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Danny examines how biopharma companies are approaching patient services, partner changes, and artificial intelligence in 2027. He argues that connected data and purpose-built technology can improve operational efficiency, accelerate access to therapy, and enhance the patient experience.
To learn more, download Courier Health's whitepaper: Patient Experience Innovation in 2027: Lessons from the 3rd Annual Patient Innovators Summit.
Read on for Danny's insights.
Biopharma’s AI Fork in the Road
By Danny Sigurdson, Founder and CEO, Courier Health
At our 3rd annual Patient Innovators Summit, I told commercial leaders that biopharma has reached a fork in the road. Every manufacturer will pick a path in 2027, whether they decide to or not.
The ground under biopharma is fracturing
Two forces are speeding things up. The first is upheaval in the partner ecosystem. Hub and services providers are consolidating, and some of the largest are exiting the market altogether. For manufacturers, the result is patients to migrate, workflows to rebuild, and data to recover from systems they never controlled.
The second is AI innovation. Every commercial leader is under pressure to automate and surface insights, yesterday, but AI is only as good as the data and workflows underneath it. A recent Harris Poll found that 72% of AI decision-makers trace failed initiatives back to a poor data foundation.
Our own research is blunter: nearly 60% of biopharma companies call their data fragmented or inactionable, and fewer than 10% have the data maturity to use AI meaningfully. Owning your first-party data and the workflows around it is what gives AI the context to deliver.
Together, these forces put biopharma commercial teams at a fork in the road. Down one path, the status quo remains and every patient start gets harder. Down the other, purpose-built technology and increased ownership make patient access smoother and more predictable.
Future A: Manual work that scales linearly until it breaks
Picture Monday morning on most Field Reimbursement and Patient Services teams. A hub report lands in one inbox, a specialty pharmacy feed in another, a partner summary in a third. Someone re-keys the same patient record into three systems. Someone rebuilds the weekly report by hand, again. A formulary change hits, a territory realigns, leadership wants numbers by Thursday. By the time the picture is stitched together, it's stale, and the patient who needed a call didn't get one.
That's treading water.
Now add pressure to do more with less and a top-down AI mandate. The workload grows, headcount doesn't, and the manual work doesn't disappear; it multiplies. Handoffs break during vendor transitions. AI pilots stall on generic use cases. Teams report activity because they can't prove impact on outcomes.
On this path, you aren't standing still, you're sinking, while manufacturers who chose differently are pulling ahead.
Future B: Leverage AI to focus on moments that matter
On the other path, the manufacturer owns a connected data foundation. Patient records don't live with a vendor. Purpose-built AI works from full context, flagging at-risk patients before they drop off, clearing the busywork and routing the right task to a person or agent to assist or approve. Teams stop maintaining infrastructure and get back to their competency of moving patients and providers to the next milestone. Value gets measured where it matters, in time to therapy and conversion rates.
This isn’t a pipe dream, it’s a reality that’s possible today, and it’s one that leading manufacturers are actively investing in.
Getting there takes an honest look at where your team spends its time versus what it's built to do. Manufacturers excel at developing breakthrough therapies, bringing them to market, and building relationships across the ecosystem. Building software for frontline access teams isn't on that list, nor should it be.
Choose your future, own what’s next
The next few quarters decide which path each manufacturer takes, and here the research is unforgiving. MIT’s State of AI in Business 2025 found that 95% of enterprise generative AI pilots fail to deliver value. The failures follow a pattern: generic tools that dazzle in a demo, then stall on real workflows, data and compliance. The 5% that succeed embed AI in high-value workflows, use systems that retain context and learn over time, and work with specialized partners instead of building alone, an approach MIT found succeeds about twice as often.
What separates AI that delivers is domain depth. The right partner for this moment is:
- Purpose-built for Field Access and Patient Services, not a generic copilot
- Structured so manufacturers own their data and a unified view of the patient journey, which is the context AI needs
- AI-native at every layer, not bolted on
- Accountable for integration, security and compliance
Standing still is a choice, too, it just ensures Future A for you.
At this year’s Patient Innovators Summit, commercial leaders from more than 75 companies representing 35 million patients with previously unmet needs shared their perspectives on where biopharma goes next. Read the full takeaways in the 2026 Summit whitepaper.
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