By Sabrina Farmer, CTO at GitLab
Across engineering organizations worldwide, artificial intelligence has fundamentally altered how teams approach software development. What was once theoretical potential now comes with concrete financial validation. And the transformation is already underway.
Recent research from GitLab’s 2025 survey of C-Suite executives reveals that AI-powered development workflows are delivering $28,249 in annual savings per developer. The study, encompassing thousands of C-level executives worldwide, points to an unprecedented economic shift. When we calculate this impact across the world’s 27 million developers, the total addressable value reaches more than $750 billion annually.
This scale of opportunity explains why C-Suite leaders are rapidly prioritizing AI-enhanced software innovation. Research shows that 91% of executives now consider software innovation a fundamental business priority for their organization.
Bridging the Human-AI Collaboration Gap
But there’s still room to grow. While executives aspire to build Human-AI collaboration that splits software development work 50-50, the majority report that AI is currently only handling about 25% of the work. To help implement AI among development teams, leaders must effectively communicate and frame its value, connecting development activities to business outcomes by focusing on problem-solving capabilities and direct business impact rather than code volume. This shift in thinking will be critical to fully realizing AI’s potential.
AI isn’t eliminating developer jobs. However, it is fundamentally changing what those jobs require and how executives need to lead and structure teams to capitalize on this massive opportunity.
Organizations achieving intelligent AI outcomes share three critical traits: They have the right CTO strategy with relentless customer focus; they’re applying platform thinking to enable their teams to scale more effectively with AI; and they’re investing in team structures and upskilling to help their developers reap the benefits of AI.
Deploy the Right Technical Leaders
With 82% of C-suite leaders willing to invest over half of their IT budgets in software innovation, it’s clear that this is the moment for technical leaders to shine. I’ve found throughout my career that CTOs come in several different styles, and companies need varying styles of technical leadership at different points in their evolution. There are three CTO styles: Builder, Strategist, and Guardian.
Builder CTOs excel at innovating with AI, establishing a core technical architecture, and developing innovative products while continually validating their assumptions with customer feedback. This style of CTO is ideal for smaller, high-growth companies and those that are still in the early stages of their AI journey.
Strategist CTOs excel when companies mature, combining deep technical acumen and business knowledge to build platforms, develop long-term visions, cultivate strategic partnerships, and position the company for long-term, scalable growth. The Strategist CTO can help make AI into a permanent, value-additive component of the company’s strategic platform.
Guardian CTOs specialize in helping companies with complex IT infrastructures and large customer bases maintain stability, security, and operational efficiency. They are the right fit for companies whose priorities include implementing governance and security measures around AI, as well as establishing AI processes and standards to maximize efficiency and cost savings.
Achieving intelligent AI outcomes in software innovation requires leadership that can identify targeted AI applications, translate them into customer value, and enable teams to focus on higher-value work.
Adopt Platform Thinking for Scale
As organizations grow, teams specialize in focusing on specific challenges, but with more teams, coordination among them can become inefficient. By the time an organization reaches the tens of thousands, those divisions often turn into silos that can hinder effective collaboration among humans and prevent the organization from realizing the benefits of Human-AI collaboration.
In my experience, the most effective CTOs are implementing platform-based approaches to set their companies up for scalable growth without creating silos. The most common way is to establish a centralized team that’s responsible for building a platform that product teams across the organization can use. This team’s primary purpose is to automate mundane tasks and provide streamlined workflows for all software innovation teams throughout the organization, a role that AI can enhance.
CTOs may need to establish specialized teams to support a complicated subsystem required by the rest of the organization. An organization with complex needs, such as evaluating fraud risk in new customers or solving supply-chain complexities in real-time, might orchestrate a team dedicated to supporting that as an AI-powered “subsystem” that the rest of the company can use.
Transform and Upskill Teams to Support Their Strengths
Building high-performing teams for success in the AI era means allowing humans to focus on work that AI can’t do well. Although AI can assist with many software development tasks, like coding, it cannot define the “why” behind a project.
Engineers who can translate business needs into technical solutions and anticipate future trends will be invaluable. Those who can combine technical skills with critical thinking skills will be better able to guide AI technologies and realize the productivity gains of Human-AI collaboration.
Training in specific AI-related skills, such as prompt engineering and data management, will be crucial. Human contributions that will matter the most are creativity, strategic vision, and collaboration.
However, there’s a significant perception gap to address. A recent GitLab DevSecOps report found that 25% of individual contributors reported that their organizations don’t provide adequate AI training, compared to only 15% of C-level executives who shared the same sentiment.
Forward-thinking CTOs will frame upskilling as an investment in the Human-AI collaboration that will deliver competitive advantages.
The Path Forward Requires Strategic Leadership and Human Ingenuity
The $750 billion opportunity in AI-powered software development won’t emerge through technology alone. Realizing this potential requires intentional leadership strategies, platform thinking, and systematic upskilling initiatives that enhance human capabilities while enabling AI to handle routine tasks.
The software development landscape continues evolving, but the core need for skilled engineers remains unchanged. AI redirects focus toward higher-impact work that demands human judgment, creative problem-solving, and strategic vision. As this evolution accelerates, software innovators will dedicate more time and energy to work that establishes lasting competitive differentiation. Organizations that successfully orchestrate AI-powered innovation position themselves to revolutionize their industries in entirely new ways.
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ABOUT THE AUTHOR
Sabrina Farmer is the Chief Technology Officer at GitLab, where she leads software engineering, operations, and customer support teams to execute the company’s technical vision and strategy and oversee the development and delivery of GitLab’s products and services. Prior to GitLab, Sabrina spent nearly two decades at Google, where she most recently served as vice president of engineering, core infrastructure. During her tenure with Google, she was directly responsible for the reliability, performance, and efficiency of all of Google’s billion-user products and infrastructure.
