By Sahil Thakur, Director & Head Tech-Enabled Businesses, Grassik Search
The Chief Technology Officer is being reborn from “head of engineering” into an architect of intelligence: the executive who designs how AI, data, and infrastructure come together to reshape the business. For years, the CTO was the “super‑engineer” who kept servers up, code clean, and releases on track. That has changed overtime. For the past few years, technology is the heartbeat of business strategy, and the CTO is expected to turn that heartbeat into a thinking brain.
During the early 2000s, CTOs were judged on uptime, tech stacks, and speed of delivery. Now they are expected to design an intelligence fabric that touches every function, from operations to customer experience. Instead of asking “What framework are we using?”, boards are asking “What can our data and AI actually do for the business?” A Google Cloud–NRG survey found that 59% of executives worldwide see the CTO as the primary leader for generative AI strategy, ahead of every other C‑suite role, a clear signal that AI has become a board‑level capability.
Historically, a CTO’s success was measured by the output of their developers. Today, building everything from scratch is often less efficient than orchestrating a web of APIs, cloud services, and pre‑trained models. Gartner estimates that 70% of new enterprise applications will use low‑code or no‑code technologies, up from less than 25% in 2020. That shift forces CTOs away from managing “lines of code” and toward managing “capabilities”: how quickly the organization can experiment, integrate, and learn from new tools.
This evolution gets reflected in the shift from product‑first to data‑first. Today the growth lies in data‑led intelligence. Every digital interaction is a potential source of insight. Data is no longer a byproduct of an application; it is the fuel for the AI models that define a company’s competitive edge. An IBM survey found that 75% of CEOs believe the organization with the most advanced generative AI will have a significant competitive advantage. For the CTO, this means worrying less about individual features and more about data governance, embedded databases, and model fine‑tuning the foundations of the company’s “brain.”
In many organisations, the new CTO mandate includes the following: AI strategy, data strategy, and product strategy. An Akkodis global CTO report notes that AI strategy is now central to enterprise transformation, even as many organisations struggle to execute because of talent and leadership gaps. Another global survey reported that 47% of CTOs had implemented machine learning, yet 41% said their companies still had no AI technologies in place—and half had zero dedicated AI, ML, or data scientists. This gap forces CTOs to become integrators of partners, platforms, and internal teams rather than just managers of engineers.
Today’s CTOs design how information moves through the company, where AI systems run, and how those systems make decisions. They turn vague goals into clear, trustworthy solutions that people can understand and rely on. Their job is no longer just picking tech vendors but to think ahead about what the business should be able to know and figure out, and then build the people, processes, and technology to make that possible.
The rebirth of the CTO represents the end of the siloed “tech person.” The new CTO must be part engineer, part data scientist, and part strategist, moving from an infrastructure mind set to an intelligence mind set. Their job is no longer to tell teams how to build a feature, but to architect an environment where the company can learn, adapt, and out‑innovate the competition through the power of its own data.