In today’s volatile tech landscape, chief technology officers (CTOs) are under immense pressure to do more with less. With rising operational costs, a competitive race for scarce developer talent, and growing demand for faster digital innovation, the challenge lies in unlocking productivity without increasing headcount or budget.
“Faced with these challenges, consider what it would mean for your business if your development team could ship code 40% faster without sacrificing quality,” says Benjamin Wentzel, CTO at Britehouse.
According to Gartner, 70% of enterprises will use artificial intelligence (AI) by 2027 in their development pipelines, yet many tech leaders are still grappling with how to implement it effectively.
As AI reshapes software development, CTOs face a pivotal moment where we adapt to this revolution or risk falling behind.
“As a CTO, I’ve seen firsthand how AI transforms not just code but the very role of technology leadership through the empowerment of developers,” says Wentzel.
The AI Revolution in Software Development
AI is no longer a futuristic buzzword but a cornerstone of modern software development. Tools like GitHub Copilot are automating repetitive tasks, from writing boilerplate code to catching bugs before deployment.
Studies show that AI-assisted coding can reduce development time by up to 35%, freeing teams to focus on creative problem-solving. But the impact goes beyond productivity.
AI is enabling hyper-efficient documentation of systems by automatically analysing and summarising codebases, providing automated peer reviews, and even autonomous debugging, all capabilities that were unimaginable a few years ago.
“With opportunity comes complexity. CTOs must now navigate a landscape of ethical AI use, tool sprawl, and team upskilling,” Wentzel says.
“Overseeing tech stacks and delivery timelines is evolving into one that blends strategy, innovation, and change management.”
Lessons from the Front Lines
In this regard, Wentzel explains that the Britehouse team faced a daunting challenge in modernising a client’s legacy Windows CE codebase to a modern, cross-platform framework.
Historically, this process would take weeks, bogged down by manual code analysis and documentation.
“Instead, we leveraged AI to transform the timeline and outcomes. Using AI-driven tools, we automated the documentation of the legacy codebase, generating clear, structured insights into its architecture and dependencies in hours.”
With this knowledge, the Britehouse developers used AI-assisted code generation to iterate rapidly, converting the Windows CE codebase to Flutter in just days.
Wentzel highlights three lessons about AI-driven development gleaned from the experience:
- AI Accelerates Legacy Modernisation: AI’s ability to analyse and document complex legacy systems slashed our prep time, turning weeks of work into days.
- Empowered Teams Drive Success: By using AI to handle repetitive tasks, our developers focused on high-value work, such as optimising Flutter’s UI/UX, boosting innovation.
- Iterative Processes Win: AI-enabled rapid prototyping and iteration, allowing us to test and refine the migrated codebase in real-time, ensuring quality and performance.
“These lessons reshaped my role as CTO. Beyond managing tech, I’m now a catalyst for transformation, ensuring AI empowers our team to tackle legacy challenges with unprecedented speed,” he adds.
Three Steps for CTOs to Embrace AI in 2025
Based on his experience, Wentzel says AI-driven development isn’t a plug-and-play solution and requires intentional leadership.
He believes that CTOs can navigate the shift successfully by piloting AI tools strategically, upskilling teams for the AI era, and aligning AI with business outcomes.
“It is best to start small with AI tools that address specific pain points. For example, adopt AI coding assistants like GitHub Copilot for prototyping or AI-driven documentation tools for legacy systems. Choose tools that integrate with your existing stack to minimise disruption.”
Regarding AI skills, Wentzel explains that AI doesn’t replace developers, but demands new skills.
“Invest in training programs that teach your team to work alongside AI, from prompt engineering to interpreting AI-generated insights. Measure AI adoption using analytics to track both adoption and acceptance rates across teams. Encourage a culture of experimentation, where failure is a learning opportunity.”
When it comes to aligning AI with business outcomes, Wentzel says AI’s value lies in its impact on the bottom line.
“It is vital to establish clear metrics, such as accelerated time-to-market, cost savings, or enhanced customer satisfaction, and align AI initiatives with these objectives. Communicate these wins to stakeholders to build buy-in for further investment.”
Embracing AI as a partner
The rise of AI-driven development is not just a technological shift but a call to rethink the CTO’s role, Wentze says.
“The AI-led transformation of software development is inevitable. The question is whether you will lead or follow the change. By embracing AI as a partner instead of a replacement, businesses can unlock unprecedented productivity and innovation. The key to success is to start small, measure rigorously, and empower your team to experiment,” he concludes.