The feedback pointed to easier access, greater flexibility and a more consistent experience across markets.
That led SATO to trial a new global LMS in 2021 before launching it across its subsidiaries in 2022. Employees were also involved in naming the platform, which became EDGE — representing the journey from engage and develop to grow, and evolve.
But perhaps the biggest lesson came after the platform was launched: what works in one market does not necessarily work everywhere.
Aoyama-san and Goh candidly shared how the content that was acceptable in Japan did not always translate well across its global workforce. The experience prompted SATO to introduce a “one-week notice” process, giving local subsidiaries the opportunity to review global content before it goes live and flag cultural or contextual concerns.
The LMS has also evolved beyond mandatory courses. Today, it brings together instructor-led training, internal subject-matter expert sessions and even self-directed learning, allowing employees to record learning they undertake independently through platforms such as YouTube.
For SATO, the experience reinforced that a global learning ecosystem cannot simply be built from the centre and rolled out everywhere in the same way. Technology can provide the infrastructure, but the learning experience still needs to reflect local context, employee needs and how people actually learn.
From knowing to doing
Just before lunch, Elena Chipalova, Human Resources Asia, Aggreko, and Suman Sharma, Head People Capability, Wealth & Retail Banking, ASEAN & Co-head of AI Leaning, Standard Chartered, got together to discuss a theme that had surfaced throughout the conference: application.
As Sharma put it:
“We are not short of content. What we are short of is application in the real world.”
That means starting with the business problem rather than the learning programme.
Learning also does not always have to look like learning. Reverse mentoring, cross-functional projects, workplace challenges and experimentation can all give people opportunities to build capability through the work itself.
Chipalova urged L&D professionals to understand their customers and competitive advantage, while Sharma argued that L&D needs to move beyond being an order-taking function. He added:
“You need to go and start to tell the business what the business needs from a people and capability perspective.”
In practice, that means understanding where the organisation is going, what is getting in the way, and what people need to be able to do differently.
The shift is clear: less about how much learning is delivered, and more about whether people can apply it to create meaningful change.
What will make future leaders irreplaceable?
After lunch, Sophie Liu, Director, Talent and Learning Development, CHAGEE University, delivered a compelling presentation on leading in the age of AI.
As digital employees take on more tasks, leaders will need to decide what AI can own, where human oversight is needed and how the two can work together.
Liu's approach is straightforward: learn by doing. Start with a real business problem, give AI a defined task, see what happens, provide feedback and gradually expand its responsibilities.
But this also changes what leadership requires. Liu summed it up in two words: “judge and connect.”
AI can provide data, recommendations and answers, but leaders still need to understand context, exercise judgement and take accountability for the final decision. And they need to build the relationships and trust that technology cannot replace.
For L&D, that means creating more opportunities for leaders to learn through experience, be it through stretch assignments, cross-functional projects, coaching and real exposure to AI-enabled work.
When hiring isn’t the whole answer
The conversation then turned to a challenge many organisations are facing: when talent is scarce, can businesses keep hiring their way out of capability gaps?
In a session on “From vacancy to velocity,” Ting Smith, Regional HR Director for Asia Pacific and the Middle East, Gensler, and Yen Do, SVP, Human Resources, Toll Group, addressed how organisations can respond when the talent they need is increasingly difficult to find.
One message came through clearly: hiring alone is not a sustainable talent strategy. As one speaker noted, companies are increasingly “snatching” talent from one another to fill mid-level roles, simply moving the same limited pool of people around the market.
That puts greater emphasis on the “build” side of talent strategy, and on the role of L&D in helping organisations develop the capabilities they will need rather than waiting for them to appear in the market.
It also means L&D needs to be part of conversations around business strategy and workforce planning earlier.
What skills are becoming less relevant? Which capabilities need to be strengthened? Where should organisations buy, build, borrow or rebalance talent?
The panel also challenged the idea that experience should simply be measured in years. Short-term assignments, cross-functional exposure, coaching and stretch opportunities can all help people build meaningful experience.
As one speaker put it:
“L&D needs to understand what is the vision of the company that we’re working in. They need to be part of the initial conversation.”
The conversation also questioned the traditional idea that career progression should be measured primarily in years of experience.
For younger employees in particular, the speakers pointed to short-term assignments, cross-functional exposure, coaching and stretch opportunities as ways to build capability faster while giving people meaningful experience.
As one speaker highlighted: “I count experience by the amount of work and assignment and exposure that you are given.”
Ultimately, the session emphasised that L&D should go beyond filling today's vacancies. The focus should be on how organisations can build enough capability internally to reduce their dependence on an increasingly competitive talent market.
From completion rates to real impact
As organisations place greater emphasis on capability and performance, the fundamental question is emerging: what actually changes after the learning ends?
That question took centre stage in a panel on measuring learning impact, led by Aloysius Foo, Talent Management, Mediacorp, with his panellists:
- Shibani Priyadarshini, APAC Organisational Development Director, Novo Nordisk,
- Anya Low, Head of HR, APAC, Watson-Marlow Fluid Technology Solutions, and
- Annie Lam, Chief People Officer, YCH Group.
For the panellists, the answer starts before a programme is designed.
Rather than immediately responding to a request for “leadership training”, L&D needs to understand the problem underneath it, and the behaviour or capability that actually needs to change.
One example showed why this matters. Managers were struggling to spend enough time coaching and giving feedback, but many had 16–17 direct reports. The issue was not simply a lack of coaching skills. The structure itself was making the desired behaviour difficult.
That diagnostic mindset also changes how learning impact is measured.
Instead of stopping at attendance, completion or satisfaction, L&D can look at whether people are applying what they learned. Are managers actually having more coaching conversations? Are behaviours changing? And, further downstream, is that translating into business outcomes?
As one panellist shared:
“Let’s find the problem. Let’s talk about the behaviours that we want to change.”
The real measure of learning, then, may not be what happens in the classroom. It is what changes when people return to work.
Keeping the spark alive
The final session turned to one last part of talent development: keeping exceptional people engaged when promotions and formal programmes are not always available.
In the last session of the day, Meike MacFarlane, Chief People Officer, Lidl & Kaufland Asia, and Rosa Cano, Talent Director, Global Supply chain International, Schneider Electric, discussed how disengagement can happen gradually.
One speaker described a progression that can start quietly: top performers stop sharing ideas, stop challenging the status quo, become a “yes person”, and eventually wait to be told what to do. They may still be delivering, but they are no longer contributing at their full potential.
That makes regular, meaningful conversations particularly important. Rather than relying on generic development programmes, managers can ask what gives their people energy, what they want to own next and how they want to grow.
For exceptional talent, development may also mean stretch assignments, job rotations, greater visibility and exposure to senior leaders, not necessarily an immediate promotion.
Coaching, too, needs to look forward. Instead of focusing only on how someone is performing today, one speaker suggested asking: “How would you act if you were now a director tomorrow?”
The bigger picture
Across the two days of Learning & Development Asia 2026, Singapore one shift kept emerging in different forms: L&D is moving from delivering learning to enabling people to do something differently.
AI is making information easier to access. It is helping people analyse data, generate content, practise scenarios and even take on parts of a job.
But the conference discussions showed that this does not make human capability less important. If anything, it makes the harder-to-measure parts of development more visible: judgement, trust, relationships, adaptability, confidence, context and the ability to turn knowledge into action.
For L&D, that means asking different questions. Not simply: How many people completed the programme?
But: What problem are we solving? What do people need to do differently? What will help them apply it? And how will we know it made a difference?
Perhaps that is the bigger lesson from the conference: The future of L&D is not about delivering more learning. It is about making learning matter.
Human Resources Online would like to thank all speakers, moderators, panellists, and attendees for being valuable contributors to this event.
We would also like to extend our gratitude to our sponsors & partners for making this conference possible:
GOLD SPONSORS
Eagles Flight
enParadigm
StoryIQ
SILVER SPONSORS
Integrated Learning Systems (ILS)
Jest Business
NTUC LearningHub
Singapore Management University and SMU Academy
Wordsburg
EXHIBITORS
AIA
Androgogic, a Totara Company
Catapult
LearnUpon
Singapore Airlines Academy
ST Engineering e-Services
Trainocate
Verztec
EVENT PARTNER
Pigeonhole Live
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