Why Building an AI Agent Without an SOP Creates Operational Risk 

Building a Generative Pre-trained Transformer (GPT) or an AI Agent without a Standard Operating Procedure (SOP) exposes organisations to significant operational risks. When AI usage is undocumented, it creates dependent workflows on specific individuals, leading to interruptions when staff leave or change roles. Establishing documented processes safeguards continuity and enhances accountability. 

Key takeaways

• Undocumented GPTs result in invisible workflows that lack ownership.

• Dependency on individual knowledge diminishes organisational resilience.

• Establishing SOPs enhances operational clarity and accountability.

• Defined inputs, ownership, and quality assurance are essential for effective AI integration.

• Small teams especially need thorough documentation to maintain operational integrity.

The Rise of the Shadow AI Process

In many organisations, the integration of AI tools like GPTs and AI Agents are often rushed and incomplete. When these technologies are implemented without proper documentation or Standard Operating Procedures (SOPs), shadow processes arise, obscuring important workflows. Consequently, critical tasks become reliant on specific individuals’ knowledge and abilities, presenting a tipping point for operational risk.

What Happens When It Isn’t Documented

The failure to document AI workflows leads to several predictable problems, marked by inconsistent outputs and a lack of clarity regarding approval authority. If only one person is accountable for operating the tool, their departure creates a vacuum, often resulting in confusion or complete abandonment of the tool. This reliance on undocumented processes halts productivity and undermines compliance efforts.

Example: Volunteer Turnover + Undocumented AI Use

Consider a scenario in a non-profit (NFP) organisation where a volunteer responsible for operating the GPT or AI Agent leaves unexpectedly. Without any documentation outlining the usage protocols or workflows, the succeeding volunteers may struggle with key tasks, leading to diminished productivity and disruption in operations. This exemplifies how a lack of SOPs can hinder organisational functionality, particularly in volunteer-heavy environments.

Embedding AI into an SOP

To mitigate these risks, organisations must embed AI like GPT within structured SOPs that clarify how to operate, manage, and review its use. Here are essential components:

Defined Inputs

Documenting the specific inputs necessary for effective operation is paramount. A clear framework ensures that all operators understand what information is required to generate consistent outputs.

Ownership (RACI)

Establish accountability through a RACI (Responsible, Accountable, Consulted, Informed) matrix that clearly defines ownership. This framework helps prevent knowledge siloing and promotes shared responsibility among team members.

QA Review

Quality assurance stages should be integrated into the workflow to ensure that outputs meet the organisation’s standards. Regular reviews mitigate errors and reinforce compliance.

Escalation and Override

It is crucial to define escalation paths and human override requirements within the SOP. This preparedness ensures that when issues arise, there is a clear route for resolution that does not rely solely on individual knowledge.

Why Small Teams Need Documentation More, Not Less

While larger organisations might manage with informal processes, small teams particularly benefit from comprehensive documentation. With fewer resources, any knowledge gaps can lead to significant operational disruptions. Documented workflows help maintain consistent practices, safeguard knowledge transfer, and meet governance expectations, particularly in funded environments.

Conclusion: Tools Must Sit Inside Systems

AI tools cannot operate in isolation; they must be part of an organised structure that allows for clarity and flexibility. By embedding GPTs or AI Agents within documented SOPs, organisations can minimise operational risks and ensure consistent, reliable outputs that advance their mission.

Frequently Asked Questions

1. Do I need an SOP for AI?

• Yes, an SOP is crucial to ensure clear guidelines and to minimise reliance on individual knowledge.

1. How do I document AI workflows?

• Documenting AI workflows involves outlining workflows, defining inputs, establishing ownership structures, and including escalation paths.

1. Is AI creating operational risk?

• Without proper documentation, AI can lead to significant operational risks, including knowledge silos and disrupted workflows.

1. What are the benefits of SOPs?

• SOPs provide clarity, promote consistent outputs, and enhance accountability in organisational processes.

1. Why is documentation critical for small teams?

• Small teams are often more vulnerable to operational disruptions, so effective documentation ensures continuity and resilience against knowledge loss.

For support in developing effective SOPs tailored to your AI initiatives, contact us to discuss practical implementations. 

Related guides

• Why Organisations Fail With Large Language Models

• Defining AI Role Before Deployment

• AI Governance for Small Organisations (coming soon)

Related DIY

• Start with structure 

Sources

American Society for Quality (n.d.) Quality management principles.

European Commission (2019) Ethics guidelines for trustworthy AI.

Gartner (n.d.) What is Shadow IT?

ISACA (2019) COBIT 2019 framework: Governance and management objectives.

International Organization for Standardization (ISO) (2015) ISO 9001:2015 Quality management systems — Requirements.

National Institute of Standards and Technology (2023) Artificial Intelligence Risk Management Framework (AI RMF 1.0).

National Institute of Standards and Technology (2010) Contingency planning guide for federal information systems (SP 800-34 Rev.1).

Organisation for Economic Co-operation and Development (OECD) (2019) OECD principles on artificial intelligence.

Project Management Institute (PMI) (2021) A guide to the project management body of knowledge (PMBOK® Guide).

Evidence base
This article draws on recognised quality management, governance, and AI risk frameworks including ISO 9001, NIST AI RMF, OECD AI Principles, and COBIT governance standards.