Every GCC has gone through the same evolution, and leaders in the room will recognize it from their own org charts:

• GCC 1.0 – cost arbitrage. Finance, IT helpdesk, back-office ops moved to India because it was cheaper.
• GCC 2.0 – shared services. Standardized processes, SLAs, some process ownership.
• GCC 3.0 – centers of excellence. India owns end-to-end functions: biostatistics, clinical data management, regulatory affairs support, pharmacovigilance case processing.
• GCC 4.0 – the India center stops executing someone else’s roadmap and starts co-creating IP: building the RWE models, the AI-assisted literature review tools, the patient safety signal detection systems, not just running them.

Most companies can already hire the AI engineers for this. What they can’t do is get the rest of the enterprise (e.g. the medical affairs reviewer, the regulatory associate, the country commercial lead) to actually trust and use what the GCC builds. You end up with a strong model sitting in a repo because nobody upstream knows how to interrogate it, sign off on it, or explain it to a regulator.

That gap shows up as a few concrete realities:

• Build capability outpaces trust capability: the GCC can ship a model faster than the enterprise can learn to rely on it
• No one upstream owns the sign-off: a model built in India, used by a country commercial or medical team, with no clear owner for validating it before it touches a real decision
• The literacy gap sits outside the GCC: it’s not the engineers who are behind, it’s HR, medical affairs, regulatory, and commercial leadership who were never brought along
• Orphaned builds become the norm: good technical work with no adoption path, which is exactly how GCC 4.0 quietly turns into more pilot purgatory

This is why co-creation has to be paired with a demand-side literacy build, not just a supply-side engineering one

This invite-only, closed-door roundtable brings together CHROs, L&D leaders, and GCC heads from global life sciences enterprises to exchange practical, experience-driven insight on:

• What it actually takes for a GCC to move from executing to co-creating IP
• Where enterprise trust breaks down even when the underlying model is good
• Who should own sign-off and validation for AI outputs that touch regulated decisions
• Building the demand-side literacy, across HR, medical affairs, regulatory, and commercial, needed to make GCC 4.0 real rather than aspirational
• Real examples – models that got built and used, and models that got built and shelved