Accelerate Clinical Trials with AI-Enhanced Financial Management

Financial management is the connective tissue of clinical trials, and strong financial stewardship has become even more critical as trials have grown in global reach, cost and complexity. Yet meaningful improvements can be difficult to implement because work remains highly complex and spread across systems that rarely speak to each other.

For sponsors, CROs and sites, the pain points are similar. Data silos limit visibility into financial activities, whereas manual processes slow payments, increase the potential for mistakes, and create frustration with time-consuming tasks.

Artificial intelligence (AI) can help by automating processes, bridging data gaps and reducing friction while providing real-time visibility into trial finances. As the clinical research ecosystem becomes more digitally connected, embedding AI is easier than ever, making the promise of streamlined, transparent financial management a reality.

AI’s potential

AI enhances clinical trial financial management not by replacing human expertise, but through enhancing how teams work. It can automate repetitive tasks, reduce mistakes and rework, and improve the completeness of financial data.

This can accelerate workflows and help prevent them from becoming a bottleneck during clinical trials. Some of the opportunities that AI presents exist today.

Others will emerge as financial management activities continue to become more digitalized. Three areas in which AI can add significant value include:

1. Automating document ingestion

One clinical trial can require sponsors or service partners to process hundreds of clinical trial agreements (CTAs) and enter their data into a payment system. Optical character recognition (OCR) technology helps accelerate this work, but traditional OCR has limitations.

It can read characters on a page, but it can’t reliably interpret complex data sets or contextual relationships. As a result, CTA processing remains highly manual.

AI changes this. It can do more than recognize text—it can interpret data points and identify which ones are relevant.

Regardless of whether a CTA is stored in a contracting system, PDF, or email, AI can ingest it, extract key unstructured information spread throughout the document and render it into a more structured format. This can unleash new efficiencies and ease staffing demands for sponsors or their partners.

Consider a scenario in which a full-time specialist manually enters six CTAs per day. By using AI, a specialist can validate exponentially more.

Now, instead of doing repetitive manual tasks such as keying in data, specialists can focus their attention on higher-value needs, such as addressing exceptions.

2. Budgeting and forecasting intelligence

Sponsors already use actual budget data and industry benchmarks to help formulate budgets. But they typically can’t put this data in a broader operational context, such as how certain assumptions could cause downstream delays.

For example, setting a budget at 80% of a benchmark could lengthen negotiations with sites. The time lost to this increased back-and-forth could then offset the financial savings the sponsor hopes to realize with its proposed budget.

In the near future, AI may be able to make these correlations so sponsors can understand trade-offs between cost, speed and operational risk when creating budgets. AI also has the potential to be prescriptive, recommending specific negotiation paths or contract adjustments to balance those tradeoffs.

AI could also soon be used to monitor and analyze payment data to more accurately forecast future payments. This could help sponsors anticipate when large payment events are likely to occur and identify potential financial bottlenecks before they happen.

3. Exception identification and reconciliation

AI capabilities for identifying and resolving exceptions are rapidly advancing, and the opportunity to apply them more widely in clinical trial finance is clear. For starters, AI could facilitate contract compliance during invoice review.

It could flag invoice and payment deviations from CTA-defined budget terms, prompting immediate adjustments. AI also could be used to detect anomalies that occur with payments or in payment processes.

It could alert a CRO or sponsor, for instance, if an invoice or payment is a duplicate. The advancements can shift detection from post-mortem audits to real-time monitoring, reducing false positives and catching nuanced anomalies missed by static rules.

Invoice reconciliation is another opportunity. AI could compare site invoices against EDC-reported visits and prior payments, which could help exceptions be flagged, reviewed, and addressed to reduce payment delays and disputes.

From fragmented systems to actionable insights

AI alone won’t solve the challenges created by siloed data and manual workflows in clinical trial financial management. Its impact will be realized when it’s paired with other advancements.

In particular, as disparate financial management systems are integrated into a single platform to unify data and eliminate repetitive tasks, AI can layer on top of this foundation to create even more efficiency and enable more data-driven decision making.

With unified systems enhanced by AI-driven intelligence, organizations can reduce delays, improve visibility and accelerate decisions—ultimately empowering clinical trials to move faster and operate with greater clarity and confidence. Through this technology evolution, financial management will pose fewer constraints on clinical trials and create more opportunities to empower and accelerate them.

About the Authors

Rajesh Patel, Senior Director, Product Management, Clinical Trial Financial Suite, IQVIA, is a seasoned product leader with over two decades of experience driving innovation, strategy, and customer-centric solutions in the technology sector. As Senior Director of Product Management, he leads the product vision and execution of the technology strategy for financial management in clinical trials—an area critical to operational efficiency and compliance in life sciences.

Rajesh has a proven track record of launching and scaling successful product lines, fostering strong customer relationships, and building high-performing teams. He is deeply passionate about leveraging customer insights to shape product strategy, ensuring long-term value creation and measurable business impact.

Zahiah (Zee Zee) Gueddar, Senior Director, Commercial Strategy, Clinical Trial Financial Suite, IQVIA, leverages over 20 years of diverse industry expertise encompassing delivery, finance, operational effectiveness, and the commercial sector. Zee Zee offers invaluable insight into the challenges encountered by sponsors, CROs, sites and patients. In her role leading IQVIA’s Financial Technology offerings, she serves as an innovative partner for clients seeking transformative outcomes and growth opportunities. Known as a strategic thinker and problem solver, Zee Zee is responsible for driving growth and differentiation, product go-to market & ensuring innovative and competitive offerings. Zee Zee is based in Southern California and is a graduate of San Diego State University.