Just_Super/iStock/Getty Images Plus Follow ZDNET: Add us as a preferred source on Google. ZDNET's key takeaways Life sciences leaders say AI agents will be "essential" within two years. 97% say trusted data is essential for effective use of AI agents. 81% of R&D leaders surveyed are "very excited" about using AI. Life sciences leaders are increasingly adopting AI and AI agents to address growing industry disruption. This shift is occurring as the sector confronts new regulatory demands that strain compliance teams, increasingly complex clinical trials, and rising expectations from healthcare professionals. A recent Salesforce study revealed that life sciences leaders see AI as a powerful tool for navigating these challenges, with 94% expecting AI agents to be critical for scaling organizational capacity and strengthening operations. Also: AI is every developer's new reality - 5 ways to make the most of it The research also identified three key areas where AI can help stabilize the industry: compliance, clinical trials, and healthcare professional (HCP) engagement. Notably, 96% of the leaders surveyed believe that AI agents will be "essential" within the next two years. Data is the biggest challenge While there's significant enthusiasm, with 72% of leaders expressing excitement about AI, several key barriers are hindering its full implementation and expansion. The top challenges include: Security, privacy, and compliance concerns. Organizational change management. Uncertainty regarding regulatory guidance on AI use. Concerns about unproven or unfamiliar AI platforms. Difficulty integrating AI into existing tools and workflows. A critical factor in building trust among life sciences professionals is the reliability of the underlying platform and data. Nearly all leaders (97%) agree that trusted data is essential for effective AI agent use, and 96% believe a widely used or proven platform is important for confidence in using AI at work. Also: 50 AI agents get their first annual performance review - 6 lessons learned The Salesforce survey revealed that only 46% of life sciences technical leaders are fully confident in the consistent availability, timeliness, and accuracy of their data. AI in healthcare engagement Despite billions of dollars spent on HCP engagement, over a third of leaders believed their strategies are ineffective. A major contributing factor is the overload of generic messages that HCPs receive, leading to disengagement. In 2024 alone, US healthcare and pharmaceutical companies spent over $30bn on advertising. More than one in three (37%) life sciences leaders said their HCP engagement strategies (including sales and marketing) are broken, and 31% said their sales and marketing teams are not scaling effectively with product launches. Also: AI just passed a brutal finance exam most humans fail - should analysts be worried? Weak segmentation strategies appear to be a significant cause. Commercial leaders estimated that 30% of their sales and marketing efforts are wasted, split between targeting the wrong people and sending the wrong message. While 58% consider their segmentation strategy advanced, only 4% view their outreach as "state of the art." This confidence could be an overestimation, as only 62% consider patient population demographics, and a mere 39% factor in digital behaviors, such as channel preferences or content consumption patterns. Life science leaders believed AI agents can summarize, streamline, and respond to HCP communications. A striking 63% of commercial leaders said they are "very excited" about integrating AI into their daily work. Valuable AI use cases for HCP engagement include: Summarizing communications between companies and HCPs (89%). Streamlining HCP interactions across channels (88%). Responding to HCP medical inquiries 24/7 (87%). Improving advertising and sales engagement (78%). These results highlight a clear opportunity for AI to address critical inefficiencies and enhance the effectiveness of HCP engagement. AI in clinical trials Life sciences leaders are facing significant challenges, with clinical trials remaining the most expensive and often delayed step in therapy development. Market swings, policy changes, and supply chain disruptions compound existing issues, such as manual workflows and difficulties in tracking long-term outcomes. Also: AI helps strong dev teams and hurts weak ones, according to Google's 2025 DORA report Over half (57%) of life science leaders acknowledged major disruptions in trials due to these external factors. The top barriers to meeting new trial requirements include: Manual regulatory workflows (55%). Difficulty tracking long-term outcomes (38%). Disconnected R&D and clinical operations (25%). Site onboarding delays (25%). Recruitment and retention struggles (24%). In response, 94% of leaders recognized that evolving trial requirements are reshaping their approach to innovation, with AI emerging as a crucial solution. R&D leaders, in particular, are enthusiastic about AI, with 81% expressing excitement about its application in their daily work. Overall, over 90% of life sciences leaders viewed AI in clinical trials as a valuable solution. Some of the top AI use cases considered include: Clinical trial site selection (94%). Providing real-time patient outcome insights (92%). Matching candidates to clinical trials (92%). Clinical trial participant recruitment and engagement (91%). These insights emphasize the need for advanced solutions to streamline clinical trials and accelerate therapy development. Compliance is a crucial AI use case Expanding regulations and intensifying audits are significantly impacting compliance teams, with 64% of life sciences leaders reporting their workloads are "heavily impacted" by recent volatility. Interestingly, compliance is both the top factor dampening AI enthusiasm in life sciences and the focus of its three most valuable use cases. Factors that curb excitement include compliance risks, a lack of change management plans, and a lack of trust in underlying data. Conversely, the most valuable AI use cases identified are: first, document generation, consent, and contract management; second, regulatory reporting; and third, streamlining compliance. Also: Got AI FOMO? 3 bold but realistic bets your business can try today Ultimately, AI is viewed as a tool to reduce routine task workloads, raise compliance standards, and help teams keep pace with evolving regulations. A significant 94% of life sciences leaders believed AI agents would be critical in managing these changing regulations. To learn more about how healthcare and life sciences professionals are leveraging AI, you can visit here.