More than 115 million American adults have prediabetes. Eight in ten of them have no idea. That statistic sits at the center of a new partnership between Abbott and Google Health, announced August 11, 2026, and it explains why two very different companies think they belong in business together.

The deal connects Abbott’s Lingo continuous glucose monitor, an over-the-counter biosensor designed for non-diabetic adults, with Google’s AI-powered Health app and its subscription-based Health Coach. The idea is straightforward: glucose data from Lingo will appear alongside other health metrics inside the Google Health app, and Google’s Health Coach will use that combined picture to generate personalized recommendations around nutrition, activity, sleep, and recovery.

What the integration actually looks like

Lingo already gives users a real-time view of how meals, exercise, and stress move their blood glucose. What’s new here is context. Seeing glucose trends in isolation tells you something. Seeing them next to sleep duration, step count, and heart rate data tells you considerably more. Google’s Health Coach, which runs on Gemini, will draw on that fuller dataset to offer guidance that’s specific to each user’s patterns rather than generic lifestyle advice.

The integration is expected to roll out inside the Google Health app later in 2026. Health Coach requires a Google Health Premium subscription, an internet connection, and compatible hardware. Abbott says users can sign up at hellolingo.com to get early access updates.

A large real-world study runs alongside it

The commercial partnership is only part of the story. Abbott and Google also plan to run what they describe as one of the largest real-world studies of its kind, using aggregated Lingo data to examine relationships between glucose patterns and everyday behaviors. That research is intended to inform future AI-driven guidance and give both companies a richer evidence base to build on. Details on study design and enrollment have not yet been released, but the ambition is notable. Consumer CGM has generated enormous amounts of real-world data; extracting clinically meaningful signal from it at scale remains an open challenge.

Why non-diabetic CGM is getting serious attention

Lingo is not a medical device in the diagnostic sense. It is explicitly not intended to diagnose diabetes or any other condition, and Abbott is careful to say results vary between individuals. But the clinical rationale for monitoring glucose in metabolic-risk populations is grounded in solid evidence. Glucose dysregulation precedes a Type 2 diabetes diagnosis by years, and research links poor metabolic health to cardiovascular disease and certain cancers.

The consumer CGM category has been building quietly for several years, with companies like Levels and Supersapiens staking out territory before Abbott brought Lingo to retail through Walmart, Walgreens, Amazon, and Publix. What changes with a Google partnership is distribution reach and the depth of AI-driven interpretation. Still, the field will need outcome data, not just engagement metrics, to demonstrate that continuous glucose monitoring in healthy or pre-diabetic populations leads to durable behavior change and measurable health improvement.

What clinicians should watch for

For clinicians, this partnership raises practical questions worth tracking:

• Will users bring Lingo trend reports into primary care visits, and how should those conversations be structured?
• Does AI coaching produce behavior change that holds beyond 90 days?
• What does the real-world study protocol look like, and will data be published in peer-reviewed journals?
• How will Google Health handle data governance for a dataset that sits at the intersection of consumer tech and sensitive health information?

None of those questions have answers yet. But the scale of this collaboration, and the prediabetes burden it is targeting, means the answers will matter well beyond the two companies involved.