In an industry where speed and precision can directly affect patient outcomes, pharma companies are under pressure to maximize the value of their data. Generative AI (GenAI) is emerging as a critical tool—not just for accelerating processes, but for making insights more transparent, accessible and actionable across teams.

Driving ROI Through Efficiency

Traditionally, getting answers from data meant waiting. Teams without technical expertise often relied on a centralized data science or analytics function to answer simple questions. Without GenAI, it takes approximately 1-2 weeks to receive an answer from a data science team. With GenAI tools, however, life sciences teams can turn around the same question in 10–15 minutes—a massive efficiency gain.

This shift improves ROI in two ways. First, business users gain immediate insights, cutting decision-making delays. Second, data scientists are freed from routine requests to focus on advanced modeling and complex analyses. In short, companies get faster results while maximizing the impact of their most specialized talent for solving complex problems.

Lowering Barriers and Democratizing Data

Data democratization has long been a challenge in pharma. Historically, only technically skilled teams could extract and interpret insights from large, complex datasets. GenAI helps change that dynamic.

Since the barrier has always been programming knowledge or clinical expertise, if you have a tool that gets rid of those barriers while still allowing for transparency and traceability, that’s incredibly powerful.

With conversational interfaces and built-in validation, GenAI empowers non-technical users to engage directly with data. That means the expensive datasets pharma companies invest in aren’t just used by a small group of specialists—they become valuable assets across the organization, driving higher ROI on data purchases.

Strategy First: Applying GenAI with Purpose

As with any emerging technology, success with GenAI depends on strategy. Companies risk chasing technology for its own sake rather than focusing on business problems. The best advice is to start with the business challenge you’re trying to solve. Look for a product or platform that applies GenAI in a way that actually addresses your needs.

In pharma, the highest ROI often comes from applying GenAI to ease bottlenecks and improve efficiency, not necessarily to replace complex, specialized work. The key is aligning the tool with real challenges.

Avoiding Common Pitfalls

One of the biggest mistakes companies make is treating GenAI as a “check the box” exercise rather than integrating it into a broader data strategy. Buying into generic AI hype without evaluating how solutions address actual business needs can waste time, money and trust.

Equally important is ensuring transparency and reproducibility. Pharma companies need to know not just the answer GenAI provides, but also how it got there—what datasets, algorithms, or codes were used. Solutions should be designed with this transparency in mind, enabling confidence, traceability and collaboration across teams.

Think of GenAI as a vehicle to get you to the right place. By nature, it answers like a human and humans make mistakes. But with transparency and reproducibility built in, you can verify and share results, which is critical in life sciences.

The Bottom Line: Partnering for ROI and Impact

When applied thoughtfully, GenAI helps pharma companies:

• Accelerate insights by cutting turnaround times from weeks to minutes.
• Increase ROI on data investments by making datasets accessible beyond technical teams.
• Empower talent by freeing up data scientists to focus on high-value, complex analysis.
• Foster trust and collaboration through transparency, reproducibility and shareability.

But success depends on working with the right partners: ones who deliver tools and platforms designed for the industry’s unique needs, not just generic AI hype.

As pharma organizations continue to explore GenAI, the ones that see the greatest returns will be those that start with a clear business challenge, adopt tools that democratize data access and prioritize transparency at every step.

Fully integrated with Panalgo’s IHD platform, Ella AI makes it easier for life sciences teams to understand patient journeys, refine study designs and accelerate evidence generation. Want to find out more? Contact us.