AI's Impact On Healthcare: Why It's Becoming A Top Driver of Rising Costs
For years, artificial intelligence promised employers faster diagnoses and lighter paperwork. New data shows the technology is reshaping billing in ways that are pushing premiums higher.
Artificial intelligence (AI) in healthcare has long been pitched to employers as a cost-saving tool, one that could speed up diagnoses, sharpen triage, and cut down on paperwork. Recent data tells a more complicated story. According to PwC's annual medical cost trend report, health plans expect commercial healthcare costs to climb 9% in 2027, the steepest single-year increase in 17 years. Providers' growing use of AI-enabled billing and coding tools ranks among the top drivers behind that jump.
This article looks at how AI and healthcare costs have become closely linked, and what plan sponsors can do to prepare their budgets, vendor evaluations, and negotiations for what comes next.
The Cost Driver Hiding In Plain Sight
AI's presence in care delivery tends to get attention for its clinical uses: diagnostic algorithms, imaging analysis, and virtual care tools. Those applications are visible and easy to picture improving outcomes. The use case actually moving the needle on cost right now is far less glamorous: administrative automation.
AI scribes and coding assistants that listen to or read clinical visits, then draft notes, suggest diagnosis codes, and flag billable complexity, have quietly become one of the most consequential AI applications in healthcare. The investment behind this shift is substantial. UnitedHealth Group, the nation's largest health insurer, is putting $1.5 billion into AI initiatives this year, with much of that spending aimed at administrative functions such as prior authorization, pharmacy benefit approvals, and claims handling rather than clinical algorithms.
These tools have spread quickly because they solve a real problem. Clinicians spend enormous amounts of time on documentation, and AI can handle much of it faster and more thoroughly than a person can. That thoroughness is exactly what makes these tools financially significant. When AI captures every detail a clinician mentions during a visit, providers can legitimately code that visit as more complex and bill accordingly, even when the treatment itself hasn't changed.
How AI Became A Top Cost Driver
Nearly 70% of health plans surveyed by PwC rank AI-driven documentation and coding tools among their top three cost inflators for next year, and about one in five call AI the single biggest driver. The issue isn't that more people are receiving more care. It's that claims are being coded as more complex and paid at higher rates per claim. A few forces are reinforcing that pattern.
Providers are under financial pressure. Rising costs and cuts to public health programs give hospitals a strong incentive to capture every dollar they're legitimately owed, and AI makes doing so consistently across every visit far easier.
The payment system rewards volume and complexity, not results. Providers are paid based on how many services they deliver and how complex those services are coded, not on patient outcomes. AI is good at maximizing both, which drives spending up even when care itself hasn't changed.
Billing rules weren't built for AI. Most payment systems assume a human pace of work. AI scales more cheaply and handles tasks no billing code ever anticipated. Until payment policy catches up, that gap will likely keep pushing costs higher without a clear improvement in outcomes.
Will AI & Healthcare Costs Come Down?
There's reason to expect improvement over time. Administrative work makes up a large share of total health spending, so automating it could eventually reduce overhead and provider burnout, savings that could translate into lower costs. Many experts also expect today's focus on AI for billing and paperwork to fade as the technology matures, with more value shifting toward tools that catch health problems early and keep people healthier, since that's ultimately cheaper than treating serious illness later.
The catch is that these gains tend to make the entire insurance industry more efficient rather than giving any single health plan a lasting edge over competitors. This is more likely to unfold as a slow, industrywide shift than a quick fix employers can count on next year.
What Employers Can Do Now
For plan sponsors, AI-driven coding intensity deserves a seat at the table in next year's budget conversations, alongside familiar drivers like hospital labor costs, prescription drug spending, and behavioral health utilization.
Push for visibility into your own claims data. Ask your health plan or third-party administrator how coding patterns, not just headline trend numbers, are shifting in your specific population.
Ask about the direction of payment models. Find out whether your carriers and provider networks are moving toward models that reward outcomes rather than volume, since that shift directly affects how AI-driven documentation gets used.
Evaluate vendor claims against evidence. Don't assume every AI-branded health solution automatically saves money. Vet these tools based on their track record before adopting them in your plan design.
AI's impact on healthcare costs is still unfolding, and the right response depends on your plan design, your population, and your carrier relationships. Contact The Siekmann Company today to talk through how these trends could affect your benefits budget next year.
Frequently Asked Questions
Is AI increasing healthcare costs for employers?
Yes. PwC's 2027 medical cost trend report identifies AI-enabled documentation and coding tools as a top-three cost inflator for nearly 70% of surveyed health plans, contributing to a projected 9% rise in commercial healthcare costs.
Why does AI documentation raise the cost of a claim?
AI scribes capture more clinical detail than a human typically would during a visit. That added detail often supports coding a visit as more complex, which increases the reimbursable amount even when the treatment provided hasn't changed.
Will AI eventually lower healthcare costs?
Many experts expect that outcome long term, as automation reduces administrative overhead and AI shifts toward early detection and prevention. Most agree it will take time, and possibly changes to how care is paid for, before those gains outweigh today's added costs.
