Are AI Agents Worth the Hype?

By Light-it, in collaboration with Federico Ruiz, Founder & CEO @Puppeteer

My Journey with Puppeteer

Puppeteer is an AI company focused on one mission: improving healthcare. I’m not talking about run-of-the-mill chatbots—I mean AI agents that can genuinely relieve staff shortages and enhance patient care.

I’ve had a front-row seat to the real impact AI can make in clinics and hospitals ever since working at Puppeteer. Here’s what I’ve learned about using AI agents effectively, and why, despite the hype, I believe they’re worth it when done right.

Are AI Agents Worth the Hype?

Everyone’s talking about AI right now, and while the technology is exciting, what really matters is where it can be useful. AI agents aren’t just a new interface—they’re a new way to get things done. They can hold natural conversations, take action based on context, and connect directly with tools teams already use. But the real question is: where do they actually help?

We’re in the midst of a full-blown staffing crisis in healthcare. A study in the Annals of Family Medicine found that primary care doctors spend 5.9 hours of an 11.4-hour workday on EHR tasks over 50% of their time on admin work that doesn’t require a medical degree. Think about it: doctors and nurses are drowning in paperwork, scheduling nightmares, and endless follow-ups. When staff are overloaded, care quality suffers, patients wait longer, appointments get missed, and there’s less room for genuine doctor-patient interaction.

Some clinics slap on patient portals or automated phone menus as a Band-Aid, but we’ve all experienced the frustration of pressing “1 for billing.” It’s a purely transactional experience, and while it handles some simple needs, it doesn’t truly address the bigger problem. What if we had AI agents that could actually hold a conversation with patients, interpret their needs, and automate a ton of the routine tasks? That’s the vision we’re working towards.

Imagine a world where, instead of messing with a rigid menu system, patients have a natural phone call or text exchange with an AI agent that genuinely understands them. This AI could:

• Schedule (or reschedule) appointments in real time.

• Check in on symptoms and relay important details back to the medical staff.

• Remind patients about follow-ups or medication refills before it’s too late.

In my experience, when clinics adopt an AI agent that actually integrates with their workflows, everyone benefits. Staff get hours back in their day, and patients feel more supported because they’re getting timely reminders and real conversations, even if it’s with an AI.

Over the past few years, my team and I at Puppeteer have introduced AI agents across various healthcare settings, from bustling outpatient clinics to specialized practices. While the core principles haven’t changed, each deployment has taught us something new.

Here’s what I’ve learned, with the real-life examples that shaped those lessons:

1. Integrations

We support a wellness platform that passively monitors users’ stress levels, sleep patterns, and recovery metrics through a wearable device. Our AI agent is integrated directly with this data stream, allowing it to identify trends and deviations in real time.

If a user experiences multiple nights of poor sleep or shows signs of elevated stress throughout the day, the agent reaches out, via text or voice, depending on their preference—with personalized check-ins. It might suggest a breathing exercise, share sleep hygiene tips, or recommend scheduling a session with a health coach.

This kind of low-friction, real-time support has helped users better understand their own health data and stay engaged with wellness goals, without needing to interpret complex charts or dashboards.

2. Thoughtful Workflows

We recently partnered with a clinic specializing in sleep apnea and crafted a detailed reactivation workflow that leans on multiple conversational AI agents. Here’s how it worked:

• Initial Engagement Agent: The moment someone filled out a website form or was imported into the clinic’s database, this AI initiated contact. It aimed to schedule an intro call right away before the lead went cold.

• Declined Agent: If a patient initially declined an appointment, a second AI agent followed up after a specified time checking if they’d reconsider.

• No Answer Agent: For those who had booked a call but didn’t pick up, a specialized AI agent reached out with personalized messages to reschedule, acknowledging that “life happens.”

• Interested Agent: Finally, patients who finished the first call but hadn’t started actual treatment were periodically nudged with tailored info on sleep apnea and potential treatment benefits.

Before this, the clinic staff spent countless hours on phone tag and repetitive follow-ups. After deploying these four “specialized” AI agents, the team saw a significant lift in actual treatment initiation. Patients felt they were being guided step-by-step, while staff could focus more on clinical care rather than cold-calling.

Results & Impact

• Leads Generated: 107

• Leads Engaged: 75 (70.1% engagement rate)

• Consultations Scheduled: 53 (49.5% booking rate from generated leads; 70.7% conversion rate from engaged leads)

3. Omnichannel Communication

Puppeteer supports phone, SMS, web embedding, and widget integrations—essentially whichever channel a patient prefers. One sleep clinic discovered that older patients preferred phone calls around midday, while younger patients wanted text messages they could respond to between Zoom calls. Another clinic embedded our AI widget directly into their website, letting visitors quickly book appointments without ever picking up the phone. By offering these varied touchpoints, both clinics saw higher response rates and fewer missed appointments.

4. Continuous Improvement (Kaizen)

At Puppeteer, we run weekly or bi-weekly check-ins with each client to review performance metrics and refine scripts or triggers. Internally, our entire team also meets regularly to discuss improvement opportunities,from how we structure our AI’s conversation flow to how we handle edge cases. While the specifics vary by clinic, this process keeps our technology aligned with real-world challenges and ensures that every new version of the AI is better than the last.

Common Concerns (and My Two Cents)

1. Safety & Privacy
   Healthcare data is sacred. We operate under strict compliance standards to ensure patient safety and confidentiality. All interactions are recorded and monitored, so clinicians remain fully in the loop.
   

2. Accuracy
   Not every use case is ripe for AI. I always recommend starting with a small pilot (maybe appointment scheduling or post-discharge check-ins) before going all-in. By testing in a controlled environment, you can fine-tune your agent’s accuracy and prove its worth.
   

3. Patient Experience
   Let’s be honest: nobody wants a lifeless script for a critical medical question. The AI agent should handle routine tasks, but real humans need to step in for emotional or complex medical issues. In other words, AI is a supplement, not a replacement, for genuine human care.

Tips for Staying Ahead

If you’re a healthcare leader, founder, or just someone curious about applying AI in clinical settings, here are a few tips I’ve picked up:

1. Pilot Programs First
   Pick a specific workflow and run a pilot. Have clear success metrics: maybe you want to cut no-shows by 20% or decrease admin workload by a certain number of hours per week. Measure, iterate, then scale.
   

2. Embrace Continuous Feedback
   Talk to your frontline staff and patients regularly. Ask them what’s working and what’s not. Tweak your AI accordingly. It’s the small, ongoing improvements that make the difference.
   

3. Stay Informed
   I’m a big fan of checking sources like MIT Technology Review for the latest on AI. We also share our own experiences on the Puppeteer blog if you want a behind-the-scenes look at what’s working.
   

4. Look for Tangible Impact
   Always ask potential AI vendors for real numbers. Look for metrics on reduced no-shows, faster response times, or better patient satisfaction scores. This is about outcomes, not just a fancy tech demo.

Why It Matters and What’s Next

When done right, AI agents can genuinely ease the load on healthcare workers and improve patient care. I’ve seen it firsthand. The key is to integrate AI in ways that address real problems, like missed appointments and administrative overload—rather than just tacking on yet another app or phone menu.

Soo… Are AI agents worth the hype? Absolutely, if you pilot carefully, integrate thoughtfully, and keep improving over time. For me, the promise of AI is the potential to free doctors and nurses to do what they do best: heal, comfort, and connect with their patients. That’s the endgame. And I believe it’s within reach.

If you’re curious or want to know more, reach out. Let’s talk real-world examples, data, and practical steps. The future of healthcare can be brighter—and I’m convinced AI agents can help get us there.