How Will Emerging AI Impact the Pharmacy Benefit Manager Space?

Artificial intelligence (AI) has risen as the key technology driving society forward through its innovation, touching almost all humans, industries, and populations. With its use increasing in real time across pharmacy, AI’s eventual introduction in the pharmacy benefits space was inevitable. The technology has quickly surpassed an investigational stage and into general use across the daily lives of millions. Experts are beginning to look into AI’s use among pharmacy benefit managers (PBMs) and how that will impact pharmacy operations.

According to many, as PBMs continue to revamp their practices through transparency, efficiency, cost savings, and patient outcomes in today’s environment, AI will only catapult change in the pharmacy benefits space even further.

“As PBMs try to gain the respect and trust of employers, patients, physicians, and pharmacists, they will need to use AI to ‘do the right thing,’” Perry Cohen, PharmD, FAMCP, CEO of The Pharmacy Group (TPG) Family of Companies, told Drug Topics^®. “The newer PBMs are making this happen and the older PBMs are trying to reinvent themselves.”

READ MORE: Navigating Pharmacy’s AI Transformation and the Future of Patient Care

Legacy Inertia and the Structural Threat to the Status Quo

The pharmacy benefits industry currently stands at a turning point where approximately 70% of the market still operates on legacy systems that are decades old. These traditional models, often dominated by the “big 3” gatekeepers—CVS Caremark, OptumRx, and Express Scripts—are increasingly viewed as a bottleneck in US drug distribution.^1,2

Industry analysts suggest that modern AI is specifically designed to compress high-volume, rules-driven processes like rebate negotiation, formulary design, and claims adjudication, which directly threatens the legacy margin pools of established PBMs. For instance, Cigna’s Express Scripts is noted as being particularly exposed to this disruption due to a heavy reliance on rebate economics that AI-driven transparency tools are now reshaping.²

This shift is characterized by a legacy inertia, where industry giants struggle to run sophisticated AI tools on top of infrastructure built in the 1980s and 1990s. Unlike modern cloud-based platforms that provide real-time data and advanced analytics, these older systems often rely on batch processing that prevents immediate insights, resulting in reports that arrive weeks or months after a claim is processed.^1,3

Put simply, experts argue that you cannot “put a Tesla battery into a horse carriage,” suggesting that the cultural and physical infrastructure of a PBM must be built for modern technology to truly derive benefit. Consequently, legacy PBMs may find themselves at a disadvantage as AI-native newcomers dismantle traditional profit margins through more efficient and transparent operations.^2,3

The Rise of Transparent and Tech-Native PBM Models

Even before AI became a primary focus, movement toward modern, transparent PBM alternatives was already underway. Employers and plan sponsors, frustrated by a lack of financial visibility and rising costs, are increasingly bypassing traditional models in favor of partners offering fiduciary alignment and 100% pass-through pricing.⁴

This structural correction of a broken model is accelerating as businesses take control of their pharmacy spend rather than waiting for federal legislative reform. AI is expected to be the engine that powers these modern PBMs, allowing them to move beyond the black box of insurance jargon to provide clear and actionable insights.^3,4

These tech-native PBMs leverage cloud-based flexibility to eliminate the operational delays common in the industry. For example, although traditional PBMs may require up to 90 days to implement a formulary update, modern platforms can process these changes in as little as an hour, ensuring immediate adaptability to market shifts.¹

This speed and accuracy extend to contracting, where generative AI can sift through dense contract language to identify leverage points and optimize pricing clauses instantaneously. By arming negotiators with real-time market trends, AI enables more productive conversations with drug manufacturers, theoretically driving down costs for both plans and patients.⁵

Impact on Pharmacy Sustainability and Reimbursement Reform

For the community pharmacist, the emergence of AI in PBM operations arrives during a period of severe instability. Independent pharmacy margins hit a 10-year low in 2022, leading to widespread closures and the expansion of pharmacy deserts.⁴

Experts warn that without significant reimbursement reform, such as a shift toward cost-plus models that decouple medication costs from dispensing fees, these closures will only intensify. The role of AI in this context is complex. Although it can optimize pricing in real-time, it also risks being used by legacy players to disguise bad actions with reform lip service, potentially maintaining incentives to take spreads from medication pricing through newer hidden fees.

However, there is hope that AI-driven transparency can facilitate a move toward more sustainable reimbursement models. Modern PBMs are utilizing AI to manage high-cost, provider-administered drugs more effectively, shifting them from opaque medical benefit plans to more manageable pharmacy benefits.⁴

Furthermore, the anticipated arrival of more affordable biosimilars and generics in 2026, driven by low-list-price disruption and streamlined FDA guidance, may redefine drug access. AI helps identify these lower-cost alternatives proactively, which can improve patient adherence and health outcomes when cost barriers are removed.^1,4

“AI will make PBMs more efficient at performing their administrative functions,” continued Cohen. “It will also enable PBMs to track the patient journey with their use of pharmaceuticals and pharmacies. This will result in improved patient outcomes and lower total cost of care.”

READ MORE: Payer Preference Shifts Toward Unbundled, Transparent PBM Models

Streamlining Clinical Workflows and Patient Adherence

Beyond the financial mechanics, AI is expected to significantly impact the clinical and administrative workflows that pharmacies navigate daily. Automated prior authorizations are already being deployed to expedite approvals by analyzing clinical guidelines and patient history.^2,6

This real-time adjudication allows for a more seamless experience at the pharmacy counter.

Additionally, AI-powered “chain of thought reasoning” can provide patients with step-by-step explanations for claim denials, transforming a frustrating denied status into an understandable roadmap for next steps.³

Patient adherence is another area where AI is poised to make significant gains. By identifying patterns in prescription data, AI can detect medication nonadherence or emerging health conditions early, allowing for personalized intervention. These tools can provide personalized reminders and insights, leading to fewer hospital visits and a generally healthier society.^1,5,6

By handling these mundane, data-heavy tasks, AI is intended to act as a “superpower” for human experts rather than a replacement. Keeping the human in the loop ensures that though AI handles information sourcing, the clinical decisions and empathetic patient interactions remain the responsibility of a pharmacist.³

The Privacy and Liability Risks of the Algorithmic Apothecary

Despite the rewards of AI integration being substantial, the technology introduces significant data privacy, regulatory, and contractual risks. One of the primary concerns for employers and pharmacies alike is the opaque nature of AI decision-making.⁷

There is a pressing need for transparency regarding how algorithms determine drug coverage and formulary recommendations to prevent biased or purely cost-driven decisions that could harm patient care. Because AI relies on massive datasets, the use of protected health information to train these models is a sensitive issue, necessitating strict adherence to the Health Insurance Portability and Accountability Act and other privacy regulations to prevent breaches or misuse.^6,7

Furthermore, the legal landscape is still catching up to the rapid deployment of these technologies. Employers are being cautioned to negotiate administrative service agreements (ASAs) carefully to ensure they do not assume liability for a PBM’s AI errors. Experts suggest that ASAs should explicitly prohibit the use of AI in final adjudicative decision-making where an improper denial could lead to legal action against the plan sponsor.⁷

Shifting the risk to the PBM is seen as a safeguard. Regular audits and independent reviews of AI-generated decisions are recommended to ensure that innovation does not come at the expense of ethical standards or patient safety.^6,7

A Dynamic and Self-Adjusting Future

Looking ahead to 2026 and beyond, the pharmacy benefits space is moving toward a model of dynamic, self-adjusting plans. The accelerating pace of drug discovery means that rigid, single-year enrollment cycles are no longer sufficient to manage a modern employee population.⁴

Future plans will likely leverage AI and real-time data to optimize for new drugs and price adjustments throughout the year, rather than just on an annual basis. This shift favors nimble, data-driven systems that can make optimal decisions in a rapidly changing market.

The impact of AI on the pharmacy benefits space will depend on how effectively the industry can pair technological innovation with human expertise. Although AI offers unprecedented efficiency and cost-saving potential, the core of pharmacy remains a human-centric profession.¹

As the industry evolves, the most successful organizations will be those that use these powerful tools to enhance transparency, improve patient experiences, and actively build a more sustainable health care ecosystem. The “intelligence revolution” among PBMs is not just about automation. It is also about realigning the entire system to prioritize patient health and fiduciary responsibility in a way that was previously impossible with legacy technology.^1,4

“AI will not save a weak pharmacy benefits strategy. It will expose it. If the culture is not built around accountability and transparency, better tools just help people make the same mistakes faster,” Tyrone Squires, CPBS, founder and managing director at TransparentRx, told Drug Topics in an exclusive interview. “The real promise of AI is not replacing people. It is helping fiduciary advisors, employers, and pharmacists catch pricing problems, utilization trends, and clinical risks before they become expensive mistakes.”

READ MORE: Technology and Data Resource Center

REFERENCES

1. How modern technology is shaping the future of pharmacy benefit management. Fierce Healthcare. February 24, 2025. Accessed June 17, 2026. https://www.fiercehealthcare.com/health-tech/how-modern-technology-shaping-future-pharmacy-benefit-management

2. Thoelcke T. AI is coming for pharmacy benefit managers: potential winners and losers. Yahoo! Finance. May 19, 2026. Accessed June 17, 2026. https://finance.yahoo.com/sectors/healthcare/articles/ai-coming-pharmacy-benefit-managers-132513165.html

3. The engine of healthcare: How AI is powering modern PBMs. SmithRx. February 24, 2026. Accessed June 17, 2026. https://smithrx.com/blog/how-ai-is-powering-modern-pbms

4. Pharmacy benefits shakeup: 2026 trends and predictions. SmithRx. January 1, 2026. Accessed June 17, 2026. https://smithrx.com/blog/2026-pharmacy-benefits-trends-and-predictions

5. How AI could change the future of PBM contracting. Pharmacy Healthcare Solutions LLC. January 29, 2026. Accessed June 17, 2026. https://phslrx.com/how-ai-could-change-the-future-of-pbm-contracting/

6. Squires T. AI in pharmacy benefits: a game-changer or a risky gamble for employers? LinkedIn. PBM Insider. March 26, 2025. Accessed June 17, 2026. https://www.linkedin.com/pulse/ai-pharmacy-benefits-game-changer-risky-gamble-tyrone-squires-cpbs-lpl9c/

7. How your PBM’s AI use can impact your health plan: key rewards, risks, and practical tips for employers. Fisher & Phillips LLP. March 19, 2026. Accessed June 17, 2026. https://www.fisherphillips.com/en/insights/insights/how-your-pbms-ai-use-can-impact-your-health-plan