Teams | Collaboration | Customer Service | Project Management

Here’s a stat that’s been rattling around in my head. In our 2026 AI SDLC study, 94% of engineering leaders told us they’re using AI, but only 6% have the systems to actually scale it across their whole software lifecycle. Almost everyone is playing with agents, yet almost no one can let agents run at scale without things breaking.

Most vendors sell "AI work management" as a prettier board with a chat box. That framing is too small for anyone running paid client delivery. AI work management is the operating layer that decides who does what, when you can safely promise dates, and what the work actually costs. It also decides which parts a supervised AI agent can take without wrecking trust. Before I joined Teamwork.com, I saw the spreadsheet version of that job repeatedly across agency environments.

AI financial insights for professional services leaders are not a chatbot bolted onto last month's export. At Teamwork.com, we see leaders need margin, utilisation, and forecast signals while work is still movable. For example, a delivery lead can change staffing mid-project before an overrun hits the P&L; I've watched firms mistake a prettier dashboard for insight.

Whatever you need to know is already in Teamwork.com: resourcing, budgets, task status, all of it live. The only question is how many clicks stand between you and it. Ask AI removes them: ask what you'd ask a colleague, typed or said out loud, and get the answer straight from your own data.

With AI assistants like Claude and ChatGPT becoming more deeply integrated into knowledge work I wanted to run a like-for-like comparison in a competency close to my heart: data analysis.

Tamar Yehoshua is Chief Product and AI Officer at Atlassian, where AI agents are now direct users of the software her team builds.

Over the past year, many companies have moved from simply experimenting with AI to integrating it into their core business operations. From customer service and analytics to communication and workflow automation, AI is becoming an integral part of how modern organizations operate. Even companies in highly competitive digital markets, such as eSIM Plus, are increasingly looking for ways to use AI to make their products, services, and customer experiences more efficient.

AI is accelerating implementation. The engineering teams who benefit most will connect context, orchestration, and accountability across the work around code. AI can now help engineers turn ideas into working code in minutes, but software delivery has always been more than just producing code.