The risks of AI: autonomy with accountability.
Process Automation with AI introduces new forms of autonomy inside the enterprise. In this edition, we explore the risks, the misconceptions, and the controls required so digital agents operate safely, responsibly, and transparently.
AI Process Automation (APA) represents a step change in how work happens. Digital agents can interpret context, initiate actions, and escalate when needed. This autonomy unlocks huge value, but it also introduces new categories of risk that organisations must understand and manage.
The goal is not to limit autonomy. It is to create safe autonomy supported by the right design, governance, and monitoring.
Let’s look at the key APA risk areas and how leading enterprises manage them.
1. Governance and Control
The risk:
Agents acting without clear boundaries or oversight.
What good looks like:
Defined decision limits
Escalation rules that are transparent and enforced
Regular review and audit cycles
In healthcare, for example, medication renewal agents can propose renewals but final approval sits with a clinician. In financial services, trade validation agents can block or flag but not release transactions above a threshold.
2. Model Drift and Outcome Degradation
The risk:
Agents that learn from feedback without control mechanisms can gradually move away from intended behaviour.
What good looks like:
Continuous model monitoring
Retraining windows with human approval
Clear triggers for rollback or pause
Learning is a strength, but only if supervised.
3. Bias and Fairness
The risk:
Agents making decisions that inadvertently disadvantage certain customers or patients.
What good looks like:
Fairness testing prior to deployment
Dataset scrutiny
Human review for high-impact outcomes
Financial institutions already do this for credit scoring. APA extends this discipline across operational decisioning.
4. Security and Access
The risk:
Agents accessing systems without the same controls applied to human users.
What good looks like:
Role-based access
Identity management for agents
Activity logs and behavioural monitoring
Digital agents need identities, permissions, and guardrails just like employees.
5. Human Trust
The risk:
Lack of trust leads to poor adoption, override behaviour, or manual workarounds.
What good looks like:
Clear visibility into agent decisions
Simple override mechanisms
Communication and training throughout rollout
Trust is a capability. It is built through visibility and control.
Conclusion
APA is powerful because agents can act with intent and judgement. The organisations that succeed are those that design accountable autonomy from day one: guardrails, visibility, supervisory control, and structured improvement loops.
Risk is not a reason to slow down. It is a reason to scale safely and confidently.