Now in its seventh year, the State of Revenue Report – sponsored by Model N and independently conducted by Dimensional Research – seeks to uncover trends and executive perceptions toward revenue management within the high-tech and life sciences industries. This year’s research highlights a strong focus from pharma and medtech business leaders on leveraging technology innovation to improve revenue management operations, with 91% reporting they believe their investment in this area has had a measurable impact.
AI and automation are taking center stage in these plans:
- 87% of companies are focused on automating revenue management operations
- 40% of pharma leaders cite process automation and efficiency as a top priority in 2025
- 99% of leaders believe AI will add value in managing and optimizing revenue and 4 out of 10 believe it will add value to their deal analytics and insights processes
- 58% of leaders and nearly one-third of companies plan to use GenAI and advanced analytics to enable revenue management
Three key avenues for AI and automation in revenue optimization
-
Automation of existing machine-based tasks
The ability to take tasks that are currently machine-driven with human support and developing additional machine-based features to reduce human intervention increases efficiency and productivity. Automating repetitive and time-consuming tasks such as data retrieval, data integration, and payment workflow steps frees up resources to focus on more strategic and value-added activities.
-
Machine translation and understanding to take on new tasks
GenAI, a subset of AI, uses large language models and generative adversarial networks to understand and generate unstructured data including text, images, video, and code. This technology enables machines to better interpret and learn from the context surrounding tasks, removing the need for humans to turn unstructured data into structured data. In revenue management operations, machine translation is a useful tool for developing in-app guides, parsing and generating contracts, and turning contract terms and conditions into data that can be passed to optimization algorithms to enhance ROI.
-
Discovery of previously unknown patterns to inform decision-making
Learning networks and pattern recognition models can understand the interactions between huge volumes of data points and define the likelihood of events and causality. These complex algorithms use real-time data feeds to determine what the likely outcome will be, supporting the smarter generation of utilization trends; risk and waste probability on inbound claims; and projected sales, rebates, and payments.
Learn more
In the webinar, “Leveraging AI and Automation for Revenue Optimization in Life Sciences,” we dive deeper into these topics and explore how Model N customers are applying AI and automation to optimize various business applications in pharma and medtech. Watch the webinar to learn how you can take steps today to start leveraging this technology innovation, and don’t forget to download your copy of the 2025 State of Revenue Report.
Want even more insight into AI and automation?
Join us May 28–30 in Austin, Texas, for Rainmaker, the industry’s premier revenue management conference. You’ll hear from Model N experts and industry leaders – including Ujjwal Ratan, AI, ML, and Data Science Leader for Healthcare and Life Sciences at Amazon Web Services (AWS) – about all the exciting ways AI is transforming business operations and boosting revenue in dynamic, complex markets.
