Today's CIOs face increasing demands to increase production, maintain reliability, and innovate faster while striving to reduce budgets and headcount.
Rapid advances in AI and intelligent automation technologies are opening the door to more independent, goal-oriented AI, known as agent AI, which can be used as “digital employees or workers” to complete end-to-end tasks and workflows. Digital employees (AI-powered software applications) act as virtual workers to handle repetitive processes and tasks, freeing up 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 can generate content using large-scale language models (LLMs).
AI assistants differ from AI agents and digital workers because they use natural language processing and machine learning to understand human commands and are more supportive and perform repetitive tasks, such as scheduling and generating reports, in response to commands. Digital workers are more independent and goal-oriented, able to understand their environment, make informed decisions, and perform multi-step actions without human intervention, allowing them to effectively manage workflows.
AI assistants and digital workers working alongside human employees are becoming more common. According to a PwC survey, 88% of senior executives plan to increase their AI budget over the next 12 months thanks to agent AI. Additionally, 66% of survey respondents reported that AI agents have already begun to improve employee productivity and reduce costs.
However, digital workers require a different strategy than simple AI operations and rigorous monitoring to meet expectations, complete workflows correctly, and maintain compliance.
What makes a digital worker different?
Digital workers and AI agents can not only complete automated one-time requests, but also run IT automation and perform end-to-end tasks. Digital workers can break down complex projects into multi-step tasks that can be completed independently.
“The real benefit is the ability to automate predictable, rules-driven tasks that take up innovation time, rather than replacing resources and staff within the IT organization,” said Brady Lewis, senior director of AI innovation at Marketri. “By empowering digital workers to perform repetitive tasks typically done within IT, high-value time to create solutions gives IT leaders more think time.”
Just like human workers, digital workers require unique identity management within your company, including:
- Unique identification.
- Specific permissions that adhere to the principle of least privilege.
- Service level agreements to define performance levels and quality.
- Continuous monitoring and check-ins.
- Defined workflow.
While more basic tools can handle a single task or instruction, digital workers can autonomously take on entire projects and execute them from start to finish.
Where digital workers double your IT output
Digital workers are particularly beneficial to IT organizations because of the large number of repetitive, data-driven tasks they can handle. With the help of a digital workforce, CIOs can double down on IT outcomes and free up time for human employees to focus on strategic decision-making, innovation, and other critical functions.
According to the ISG report, more than half of feature-specific agent AI applications are used in IT, specifically DevOps, cybersecurity, and infrastructure management.
“The benefit is not cost savings,” said Sean Jaromi, founder and principal advisor at Alpharay Consulting. “The real benefit is operational reliability. Digital Workers reduce variance, eliminate backlog spikes, and deliver 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 augmentation for tasks such as:
- IT Service Desk Automation.
- Software provisioning and access requests.
- Manage and optimize cloud resources.
- Security alert triage and remediation.
- Finance and procurement workflows.
“IT production increased not because agents were working 24/7, but rather because bottlenecks were removed,” said Roman Rylko, chief technology officer at Pynest. “Recruiters in our HRM system receive ready-made profiles of engineers who are already interested in the job. Nobody likes sorting through raw resumes in different formats. This action saves time on copy-pasting and manual data structuring, allowing employees to focus more on their immediate responsibilities.”
How can we make digital workers more efficient?
To make the digital workforce effective, it is essential to understand that its capabilities go beyond traditional AI software. “Rather than viewing digital workers simply as a tool to automate labor, companies that successfully leverage autonomous workers will manage digital workers through the same operational processes they use when hiring new members of their IT organizations,” Lewis said.
Ineffective use of digital workers can slow down processes, increase the likelihood of downtime and errors, and ultimately waste resources.
“An effective model clearly defines where digital workers need to stop and take over,” says Jahromi. “For example, digital workers can prepare access decisions, but humans approve edge cases. This allows humans to stay focused on empathy, trust, and accountability while digital workers handle scale and consistency.”
Here's what CIOs can do to help the digital workforce optimize IT outcomes without compromising them.
- Shift your operating model. Operations strategies must change to accommodate hybrid human-AI teams and foster collaboration with digital workers and employees.
- Implement workflow and task handoff. Determining in detail what workflows digital workers will be involved in, and to what extent, will ensure that they are integrated at the right time to maximize efficiency and outcomes.
- Prioritize AI management skills. Shifting your upskilling and development efforts to focus on skills like AI monitoring and automation engineering will enable your workforce to effectively collaborate with and manage your digital workforce.
- Track key performance indicators for your digital workforce. CIOs must define and measure KPIs such as task completion rates, frequency of intervention, and level of autonomy.
Governance, risk and responsibility
Digital workers cannot be treated as a one-time initiative. Consistent oversight and governance is required. By hiring digital workers to support IT outcomes, organizations accept the risks and responsibilities associated with agent AI.
“We treat them as tools with clearly formalized lines of responsibility. Each AI agent has an owner, a list of actions allowed to the AI agent is defined, a log of all operations is kept, and of course there is a clear 'red button',” Rirko said. “Most importantly, we do not cede power to AI agents that we ourselves are not prepared to take responsibility for our employees and customers.”
“Governments should answer who owns digital workers, what they are allowed to do, what access they have, how their actions are recorded, and who is held accountable if something goes wrong,” said Eddy Abou-Nehme, director of operations at RevNet Ottawa. “Responsibility should be clear, with a designated leader approving the scope of the digital workforce, monitoring performance, and ensuring human escalation paths for exceptions and incidents.”
When implementing a digital workforce strategy, governance should be integrated into a strong CIO strategy and focused on core areas such as:
- AI monitoring and auditability. Keeping a comprehensive record of decisions and results allows output to be tracked and evaluated for post-incident response and optimization.
- Security and access control. Digital workers should be given the same access to digital resources as other employees, especially when dealing with sensitive information such as financial data.
- Accuracy, predictability, and explainability. Agentic AI tools can exhibit unexpected behavior and disrupt operations and organizational stability. Guardrails and validation measures help ensure that the output is predictable and accurate.
- Vendor management. When using third-party vendors to implement a digital workforce, organizations should ensure that these vendors are transparent, reliable, and secure by evaluating them based on factors such as data management and security controls.
Future prospects
As AI continues to evolve, autonomous IT operations or AIOps, including digital workers and other agent AI, will continue to be integrated into IT environments and become a core component of operations.
As AI automation and analytics advance, organizations will be able to create and maintain IT environments that are predictive and self-healing, enabling them to be proactive rather than reactive. Advanced AI technology can identify and fix problems before they occur or trigger responses to mitigate failures, reducing downtime and improving system reliability.
As the capabilities of the digital workforce expand, organizational structures and IT operations may change significantly. Some roles, such as administrator roles and manual system administration, may be eliminated, while new roles, such as AI supervisor and automation architect, will emerge.
By integrating agent AI into daily operations, CIOs and other IT leaders will be able to shift priorities and focus on high-value tasks and strategic initiatives such as architectural design and innovation.
How to get started
Digital workers can increase IT output. However, its implementation into workflows and operations must be carefully managed to enhance rather than hinder output.
“The most effective approach is to start with digital workers running in assisted mode, with employees approving actions and gradually increasing autonomy once performance stabilizes,” Abou-Nehme said. “Teams get the best results when digital workers are treated like part of an operating model, with ownership, documentation, runbooks, and a plan for what happens if workers are unsure or fail.”
Here's how to get started on your digital workforce journey.
- Efficiently bringing digital workers into your business starts with a large number of rules-based processes that digital workers can complete autonomously, such as systems management and incident triage.
- Assess integration readiness, such as APIs, to ensure Digital Workers can easily integrate into operations.
- Start with a low-risk pilot before scaling a large number of digital workers to improve workflows and optimize processes.
- Create a digital workforce roadmap that spans all IT domains and ensures that digital worker adoption is scalable and coordinated across your organization.
Alison Lawler is a freelance writer with experience in technology, human resources, and marketing.
