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Key takeaways of zdnet
- Life science leaders say that the AI agent will be “necessary” within two years.
- 97% states that reliable data is necessary for effective use of AI agents.
- 81% of the surveyed R&D leaders are “very excited” about using AI.
Life science leaders are fast adopting AI and AI agents to address the growing industry disruption. This change is taking place because the sector faces new regulator demands that stress growing expectations from compliance teams, rapid complex clinical trials and healthcare professionals.
recently Sales force The study has shown that life science leader sees AI as a powerful tool to navigate these challenges, in which 94% of AI agents are expected to be important to increase organizational capacity and strengthen operations.
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Research also identified three major areas, where the AI can help stabilize the industry: compliance, clinical testing, and healthcare professional (HCP) engagement. In particular, 96% of the leaders involved in the survey believe that the AI agents will be “necessary” within the next two years.
Data is the biggest challenge
While there is significant enthusiasm, 72% of the leaders expressed enthusiasm about AI, many major obstacles are obstructing its complete implementation and expansion. Top challenges include:
- Security, privacy and compliance concerns.
- Organizational change management.
- Uncertainty about regulatory guidance on AI use.
- Concern about unproven or unfamiliar AI platforms.
- Difficulty integrating AI in existing tools and workflows.
An important factor in the creation of a trust among life science professionals is the credibility of the underlying platform and data. Almost all leaders (97%) agree that reliable data is essential for the use of effective AI agents, and 96% believe that a widely used or proven platform is important for confidence in using AI at work.
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The salesforce survey has shown that only 46% of the technical leaders of life science are completely confident in the frequent availability, timeliness and accuracy of their data.
In healthcare engagement
Despite the billions of dollars spent on HCP engagement, more than a third of the leaders believed that their strategy was ineffective. A major contribution factor is the overload of general messages that receive HCP, which leads to disintegration.
In 2024 alone, US healthcare and pharmaceutical companies spent more than $ 30BN on advertisements. More than one of the three (37%) life science leaders said that their HCP engagement strategies (including sales and marketing) were broken, and 31% said their sales and marketing teams are not effectively scaling with product launch.
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Weak partition strategies seem to have an important reason. Commercial leaders estimated that 30% of their sales and marketing efforts are ruined, divided between targeting wrong people and sending wrong messages. While 58% consider their partition strategy to be advanced, only 4% see their outreach as “art status”.
This confidence can be an overestimation, as only 62% of patients consider population demographics, and only 39% factors in digital behavior, such as channel preferences or material consumption patterns.
Life science leaders believed that AI agent HCP could briefly, streamlined and reaction to communication. 63% of commercial leaders said they are “very excited” about integrating AI into their daily work. HCP engaged in cases of valuable AI use for engagement:
- Summining communication between companies and HCP (89%).
- To streamline HCP interactions in channels (88%).
- HCP medical inquiry reply to 24/7 (87%).
- Improvement in advertising and sales engagement (78%).
These results highlight a clear opportunity to address important disabilities for AI and increase the effectiveness of HCP engagement.
In clinical trials
Life science leaders are facing important challenges, the most expensive and often delayed steps in medical development with clinical trials. Market swings, changes in policy, and dissolution of supply chain compound existing issues, such as manual workflows and difficulties in tracking long -term results.
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More than half (57%) of life science leaders accepted major disruption in tests due to these external factors. Top barriers are included to meet new test requirements:
- Manual Regulatory Workflows (55%).
- Difficulty monitoring long -term results (38%).
- R&D and diagnostic operations (25%) were disconnected.
- Site onboarding delay (25%).
- Recruitment and Retention Conflict (24%).
In response, 94% of the leaders admitted that the Testing requirements are re -shaping their approach to innovation, AI is emerging as an important solution. The R&D leaders, in particular, are excited about AI, expressed enthusiasm about its application in their daily tasks with 81%.
Overall, more than 90% of life science leaders saw AI as a valuable solution in clinical trials. Top AI is believed to be in some cases of use:
- Clinical test site selection (94%).
- Real -time patient results providing insight (92%).
- Matching of candidates for clinical trials (92%).
- Clinical testing participants recruitment and engagement (91%).
These insights emphasize the need for advanced solutions to streamline clinical trials and accelerate medical development.
Compliance is an important AI use case
Extending the rules and intensifying the audit is greatly impressing compliance teams, 64% of life science leaders have reported their assignments that are “heavy affected” by recent instability.
Interestingly, compliance is both AI enthusiasm in life science and top factor focusing on its three most valuable use cases. Factors that curb enthusiasm include exposure risk, lack of change management plans and lack of confidence in the underlying data. In contrast, the most valuable AI use cases are: first, document generation, consent and contract management; Second, regulatory reporting; And third, well -organized compliance.
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Ultimately, AI is seen as a tool to reduce regular task charge, increase compliance standards, and help to keep pace with teams developing teams. An important 94% of the leaders of life science believed that the AI agents would be important in the management of these changing rules.
How to learn more about healthcare and life science professionals, how are you taking advantage of AI Here,
