Artificial intelligence (AI) continues to rapidly reshape the global pharmaceutical landscape, as companies look to embed it across research, development and commercialization. As the industry faces mounting pressure to improve efficiency, reduce costs, and deliver better patient outcomes, AI-driven technologies are becoming essential tools to maintain competitiveness and accelerate transformation across the pharmaceutical value chain, says GlobalData, a leading intelligence and productivity platform.

GlobalData’s latest report, “The State of the Biopharmaceutical Industry 2026,” reveals that AI is leading the technological transformation of the pharma industry with 74% of respondents identifying it as the most disruptive emerging technology.

Wafaa Hassan, Senior Strategic Intelligence Analyst at GlobalData, comments: “AI’s appeal to the pharmaceutical industry lies in its ability to accelerate processes like drug discovery, reduce R&D costs, and predict patient outcomes with unprecedented precision. By analyzing complex datasets at scale, AI can identify patterns and insights that otherwise may be disregarded.”

While AI stands out in impact, its effectiveness is closely tied to big data. AI and big data are poised to significantly optimize the entire pharmaceutical value chain with their combined capabilities. This powerful duo has the potential to enhance a wide variety of processes, ranging from target identification to end-user reach.

Data derived from numerous pharmaceutical processes can only add value if it is properly analyzed and produces actionable results. As a data-driven algorithm, AI requires high-quality data. The more data AI receives, the more accurate and efficient it can become.

One of the primary aims of AI in various industries, including pharmaceutical, is to cut costs and increase productivity. Although opinions varied, when the respondents were asked by what percentage they believed that AI-driven platforms could increase productivity in R&D efforts over the next 12 months, the most popular answers were 11–20% (27%) and 21–30% (25%). It reflects a positive outlook towards the technology and suggests willingness to embrace future AI developments.

Hassan concludes: “Pharmaceutical companies that successfully integrate AI with big data capabilities will be better positioned to unlock efficiencies across the entire value chain, from early-stage target identification to market access and post-launch optimization. As data volumes continues to grow, organizations that invest in scalable analytics platforms and data governance frameworks will gain a significant competitive advantage, enabling AI models to deliver more reliable, actionable and impactful insights. In 2026, it will be key to monitor how AI matures from pilots to more deployment and measurable impact.”