エンドバが AI エージェントを中心にソフトウェアデリバリーを再設計する方法

Endava is a global technology services company that has spent more than 25 years helping enterprises solve complex business problems through technology. Today, that mission increasingly centers on AI.

But for Endava, adopting AI meant more than introducing new tools. It required rethinking workflows, leadership behaviors, and how teams collaborate across the business.

We sat down with Matthew Cloke, CTO, to hear how Endava is embedding AI across the organization, redesigning software delivery around agents, and creating a culture where experimentation is expected—not optional.

“AI has had a fundamental impact on Endava over the past couple of years,” says Cloke. “We really had to answer the question of how to be a relevant organization in the new AI world.”

That mindset led Endava to make OpenAI its enterprise AI platform, giving employees across the company access to ChatGPT Enterprise and Codex. The goal wasn’t simply adoption—it was making AI part of the flow of everyday work.

“To be AI-native at Endava, it’s about thinking about AI to solve the problem first,” Cloke explains. “It’s the first thing you do rather than the last thing that you do.”

“If I don’t have an agent running in the background, I somehow think I’m wasting my time.”

—Matthew Cloke, CTO, Endava

Inside the rollout

Endava’s AI transformation began inside its software delivery teams.

As developers started experimenting with AI-assisted coding and agentic workflows, teams quickly realized the bottleneck was no longer engineering output. Requirements gathering, business analysis, planning, and stakeholder coordination all needed to move faster too.

“We started to challenge how quickly we could produce requirements and how quickly we could produce the right business solutions for our clients,” says Cloke.

Today, OpenAI technology is embedded throughout the entire DavaFlow lifecycle—from meeting preparation and business planning to product discovery, software engineering, and deployment.

“There isn’t a part of DavaFlow that doesn’t use OpenAI technology.”

—Matthew Cloke, CTO, Endava

Importantly, adoption didn’t stop with developers.

Legal teams began using AI to streamline research and documentation workflows. Project managers started using Codex to generate governance reports and summarize engineering progress. Commercial teams replaced spreadsheet-heavy planning exercises with lightweight AI-generated applications.

In one internal pricing discussion, employees skipped spreadsheets entirely and instead built a single-page pricing app teams could interact with immediately.

“It changed the conversation completely,” Cloke says.

AI agents have also become embedded in day-to-day operations. Leadership teams use agents to summarize projects, automate communications, manage inboxes, and coordinate work asynchronously.

Results at a glance

• Accelerated software delivery by integrating AI agents into engineering workflows
• Expanded AI adoption beyond engineering into legal, finance, and operations teams
• Reduced manual reporting and coordination work through AI-assisted workflows
• Enabled teams to build internal tools and applications without dedicated engineering support
• Established AI fluency as part of hiring and promotion expectations across the company

Lessons learned from Endava

As Endava rolled out AI across its 11,000-person global workforce, several principles emerged:

• Treat AI adoption as a behavior change, not a software rollout
• Leaders need to actively use AI to drive organization-wide adoption
• Create space for experimentation—even when outcomes are imperfect
• Bring non-technical teams into the process early, not later
• Hands-on experience is the fastest way to overcome skepticism
• Make AI part of everyday workflows, not a separate initiative

What’s next

As a long-term OpenAI partner, Endava sees the next phase of enterprise AI centered around orchestration—combining models, agents, workflows, and human expertise into integrated systems that fundamentally reshape how organizations operate.

“We’re really excited about the workflows that can be created by combining these tools,” says Cloke.

From reasoning models and Codex agents to automation and enterprise-scale collaboration, Endava believes AI is becoming more than a productivity layer. It’s becoming the operating model itself.

And for organizations still early in the journey, Cloke’s advice is straightforward: start using the technology personally.

“The future arrived,” he says. “You just have to lean into it.”