As AI agents enter everyday work, leaders who learn to manage human and digital capabilities as one system of record will have the competitive edge.
Dean Arnold
Vice President, AI Platform
Workday
For a long time, the way we worked was easy to understand. People made choices, built relationships, and accomplished tasks with simple tools.
But today, the whole workforce is changing. We now have AI agents that do much more than follow a list of rules. These agents can study complex information and finish big projects. They can handle schedules and predict what's coming next. Because they can make their own decisions, they are acting more like new team members than merely tech tools.
The workforce is still the most important part of a company. But now they have a layer of AI helpers working right alongside them. This leaves leaders with a big question:
How do organizations manage AI agents as part of their operating model while keeping people at the heart of it?
The answer is an AI-ready leader who is accountable for outcomes delivered by blended teams, and who deliberately designs how humans and AI capabilities work together.
Report
AI agents are changing what is possible in how work is structured. They open up new ways for people to apply their skills and judgment, and give teams more flexibility in how they respond to change.
What does not change is the core purpose of the enterprise. People remain at the center. They bring direction, values, creativity, and connection. AI exists to support that center, not to compete with it.
The organizations that will thrive in this next chapter are the ones that treat AI as part of how work is designed, not as a side experiment. They build a unified, people‑first view of work, where AI capabilities are measured, governed, and clearly connected to human roles.
They develop leaders who are comfortable managing agents, directing blended teams, and staying accountable for outcomes and experience. They give agents clear, bounded roles and revisit those roles as needs, skills, and technology evolve. And they establish simple, explicit levels of trust so that everyone knows when AI is only suggesting, when it’s acting under review, and when it’s handling routine tasks on its own.
This is not a one‑time transformation. It’s an ongoing discipline: tuning the balance between human and digital effort, refining guardrails, and listening closely to how work feels for employees and customers.
The blended workforce is not a choice between humans and technology. It’s a chance to design systems where technology reliably amplifies human intent. Leaders who embrace that role—who make deliberate decisions about how agents show up in their operating models—will be doing more than using AI. They’ll be leading as true enterprise innovators.
Successful companies will pivot from looking at AI as just a tech tool to integrating it as a real part of the team.
The first step is getting a clear view of what is really doing the work in an organization.
Today, most companies have a sharp picture of their people. They know who sits where in the org chart, how teams are structured, and which skills live in which roles. That view usually comes from an ERP system for the workforce.
The digital side is fuzzier, with automations, integrations, and early AI agents scattered across teams. Different teams build and run them. They may not be visible beyond a slide, a spreadsheet, or a local dashboard.
When AI agents are simple, this fragmentation is mostly an efficiency problem. As those agents become more capable, it turns into a leadership problem.
If teams cannot see where and how digital capabilities are acting, they risk:
Misjudging capacity because a portion of output comes from capabilities that never show up in their workforce view.
Struggling to manage risk because they don’t know which agents touch which data or processes.
Duplicating work because teams spin up similar agents without realizing it.
Forward-looking organizations are starting to build a single view of work that covers both human roles and AI capabilities. They are not giving agents a “human” status. They are treating them as first-class elements in how work is designed, governed, and improved.
In a typical enterprise context, a leader might look at a shared services group and see:
80 people in defined roles
25 AI-driven capabilities that support those roles
Clear information on what each capability does, which processes it touches, and which controls apply
That kind of view makes one thing possible: leaders can keep human talent as the anchor while using AI with far more clarity and confidence.
Once teams can see AI capabilities in their system of work, the next change is how they think about them.
Traditional software is feature based. We learn what it can do and then decide when to use it. AI agents are more goal based. We decide what outcome they should support and where they fit in the flow of work.
A forward-thinking leader asks questions like:
Which part of this process could be handled consistently by an AI capability so people can focus on meaningful work?
How is this capability improving outcomes, cycle times, and experiences?
What would a well-designed human and digital workflow look like for this problem?
Specialization and collaboration sit at the heart of this. The aim is not to push people aside. The aim is to let people move up the value chain.
Imagine a people operations team in a period of rapid growth. Historically, spikes in hiring create a flood of candidate questions, scheduling changes, and onboarding tasks.
Now picture the same team with a thoughtful layer of AI:
A Recruiting Coordination Agent manages most scheduling logistics and standard messages.
An Onboarding Agent tracks completion across systems and nudges new hires and managers when something is at risk of slipping.
HR partners and recruiters focus more on interviews, talent strategy, and coaching managers through key decisions.
The leader is still accountable for the full experience. They support their people. They protect the culture. At the same time, they are also shaping how digital capabilities show up for that team and where they create the most leverage.
That is the work of an AI-ready leader.
The aim is not to push people aside. The aim is to let people move up the value chain.
For AI to be sustainable at scale, it needs structure. Prompts alone are not enough.
Many organizations start by giving people broad access to AI tools and encouraging experimentation. That can unlock quick wins, but it doesn’t create a sustainable model for how work should run.
Smart leaders take a more intentional approach. For each AI capability, they define a clear role:
Purpose: What specific problem is this agent here to help solve?
Scope: Which tasks will it take on and which tasks stay fully human led?
Permissions: Which systems and data can it access, and under what conditions?
Guardrails: Where must a human review or approve, and where is simple monitoring enough?
Take a Payroll Inquiry agent as an example. Its defined role might include:
Reading pay slips and relevant policy documents.
Answering standard questions about timing and deductions.
Routing complex or sensitive issues to human experts.
That same role might explicitly exclude:
Making any direct changes to pay records.
Accessing data that is not necessary for a specific inquiry.
Handling edge cases that involve judgment about fairness or intent.
These boundaries live in guidance documents, but it’s also helpful to capture them where leaders already manage roles, permissions, and workflows for people. That’s the way to keep AI firmly in service of human goals and values.
The business world is moving too fast for the old way of leading to work anymore. Successful companies will pivot from looking at AI as just a tech tool to integrating it as a real part of the team.
When teams give AI agents clear roles, they protect their business from mistakes and help people do more. The organizations that stay ahead will be the ones that successfully bring humans and AI together to create one powerful team.
The only way to achieve this is to rethink the overall team strategy. Become a leader of the future who is accountable for outcomes delivered by blended teams and deliberately designs how humans and AI work together.
Report
62% of leaders welcome AI, but only 55% of employees feel the same way. Closing this AI trust gap and ensuring that your organization is prepared for widespread AI implementation will prove decisive to your company's future success.