Growth in medical devices rarely arrives in a straight line. A new indication is approved, a distribution agreement lands, a hospital network standardizes on your product — and suddenly the operation that worked at last year’s volume is running on spreadsheets, overtime and goodwill.

The instinct is to hire. But for most growing medtech companies the real constraint isn’t headcount. It’s the number of decisions that have to be made quickly, accurately and with a complete audit trail. That is exactly where agentic AI earns its place.

What makes an agent different

Traditional automation follows a script. An AI agent works toward a goal: it gathers the information it needs, proposes an action, and either completes it within agreed limits or routes it to a person for approval. In a regulated industry, that last step matters most. The best agents don’t replace judgment — they prepare decisions so people can make them faster.

For companies running SAP Cloud ERP, agents built with SAP Business AI and extended on the Business Technology Platform can work directly with live transactional data rather than stale exports. That is the difference between a clever demo and a tool the quality team will actually trust.

Where to start: four agents with fast payback

The same four candidates rise to the top in almost every assessment we run. Each one targets a process that is high-volume, rules-heavy and painful to scale by hiring alone.

1. The demand sensing agent

Device demand is shaped by procedure schedules, consigned inventory at hospitals and tender cycles — signals that rarely show up in a monthly forecast. A demand sensing agent watches order patterns, field stock levels and pipeline updates, flags deviations from plan and suggests adjustments to planners before shortages or excess stock appear.

Where it pays off: fewer expedited shipments, lower safety stock and more confident conversations with sales.

2. The field inventory agent

Loaner kits and consigned stock are notoriously hard to track. An agent that reconciles usage reports, replenishment orders and lot information can spot missing or expiring items, trigger replenishment and prepare billing for implants used in surgery.

Where it pays off: faster revenue recognition, fewer write-offs and cleaner lot traceability.

3. The complaint intake agent

Every customer complaint has to be captured, assessed for reportability and linked to the right product, lot and investigation. An intake agent can read incoming emails and service notes, pre-fill complaint records, suggest a risk classification and highlight events that may need regulatory reporting — leaving the final call to a qualified reviewer.

Where it pays off: shorter intake times, more consistent records and less risk of missing a reporting deadline.

4. The supplier quality agent

Growing companies often add suppliers faster than they can monitor them. A supplier quality agent tracks certificates, audit findings, incoming inspection results and delivery performance, then alerts procurement and quality teams when a supplier’s risk profile changes.

Where it pays off: fewer surprises at receiving, smoother audits and a stronger negotiating position.

Getting the foundations right

Agents are only as good as the data and processes underneath them. Before deploying the first one, check three things:

  • A clean core. Agents that work against standard processes and consistent master data are far easier to validate and maintain than ones built around years of customization.
  • Clear guardrails. Define which actions an agent may complete on its own, which need approval and how every step is logged. In a validated environment this is part of the design, not an afterthought.
  • An owner for every agent. Someone in the business should be accountable for each agent’s performance, just as they would be for a member of their team.

Measuring success

Pick two or three metrics per agent before go-live and review them monthly. Cycle time, touchless rate, exception volume and time-to-decision are usually more telling than broad productivity claims. If an agent isn’t moving its numbers within a quarter, narrow its scope or retire it. A small portfolio of agents that work beats a long list that nobody uses.

The bottom line

The companies getting the most from agentic AI aren’t the ones with the biggest budgets. They’re the ones that start narrow, prove value in a single process and expand from there — the same discipline that makes a smaller first wave work for ERP.

Want to see these agents in action? Watch Session 1 of our webcast series, or contact us to talk about where agents could help your operation first.