Agentic AI is having its moment. Boards are asking about it, vendors are rushing to build it into their technology, and leaders are eager to see what it can do. The potential is undeniable. AI agents can reason, decide and act across workflows. They can handle exceptions and edge cases that would stump traditional automation. But Agentic AI isn’t a default choice for every process.
At Dispatch Integration, we see Agentic AI as an evolution of automation—not a wholesale replacement. It builds on the solid foundations of integration and automations, and it delivers its best results when applied selectively, to the right problems, with the right infrastructure in place.
The Difference Between Automation and AI Agents
Integrations move data between systems. Automations apply business logic to reduce manual work. Orchestrations coordinate multi-step, multi-system processes so they happen in the right sequence.
Agentic AI adds something different. AI Agents bring goal-driven, context-aware reasoning. Instead of following rigid if-then rules, agents evaluate the situation, choose an approach and take independent action. In the right scenarios, that means removing human intervention entirely from a workflow.
Identifying The Best Use Cases for AI Agents
Not every process needs an AI agent—but the right process can see transformative gains. The strongest candidates are those where complexity, variability and interdependencies make rules-based automation too rigid or costly to maintain. In these scenarios, an AI Agent’s ability to reason, adapt and act autonomously delivers clear business value.
Agentic AI delivers the most impact when:
- Edge cases drive workload – Processes where every scenario can’t be pre-coded.
- Context changes outcomes – Tasks that require reading multiple data sources in real time before deciding.
- Decisions span multiple systems – Workflows with dependencies that stretch across the enterprise.
- Volume amplifies friction – High-volume processes where manual exceptions create costly bottlenecks.
A good example is intelligent onboarding. An agent could evaluate a new hire’s role, location and department, then assemble the exact mix of system access, equipment provisioning and approvals needed while handling variations automatically.
Knowing When Rules-Based Automations Are A Better Fit
For cases when AI isn’t the right choice, our team at Dispatch follows a few core principles to determine when rules-based automation will deliver the best results. These guidelines help ensure processes are handled with maximum efficiency, accuracy, and stability without introducing unnecessary complexity or risk.
Implement automation over agents when:
- Accuracy must be absolute – Use deterministic automation for processes where mistakes aren’t acceptable.
- The steps never change – If every path can be defined in advance, rules-based automation is more efficient.
- Data can’t be trusted – Poor quality or incomplete data undermines agent decisions.
- Governance isn’t ready – Without privacy, compliance and audit controls, autonomous actions create risk.
- There’s no ROI – Deploying agents without a clear business case turns innovation into a distraction.
By applying these principles, organizations can keep automation strategies grounded in business reality—making it easier to see where agents truly add value and where proven rules-based approaches should remain in place.
Don’t Let AI Jump the Line
Agentic AI is not a shortcut past the work of building strong business systems. Successful agents rely on the same foundation as every other automation:
- Integrations to keep systems aligned.
- Automations to eliminate repetitive work.
- Orchestrations to control process flow.
Without these in place, agents make decisions and take actions in an unstable environment, which is a fast path to failure.
The path to meaningful Agentic adoption means building on what’s already working and inserting agents where they deliver unique value. Agentic AI is a powerful addition to the enterprise automation toolbox—but it’s not a universal solution. By pairing strong automation fundamentals with clear criteria for where agents truly add value, organizations can move past the hype and into sustainable results.
To explore more about where Agentic AI fits in your business systems, watch our on-demand webinar on How To Add Agentic AI Into Your Business Systems.
Cameron Hay is the CEO of Dispatch Integration, a data integration and workflow automation company with clients in Canada, US, Europe and Australia. He has over 30 years of leadership experience in various technology-oriented industries.
