Why Giving Options Matters in Enterprise Healthcare AI Adoption

We’re at a fascinating time in healthcare. Over the past year, the buzz around AI has reached a fever pitch. It’s fair to say we hit peak hype earlier this year, with widespread talk of AI revolutionizing healthcare. But beyond clinician-facing use cases - like ambient scribes and clinical reference tools - we’ve yet to see mass adoption of patient-facing tools powered by AI, especially those delivered by healthcare stakeholders.

More broadly, across industries, we’re seeing similar challenges. As the MIT GenAI Divide report highlighted, around 95% of GenAI-native company pilots haven’t made it beyond the pilot stage. That’s a sobering statistic - and a reminder that scaling generative AI is no simple feat in any sector, let alone healthcare.

There’s been no shortage of explanations. The commonly cited barriers include lack of explainability, regulatory complexity, medico-legal ambiguity (like who carries liability, as we discussed here), and hallucination risks. But to me, the clearest way to frame the issue is this:

Healthcare is not a sandbox - yet we often ask it to behave like one.

It’s not a place for casual experimentation. Real lives and health outcomes are at stake, and as a result, there’s low tolerance for error.

How nymble navigates this reality

As a company that leverages generative AI, we’ve had to be clear-eyed about what this space demands.

First, our strategic focus. We’ve chosen to solve a specific, high-impact problem: helping people succeed in their treatment journey for metabolic disorders - namely, obesity and diabetes. Nearly half the global population is at risk of or living with these conditions. It’s a big lane, but a defined one. And our deep clinical expertise helps us stay grounded in evidence and nuance.

Second, our product philosophy. I’ve written before about how nymble is more than a chatbot - it’s a comprehensive, clinically-informed communication platform designed to help people build a new relationship with their treatment journey. We’ve created a new category of tools, built for long-term outcomes.

Why control matters

When it comes to enterprise adoption, especially in healthcare, control is critical. Procurement teams and AI governance committees don’t want to be forced into a black box - they want options, transparency, and the ability to make decisions that align with their risk profile. These teams are our partners. We don’t presume to know what’s best for their organization - we provide them with flexible options that give them control.

Our enterprise customers can choose:

• If Generative AI is leveraged, and how much they want to use

• What forms of GenAI are implemented (e.g., summarization vs. open-ended responses)

• Which domains are covered (e.g., diet and exercise only, excluding medication or diagnosis)

Some customers may prefer to use our platform without any generative AI at all. Others may selectively activate AI support in specific areas while retaining full editorial control elsewhere.

This flexibility helps us:

• Reduce barriers to adoption

• Fit into an organization’s current comfort level

• Offer a clear, low-risk path to scaling over time

And most importantly, it helps us build trust from the ground up.

In other words: we don’t just ask for trust - we design for it.

From how we approach the market, to how we build our product, to how we manage privacy and risk - trust is built into our operating model.

We believe AI will transform healthcare, but it’s going to take longer than the hype cycle suggests. Our deep conviction is that real progress will come from those who build trust, enable choice, and think long-term with the patient in mind.

That’s the nymble way.

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Learn more!

For organizations interested in learning more about nymble, reach out to us at info@nymble.health.

For individuals, check out this page and email us at enroll@nymble.health.