Artificial intelligence is forcing organisations to rethink a fundamental assumption about workplace learning. Simply delivering more content is no longer enough. Organisations are discovering that the real competitive advantage lies in helping people make better decisions, adapt to uncertainty, and apply judgment in complex business situations.
Against this backdrop, learning is increasingly being measured not by course completion but by whether it translates into stronger workplace capability and business outcomes.
In this conversation with People Matters, John Cherian, Co-founder and CEO of enParadigm, discusses why experiential learning is becoming central to workforce capability, how AI is transforming simulations and assessments, and why organisations that treat capability as a strategic business advantage will be better prepared for the future.
(Some responses have been edited for readability and flow.)
Q1. AI is changing how work gets done, but how should organisations rethink learning itself? Where do traditional learning models begin to fall short?
John: I would look at it differently. For years, corporate learning has been built on a fairly simple assumption: give people content, get them to consume it, and hope that it turns into capability. But in practice, completion rates for e-learning have often been poor, sometimes in the range of 10 or 15 per cent, but the industry accepted it because there was no better way to do this at scale.
Today, the shelf life of any specific skill has become much shorter. What someone learns or gets certified in today can become partly outdated within 18 months. So, if the entire strategy is to keep teaching the latest skills, organisations will always be playing catch-up.
What does not become obsolete as quickly is judgment. The ability to read a situation, weigh trade-offs, make decisions under pressure, and adapt when the playbook does not quite fit. That is the real capability muscle, and it cannot be built through content alone.
That is where traditional learning models begin to fall short. They were designed largely for information transfer. And information transfer is exactly the part AI can now do faster, cheaper, and more easily than a classroom or a module. So, the part that becomes truly valuable is the experiential part: practice, feedback, reflection, and a safe space to fail before it matters in the real world.
Q2. enParadigm has championed simulation-based learning long before AI became mainstream. How does AI strengthen, or challenge, this philosophy today?
John: Earlier, high-quality simulation-based learning required skilled facilitators, carefully designed scenarios, customisation, and a lot of manual effort. It was not easy to tailor to every learner in a highly personalised way. AI changes that.
AI strengthens personalisation and feedback. Now the scenario can respond to how an individual is thinking, deciding, or communicating.
That is the engine we have built into our platform. A real business situation, whether it is a sales conversation, a difficult leadership discussion, a customer objection, or a decision under pressure, can now become an AI-led simulation that people can practise repeatedly and get coached through.
Here, the difficult part is designing a very real and contextually relevant experience that changes how someone behaves at work, and then being able to show that the change actually happened. AI is a very powerful tool in that journey, but it cannot replace the thinking behind the design.
Q3. As organisations invest heavily in AI skills, how can leaders ensure employees build decision- making and business judgment, not just technical proficiency?
John: Leaders need to be careful not to confuse tool fluency with real capability. The specific AI tool someone learns this quarter may change or become outdated next year.
But judgment does not expire in the same way. Business judgment is built through repeated exposure to real-world situations. Good leaders often make better decisions because they have seen patterns play out many times.
This kind of competence cannot simply be downloaded. It has to be built through practice.
You put someone in a realistic situation. You make them own the decision. You let them experience the consequence of that decision. Then you debrief what happened. If you do these enough times in a safe setting, you can compress years of on-the-job learning into a much shorter and more focused experience.
This is why simulations work.
So, my advice to leaders would be to not just invest in AI proficiency but hold the learning function to a higher bar than completion. Ask whether people are making better decisions than they were six months ago, and it’s visible in the way they work.
Q4. What shifts are you seeing in how organisations assess and develop talent, particularly for leadership roles, in an AI-driven workplace?
John: I see two major shifts that are closely connected.
The first is that traditional assessment is beginning to break down. If the evaluation is a static questionnaire or a predictable interview, AI can influence the outcome quite easily. In that case, organisations may end up measuring who is better at using AI, rather than who is actually better suited to the role.
The better answer is to assess people, thus is to put them in a live, situational, role-relevant context. Add a degree of pressure. See how they think, communicate, prioritise, and decide.
For instance, we worked with a large luxury hospitality group that was expanding very quickly, opening a hotel every few days and dealing with a huge interview load. Simulation-led AI assessment helped reduce their hiring timeline from eight months to two, freed up close to 18,000 management hours, saved roughly ₹6.5 crore annually, and the AI recommendations matched expert hiring panel decisions about 87 per cent of the time.
For me, the most important part was the consistency, structure, and the ability to stand up against expert human judgment.
The second shift is in leadership development.
When people go through simulations, a rich view of their strengths, gaps, behaviours, and decision patterns across roles and functions is also generated. That gives leaders a much clearer picture of where capability risks actually sit.
For senior roles and succession planning, this is extremely important. The cost of a wrong leadership bet is very high. If the same experience can help build capability and give an honest read of capability, that is where the field is moving.
Q5. Looking ahead, what will differentiate organisations that truly build capability from those that simply deploy learning technologies?
John: The first differentiator will be how seriously organisations are connecting technology deployment to business outcomes. The organisations that do this well will be very clear about the result they are trying to create.
“We rolled out a new learning platform” is not an outcome. It is an input. The real question is whether people are demonstrably better at their jobs. Is it showing up in sales conversations and hiring decisions?
Are there fewer avoidable escalations? Are leaders making sharper calls? Capability has to be seen as a business result, not a software purchase.
The second differentiator will be cultural. Organisations will need to make it safe for people to practice and fail. The best organisations will build the equivalent of a flight simulator into the way they operate.
And the way I see it, the organisations that treat capability building as a genuine competitive advantage, not as a compliance activity or a box to tick, are the ones that will be better prepared for the next decade. That is the bet we have made, and it is the bet we are helping our clients make.