Artificial Intelligence: Ruthlessly target bottlenecks

Q. What are the biggest mistakes HME leaders make when implementing AI, and how can they avoid them? 

A. AI is no longer a future-state concept in the HME space—it’s here, and it’s redefining how enterprise operations scale. But as many early adopters have discovered, AI alone doesn’t deliver ROI. Success depends on strategic implementation, cross-functional alignment and clear ownership. Here’s what we’ve seen go wrong—and how to avoid it. 

Measuring the wrong things 

Many enterprise teams focus on technical metrics like precision or accuracy. But those don’t always translate into operational value. The real ROI comes from time saved, manual work avoided and throughput increased. If your AI reduces error but barely impacts workload, it’s solving the wrong problem. 

Over-engineering instead of prioritizing workflow 

Instead of fine-tuning AI models for edge-case accuracy, the focus should be on automating high-friction, repetitive tasks that slow teams down like routing exceptions and triaging incoming faxes. Even an 80% solution here can unlock real efficiency at scale. 

Skipping business metrics 

AI success isn't just an engineering win—it’s a business outcome. Without clear operational KPIs (e.g., time-to-completion, touches per intake, staff hours saved), enterprise teams can lose momentum. Aligning on these metrics early ensures cross-functional buy-in and faster impact. 

Not empowering tech leadership 

In large organizations, the difference between stalled pilots and scaled success often comes down to ownership. If your tech leadership isn’t empowered to drive AI initiatives, the implementation will struggle. AI can’t just be a pet project in one department—it must be a cross-functional priority, led by a team with the authority to make systemic changes and integrate across tools, data and workflows. 

The bottom line is, AI isn’t just about the tech—it’s about orchestration. The most successful HME implementations empower technical leaders, align around business goals and ruthlessly target workflow bottlenecks. That’s how AI becomes a true force multiplier. 

For more information, contact Teresa Power, director of marketing at Synthpop, at teresa@synthpop.ai.