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Digital workers: The CIO's new IT multiplier
CIOs are being asked to scale IT output without scaling teams. Autonomous digital workers are reshaping how leaders drive reliability, governance and execution across IT.
Today's CIOs face growing demands to increase output, remain reliable and innovate faster – all while trying to reduce budgets and head count.
The rapid advancement of AI and intelligent automation technology has opened the door to more independent, goal-oriented AI – known as agentic AI – that can be used as "digital employees or workers" to complete end-to-end tasks and workflows. Digital employees – or AI-powered software applications -- function as virtual workers to handle repetitive processes and tasks, allowing human staff to focus on more strategic activities.
The use of AI in the workplace has evolved dramatically, from simple rule-based scripts to bots that can handle multi-step tasks to AI assistants that use large language models (LLMs) and can generate content.
AI assistants are different from AI agents or digital workers because they use natural language processing and machine learning to understand human commands and are more supportive and perform repetitive tasks on command, such as scheduling or generating reports. Digital workers are more independent and goal-oriented and can understand their environment to make informed decisions and execute multi-step actions without human intervention, thereby managing workflows effectively.
AI assistants and digital workers that work alongside human employees are becoming more common. Eighty-eight percent of senior executives plan to increase AI-related budgets in the next 12 months due to agentic AI, according to a survey by PwC. Additionally, 66% of survey respondents report that AI agents have already begun to increase workforce productivity and reduce costs.
However, digital workers require a different strategy than simple AI operations and rigorous oversight to ensure that they meet expectations, complete workflows correctly, and stay compliant.
What makes a digital worker different?
Digital workers and AI agents are not just completing automated, one-off requests – they can also perform IT automation and execute end-to-end tasks. Digital workers can break complex projects into multi-step tasks that can be completed independently.
"The true advantage is that it does not replace the resources and staff within IT organizations, but allows for the automation of predictable, rule-driven tasks that take away from innovative time," said Brady Lewis, senior director of AI innovation at Marketri. "By allowing digital workers to perform the repetitive tasks that are typically done within IT, the high-value time for creating solutions gives the IT leaders more time to think."
Similar to a human worker, digital workers need their own identity management within the company, including:
- Unique identification.
- Specific permissions, adhering to the principle of least privilege.
- Service Level Agreements to define performance levels and quality.
- Continuous monitoring and check-ins.
- Defined workflows.
While more basic tools can handle one task or instruction, digital workers can take on entire projects autonomously and execute them from start to finish.
Where digital workers multiply IT output
Digital workers can be particularly beneficial to IT organizations due to the large number of repetitive and data-driven tasks they can handle. With the assistance of digital workers, CIOs can multiply their IT output and free up time for human workers to focus on strategic decision-making, innovation and other vital functions.
According to a report from ISG, over half of functional-specific agentic AI applications are found in IT, particularly in DevOps, cybersecurity and infrastructure management.
"The benefit is not cost-cutting," said Shawn Jahromi, founder and principal advisor at Alpharay Consulting. "The real benefit is operational reliability. Digital workers reduce variance, eliminate backlog spikes and create consistent execution across shifts, time zones and peak periods. This directly improves service levels, audit readiness and system hygiene."
IT organizations can use digital workers as a workforce multiplier for tasks such as:
- IT service desk automation.
- Software provisioning and access requests.
- Cloud resource management and optimization.
- Security alert triage and remediation.
- Finance and procurement workflows.
"The increase in IT output is not so much because 'the agent works 24/7,' but rather because bottlenecks are eliminated," said Roman Rylko, chief technology officer at Pynest. "Recruiters in our HRM system receive ready-made engineer profiles that are already interesting to work with. No one likes sorting through raw resumes in various formats. This operation saves hours of copy-pasting and manual data structuring, allowing employees to focus more on their direct responsibilities."
How to make digital workers effective
To make digital workers effective, it's essential to understand that their capabilities go beyond traditional AI software. "Instead of viewing digital workers merely as tools to automate labor, companies that successfully leverage autonomous workers will manage them through the same operational processes that are used when hiring a new member of an IT organization," said Lewis.
Used ineffectively, digital workers can slow down processes, increase the likelihood of downtime and errors, and ultimately waste resources.
"Effective models clearly define where a digital worker must stop and hand off," said Jahromi. "For example, a digital worker can prepare an access decision, but a human approves edge cases. This keeps humans focused on empathy, trust and accountability while digital workers handle scale and consistency."
Here's what CIOs can do to ensure that digital workers are optimizing IT output instead of hurting it:
- Shift operating models. Operational strategies must shift to accommodate hybrid human-AI teams, promoting collaboration with digital workers and employees.
- Implement workflows and task handoffs. Determining the specifics of what workflows digital workers will be involved in and to what extent ensures that digital workers are integrated at the right time to maximize efficiency and output.
- Prioritize AI management skills. Shifting upskilling and skill development initiatives to focus on skills such as AI supervision and automation engineering ensures that employees can effectively collaborate with and manage digital workers.
- Track key performance indicators for digital workers. CIOs should define and measure KPIs, such as task completion rate, intervention frequency and autonomy level.
Governance, risk and responsibility
Digital workers cannot be treated as a one-time initiative; they require consistent oversight and governance. By hiring digital workers to support IT output, organizations are accepting the risks and responsibilities associated with agentic AI.
"We treat them as tools with a clearly formalized area of responsibility. There is an owner for each AI agent, a list of permissible actions for the AI agent is defined, a log of all operations is kept, and of course, there is a clear 'red button,'" said Rylko. "The most important thing is that … we do not transfer to AI agents any authority for which we ourselves are not prepared to be accountable to employees and clients."
"Governance should answer who owns the digital worker, what it is allowed to do, what access it has, how actions are logged, and who is accountable when something goes wrong," said Eddy Abou-Nehme, director of operations at RevNet Ottawa. "Responsibility should be explicit, and a named leader should sign off on the digital worker's scope, monitor performance, and ensure a human escalation path for exceptions and incidents."
When implementing a digital worker strategy, governance should be baked into a strong CIO strategy, focusing on core areas including:
- AI oversight and auditability. Keeping comprehensive records of decision-making and outcomes ensures that outputs can be traced and evaluated for post-incident response and optimization.
- Security and access controls. Digital workers should be granted access to digital resources just like any other employee, especially when handling sensitive information such as financial data.
- Accuracy, predictability and explainability. Agentic AI tools can exhibit unpredictable behavior that can disrupt operations and organizational stability. Guardrails and validation measures help ensure that output is predictable and accurate.
- Vendor management. When using third-party vendors to implement digital workers, organizations must ensure that these vendors are transparent, trustworthy and secure by evaluating them based on factors such as data management and security management.
Future outlook
As AI continues to advance, autonomous IT operations or AIOps – including digital workers and other agentic AI – will continue to be integrated into IT environments, becoming a core component of operations.
As AI automation and analytics advance, they can help organizations create and maintain predictive and self-healing IT environments, enabling proactive responses instead of reactive ones. Advanced AI technology will be able to identify and rectify issues before they occur or trigger responses to mitigate failures, thereby helping to reduce downtime and improve system reliability.
As the capabilities of digital workers expand, organizational structure and IT operations may undergo significant transformation. Although some roles may become obsolete – such as administrative roles and manual system management – new roles will emerge, such as AI supervisors and automation architects.
With the integration of agentic AI into daily operations, CIOs and other IT leaders will shift their priorities to focus more on high-value tasks and strategic initiatives, such as architecture design and innovation.
How to get started
Digital workers can increase IT output. However, implementing them into workflows and operations should be managed carefully to ensure they enhance -- not hinder -- output.
"The most effective approach is to start by running the digital worker in assist mode, where employees approve actions, and gradually expand autonomy once performance is stable," said Abou-Nehme. "Teams get the best results when digital workers are treated like part of the operating model, with owners, documentation, runbooks, and a plan for what happens when the worker is unsure or fails."
Here's how to get started with implementing digital workers:
- Start with high-volume, rules-based processes, such as system management or incident triaging, that can be autonomously completed by digital workers, to introduce digital workers into operations efficiently.
- Assess integration readiness, such as APIs, to ensure that digital workers can be easily integrated into operations.
- Start with low-risk pilots before scaling large numbers of digital workers to refine workflows and optimize processes.
- Develop a digital workforce roadmap that spans all IT domains to ensure the adoption of digital workers is scalable and coordinated throughout the organization.
Alison Roller is a freelance writer with experience in tech, HR and marketing.
