Share

Citizen Development in the Era of AI Agents: A Balanced Approach

In the era of AI agents, are we stepping back into the realm of Citizen Development?
This concept, which, when done right as an organizational effort, helped to democratize task automation through no-code or low-code platforms, gained traction in Robotic Process Automation (RPA) circles a few years ago. However, when poorly managed, it also introduced significant challenges, such as creating disjointed automation efforts and operational headaches for IT departments. Today, as AI agents become more advanced, it’s crucial to strike a balance—leveraging the domain expertise of business users while maintaining centralized governance and oversight.

Empowering Business Users, Maintaining Control

The Power of Natural Language
One of the key enablers of ‘citizen development’ in the context of AI agents is the use of natural language to define goals, tasks, and workflows. The “runbook” concept exemplifies this—a plain English document defining a goal and outlining an agent’s actions. Business users, equipped with a deep understanding of their business context, can directly shape agent behavior. This represents a paradigm shift from traditional automation approaches, where technical expertise was required to translate complex, process-specific business needs into code.

  • Direct Mapping of Runbook to Agent Behavior: Unlike traditional process documentation, runbooks provide a one-to-one mapping between written instructions and agent actions. This approach reduces the disconnect between planning and implementation, making automation logic more transparent and easier to maintain.

 

Collaboration and Iteration
AI agent development thrives on collaboration. Business users actively participate in runbook creation, iteratively refining agent logic and connections to company systems with technical teams. This empowers them to take ownership of the automation process while ensuring the final implementation aligns with organizational goals.
Centralized Governance and Oversight
While empowering business users is essential, maintaining centralized governance is equally important. Oversight ensures that AI agents adhere to organizational standards, security protocols, and regulatory requirements. A dedicated team or center of excellence can oversee agent deployment, testing, and maintenance, preventing the uncontrolled proliferation of agents.

  • Transparency and Auditability: For all agent-related tasks, transparency and auditability are non-negotiable. The runbook provides a clear record of an agent’s instructions, while reasoning logs offer insights into decision-making processes. Detailed audit trails ensure accountability and facilitate compliance with regulatory standards.

 

Shifting Roles, Evolving Skillsets

From Citizen Developers to AI Operators
The rise of AI agents signals a shift from citizen development to more specialized roles. Rather than every business user becoming an independent agent developer, the focus is on upskilling automation professionals and business users to work effectively with AI agents through different roles.

 

The Emergence of New Roles
New roles are emerging to support AI agent ecosystems:

  • AI Operators / Program Management: Oversee the deployment and operation of AI agents.
  • AI Agent Developers: Developers create production-grade actions that connect agents to enterprise applications and data sources.
  • Business Process Owners / Analysts: Leverage their domain knowledge to contribute to agent development.

This role-based approach creates clear divisions of responsibility, ensuring accountability while enabling effective collaboration.

 

Upskilling Existing Teams
The emphasis is on equipping current teams with the necessary skills to manage AI agents. By enhancing the expertise of automation professionals and business users, organizations can maximize the benefits of AI while minimizing risks.

 

agentacademy.ai, developed by Digital Workforce, is a comprehensive online learning platform dedicated to training professionals in the critical roles required for Enterprise AI Agent success. Designed for business users, developers, automation professionals, and IT experts, the academy offers structured, hands-on courses and certifications tailored to practical learning needs.

From identifying the most suitable applications for AI agents to building agents, managing AI initiatives, and scaling enterprise-grade solutions, agentacademy.ai equips teams with the skills to drive innovation, enhance operations, and achieve sustainable success in AI adoption.

With role-based courses covering AI Agent Development, Analysis, Program Management, and more, agentacademy.ai bridges the knowledge gap to empower organizations for enterprise-wide AI transformation.

Share

More resources

AI Literacy

Digital Workforce Launches agentacademy.ai to Accelerate Enterprise AI Literacy and Upskilling

Press Release – 23 January, 2025 10:00 AM EET Digital Workforce, a global leader in business automation solutions, ...
Data Security with AI Agents

Addressing Data Security Concerns with AI Agents

Data security is a critical concern for organizations exploring the use of AI agents, especially in enterprise environments. ...
AI Assistants Vs AI Agents

About Human-Agent interaction

There are many scenarios where AI agents and human users can collaborate. However, building a robust automation solution ...