Healthcare and life sciences organisations are moving from pilots to production with agentic artificial intelligence, reporting measurable return on investment while tightening governance around data and safety. According to Google’s Return on AI 2025 report, adoption is broadening beyond chat to agents that plan, reason and take actions through secure tool and data access under human oversight. Budgets tilt toward agents as overall generative AI spending rises even as unit costs decline. Early deployments focus on high-volume processes in clinical, operational and compliance-heavy domains where automation can relieve workload and improve responsiveness. Delivery speed, leadership sponsorship and disciplined guardrails are shaping outcomes, with time to value compressed by targeting repeatable workflows that integrate cleanly into existing systems.
Adoption and Investment Priorities
Agentic deployment is already present at scale. Among healthcare and life sciences executives, 44% say their organisations have agents in production. In healthcare, 34% report launching more than 10 agents, underscoring movement from experimentation to portfolio deployment. Priority use cases reflect operational and compliance needs. In healthcare, inventory tracking and restocking leads at 39%, automated document processing at 36% and regulatory compliance at 35%. Life sciences organisations emphasise quality control at 37%, automated document processing at 36% and supply chain risk identification and process augmentation at 33%, aligning agents to throughput, quality and oversight.
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Investment intent is firming. Almost half of executives indicate that over 50% of future AI budgets are earmarked for agents, and 74% say overall generative AI spend has increased as costs decline. AI already accounts for a mean 23% of total annual IT spend, and organisations are reallocating non-AI budgets to sustain momentum. When selecting large language model providers, data privacy and security is the top factor at 37%, followed by cost at 30% and ease of use and deployment at 27%, reflecting the sensitivity of patient data, intellectual property and regulated workflows. Leaders link comprehensive C-suite sponsorship with faster, more consistent realisation of ROI, highlighting the cross-functional nature of agentic programmes.
Where Returns Are Emerging
Early ROI is visible in both industries with clear patterns. In healthcare, tech support and patient experience each deliver ROI for 34% of organisations. Core functions show strong traction and further potential: inventory tracking and restocking, medical image recognition, and patient screening and on-demand personal care are each cited by 22% as already returning value, positioning them for scaled impact as adoption matures. These domains sit at the intersection of high volume, repeatable tasks and measurable outcomes, enabling rapid proof of benefit without extensive redesign of clinical pathways.
Life sciences report returns where document intensity and compliance meet operational throughput. Product innovation and design is cited by 28%, marketing by 27% and automated document processing by 26% as ROI sources. Additional returns appear in medical image recognition at 19%, inventory tracking at 18% and production planning at 18%. Across both industries, generative AI shows compounding effects: 72% report improved productivity, 61% improved patient experience, 52% business growth, 49% marketing impact and 46% security improvements. Among those citing productivity gains, 33% say employee productivity at least doubled, and 42% report ROI from individual productivity use cases such as emails, documents, presentations, meetings and chat. Among organisations reporting revenue increases, 83% place gains at 6% or more, with 53% in the 6–10% range and 30% above 10%, indicating that financial impact is becoming more common as adoption deepens.
Security outcomes are nuanced. While 46% report meaningful impact, underlying metrics have softened year on year, prompting interest in specialised agentic use within security operations and cybersecurity. Given the value of patient records, research data and proprietary assets, organisations are applying agents to threat detection, response acceleration and policy enforcement as part of layered defence.
What It Takes to Scale
Scaling value depends on budgets, data and execution discipline. With 74% increasing spend and nearly half directing at least half of future AI budgets to agents, investment is being positioned as strategic rather than experimental. Realising returns requires robust data foundations, governed access to operational systems and human-in-the-loop controls that match clinical and regulatory stakes. Provider selection criteria led by privacy and security mirror these requirements and influence architecture choices for integration with electronic health records, billing, laboratory and quality systems.
Time to value is a competitive lever. Many organisations report three to six months from idea to production for focused use cases, favouring repeatable workflows with clear success metrics. Common starting points include tech support, patient care interactions, prior authorisation requests and security operations. Execution quality hinges on cross-functional alignment and skills development so teams can design, integrate and monitor agents across complex estates. Integration risk rises with specialised legacy platforms where errors may carry clinical or regulatory consequences, reinforcing the need for C-suite sponsorship, clear guardrails and staged rollouts. As implementations mature, emphasis shifts from isolated wins to orchestrated workflows that compound benefits across departments and maintain consistent governance.
Agentic AI in healthcare and life sciences is progressing from isolated pilots to measurable value, with adoption, budgets and outcomes pointing to sustained momentum. Returns are strongest in high-volume operational, clinical and compliance workflows where automation under human oversight reduces friction and surfaces timely insights. Gains in productivity, patient experience, business growth, marketing and security are tempered by the need for rigorous governance and secure data access. Organisations that pair focused use cases with disciplined execution, strong leadership sponsorship and robust guardrails are best positioned to turn targeted deployments into enterprise-level impact on care delivery, research velocity and operational efficiency.
Source: Google Cloud
Image Credit: iStock
