What sixty senior leaders attending the GCC Leadership Conclave in Hyderabad this July are signaling about where the market has moved, and what it means for the centers being built right now.
The room tells you more than the agenda
Conference agendas are written six months before the event. Speaker lists are assembled three months out. The functions and seniority levels of the people who actually show up tell you what the market has decided matters right now, and that signal is more current than anything on the agenda.
The GCC Leadership Conclave’s eighth edition arrives in Hyderabad on July 9th and 10th with more than 700 senior leaders and 250-plus CXOs confirmed. Sixty-plus speakers from organizations including Deutsche Börse, HSBC, Shell, Novartis, UBS, Swiss Re, Medtronic, Kimberly Clark, Lonza, Marriott, Honeywell, Broadridge, Verizon, SAP Labs, Schneider Electric, and DBS Bank. Vice Presidents, Managing Directors, and CTOs across financial services, pharmaceuticals, industrials, healthcare, consumer goods, and technology.
I have been reading GCC rooms for a long time. This one tells a specific story, and three signals in the composition are worth naming before the sessions start.
Signal one: the new verticals bring operating model problems the standard GCC playbook was not built for
Three years ago this conclave would have drawn predominantly from financial services and technology. The 2026 speaker list runs across pharma and life sciences, industrials, healthcare, consumer goods, insurance, and agribusiness at VP-and-above level alongside the legacy BFSI and tech representation.
Lonza sends a VP and Head of GCC. Kimberly Clark sends a Global Head and Site Leader. Medtronic sends a Senior Director of Engineering R&D. Sandoz sends a Head of Commercial FP&A. Corteva Agriscience sends a VP and Site IT Leader.
These are regulated, asset-intensive, globally complex businesses. The operating model a pharma company needs from its Indian captive is structurally diAerent from the one a financial services firm needs. The compliance surface is diAerent. The data architecture is diAerent. The talent profile is diAerent. The relationship between the center and the global parent’s operating model is different.
The centers in this room that are navigating this well started with the parent’s specific operating constraints. The ones that applied a technology-sector GCC template to a pharmaceutical or industrial environment are already discovering the gaps.
The vertical diversification of this speaker list is not a celebration of GCC’s mainstream arrival. It is a signal that the operating model problem has diversified alongside it, and a standard playbook that worked for IT services and financial processing does not transfer cleanly to a regulated manufacturing or life sciences environment without deliberate redesign.
Signal two: the CTO and the site leader are in the same room, and most GCC governance is not built to hold that
The technology leadership at this conclave carries P&L adjacency and board-level visibility. A CTO at Swiss Re Global Business Solutions. A VP of Technology at Shell India. A MD and CTO at UBS. A Global Director of Data and AI at Novartis. A Head of Applied AI at Google. A Technology and Data Strategy Leader at DBS Bank.
These are not IT delivery leaders. They are the people who determine where AI and data investment goes inside their centers, and they are attending a GCC operating-model conversation. That is the signal. When the technology leader and the site leader are in the same room at this level, it means the center’s AI agenda and its operating-model agenda have converged into a single decision, and the governance structure has to accommodate both simultaneously.
Most GCC governance structures were not built for this. The standard model separates technology decisions, which go through the CTO or IT function, from operating-model decisions, which go through shared services or operations. Deploying agentic AI inside a GCC breaks that separation. An agentic AI deployment is simultaneously a technology decision, an operating-model decision, a workforce decision, and a compliance decision. All four have to be made coherently and simultaneously.
Centers where the technology leader and the site leader each bear separate accountability for adjacent outcomes will see AI deployments stall in the space between their mandates. The centers that hold both leaders give joint accountability for the same outcome.
The conversation in that room on July 9th and 10th is one of the few forums where both people are present. What comes out of it, the governance design that gives them shared accountability rather than parallel mandates, is the operating model decision that determines whether AI deployment inside these centers delivers or stalls.
Signal three: HR is at the table, which means the centers that understand the real
problem have already moved
HR and talent leadership sit at the same seniority level as technology leadership across multiple organizations in this speaker list. A VP of Human Resources from New Relic. A Senior Director and Hyderabad Center HR Head from HCA Healthcare. A VP of Talent Acquisition from HSBC. A Head of HR from Chubb Insurance. An Executive Director People and Culture from Syneos Health.
This is the most consequential of the three signals because of what it implies about sequencing.
When HR leadership is present at this level by design rather than by invitation, it means those organizations have concluded that the AI-native GCC is a workforce architecture problem before it is a technology problem. They are making the workforce decision alongside the technology decision, not downstream of it.
The centers sequencing workforce architecture after technology deployment are repeating an error that manufacturing companies made in the 1980s during automation. The productivity gains automation was supposed to deliver did not materialize at the expected rate because the workforce model around the technology had not been redesigned to capture the value it could generate. The technology worked. The operating system around it constrained what the technology could deliver.
An AI-native GCC where the workforce model was designed for the previous generation of work will underdeliver on its AI investment by exactly that mechanism. The board approved the technology. Nobody redesigned the system the technology has to operate inside.
The HR leaders in this room represent the organizations that have understood this. For anyone building or advising on a GCC in 2026, their presence at this level is the clearest available signal that workforce architecture is a first-order decision, not a downstream one.
What the three signals say together
The GCC market is not maturing into a stable model. It is restructuring around a new set of constraints: industry-specific operating models that require first-principles design rather than template application; AI deployment that collapses the separation between technology and operating model governance; and workforce architecture that must be decided alongside technology rather than after it.
The boards that approved AI-native GCC builds in 2025 and early 2026 mostly approved them against the previous model, with AI added as a capability layer on top of a center designed for a diAerent kind of work. The centers in this room that are ahead are the ones redesigning the model, not extending it.
At Smart IMS, this is the specific work our Xymphony agentic AI platform is built to support: closing the gap between what global parents are now asking their captives to deliver and the operating model the center was originally built to run. The conclave conversations will sharpen that work, because the leaders navigating the live version of this transition are in the room.
What I am taking into the room
I will be at the GCC Leadership Conclave as a delegate on July 9th and 10th. The three signals above are the frame I am bringing into every conversation.
The specific questions I want to test in the room: In pharma and industrial organizations new to the GCC at scale, are operating models being designed from industry-specific constraints or adapted from a technology-sector template? In organizations where the CTO and the site leader both attend, do they share accountability for the same outcome, or do they each carry separate accountability for adjacent outcomes? And in the centers where HR leadership is present at this level, was that a deliberate first-order decision, or did workforce architecture arrive late?
The answers will tell me more about where the GCC market is in the second half of 2026 than any analyst report.
If you are attending and would like to connect before or during the event, I welcome the conversation.
About Smart IMS: Smart IMS is a global technology group with operations across North America, APAC, and EMEA. Its Xymphony agentic AI platform is deployed across enterprise and GCC environments to close the gap between global AI commercial commitments and captive operating-model delivery. smartims.com
About the author, Mahesh Iyer is EVP Global Revenue at Smart IMS. He writes The Revenue Circle, a LinkedIn newsletter on the architecture of predictable enterprise revenue, and advises AI and enterprise companies on revenue systems, GTM strategy, and GCC operating-model design.