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At Banpu, AI readiness isn’t about chasing the latest tools or job titles – it’s about cultivating critical thinkers who are willing to question what they know, and how they learn.
In the race to become “AI-ready”, many organisations are doubling down on tools and technical training. But for Sundaram Iyer (pictured above), Head of Banpu Academy at Banpu Public Company Limited, that approach only scratches the surface.
At its core, he says, an AI-ready workforce is defined not by what people know – but by how willing they are to rethink it.
"It’s a workforce willing to unlearn – and that’s harder than it sounds. At Banpu, as an integrated energy company, we have deep operational expertise and legacy practices built over decades. AI-readiness means holding that expertise with confidence while staying genuinely open to having it challenged."
This balancing act – between confidence and curiosity – underpins how the organisation is approaching workforce transformation in an AI-driven world.
This also reflects Banpu’s long-standing direction as a technology-driven energy company, where digital transformation has been underway for more than a decade – supported by the establishment of a Digital Center of Excellence (DCOE) in 2018 to systematically drive innovation and new ways of working across the organisation.
From adoption to interrogation
For Iyer, one of the biggest risks organisations face today is not low adoption, but uncritical use of AI.
"It means every employee – regardless of role – has enough AI literacy to ask the right questions, not just accept the output. For example, an operation manager who blindly trusts an AI-generated forecast is more dangerous than one who doesn’t use AI in the decision process at all."
This is why Banpu is building AI literacy as a universal baseline across functions – from project development and sustainability to finance and HR – with a clear objective.
"The goal isn't to qualify people by trendy job titles, but to produce critical thinkers who can interrogate and use AI for both their and the company’s benefit.”
Underlying this is a deliberate shift towards self-directed learning.
"At its core, it's about self-directed, intentional learners – people who don't wait to be trained, but take ownership of their own development. That's adult learning in its finest form, and that’s what we support and encourage."
Challenging how learning works
AI is not just reshaping skills – it is forcing L&D to rethink long-standing assumptions about learning itself.
"It's forcing L&D to confront an uncomfortable truth: most of what we taught as best practice may need revisiting. AI doesn't just change what people need to learn – it challenges how we believed learning worked in the first place and surfaces evidences on what works and doesn’t."
Iyer is also clear-eyed about a widely accepted idea in corporate learning.
"I'd personally push back on the popular idea that learning now happens 'in the flow of work'. Real learning – the kind that rewires thinking and builds lasting capability – requires dedicated focus, reflection, and the deliberate discomfort of questioning what you thought you knew. That doesn't happen between Outlook notifications and meetings."
In response, Banpu is creating space for deeper, more intentional learning – "not microbursts of content, but meaningful nudges and programmes where people can step back from routine, engage deeply, and surface the assumptions they've stopped questioning."
Making learning real – and relevant
A key part of this strategy is grounding AI learning in real-world applications.
"We're anchoring everything in real use cases – from Industrial AI use cases like optimising the complex mining supply-chain, predictive maintenance on machinery assets, price forecasting in energy trading, to corporate use cases like scenario-based decision support, talent analytics and investor sentiment analysis – because adult learners engage when content connects directly to their world."
This is further reinforced by Banpu’s Strategic Capability Cluster – established by integrating its people, academy and digital capabilities – to accelerate organisation-wide agility, digitalisation, adoption of AI and data analytics, and deliver tangible business impact across operations and corporate functions, from a people-first mindset.
At the same time, capability gaps are identified through ongoing, real-time dialogue with the business.
Iyer explains: "When a trading desk says, 'we have an AI tool but nobody trusts its signals,' that may not be a technology problem; it could be a skills and mindset gap that needs unpacking."
This is complemented by external benchmarking.
"By mapping capabilities honestly against where the industry is heading – what are energy companies hiring for externally tells you exactly what's missing internally. We treat that as a live signal, forming a continuous skills gap analysis rather than a static review."
"And then translating these into strategic context for Banpu – the material impact of the presence or absence of such skills gaps for our business model and geographic presence, for the short and medium term."
Tackling perceptions head-on
Driving AI adoption also means tackling the perceptions around it. When asked how employees can be encouraged to develop AI skills and embrace the learning that comes with it, Iyer says it starts by addressing the fear, hype, and hyperbole around AI and its impact on people’s jobs head-on.
"We believe AI is an augmentation to human cognitive skills and capabilities, not a replacement. Through our Hi-AI programme, a direct reminder of Human Intelligence + AI, all employees and executives experienced first-hand why, what and how AI could help, and could not."
Equally challenging is what Iyer describes as the "illusion of familiarity".
"The biggest is the illusion of familiarity and fluency – people who use GenAI chat tools casually assume they're sufficiently AI-literate.
"Getting someone to move from comfortable hobbyist, to critical, skilled practitioner requires them to first acknowledge there's a gap. That's a hard conversation with smart, experienced people."
To reinforce behavioural change, Banpu leans on peer influence and recognition.
"Internal champions matter enormously: when a respected site engineer or trading lead says, 'I tried this and it changed how I work', it carries more weight than any top-down mandate or slick learning campaign."
"It turns out, that they are also the best adult learners who are willing to say ‘I don't know’ in a room full of people who expect them to – which is genuinely difficult for senior professionals with well-established expertise," he adds.
Finally, the company also runs a quarterly AI showcase to recognise and celebrate people who have effectively learnt to use AI and applied it to transform not just the way they worked, but became a catalyst by helping others in their business process chain adopt AI to achieve better, faster, efficient outcomes together.
Making learning a non-negotiable
Time, however, remains a constant constraint.
"Operational pressure is real – business environments don't pause for learning. But the answer isn't to fragment learning into smaller and smaller pieces, but to make a genuine organisational commitment that protects learning time as non-negotiable."
Measuring impact is another evolving challenge.
"Measuring impact remains the honest frontier challenge. We can track completion and satisfaction; what's harder – and more important – is evidencing changed behaviour and better decisions. We're building towards that, but I won't pretend we've solved it."
A more human approach to future-proofing
For HR and L&D leaders, Iyer’s advice is to focus on transformation, not just capability-building.
"The first is to recognise that future-proofing in the people context fundamentally means addressing the emotional and psychological aspects. So, design your interventions for personal transformation, not just upskilling. Your programme should encourage and support people to reimagine the way they add value to the business and their lives – this is where a clear AI learning strategy becomes critical in an AI-driven world."
He also calls for a return to the fundamentals of adult learning.
"Treat your learners as the experienced, intelligent adults they are. Andragogy – the adult learning theory — tells us people learn best when they understand why something matters, can connect it to their experience, and have agency over their learning journey. Most corporate programmes still ignore this. So, break the mould and provide memorable learning experiences (without breaking the budget account)."
And critically, leaders must embody the change themselves.
"And finally: model it yourself. L&D leaders who aren't personally grappling with AI, questioning their own practice, and learning in public have a credibility gap."
Learning in public
For Iyer, staying relevant in a fast-moving space comes down to discipline and honesty.
Personally, his approach is to deliberately use AI in his own work – not as a shortcut, but as a thinking partner he pushes back against.
"I learn a lot more about the topics of my interest by using AI, as well as about AI itself, by using it than by reading about it," he says.
"By protecting time for learning – reading, reflection, peer conversations with people who challenge my views. I practise not being busy (yes, you can too); I learn by occasionally stopping and thinking and trying."
"By staying honest about what I don't know – which, in this space, is still plenty. Intellectual humility isn't a virtue; in this fast-moving field, it could be a survival skill."
As can be affirmed, in an industry grappling with complex operational and sustainability challenges, the stakes are high.
As such, building an AI-ready workforce, Iyer and team believes, is not just a capability agenda – it is a human one.
"It’s a strategic imperative at a human level. And it starts with the belief that people, given the right conditions, learn, adapt, and thrive extraordinarily," Iyer affirms.
Photo / Provided
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