Before Your Next AI Investment, Connect Your Systems First

By Sarah Lindenfeld Hall

Organizations are spending billions on AI — as much as $207 billion this year on AI agent software alone, Gartner forecasts. Even so, a recent survey conducted by Atlassian found that most senior leaders hesitate to use it for more than daily tasks, and only 26% say they trust AI for making strategic decisions.

That hesitation has less to do with AI itself than with the fragmented operating models it’s drawing on, says Asha Thurthi, Atlassian’s senior vice president of product for Strategy Collection, the company’s solution for AI-native strategic portfolio management.

“Leaders have every right to be cautious,” Thurthi says. The real issue, she argues, isn’t AI itself but whether an organization has a connected operating model that AI can reason over. Strategic decision-making requires context from across an enterprise — investments, goals, progress and AI use. Most organizations, however, still rely on scattered meeting notes, slide decks and reports rather than a connected system.

Deploying more AI on top of a fragmented operating model only widens the problem, Thurthi says. Even the most sophisticated models can’t deliver reliable guidance without the organizational context to reason effectively. Before spending more on AI, she recommends, organizations must connect their systems first.

The Connectivity Advantage

Better AI outcomes aren’t about picking a smarter model, Atlassian’s research finds. Organizations that are taking full advantage of AI are those whose strategy, investments, work and execution data live in a unified system. It’s that connectivity, not which AI model they use, that is the biggest predictor of whether AI earns leaders’ trust and drives real results.

Linking daily work with strategy also helps teams move faster, the research found. Teams unblock each other and catch risks more quickly. Connectivity was the single biggest factor behind both those improvements.

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