The Future of Substance Use Care Is AI-Native

A clinician finishes a 50-minute session. The member leaves. The clinician opens their laptop and begins the second session: 45 minutes of documentation. They reconstruct the conversation from memory, translate it into billing codes, fill templates designed for auditors, and hunt through tabs to cross-reference previous notes. Then they move to the next patient.

This happens six times a day. More time documenting than treating. It’s not an edge case. It’s the norm.

Show me the incentive and I’ll show you the outcome

Electronic Health Records (EHRs) were never built for care. They were built for billing. The systems designed in the 1990s now stand between clinicians and patients, optimized to capture every action, convert it into codes, and generate revenue. Clinical workflows became data-entry workflows – serving payers, not patients.

This design misalignment produces predictable distortions. Providers maximize billable sessions because income scales with time spent, not outcomes achieved. The financial incentive isn’t to solve the problem efficiently. It’s to extend the engagement. In that sense, the system isn’t broken, it’s working exactly as intended. The flaw lies in what it was designed to optimize.

The consequences are staggering. The U.S. spends roughly $50 billion each year on substance use disorder (SUD) treatment, yet reaches only about 10% of those in need. The remaining 90%, generate an estimated $135 billion in preventable downstream costs, from ER visits to comorbidity complications to inpatient care.

We’re spending more and helping fewer. The bottleneck isn’t money. It’s infrastructure built around the wrong objective function.

Innovation means reducing cost while expanding access

Pelago was founded on the belief that true innovation expands access to care while sharply reducing costs. By reinventing the way addiction care gets delivered through technology, Pelago’s digital clinic has reduced the average cost to treat someone with a SUD from $30,000 in traditional outpatient settings to just $3,000, delivering a 4.5:1 ROI to employers through reduced medical claims.

The foundation is a value-based care reimbursement model. Employers and health plans pay a fixed amount per member, not per session. The incentive shifts from billable hours to outcomes, making efficient care profitable, not just possible. That alignment enabled us to build Atlas, Pelago’s AI-native EHR designed from the ground up to maximize clinical impact per hour of clinician time. The platform has three components: context preparation, real-time guidance, and documentation automation. 

Before the call: smart triaging, full context

Atlas continuously analyzes clinical signals, engagement patterns, and contextual data to automatically surface members who may be at risk or in crisis. This smart triaging capability helps care teams prioritize outreach, escalate clinical support when needed, and ensure that the highest-risk members receive timely, personalized attention.

Ahead of each session, Atlas generates a clinical summary of the member’s history and recent interactions. The clinician opens the session with full context already assembled: previous concerns, medication changes, family dynamics, recent check-ins. No tab-switching, timeline reconstruction, or spending the first 10 minutes piecing together fragmented notes. The narrative is coherent before the conversation starts.

This matters more than it sounds. As a physician, I’ve seen firsthand how coming into a session with context sharpens the conversation. Clinicians ask better questions, pick up on subtle shifts in mood or behavior, and earn trust faster. Preparation creates precision.

During the call: evidence in real time

During a session, the care co-pilot surfaces evidence-based strategies personalized to the member in real time. When a member mentions sleep disruption, Atlas instantly retrieves trauma-informed techniques relevant to their treatment history. The clinician stays fully engaged in the conversation instead of mentally flipping through protocol manuals.

This transforms the balance between presence and rigor. Clinicians no longer have to choose between warmth and thoroughness. Atlas carries the guidelines, the clinician carries the connection, and together, they deliver better care.

After the call: documentation done

After the call, AI-assisted notes record, transcribe, and summarize the interaction. Documentation completes automatically. The clinician closes their laptop and transitions to the next patient. The 45-minute admin block vanishes.

The impact goes beyond incremental efficiency gains. By eliminating a bottleneck that consumed half the working day, Atlas fundamentally changes how clinicians spend their time.

How we’re building AI for substance use care

Atlas reflects Pelago’s approach to AI: purpose-built for substance use care. In substance use care, the line between helpful and harmful is often invisible to general-purpose systems. An off-the-shelf model trained on the open internet won’t understand the nuances of motivational interviewing or when a member’s statement requires immediate human intervention. 

Every AI capability at Pelago is grounded in evidence-based practices. The system knows its boundaries and hands off to human care when it reaches them, with full context intact. Member data is protected structurally, from storage to transmission to access. The goal isn’t to automate care but to amplify it by freeing clinicians to focus on connection while strengthening the care every member receives. 

Building for a new paradigm

Atlas represents a bet that the next generation of healthcare software won’t be built by bolting AI onto legacy platforms. The systems designed for fee-for-service billing, with their emphasis on CPT codes, encounter forms, and defensible documentation, carry too much embedded assumption about what matters. Vertically integrating specialty care, with AI as the foundation rather than the add-on, allows different design choices.

This matters beyond Pelago. Behavioral health sits at the intersection of two crises: surging need and shrinking capacity. We can’t solve that equation by asking clinicians to work harder within the old system. We need technology that genuinely multiplies clinical impact, not software that tracks the work of care while slowing down the work itself.

Atlas works because we control both the technology and the care delivery. The real test is whether employers and health plans are willing to address the misaligned incentives that still dominate most of healthcare. Software alone won’t fix incentive structures. But when the economic model rewards outcomes and the technology stack serves that goal, we get a glimpse of what’s possible: clinicians practicing at the top of their license, members receiving personalized support at scale, and systems learning their way toward better care.

The question isn’t whether AI belongs in behavioral health. It’s whether we’ll use it to optimize the old paradigm or build a new one.

Read more about Pelago Atlas in our Fall Product Update