64% of Life Sciences Leaders Implementing AI Governance for Scaling Success

In a recent study titled the Responsible AI in Life Sciences (RAIL) Report 2026, it was revealed that 64% of leaders in the life sciences sector are actively working to implement AI governance protocols. This initiative is essential for scaling artificial intelligence applications effectively in their business operations, medical practices, and patient interactions. The report, conducted by ACTO, highlights that while the industry is ripe for AI adoption, there are considerable trust issues that need to be addressed first.

The study is based on insights gathered from roundtable discussions and surveys among senior executives in pharmaceutical, biotechnology, and medical device companies. A notable insight from the report is that two-thirds of those surveyed have either a fully established AI governance process (22%) or are still in the development stages (42%). However, over one-third of respondents either lack a defined governance framework (21%) or operate with minimal oversight, relying on ad-hoc approvals from IT departments (15%).

Trust as a Barrier to Scalability

Key findings from the RAIL report illustrate that while technology is no longer seen as the primary barrier to AI scalability, a lack of trust remains a significant hurdle. About 58% of respondents believe that the life sciences sector is still lacking clear standards for responsible AI. Concerns regarding internal regulatory, legal, or compliance issues (21%) posed a greater obstacle than technical readiness (9%) when it comes to scaling AI initiatives.

The survey also revealed that when evaluating pilot AI projects, leaders prioritize trust and adoption (24%) over efficiency (23%), showing a shift in focus towards ensuring sustainable and reliable AI integration.

More than two-thirds of leaders (68%) are directly involved in AI projects within their organizations, with 69% expressing comfort with the technology. Despite this, over half (54%) still harbor concerns about how AI is utilized within their firms. Furthermore, there is no consensus among leaders regarding who should ultimately be accountable for an AI agent's actions, indicating a lack of clarity in roles and responsibilities.

Governance Models Matter

The leaders defined governance as a continuous operational model that extends well beyond initial approvals. This model necessitates clearly designated business owners, precise scaling pathways, and standard operating procedures (SOPs), allowing for the implementation and retraction of AI agents as needed. However, only 34% of leaders believe the end-user should bear ultimate responsibility for AI agent actions, while others allocate that to legal and compliance teams (28%), external AI providers (22%), or IT departments (16%).

Despite the prevalent challenges, leaders envision a future where AI enhances performance and is assessed fairly. Roughly 79% agree that AI risk and return on investment (ROI) should be measured against how tasks are currently performed by humans.

Prioritization of AI Projects

The report suggests that organizations should begin AI projects with tasks that are simpler to govern, such as review and approval cycles or knowledge management, and progress towards more complex integrations, like supporting comprehensive product launches.

The most anticipated benefit from AI adoption is improved outcomes (29%), followed by efficiency (25%) and productivity (24%). In contrast, cost savings and risk reduction are viewed as less critical gains. However, organizational barriers and regulations remain the foremost challenges that need addressing to achieve broader AI adoption.

Introducing the RAIL Score

To aid in defining a common trust criterion, the RAIL Score presents a framework to evaluate AI systems based on six components: governance, security, testing and certification, human-centered approaches, value creation, and orchestration. Each element is rated, allowing teams to systematically assess systems against the stringent requirements of the regulated life sciences industry.

The free RAIL Report 2026 and associated tools are currently accessible at acte.com/RAIL. For further insights, a webinar titled "Responsible AI in Life Sciences" is set to take place on November 4, focusing on scalability perspectives among industry leaders.

About ACTO

ACTO specializes in enabling life sciences companies to deliver therapies to patients following regulatory approvals. Their AI-driven platform enhances product launches, strengthens field execution, and deepens commercial and medical engagement through intelligent automation. With products currently in use by 14 of the top 50 pharmaceutical companies, ACTO ultimately aims to optimize workflows, allowing professionals to focus on strategic execution and patient relationships.