From waitlists to wellness: How AI is closing the autism care gap and making access more equitable

Executive Summary

The Cognoa and League partnership addresses the US crisis in Autism Spectrum Disorder (ASD) care by using data-driven tools and AI to enable faster, more equitable evaluations and reduce long-term healthcare costs.

Key takeaways:

• Diagnostic delays average 20 months from initial parental concern.
• Each month of diagnostic delay adds an estimated $331 in excess healthcare spending.
• Data-driven tools and AI reduce the diagnostic timeline from nearly two years to a matter of months.
• Up to 37% of children may no longer meet diagnostic criteria after timely intervention.
• Early diagnosis lowers the total cost of care and improves member retention for payers.

The Autism access crisis

In the United States, one in every 31 children is diagnosed with Autism Spectrum Disorder (ASD). In some regions, that rate rises to one in 26. Yet for too many families, the path to diagnosis remains long, confusing, and unequal.

There are fewer than 750 pediatric neurodevelopmental specialists nationwide. At leading centers, waitlists can exceed 8,000 children, and the average time from a parent’s first concern to formal diagnosis can stretch to 2 years.

That delay comes at a cost. Each month without diagnosis adds an estimated $331 in excess healthcare spend, as developmental and behavioral challenges compound. More importantly, it costs children valuable time in which early intervention can change their lifelong trajectory.

But access isn’t the only issue — inequity is built into the system. For decades, autism research and diagnostic frameworks focused primarily on boys, leading to the under-identification of girls, who often “mask” symptoms differently. Black, Hispanic, Indigenous, and low-income families are diagnosed years later than their peers, and rural communities face geographic and financial barriers that make timely care nearly impossible.

Behind these statistics are real families — waiting, worrying, and navigating systems not built for them. And yet, we know autism can be reliably identified as early as 18 months, and that up to 37 percent of children who receive timely intervention no longer meet diagnostic criteria later in life. The problem isn’t our knowledge. It’s our infrastructure.

How Cognoa has been impacting outcomes

The work that Cognoa has been doing is simple but not easy: providing every child — regardless of geography, gender, or background — with the opportunity for the best possible developmental outcome. That means addressing one of healthcare’s most persistent challenges: the long, uneven path to an autism diagnosis.

At Cognoa, we’re focusing on empowering primary care providers and expanding equitable access to timely developmental evaluations. By rethinking traditional workflows and applying data-driven rigor to the diagnostic process, we’ve shown that children can be evaluated and supported months — even years — earlier than before.

While efficiency is the most obvious benefit at the outset, the big win is changing outcomes. That looks like:

• Families getting answers sooner, reducing anxiety and unlocking earlier intervention.
• Clinicians gaining objective, structured insights to guide care decisions with confidence.
• Health systems benefitting from a scalable model that reaches more children with fewer bottlenecks.
  

Equity is built into the foundation of this work. By designing tools that are available in multiple languages, accessible on common devices, and validated across diverse populations — including girls, Black, Hispanic, and Indigenous children — we’re reducing the disparities that have defined autism care for decades.

What once took nearly two years can now be achieved in a matter of months, leading to faster intervention, improved family wellbeing, and long-term cost savings across the care continuum.

Why early, equitable autism diagnosis matters to payers

For healthcare payers, the benefits of early diagnosis extend far beyond compassion. They represent measurable, long-term value.

1. Better Long-Term Outcomes
Early identification and intervention help children build communication and social skills, setting them on a path toward lifelong independence.

2. Lower Total Cost of Care
Preventing or mitigating co-occurring conditions such as anxiety, depression, and learning challenges reduces utilization and costs over time.

3. Improved Member Experience and Retention
Families who receive timely, coordinated care report higher satisfaction and continuity with their health plan — particularly when navigating developmental or chronic conditions.

4. More Appropriate Resource Allocation
Data-driven insights and journeys, powered by AI tools, help clinicians match children to the right therapies, ensuring precision in both care and cost.

Early diagnosis is one of the most effective forms of preventive medicine — it turns reactive systems into proactive ones, improving outcomes for families and creating sustainable value for payers.

How AI-enabled care platforms can extend the impact

Early diagnosis represents a breakthrough, but families still need guidance, structure, and sustained support to move from answers to action. This is where AI-enabled care platforms can play a transformative role—by helping families navigate complex healthcare journeys in ways that are timely, accessible, and equitable.

The potential lies in how AI can interpret signals across a family’s experience: their concerns, their digital behavior, and their interactions with the healthcare system. When applied thoughtfully, AI can anticipate when a parent is most likely to need assistance, surface relevant resources or next steps, and reduce the burden of navigating a system that can feel overwhelming even to healthcare professionals themselves. 

These AI-supported systems can also help close longstanding gaps in equity. By identifying developmental concerns earlier, prompting action in the everyday environments where families already are, and supporting primary care providers—not just specialists—AI helps extend the reach of early identification into communities that have historically been missed: rural families, low-income households, and populations whose developmental differences often go unrecognized.

As more organizations collaborate across the healthcare ecosystem, the opportunities grow. AI can help align what families report at home, what clinicians observe, and what the healthcare system knows, turning early detection into a connected, continuous path of support instead of a fragmented process.

League’s platform enables this kind of coordination at scale. In partnering with Cognoa, we can improve and speed up autism diagnoses. League helps identify families who need an evaluation and then guides them through offering Cognoa’s CanvasDx FDA-authorized digital assessment for a faster and more accurate diagnosis.

By using AI to recognize engagement patterns, surface risk signals, and connect families to clinicians and services, it operationalizes many of the capabilities needed to make these early-identification breakthroughs truly accessible. In a broader network of payers and innovators, this approach helps ensure that families across large, diverse populations receive timely, personalized guidance—moving early diagnosis from possibility to reality.

Smarter systems, healthier futures

We already have the knowledge to identify developmental concerns early. What has been missing is a system that makes it possible for families to benefit from that knowledge in time and at scale. By rethinking how we evaluate children, support clinicians, and guide families through the complexity of care, we can narrow one of the most persistent gaps in pediatric health.

The work underway across organizations like Cognoa and League shows that meaningful change comes from using the tools and technology we have today to shorten delays, reduce disparities, and give families clearer, earlier answers. When we do that consistently, outcomes improve for children and the entire system that supports them.

The opportunity now is to build on this momentum and create a healthcare environment where timely developmental evaluation is a standard expectation, not an exception. If we commit to that goal, we can ensure that more children receive the right help at the right moment, setting the stage for healthier futures. burden is real. It’s not just frustrating—it can have real world impacts on health. 

Frequently asked questions

Who is the author of this article?

Dr. Sharief Taraman is the CEO of Cognoa and is dual board-certified in Neurology with special qualifications in Child Neurology from the American Board of Psychiatry and Neurology and Clinical Informatics from the American Board of Preventive Medicine.

What is Cognoa?

Cognoa is a pediatric behavioral health company that develops digital diagnostics and therapeutics. Its lead product, Canvas Dx, is the first FDA-authorized diagnostic device for early autism diagnosis.

What is League?

League is a leading healthcare Consumer Experience (CX) platform, powered by AI. It is used by major payers to build personalized digital experiences for their members.

How long does an autism diagnosis typically take in the current healthcare system?

The average time from a parent’s initial concern to a formal Autism Spectrum Disorder (ASD) diagnosis is currently around 20 months, due primarily to specialist shortages.

How does the Cognoa and League partnership reduce the time to diagnosis?

By leveraging data-driven tools, the partnership empowers primary care providers to conduct developmental evaluations, effectively reducing the diagnostic timeline from nearly two years to a matter of months.

What is the financial impact of delayed autism diagnosis?

Delayed diagnosis is costly; each month a child goes without a diagnosis is estimated to add $331 in excess healthcare spending.

What is the benefit of early intervention for children with ASD?

Early and timely intervention is highly effective, with studies suggesting that up to 37% of children who receive support early in life may no longer meet diagnostic criteria later on.