AI Set to Transform Pharma: Drug Development Could Speed Up and Boost Profits by 10%, Says Bernstein
Artificial intelligence is rapidly reshaping pharmaceutical research, with analysts predicting faster drug development timelines and significant gains in industry profitability
- By PharmaNews Live Desk
- New Delhi
- Mar 16, 2026
Artificial intelligence (AI) is expected to significantly accelerate drug development and improve profitability across the global pharmaceutical industry, according to a recent analysis by research and brokerage firm Bernstein.
The firm estimates that AI-driven efficiencies could increase operating profits for pharmaceutical companies by more than 10 percent, as new technologies streamline the complex and expensive drug development process.
AI tools are increasingly being adopted across multiple stages of clinical development, enabling companies to design clinical trials more efficiently, recruit patients faster, and automate regulatory documentation. These improvements could shorten development timelines by around 18 months and reduce research and development (R&D) costs by about 5 percent over the coming years, Bernstein said.
Reducing the time and cost of drug discovery
Developing a new medicine is traditionally a lengthy and expensive process that can take more than a decade and requires extensive investment before a drug reaches the market. Much of the time and cost occur during clinical trials and regulatory review stages, where companies must manage vast datasets, recruit suitable patients, and prepare detailed submissions for regulators.
According to Bernstein, AI technologies can help address these bottlenecks by analyzing historical clinical trial data, improving trial protocol design, optimizing site selection, and enhancing patient monitoring during studies. These capabilities can reduce delays and limit costly amendments to clinical trial protocols while also accelerating regulatory documentation processes.
Earlier market entry could improve profitability
The use of AI may also have significant commercial implications for drugmakers. Bernstein noted that faster development timelines could allow medicines to reach the market earlier, effectively extending the period during which pharmaceutical companies can generate revenue before patents expire and generic competition enters the market.
This combination of earlier launches and reduced R&D spending could translate into a notable improvement in profitability across the sector.
Large pharma companies likely to benefit most
Bernstein suggested that large global pharmaceutical companies are particularly well positioned to benefit from AI adoption because they possess the scale, data resources, and infrastructure required to deploy advanced analytics effectively.
Companies such as Daiichi Sankyo, Takeda, and Astellas were highlighted as examples of firms that could capture significant upside from AI-driven efficiencies in research and development.
AI to enhance — not replace — the pharma model
Despite its potential to improve productivity, Bernstein noted that AI is unlikely to fundamentally disrupt the pharmaceutical industry’s core business model. Drug development will remain capital-intensive and heavily regulated, meaning technology will function primarily as a tool to enhance efficiency rather than replace existing processes.
Still, the growing integration of AI into clinical research, data analysis, and regulatory processes signals a major shift in how pharmaceutical innovation may unfold in the coming decade.