Artificial Intelligence Agents Altering the Business Landscape through Operations Reform
In today's fast-paced business environment, the integration of AI agents is revolutionising various sectors, promising increased efficiency and streamlined workflows. This article will delve into the key aspects of implementing AI agents, their benefits, and potential pitfalls.
Firstly, it's crucial to understand that policy as code should be treated like application code. Changes should be reviewed, merged, and tracked, ensuring transparency and accountability. For high-value financial actions, irreversible changes, or sensitive data access, human approval is required. However, for routine steps, relying on sampling and anomaly alerts is more efficient.
When it comes to measuring the effectiveness of AI agents, it's recommended to ship a pilot with clear metrics, such as cycle time, first contact resolution, deflection rate, and user satisfaction. Measuring the before state is important to unlock buy-in, budget, and momentum. On the other hand, automating a broken process will only result in the mess being moved faster, so it's essential to clean the workflow first, remove redundant steps, align ownership, and document policy before automation.
One of the key operational metrics to consider is the cost per transaction, which includes labor and compute costs per unit of work. As AI agents become more widespread, teams will spend less time on status and updates and more time on decisions that require judgment.
Another operational metric is the deflection rate, which is the share of inbound work resolved by agents. The focus will shift to cross-functional orchestration, where agents coordinate end-to-end journeys like order to cash or incident to resolution.
Quality and risk metrics, such as accuracy and audit completeness, are also vital. Accuracy is the share of agent actions accepted without revision, while audit completeness is actions with traceable rationale and evidence. As AI agents become more widespread, audits will get easier because every action has a record.
However, there are potential pitfalls to be aware of. Teams sometimes launch agents without a baseline, making it difficult to prove value. Shadow integrations, or untracked connectors, can cause surprises during audits, so it's important to register every integration, define data flows, and add monitoring for visibility. Underestimating change management can lead to resistance and low adoption, so it's important to communicate early, invite feedback, and provide easy ways to correct or improve agent behaviour.
The mix of work will change, with teams focusing on decisions that require judgment, and customers will feel the difference because responses will be timely and consistent. Documentation will improve because agents rely on clear policies. Revenue lift, which is wins tied to faster cycles or higher conversion, is another financial metric to consider.
Companies like Wolters Kluwer are already leveraging AI agents in the legal operations sector, integrating AI assistants in software for law firms and notaries to automate tasks such as document review and contract drafting, significantly improving workflow efficiency. AI agents have proven effective especially in legal, cybersecurity, finance, procurement, and human resources sectors, supporting functions like threat detection, financial control, procurement, HR development, and adaptive supply chain management.
To get started with AI agents, pick one process with measurable pain, long handle time, or error-prone steps, write the policy in plain language, including thresholds and exceptions, integrate with systems of record, not shadow spreadsheets, launch to a small audience, gather feedback daily, and iterate. Publish results, including cycle time, accuracy, and user sentiment, template the pattern and repeat in the next team.
In conclusion, the implementation of AI agents offers numerous benefits, from improved efficiency to increased accuracy and reduced costs. However, it's essential to approach this transition with a clear understanding of the potential pitfalls and a robust change management strategy. With the right approach, businesses can unlock significant improvements in their operations and customer experiences.
