DEVOPSdigest

Technical leaders across the industry have observed the powerful impact of AI on software development workflows. New research provides quantifiable proof of this sweeping transformation.

AI-powered software innovation is generating annual savings of $28,249 per developer, according to GitLab's 2025 executive research report, which surveyed thousands of C-level executives from around the world. When implemented across the world's 27 million developers, AI's potential translates to more than $750 billion in global value annually.

With savings of this scale, it's no wonder C-Suite leaders support AI's potential to drive greater efficiency in software innovation. Nine out of ten executives (91%) say that software innovation is now a core business priority for their organization.

Narrowing the Human-AI Collaboration Divide

Room for growth clearly exists. While executives aspire to build human-AI partnerships that split software development work 50-50, the majority report that AI is currently only handling about 25% of the work. For leaders to successfully operationalize AI among development teams, they 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 that successfully realize AI value share three critical traits: They have the right CTO strategy with a 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.

Choose the Right Technical Leadership

With 82% of C-suite leaders willing to invest over half of their IT budgets in software innovation, technical leaders face an opportunity to demonstrate their value. In my experience, CTOs work in various styles, and companies require different styles of technical leadership at different stages of their evolution. Three of these CTO styles stand out particularly: Builder, Strategist, and Guardian.

Builder CTOs thrive when innovating with AI, establishing core technical architecture, and developing innovative products while constantly validating their assumptions with customer feedback. They work best with smaller, high-growth companies and those that are still in the early stages of their AI journey.

Strategist CTOs reach their peak performance 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 integrate AI as a permanent, value-additive component of the company's strategic platform.

Guardian CTOs excel at helping companies with complex IT infrastructures and large customer bases maintain stability, security, and operational efficiency. They align perfectly with 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.

Success in AI-powered software innovation requires leadership that can identify targeted AI applications, translate them into customer value, and enable teams to focus on higher-value work.

Scale Through Platform-First Strategies

As organizations grow, teams specialize in addressing specific challenges, but with more teams, coordination among them can become inefficient. When organizations scale to tens of thousands of employees, 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.

Based on my observations, the most effective CTOs implement platform-based approaches to position their companies for scalable growth without creating silos. Their most frequent approach centers on establishing a centralized team that's responsible for building a platform that product teams across the organization can use. These teams focus primarily on automating mundane tasks and creating 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 develop a team dedicated to supporting that as an AI-powered "subsystem" that the rest of the company can use.

Reorganize Teams and Build Skills for the AI Era

Positioning software teams for success in the AI era means letting humans focus on tasks that AI can't do well. Although AI supports 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 excel at guiding AI technologies and achieving the productivity gains of human-AI partnerships.

Building expertise in AI-related skills, such as prompt engineering and data management, will be crucial. The human capabilities that are the most valuable include creativity, strategic vision, and collaboration.

However, an important perception gap needs to be addressed. 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 partnership that will deliver competitive advantages.

The Future Demands Strategic Human Leadership

This $750 billion AI opportunity won't materialize automatically. Leveraging AI's full potential requires appropriate leadership, platform thinking, and upskilling in a way that enables humans to focus on their strengths while allowing AI to manage and automate mundane tasks.

While AI transforms the software development landscape, it does not eliminate the need for skilled engineers. The technology shifts emphasis toward higher-value work that requires human judgment, ingenuity, and strategic thinking. Moving forward, human software developers will have more time to dedicate to work that drives competitive advantage. Companies that fully embrace AI-powered innovation can then transform themselves and their industries in ways we haven't yet imagined.