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The New Era of Work: Agentic AI, Model Selection, and the Looming Security Question

A recent discussion focused on the rapid evolution of AI in the workplace, sparked by the Atlassian and Google Cloud partnership for agentic AI. The conversation quickly shifted to the new skills required to manage these powerful tools and the critical security implications of pervasive AI data access.

The Agentic AI Shift in Project Management

The Atlassian and Google Cloud partnership is bringing "agentic AI" into daily work, meaning AI that can plan, execute tasks, and coordinate across various tools. This capability prompts a major question: how much trust should be placed in AI for team task management? This deep integration, particularly allowing Gemini to perform actions in Jira and Confluence, could lead to the complete elimination of human project managers.

While AI is reliable for tasks like building reports, alerting people, or sending notifications about pending work, allowing it to plan the work entirely may not be ideal yet. The trust in AI is expected to grow, but for now, human minds remain more reliable for setting and assigning complex tasks. Traditional project management—breaking down epics into stories, estimating work, and assigning tasks based on timelines—is currently still best managed with human oversight.

AI Model Selection as a Crucial Future Skill

The complexity of AI tools is increasing, as evidenced by the introduction of multiple AI models, such as Gemini 3 flash, into Atlassian’s Robo. This feature allows users to choose between faster or more powerful AI based on their specific needs.

The question was posed whether choosing the appropriate AI model will become a necessary skill in the future. It was agreed that models have different capabilities, and selecting the most suitable model will be crucial for complex automations, integrations, or achieving the best outcome for detailed queries.

The Critical Concerns of Data Access and Security

Perhaps the most critical topic raised was the concept of "deep integrations." An AI model having the ability to see and act on all work data—including emails, documents, and tasks—across a user’s workflow raises significant security concerns. While greater access makes the AI more useful, it simultaneously means giving away more control.

Users of Google-based solutions, especially with a pro plan, may not have a choice in connecting applications like Google Drive and emails to tools like Gemini. This shift means corporate and personal data is being read by a tool, and users often don't know how these companies are using the information. With Atlassian previously mentioning they would use user data unless opted out (a choice often unavailable for free or standard plans), the potential for secrets and strategies to leak is a major concern.

For corporates, data privacy and protecting strategies are paramount, meaning the review of these data usage practices must be prioritized within the corporate security review process. The adoption of agentic AI marks a fundamental, irreversible shift in how corporate and day-to-day work is conducted.

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