March 2026

When AI Agents Become Part of the Workforce

For the first time in history, organisations are managing two fundamentally different types of workers: humans and artificial agents. The shift is subtle but profound. Artificial intelligence is no longer just a tool that employees use. Increasingly, it performs work itself — screening applications, generating reports, monitoring compliance and executing tasks inside business workflows.

At Kinatico (ASX:KYP), an ASX-listed compliance technology company, we recently reflected this shift in our organisational structure by expanding the role of Head of HR to Chief People & AI Officer. The idea is simple: if AI agents are doing work, they must be managed, governed and aligned just like any other organisational resource.

The Emergence of the Second Workforce

For most of the digital era, technology has helped humans work faster. Software augmented employees. Agentic AI changes this equation.Instead of merely assisting employees, AI increasingly performs work autonomously inside workflows. In compliance and screening technology, for example, AI systems can analyse data, verify information, identify anomalies and generate reports.

At Kinatico, technology — including AI — has already transformed how we onboard new customers. Processes that historically took months can now often be completed in hours. Key steps such as verification and document analysis can be performed by AI systems with human oversight, delivering both faster turnaround and higher accuracy than before.

This does not remove humans from the process. It changes their role. Humans increasingly focus on supervision, judgement and exceptions, while AI agents handle large volumes of repeatable work.

In practical terms, companies are beginning to operate with two workforces:

• Human employees

• Artificial agents embedded in workflows

Managing that combination is becoming a new leadership discipline.

What Are “Artificial Resources”?

Artificial Resources include the growing class of AI systems that perform operational work inside organisations. These may include:

• AI workflow agents

• automated compliance monitoring systems

• AI report generation tools

• screening and verification agents

• decision-support systems

• AI copilots embedded in software

The key shift is that these systems increasingly act as participants in workflows, rather than just tools used occasionally by employees.

They generate outputs, influence decisions and perform tasks that were historically handled by people.

Once that happens, they effectively become part of the workforce.

The Surprising Similarities Between Humans and AI Agents

One of the interesting discoveries organisations make when deploying AI agents is that managing them begins to resemble managing employees. Both produce work and require supervision. From a management perspective, this means AI cannot simply be left inside the IT department. If AI systems are performing operational work, they become part of the broader organisational system.

The Critical Differences

Despite these similarities, the differences between humans and AI agents are equally important.

Motivation - Human: Intrinsic and extrinsic // AI: None

Judgement - Human: Contextual // AI: Probabilistic

Fatigue - Human: Yes // AI: None

Scalability - Human: Limited // AI: Near-instant

Accountability - Human: Personal // AI: Organisational

Learning - Human: Experience and education // AI: Data

Risk Factors - Human: Politics, emotions, mental health // AI: Reward hacking

Humans bring contextual understanding, ethical judgement and creativity. AI agents bring scale, speed and consistency. The organisations that succeed will not try to choose between the two. They will orchestrate both.

Why HR and Technology Must Converge

Historically, organisations separated responsibilities:

• HR managed people

• IT managed technology

Agentic AI sits somewhere between those two worlds.

AI agents affect:

• workflows

• decision making

• employee productivity

• operational risk

As a result, leadership of these systems cannot sit purely inside technology teams. At Kinatico we recognised this by evolving the role of HR leadership into Chief People & AI Officer. The intention is to align all organisational resources — human and artificial — so that they work together effectively. It also recognises that AI governance, workforce design and operational processes are becoming increasingly interconnected.

The Dynamics of Human and AI Collaboration

Another interesting difference between humans and AI agents emerges in collaborative settings. AI agents can communicate and process information extremely efficiently. In a technical sense, multiple AI agents can effectively “participate” in discussions simultaneously, analysing inputs and generating responses in parallel. In other words, AI agents can conduct the equivalent of very efficient meetings.

However, they currently lack one important feature that human teams possess: diversity of perspective and personality. Human teams bring different backgrounds, experiences and cognitive styles to discussions. Those differences often improve decision making. AI systems today tend to operate with more uniform reasoning patterns, reflecting the structure of their training data and models. Over time, technological advances may introduce greater diversity into agentic systems. But for now, the combination of human perspective and AI analytical power remains a powerful pairing.

The Challenges Organisations Will Face

As AI agents become part of operational workflows, organisations will face several practical challenges.

1. The Responsibility Gap: When an AI system produces an incorrect output, who is responsible? The organisation must ensure there is always clear human accountability.

2. Shadow AI: Employees increasingly experiment with AI tools independently. Without governance, this can introduce data security, privacy and compliance risks.

3. Skill Gaps: Most managers have been trained to manage people. Very few have been trained to manage AI agents and AI-driven workflows.

4. Process Redesign: AI does not simply automate existing processes. It often fundamentally changes how work flows through the organisation.

5. Cultural Resistance: Employees may initially see AI as a threat rather than a collaborator. Leadership must actively communicate that the goal is augmentation, not replacement.

Practical Advice for Boards and CEOs

For leadership teams and boards, several practical lessons are emerging.

Treat AI agents as workforce components. If AI performs operational work, it must be governed accordingly.

Assign clear ownership. Someone must take responsibility for managing Artificial Resources.

Measure AI productivity. Track accuracy, output volume, escalation rates and cost per task.

Design human-AI collaboration. The most effective systems combine human judgement with AI speed.

Develop AI supervision skills. Managing machines that think will become a core management capability.

The New Management Discipline

The industrial era created Human Resources. The AI era will require Human and Artificial Resources. The organisations that succeed will not replace people with machines. They will design systems where humans and AI agents work together — combining judgement, creativity and experience with scale, speed and analytical power. For decades companies optimised their human workforce. The next decade will be about optimising human and artificial workforces together.