Embracing AI is a strategic imperative for companies across the life sciences value chain, with the technology now a prerequisite for innovation, efficiency and future-readiness. The overwhelming consensus from our survey respondents highlights the imminence of this change. Two thirds (66 percent) say AI's impact on life sciences in the next 24 months will be transformational.

This sentiment is strongest in human pharma (78 percent) and medical devices (70 percent), where AI is already being deployed for complex tasks such as drug discovery and diagnostic analysis. The share is lower, though still material, among healthcare providers (52 percent) and animal health companies (48 percent), reflecting tighter budgets, more fragmented data and heavier reliance on third-party tools.

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"The impact will be huge. Companies that do not use AI frequently in their activities will fall behind the rest and the level of innovation will suffer," says the head of technology of a pharma company in Ireland.

This transformation cannot be achieved without first defining what success looks like. This ensures that budgets are aligned with outcomes, enabling further funding when positive results are delivered. Companies must set clear, measurable objectives so they understand exactly what they seek to achieve and whether those milestones are being met. AstraZeneca has publicly detailed internal tools, such as its Development Assistant, which allows clinical operations teams to query structured and unstructured data using natural language, backed by generative agents and retrieval-augmented generation. It was first launched as a proof of concept in mid-2024 and built into a production-ready MVP within six months, improving patient recruitment, site selection and clinical trial design.

Metrics for success differ depending on each subsector's priorities. Diagnostic accuracy (44 percent) leads overall, rising to 58 percent for medical device companies. Meanwhile, healthcare providers, who are more directly concerned with patient-facing services, prioritize metrics related to patient access and health equity (58 percent). For animal health companies, the primary focus is on healthcare cost reductions (52 percent).

Access to capital has always been a competitive differentiator in life sciences, but with margins under pressure, R&D pipelines growing more complex and regulatory expectations intensifying, investors are becoming more selective. Increasingly, effective AI adoption is seen as a proxy for agility, data maturity and long-term value creation. Respondents are unanimous on this point: 97 percent agree that companies will be less attractive to investors unless they adopt AI effectively within the next 24 months. This includes 60 percent of North America–based and 50 percent of EMEA–based respondents who strongly agree. Asia-Pacific–based executives are more measured, with 57 percent somewhat agreeing.

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While much of the focus on AI has centered on operational efficiency and commercial upside, its ultimate test will be its impact on care. Across the sector, the belief that the technology can improve patient outcomes is nearly universal—reflecting growing confidence in AI's ability to sharpen diagnoses, tailor interventions and support more consistent, equitable delivery.

Nearly every respondent (98 percent) expects AI to improve patient outcomes to at least some extent, and in many cases, the expectations are high. Seven out of ten life sciences companies based in EMEA anticipate a great improvement over the next two years, a bullish view that reflects the region's regulatory momentum around digital health and concrete progress in imaging, diagnostics and care coordination.

Human pharma firms also stand out for their optimism, with 68 percent expecting a significant step forward in outcomes by 2027, with the remainder still anticipating at least moderate gains. Much of this confidence rests on AI's growing role in uncovering novel treatment pathways, including by improving how candidates are modeled and prioritized.

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