How CTOs can capture the $750 billion AI opportunity

Technical leaders understand how profoundly AI has reshaped innovation workflows. Now we have data that quantifies the massive impact it’s creating.

GitLab’s 2025 executive research report, which surveyed 2,786 C-level leaders worldwide, reveals that AI-powered software innovation delivers an average of $28,249 in annual savings per developer. With 27 million developers globally, that means AI could unlock over $750 billion in value each year.

Given these potential savings, it’s unsurprising that C-suite executives are embracing AI’s efficiency-driving capabilities. Ninety-one percent of leaders now consider software innovation, including AI, a core business priority for their organizations.

Bridging the human-AI collaboration divide

Despite the enthusiasm around AI, significant growth opportunities remain. Executives say their ideal state is splitting development work equally between humans and AI, but the reality is that AI currently handles only 25% of tasks. To maximize the benefits of AI across development teams, leaders must effectively communicate the value of AI, linking development activities to business outcomes through problem-solving capabilities and measurable business impact rather than focusing solely on code output. This mindset shift will prove essential for realizing AI’s full potential.

AI isn’t going to eliminate the role of the developer. Instead, it is fundamentally transforming role requirements, and how executives must lead and organize teams to capitalize on this enormous opportunity.

Most organizations that successfully capture AI value share a few things in common: they have strategic CTO leadership with an unwavering customer focus; they implement platform-based approaches that enable teams to scale effectively with AI; and they invest in team structures and upskilling initiatives that help developers maximize the benefits of AI.

Which type of technical leader is right for your team?

The vast majority (82%) of C-suite executives we surveyed said they are prepared to invest over half of their IT budgets in software innovation. This is an unprecedented moment for technical leaders to shine, but what kinds of leaders are best placed to seize the opportunity? Throughout my career, I’ve found that organizations need specific leadership approaches at different points in their evolution. I like to categorize CTO leadership styles into three distinct buckets that correspond to different phases of organizational growth: Builder, Strategist, and Guardian.

Builder CTOs excel at AI-driven innovation, establishing core technical architecture, and creating innovative products while continuously validating their assumptions through customer feedback. They’re ideal for smaller, rapidly growing organizations and those just starting their AI transformation journeys.

Strategist CTOs become invaluable as companies mature, combining deep technical expertise with business knowledge to build platforms, develop long-term visions, nurture strategic partnerships, and position the organization for sustained, scalable growth. Strategist CTOs help transform AI into a permanent, value-generating component of the organization’s strategic platform.

Guardian CTOs are critical for supporting organizations with complex IT infrastructures and extensive customer bases to maintain stability, security, and operational efficiency. They are a good fit for organizations whose priorities include AI governance, security implementation, and establishing AI processes and standards that maximize efficiency while reducing costs.

To drive success in AI-powered software innovation, leaders must be able to identify targeted AI applications, translate them into customer value, and enable teams to concentrate on higher-value activities.

Adopt platform thinking for scalability

As organizations grow, teams specialize in addressing specific challenges. But with larger teams come difficulties in coordination. By the time an organization reaches tens of thousands of employees, these challenges often become silos that hinder effective collaboration and prevent organizations from realizing the benefits of human-AI partnerships.

In my experience, the most effective CTOs implement platform-based strategies to position companies for scalable growth without creating silos. The most common approach involves establishing a centralized team that is responsible for building platforms that product teams can utilize organization-wide. This team’s primary function is to automate routine tasks and provide streamlined workflows for all software innovation teams throughout the organization, a role that AI can significantly enhance.

CTOs may need to create specialized teams that support complicated subsystems required by the broader organization. An organization with complex requirements, such as evaluating fraud risk in new customers or solving supply-chain complexities in real time, might organize dedicated teams to support these as AI-powered “subsystems” that the entire company can use.

Restructure and upskill teams to maximize their capabilities

Setting up software teams for success in the AI era means freeing up humans to focus on work that AI can’t perform effectively. AI can help with tasks such as coding and answering questions, but it can’t determine the “why” behind a project.

Engineers who translate business requirements into technical solutions and anticipate future trends will be invaluable. Those who can combine technical skills with critical thinking will better guide AI technologies and achieve productivity gains from human-AI partnerships.

Training in specific AI-related skills, such as prompt engineering and data management, will also be essential. Our survey found that executives view creativity, strategic vision, and collaboration as the most valuable human contributions to software development.

However, there’s also a significant perception gap here: Our global survey of more than 5,000 DevSecOps professionals at all job levels found that 25% of individual contributors feel their organizations don’t provide sufficient AI training, compared to only 15% of C-level executives.

Forward-thinking CTOs will frame upskilling as an investment in human-AI partnerships that is crucial to delivering competitive advantages.

The future requires human innovators

The $750 billion opportunity from AI-powered software innovation won’t materialize automatically. Harnessing the power of AI requires appropriate leadership, platform thinking, and upskilling that enables humans to focus on their strengths while AI manages and automates routine tasks.

AI is transforming the software development landscape, but it’s not eliminating the need for skilled engineers. Instead, it’s shifting focus toward higher-value work requiring human judgment, creativity, and strategic thinking. Over time, human software innovators will increasingly concentrate on work that drives competitive advantage and allows organizations to transform themselves and their industries in unprecedented ways.