There’s a lot of talk about AI agents, but for an SME or mid-market enterprise, the real question is not “do they exist?” It’s “do they actually deliver in production?” Based on the field feedback highlighted by Softblues, the answer is finally yes in three very practical areas: support ticket triage, extraction from business documents such as invoices and contracts, and regulatory monitoring. The common thread? Narrowly defined tasks, clear tools, and a human in the loop for anything that could become expensive if it goes off course.
The SME Opportunity
The first gain is time. An AI support agent can read incoming requests, detect urgency, enrich the customer record, and route the ticket to the right place. The result: fewer unnecessary back-and-forth exchanges and faster responses. For a small team, that can translate into several hours saved every week.
The second highly profitable use case is document extraction. Reading inconsistent PDFs, pulling out amounts, due dates, or key clauses, then pushing that data into the ERP or accounting system is exactly the kind of work teams hate doing manually. In this case, the agent does not replace the business expertise: it removes repetitive data entry and reduces errors.
The third use case, often underestimated, is regulatory monitoring. An agent can track updates, summarize changes, and prepare a clear briefing for leadership. For a business owner, that means less risk of missing a rule that affects billing, compliance, or contracts.
The Caution
The classic trap is trying to build a “magic” agent that does everything. In practice, the projects that make it to production are the ones that stay focused: one ticket type, one document workflow, one monitoring scope. The broader the use case, the faster complexity explodes.
Another sensitive point is data quality. An agent connected to a messy CRM, a shaky document repository, or vague business rules will mostly generate noise. And if you give it too much access, it can send the wrong message, alter critical data, or trigger an irreversible action. In short: more autonomy, yes; more blindness, no.
The Compliance Angle
These agents often process personal data, and sometimes financial or contractual data. That means they need to be documented in the processing register, limited to the minimum data required, governed by subcontractor controls, and backed by human oversight for sensitive decisions. The same logic applies to Switzerland’s nLPD and, in the EU, to the transparency and oversight expectations associated with the AI Act. In plain terms: AI can assist, but it should not decide alone when the impact is material.
Conclusion & How Cohesium Can Help
The message for leaders is simple: AI agents are now mature enough to generate ROI, provided you target the right processes and put strong controls in place. Instead of improvising, Cohesium AI can audit your support, invoicing, contract, or compliance workflows, identify the use cases that are truly automatable, and design a scoped, measurable AI agent that is ready for production with the right guardrails. Let’s discuss a custom integration or a strategic audit.