Ask coders how they spend their time these days, and they’re likely to tell you they mostly oversee generative AI tools that craft most of the code. The quality of the code LLMs produce has improved dramatically. People who used to craft code from scratch now review and adjust AI chatbot outputs. For all practical purposes, they have become AI managers.

To some extent, that’s a part all managers are destined to play. The arrival of AI agents will catalyze this transition.

Agents—AI systems that act autonomously to carry out multiple tasks in pursuit of a goal—will become part of most managers’ teams. Working alongside human employees, they will complete work in a fraction of the time it takes a human. It won’t be long before hybrid human-AI teams are common in every industry.

Consider healthcare, where an AI agent will draft post-visit follow-up patient care plans, schedule check-ins, send reminders, and flag unusual symptoms in post-visit surveys for review. The human nurse practitioner will review and personalize the follow-up plan, contact patients in need of emotional support or clarification, and make clinical decisions about concerns the AI has flagged.

In financial services organizations, agents will monitor client portfolios, market conditions, and life events, suggesting portfolio rebalancing or financial moves. The human financial advisor will evaluate the agent’s suggestions based on their understanding of client goals, appetite for risk, and emotional readiness, and hold relationship-building meetings with clients.

In law firms, agents will scan contracts for risk clauses, missing terms, or compliance issues, while junior associates will analyze the agent’s highlights, apply legal reasoning to ambiguous cases, and advise on negotiation strategies based on client context.

Even in the industry in which I work—commercial construction—we are likely to see agents monitoring site sensors, drone footage, and safety incident reports in real time to auto-generate daily construction logs, track progress against schedule, and flag potential safety or quality issues. The assistant superintendent on the job will review the agent’s reports, resolve discrepancies (for example, an agent might not consider a weather delay), and make judgment calls on escalating issues or adjusting plans.

These are but a few of the ways agents will alter the means by which work gets done.

Managers Aren’t Ready

The addition of AI agents to teams will have profound implications for how managers manage. Consider the four examples above:

• Healthcare—Healthcare managers will have to align clinical protocols with AI-generated outputs, ensure HIPAA compliance (in the U.S.), and train staff to interpret and override AI recommendations when necessary.
• Financial Services—Managers will need to ensure their advisors understand the limits of AI recommendations, balance automation with trust-building, and train teams to explain AI logic to skeptical clients.
• Law firm—Partners or legal managers will have to assign roles clearly (AI as first-pass filter, human as final reviewer), prevent overreliance on AI in nuanced deals, and maintain audit trails for liability.
• Construction —The manager will ensure the AI is calibrated to real-world conditions, train staff to verify AI data, and build workflows that integrate AI updates into morning planning hurdles.

Countless challenges will face managers AI agents become a routine part of the mix. Scheduling alone will require new ways of thinking, since agents will complete tasks in hours or days instead of the weeks or months it may have taken humans, yet humans will continue to need the same amount of time they always have to complete their assignments. Rethinking how and when things need to get done, accounting for the handoffs between humans and AI agents, will test managers’ skills.

Other challenges managers will face include…

• Defining roles and responsibilities—What do AI agents do and what requires the human touch? There is more to this than just passing out assignments. In many cases, it managers will have to redesign their processes from scratch.
• Oversight and trust—While AI agents operate autonomously, managers will remain accountable for the results they produce, requiring them to monitor AI decisions and intervene when necessary. Managers will also need to establish clear protocols and boundaries for agents’ autonomy (like setting rules for what an agent can decide on its own and what should require human approval).
• Skill gaps and training—To manage AI agents, managers must understand how they work and ensure their team members are trained to work alongside them.
• Maintaining morale and trust—Introducing AI agents to teams is bound to raise employees’ anxiety levels. Managers must proactively address job security fears and demonstrate how AI agents assist but don’t replace the team.
• Performance evaluation and accountability—How do you evaluate performance in a hybrid human-AI team? A rethinking of success metrics is in the cards.more to this than just passing out assignments. In many cases, it managers will have to redesign their processes from scratch.

And all of this must happen while managers retain all their usual people-management duties—including, in some cases, managing remote workers, a challenge to which many managers still haven’t risen.

Redefining the Manager’s Role

Much of the work that occupied managers will shift to AI, especially administrative work like handing out assignments, tracking progress, compiling reports, and making routine decisions. With less busy work, managers should be able to to focus on those aspects of managing that require a human touch, shifting to leading and mentoring, employing soft skills over hard skills, as shown in this chart:

Wharton professor and AI thought leader Ethan Mollick has suggested companies may shift to more fluid, project-based structures where “AI will act as connectors, while middle management will focus more on human-AI coordination.” Instead of managing a rigid all-human team that grinds through its work, a manager might move from project to project as needed, overseeing a flexible AI-human hybrid team.

A day in the life of a manager in an AI-integrated team might involve checking a dashboard of AI agents’ overnight work, consulting with a data AI about market trends to inform strategy, and then spending the afternoon in one-on-one meetings with team members to coach them through challenges and build morale.

Managers may also work closely with technical staff on agent fine-tuning (a bit like managing the “training” of an AI much as they manage the development of an employee). As Anthony Mavromatis at American Express observed, AI is “freeing up (managers’) time and allowing them to focus on the essence of their job”– the creative and innovative aspects that AI can’t do

Empathy, ethical judgment, communication, and adaptability will define great managers in the AI era.

In fact, despite growing consensus (including among employees) that AI could one day take over their managers’ jobs, the manager’s role will become more pivotal as they focus primarily on leadership. If adding AI agents creates a “digital workforce” with humans working together, the manager’s role is to orchestrate this human-AI symphony.

However, too many managers lack soft skills, focused as they are on driving their teams’ work and slogging through hours and hours of administrative tasks. The management training most companies provide their managers has not been updated to account for the transformational role AI will play on teams.

Can Communicators Help?

As a communicator, I don’t look at any business activity without seeing it through the communication lens. Internal communicators who choose to wade into these waters can have an outsized impact on how well their organizations adapt. After all, like so many things digital in organizations, this is as much about change management as it is about the technology. Communicators will get people on board, informed, and comfortable, ensuring everyone understands what’s changing and why.

To do this, communicators need to…

• Set expectations with transparency—Communicate how AI agents will affect workflows, job roles, and day-to-day activities. When employees know the facts, they’re less likely to fear the worst.
• Two-way dialogue to address concerns—Provide channels that allow employees to voice their concerns and get answers.
• Communicate the “why”—A compelling narrative will make it easier for the pivot to go smoothly. Tell the story of why the company is embracing agents. Is it to improve customer experience? To reduce tedious work and free people for creative tasks? Paint the vision of how AI will ultimately benefit the employees and the company.
• Guidance, training, and resources—Let employees know what support is available, and create some of that support in the form of intranet and other easily-accessible resources.
• Highlight success stories and quick wins—Nothing motivates employees to adopt a new behavior like seeing other employees recognized for that behavior.* Set expectations with transparency—Communicate how AI agents will affect workflows, job roles, and day-to-day activities. When employees know the facts, they’re less likely to fear the worst.
• Two-way dialogue to address concerns—Provide channels that allow employees to voice their concerns and get answers.
• Communicate the “why” —A compelling narrative will make it easier for the pivot to go smoothly. Tell the story of why the company is embracing agents. Is it to improve customer experience? To reduce tedious work and free people for creative tasks? Paint the vision of how AI will ultimately benefit the employees and the company.
• Guidance, training, and resources—Inform employees about the support available and create some of that support in the form of an intranet and other easily accessible resources. Highlight success stories and quick wins—Nothing motivates employees to adopt a new behavior like seeing other employees recognized for that behavior.

Internal communication should be the bridge between the technological change and the human side of the organization. When done right, robust internal communication ensures that AI agents are introduced not as mysterious black boxes, but as well-understood new teammates that everyone knows how to work with.

Management in an AI-Driven Workplace

Once human-AI hybrid teams are up and running, organizations will find themselves on a trajectory to a time when they will be flatter and more agile, with managers serving as AI strategists. New definitions of what a “good manager” is will emerge. Looking 5-10 years out, I can envision a workplace where AI agents are ubiquitous, embedded in almost every process. The very definition of a “team” or “workforce” will evolve to include digital entities. The managers who thrive will be those who embrace this future and guide it rather than resist it. They will be lifelong learners, continually adapting as AI evolves. They’ll also be advocates for their team’s humanity – ensuring that technology serves to enhance human potential rather than replace it.

The managers of the AI era won’t be those who can out-calculate a computer but those who can leverage AI to amplify human ingenuity. They will create teams that are not only highly efficient but also creative, resilient, and ready for whatever the future of work brings.