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The New Role of Eng Leadership in an AI World?

The New Role of Eng Leadership in an AI World?

As AI reshapes management, it leaves a lot behind...

Gino Ferrand
April 08, 2025

"It is not the strongest of the species that survives, nor the most intelligent, but the one most adaptable to change."

Charles Darwin

Gino Ferrand, writing today from Seattle, WA 🌄

Engineering leadership is undergoing a metamorphosis. Not a revolution. Not a slow march. Something stranger: a morphing of roles driven by the relentless infusion of AI tools that shift duties, expand skill requirements, and tangle old hierarchies into new shapes.

Scrum Masters, Engineering Managers, DevOps Leads, and Data Science Team Leads are all encountering this transformation. The question is: Who's evolving, and who’s just running on a hamster wheel, hoping the landscape stops changing long enough to catch a breath?

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The Cautious Transition

Some leaders are treading carefully. They’re not buying into the shiny AI promises wholesale. They see AI as a tool...an immensely powerful one...but not a master. When Harry Guinness wrote for LeadDev that “AI is changing engineering management by expanding the quantity of code produced,” he wasn’t celebrating. He was warning.

Gartner’s 2023 study went further, noting that AI is introducing new compliance and data privacy challenges. Engineering Managers, in particular, are finding themselves responsible not only for managing people but also for managing how AI is used within their teams, including mitigating risks of AI introducing security flaws or intellectual property issues.

The story is the same across roles. Scrum Masters are now “AI wranglers,” as agile coach Venkatesh Rajamani described, guiding human-AI collaboration and ensuring that automated suggestions align with agile values. Rather than eliminating roles, AI shifts them. More mentoring, less status-reporting. More orchestration, less note-taking.

It’s the same for DevOps Leads, whose job descriptions are morphing from hands-on fire-fighting to strategic oversight of AI-driven operations. As GitLab describes it, AIOps is moving teams “from manually monitoring systems to automating incident response and optimizing pipelines.” DevOps Leads are evolving into curators of intelligent pipelines...responsible for configuring and verifying AI-driven tools rather than personally implementing every fix.

The Hybrid Model: Partnership with AI

If some are proceeding with caution, others are leaning in. This isn’t the age of AI replacement...it’s the age of AI partnership.

Atlassian’s rollout of AI-powered tools illustrates this hybrid approach. Jamil Valliani, Head of Product for Intelligence at Atlassian, described how AI-driven Jira Intelligence is “transforming how project managers work” by automating routine processes and offering smart suggestions tailored to each team’s historical patterns.

Microsoft’s internal use of AI in Teams offers another example. Features like Intelligent Recap automatically produce summaries and highlight decisions from meetings, ensuring nothing gets lost. For Engineering Managers, the message is clear: Delegate the drudgery and keep your eyes on the big picture.

Even in the DevOps space, companies like Microsoft are experimenting with AIOps platforms that detect anomalies, suggest fixes, and even perform automatic rollbacks if something goes wrong. These tools don’t eliminate the need for DevOps Leads...they elevate their focus from handling individual alerts to designing resilient systems that can self-correct.

Where This Leaves Engineering Leadership

It’s not just the tools that are evolving. It’s the very concept of leadership itself.

Traditional coordination skills are increasingly automated. Status reporting, metrics gathering, even some aspects of communication are now handled by AI. Leaders who cling to these functions risk becoming obsolete. But those who understand the new terrain are carving out fresh, impactful roles.

They’re the ones who use AI not just as a productivity booster but as a strategic partner. The leaders who know that the real challenge isn’t using AI...it’s figuring out when not to use it. It’s about drawing the line between what AI can do and what humans must do. That line is constantly shifting, and that’s the skillset leaders need to master.

My prediction? AI will continue to augment rather than replace leadership. The best leaders will become curators of machine output, deciding which suggestions to embrace and which to discard. Those who thrive will be the ones who see AI not as a tool to be feared, but as an opportunity to be harnessed.

In a world where AI is increasingly involved in every layer of the engineering stack, the most valuable leaders will be those who can navigate the complexity, embrace the partnership, and steer their teams through uncharted territory.