Teams | Collaboration | Customer Service | Project Management

As a cloud architect, you’re going to have to embrace AI as part of your job — unless handcrafted artisan cloud becomes a niche in the future. But this doesn’t mean that you’re going to be left by the wayside. Anybody who has used AI coding tools knows that interesting things can happen when decisions are left up to them. So, that means decision-making should be left up to the people and the code writing to the AI bots … right?

Endava is a leading provider of next-generation technology services with 11,000 full-time employees serving enterprise clients across multiple industries. At a time when many organizations are testing AI in pockets — a chatbot here, a model there — Endava recognized the business imperative of a holistic AI transformation strategy at a company-wide level.

The real advantage of using AI comes from teaming up, not just speeding up.

AI code-generation tools promised a revolution in software development. And in many ways, they’ve delivered. Code that once took hours to generate now takes minutes. But the goal isn’t just to code faster; it’s to code well. Your teams need to feed AI coding tools the right context to generate code that works with your existing systems, meets your business requirements, and integrates without expensive rework.

AI adoption doesn’t stall because teams lack access to the technology. It stalls because people don’t know where the boundaries are. Collective Next — a consultancy that co-designes solutions with Fortune 500 and nonprofit clients — saw this firsthand, both internally and with their clients.

The story of AI at work is often told in big, sweeping terms: platforms, transformations, enterprise rollouts. Those things matter. But day to day, what actually shapes behavior is what teams talk about regularly. So instead of launching yet another AI program, Atlassian’s Teamwork Lab gave an AI upgrade to a ritual we already had: retrospectives.

When checking recordings for possible compliance breaches, you shouldn't need to listen to millions of calls. AI promises to find the three that matter. But before it can help, it needs something solid to work with. Without a compliant recording foundation, AI doesn't reduce your risk. It amplifies it.

McKinsey’s 2025 State of AI research lands with a clear message: AI adoption in the workplace is stalling not because of the technology but because of the people. Most organizations are experimenting with AI, but few have scaled it in ways that deliver meaningful value.