Rethinking Work When AI Becomes a Digital Worker
At the June 2026 Agentic & Applied AI for the Enterprise conference, a common thread speakers explored was the view that autonomous agents are an extension of the workforce. According to Google's Sharad Aggarwal, shared services teams should not view "an agent as an automation piece, look at it as a digital worker."
This shift creates complexity in how AI will impact the human workforce – concerns arose regarding how operating models, workforce strategies, and accountability frameworks must be reconsidered. There is also a reasonable fear that digital workers will increasingly supplant human workers.
So, are these concerns justifiable? What does the rise of digital workers really mean for the human workforce?
Shifting to a Hybrid Labor Model
Where traditional automation completes rules-based activities, digital workers extend capabilities by combining reasoning, orchestration, and autonomous action. Matt Shait, Partner at ScottMadden, described this shift as moving "from augmenting tasks to changing how work gets done."
This redesign of agentic-powered workflows sounds daunting, but the goal is not job replacement – it's a hybrid labor model where humans and AI systems collaborate towards the same business outcomes. This requires organizations to consider where human oversight is most needed. Digital workers can assume responsibility for portions of the end-to-end process but defer to human judgment when necessary.
This is impactful for shared services and Global Business Services (GBS), as these functions already understand cross-functional workflows and service delivery models. They are better equipped to determine where digital labor can be introduced safely and where human expertise must remain central.
Human Employees' Value Lies in Strategic Work
As digital workers can absorb execution-heavy workflows, human employees can focus on more strategic work, involving:
- Judgment
- Creativity
- Relationship-building
- Interpretation
- Exception management
- Accountability
Aggarwal described this as "living above the algorithm." Organizations need to draw a clear line between activities that require execution at scale and activities that require human judgment. The priority is developing roles that make the most of the capacity created by digital workers.
However, without redesign, AI may just add another layer of work. Employees may be expected to supervise agents, correct outputs, and learn new tools, all while continuing their existing responsibilities. What is presented as augmentation becomes a multiplying workload. To shift human employees to more strategic roles, leaders should ask:
- What work should the digital worker own?
- What work should remain human-led?
- When is human approval required?
- What happens when the agent encounters an exception?
- Who is responsible for reviewing the outcome?
- What new skills will employees need?
Human-in-the-Loop Versus Human-Led Processes
With traditional automation, the concept of human-in-the-loop became commonplace. This positions an employee at the end of an AI-driven process to approve or reject an output. However, human-led automation begins with the employee's role and workflow, then determines where AI can provide meaningful support.
Corean Canty, founder of Speak More Human and Shift to Play, encouraged organizations to ask where AI should be inserted into the human workflow, as "AI is the newest member of your talent stack." Organizations need to "treat AI onboarding like a new member of your team."
It would be risky to allow a new hire to run a process end-to-end unsupervised. In the same way, a digital worker requires a defined role, clear access permissions, measurable objectives, feedback, performance monitoring, and an escalation path.
This new workforce model also requires an environment in which human employees understand how they are expected to interact with agents. Kandi Gongora, CHRO at The CAR Group, emphasized that "we need both humans and AI to continuously improve and learn."
The human employee should not just correct an agent's mistake and move on. The correction should be used to improve the system. Otherwise, organizations create what the workshop described as a "feedback theater," where humans repeatedly intervene, but the digital worker never meaningfully improves.
Establishing Trust is Paramount to AI Success
Even when leaders describe AI as augmentation, employees will judge the technology according to how it affects headcount and career opportunities. Ram Menghani, former NECAM ECT President and spokesperson for NEC, framed it, "We are not looking to replace employees, but to empower employees to work better."
For that message to be credible, it must be reinforced through workforce planning and ongoing communication. Employees must be shown how their jobs will change. As Canty noted, "We need to show people that we're teaching AI as it's a new responsibility, and a job evolution."
However, Sandhya Ramadasan, from Oracle, highlighted that enterprise trust does not emerge from messaging alone. It must be built through system design. Digital workers should:
- Show their sources where appropriate
- Operate within defined permissions
- Log their actions
- Involve humans at predetermined decision point
As Ramadasan's session emphasized: "Build agents that do not just amaze people once, but earn their trust every day."
Managing and Governing Agents
As digital workers become active participants in business processes, organizations must manage them like any other part of the workforce. According to Atlassian's Prakash Reddy, successful deployment requires dedicated ownership and a continuous "build, manage, maintain" approach. Organizations need visibility into how agents are used, where they fail, and whether they are improving workflows.
At the same time, AI governance is evolving into a form of digital workforce management. Satya Angara from Brink's Global Services argued that AI agents should be governed as digital employees, with:
- Identities
- Permissions
- Onboarding processes
- Supervision
- Auditability
- Offboarding processes
While organizations can delegate tasks to digital workers, accountability remains a human responsibility.
Final Thoughts: Redesigning the Workforce for the Agentic Era
So, are fears about digital workers replacing human workers justifiable? Not entirely. The concern is understandable, as agentic AI will change roles, redistribute tasks, and reduce some forms of manual execution.
But this does not mean the rise of digital workers should be seen as a replacement. If agents are introduced deliberately, they can expand capacity rather than reduce headcount. This is where the opportunity lies. Digital workers can create space for employees to focus on more value-adding work.
The rise of digital workers should therefore prompt neither complacency nor panic. It should prompt deliberate workforce planning.