Over the last few weeks, we have been discussing AI and its impact on operating models. We touched upon how AI can fail if we don't have the right models in place and change management of the same as we implement AI tech tools within our organization. On the same lines, one of the really important factors is talent development for tomorrow and not just today, given what I call an Industrial Revolution of a new kind; the AI kind 🙂...
If we automate the work that once created experts, what will replace it as the training ground for expertise?
“If AI removes the bottom rungs of the talent ladder, where will tomorrow’s operations leaders learn to climb? For decades, global delivery models have traditionally been built as pyramids.”
Large numbers of early-career employees handled repeatable, high-volume work. Through this daily grind, they developed vital pattern recognition. They learned the business from the ground up, internalizing the nuances of customer exceptions, operational bottlenecks, and compliance mandates. Gradually, through sheer volume and exposure, these entry-level workers matured into our subject-matter experts, our team leaders, and our transformation managers.
AI is now rapidly absorbing much of that foundational work. Algorithms can process invoices, resolve tier-one customer queries, and draft summaries faster and more accurately than humans. This undoubtedly improves speed, margin, and productivity. However, where will we find the leaders and the mid-level managers of tomorrow who have evolved from the ground up?
The next global delivery advantage will not come from having the largest talent pyramid or the cheapest offshore labor pool. It will come from building the fastest AI talent flywheel and not a pipeline.
In a traditional pipeline, talent moves linearly from novice to expert over years of repetitive tasks. In a flywheel model, AI accelerates the baseline learning curve, while experienced human practitioners continuously transfer context, judgment, and accountability back into both the machine and the junior talent.
Tomorrow's talent will need to possess a rare combination of technical capability, deep domain knowledge, an intricate understanding of regulatory requirements, and above all, the ability to make sound, ethical judgments. All of this gets honed only through real-world friction. There is no substitute for Experience. So, what now!!
Read about human-in-the-loop AI-augmented use cases >>
A recent report on India’s global capability centers (GCCs) found that while 52% plan to expand their footprint, a 42.6% of graduates do not currently meet industry employability standards. In response, nearly eight in ten centers are already running internal Generative-AI upskilling programs.
The implication for global delivery and enterprise operating models is abundantly clear. We cannot automate the apprenticeship phase of a career and still expect world-class expertise to magically appear five years later. This experience deficit has to be methodically worked out and the only way out is deliberate, strategic investment in human capital.
To secure our future leadership pipeline, entry-level roles must be completely redesigned. This means we, as business leaders, must actively invest in talent development rather than strictly measuring the traditional "throughput productivity" of our entry-level staff. The RoI of an entry-level employee is no longer how many widgets they process, but how quickly they learn to manage the AI that processes the widgets.
We should proactively invest in giving our employees the experience of:
Let us invest in the talent for tomorrow. The initial cost of redesigning career paths will pale in comparison to the cost of waking up in five years with a highly automated business run by people who do not understand how it works. Any organization worth its salt has already begun to look closely at this gap; are you one of them? As you reflect on your digital transformation agendas, remember this undeniable truth: that at the end of the day, businesses are run by people.