How To Lead in the Age of AI Agents

AI agent adoption is expected to jump 327% over the next two years.

While we let that statistic sink in, let’s put it another way: AI agents will soon be everywhere, embedded across every business function, in every industry.

If you’re a manager, this means you’ll no longer just be leading people — you’ll be overseeing a blended workforce of humans and artificial intelligence (AI) agents. You’ll need to build on your existing skills and develop new ones, to make sure that your digital and human employees are working collaboratively to their full potential.

What does AI workforce management look like? What skills will you need and what measures should you take to manage a workforce that’s part human, part machine, and all high performance? Let’s take a look.

Address employee concerns early

If you’re adding an AI agent to your team, you’ve already thought about its role and the tasks where it could be most efficient: highly repetitive or high-volume tasks like scheduling appointments, answering basic customer inquiries, processing transactions, or analysing data. You might have also identified workflows where an agent could help make humans more successful — for example, adding an agent that provides real-time information to a rep during a customer call.

But during this planning stage, you should also be paying attention to your employees. It’s crucial that you openly address their anxiety about job displacement — and do so early in the process. As new research from Slack puts it: “In a world where [AI] agents could outnumber employees, … managers will need to become facilitators and coaches, helping their teams navigate the new landscape of work and maximise the potential of AI tools.”

Look for opportunities to upskill team members for roles that will become critical in an AI-driven workplace, and that take advantage of uniquely human qualities like creativity, judgment, and critical thinking. By investing in and supporting upskilling, you can build trust with employees by showing you’re committed to their growth. 

Salesforce offers a great example of this type of support. In addition to ongoing departmental AI training, the company hosts a quarterly Agentforce Learning Day, where employees learn how to use AI tools and integrate them into their daily tasks, and skill up on Agentforce, the platform for building AI agents. 

“We know from years of studies that the more engaged someone is with their work, the more engaged they are with the company,” said Jenny Simmons, VP of onboarding and employee learning at Salesforce. “And the better their work is, the better customer experience we create.

“This is about building capacity for humans. It’s about the evolution of the job to a new place.” 

Adjust your onboarding strategy for AI agents

Forget the welcome packets and water cooler chats: Integrating an AI agent into your workforce demands a different approach. Here are some key distinctions:

Configuration vs. training

Unlike onboarding humans, which involves an extended period of training and development, bringing an AI agent onto your team is a more technical process. You’ll need to configure it with the necessary data, workflows, permissions, and contextual knowledge so it can perform its tasks effectively. 

Precision vs. interpretation

Humans can understand nuance and ask clarifying questions, while an AI agent relies on clearly defined parameters. If those aren’t in place, it can produce nonsensical answers, or hallucinate. Be very specific about how the agent should handle unexpected situations,  or edge cases, and define when it should hand off a task to a human. 

Monitoring vs. managing

AI agents don’t need motivation or feedback in the traditional sense, but they do need monitoring. Put systems in place to track performance, spot problems, and identify when human intervention is needed. Key performance indicators (KPIs) will likely be different for AI agents and humans. For example, an AI agent can handle a much greater volume of customer service cases, faster, so expectations are higher. 

Must-have skills for AI workforce management

Getting the most out of your blended workforce entails using the managerial skills you already have, and building some new ones.

Communication and delegation

While AI agents don’t have emotions, working with them requires clear communication, thoughtful delegation, and alignment with strategic goals. In fact, you may find that some of the skills you already use to manage people can be extended to agents. 

For example, setting expectations and boundaries. With humans, you define the job description, performance targets, deadlines, and project scope. With agents, you also define those things, as well as data sources, output formats (such as spreadsheets, videos, pie charts, or social media posts), and guardrails for escalating thorny or sensitive situations. 

And just as humans benefit from regular check-ins and performance reviews, agents need oversight to make sure they’re working correctly, achieving goals, and adhering to guidelines.  This lets you make adjustments, correct errors, and optimise their performance.

AI and data proficiency

As you add agents to your team, you’ll likely need to step up your tech skills, particularly around data: how it powers agents, how to interpret and act on performance dashboards, and more. 

“Technical skills will be more important, including a deep understanding of agentic AI and data literacy,” said Simmons. You’ll need to understand and shape the data environment that drives your digital workforce to make sure your agents are effective and reliable. This may include: 

• Understanding the data requirements of AI agents.
• Identifying gaps in the data that AI agents need, and figuring out how to collect or acquire new data sources.
• Knowing the origin of the data so you can assess its reliability, accuracy, and flag any biases.
• Understanding how different data sources can be integrated into an AI agent workflow.
• Troubleshooting when AI agents don’t perform as expected.
• Anticipating future data needs.

Empathy, ethics, and judgment

Uniquely human qualities like emotional intelligence will continue to be key for managers, said Simmons, but so will ethics and judgment. You’ll have to decide when it’s appropriate to use agents, and when and how to use data. AI’s potential is vast, and company policies won’t cover every scenario, so you must firmly grasp AI guidelines and use sound judgment. 

For example, an AI agent in financial services might flag a customer for a high-yield investment based on their portfolio size, which is the company policy. However, a human advisor would know that the customer was approaching retirement and seeking lower-risk options. The advisor’s judgment would override the AI’s policy-driven suggestion.

A high-performing blended workforce starts with you

In the age of AI agents, the old idea that leadership is purely about motivating people — without understanding how the work gets done — no longer holds. Effective AI workforce management means building on your people-managing skills to understand AI capabilities, interpret data, and design successful collaboration between humans and agents. The key is to involve employees from the start — positioning AI as a tool to elevate human talent, not erase it — and to celebrate every success born from human ingenuity and amplified by AI. When employees see themselves as co-creators in this transformation, AI becomes an indispensable ally, not a threat.