Artificial intelligence is transforming the health and life sciences landscape. Insights from our 2025 Voice of Our Clients research reveal that IT modernization and cloud migration are top priorities, with over half of executives (51%) committed to driving operational efficiencies through AI and automation.
From automating claims and accelerating drug discovery, to streamlining patient engagement and powering precision medicine, the potential of AI is immense. Realizing its transformative capabilities, however, demands more than pilots and proofs of concept. It requires strategic commitment and scaled execution. Enterprise AI is about bringing advanced AI technologies into large organizations in a way that truly drives business value. When applied at scale, enterprise AI helps organizations work smarter, respond faster, and open the door to new opportunities, all while building trust and resilience for the future.
Too often, discussions about AI are limited to governance, data, or use cases. What is frequently overlooked is just as critical: the infrastructure and horsepower required to make AI real at scale.
In our daily work with clients across the globe, we see this reality every day. To bridge the gap between innovation and impact, we’ve developed the Five Pillars of Enterprise AI, a model that goes beyond theory to focus on the practical domains where firms must excel. These pillars define the capabilities needed to ensure AI delivers measurable, sustainable value across an entire organization to automate tasks, enhance efficiency, improve decision-making, and more at scale.
Our perspective builds on CGI’s broader cross-industry thought leadership, Building a mature AI ecosystem for scalable impact, which defines critical elements for enterprise-wide AI success. This blog shares these principles in a health and life sciences context, showing how the five pillars of enterprise AI provide a practical roadmap for payers, providers, governments and life sciences firms to move from innovation to measurable outcomes.
1. Infrastructure and compute power: The backbone of AI at scale
AI in health and life sciences is only as strong as the compute power behind it. High-value use cases, from radiology imaging to genomics pipelines, are highly resource-intensive and demand modern, secure, and sustainable infrastructure. To succeed, hospitals, government agencies, and life sciences firms need flexible, high-performance environments that balance performance, cost and energy efficiency.
Client success story: A global retail pharmacy chain partnered with us to modernize its data and analytics platforms by migrating the majority of workloads to the cloud. Our phased approach incorporated secure landing zones, zero-trust networking, infrastructure-as-code, and graphic processing unit (GPU)-ready clusters designed to support future AI applications. The outcome was clear: faster innovation cycles, greater resilience, and a scalable foundation for enterprise-wide AI.
2. Data and integration: The lifeblood of health and life sciences
AI is only as powerful as the data it runs on. In health and life sciences, however, critical data is often siloed across electronic medical records (EMRs), payer claims systems, lab platforms, and research archives. To unlock real value, data must be trusted, accessible, and interoperable. Only then can it fuel actionable insights that improve outcomes and accelerate innovation.
Client success story: A provincial health authority partnered with us to digitize and automate COVID-19 reporting. By replacing paper-based processes with an integrated, data-driven approach, leaders gained accurate insights that enabled faster, more effective decision-making.
3. Governance and responsible AI: Guardrails for trust
In healthcare, trust is the ultimate currency, and it cannot be compromised. Patients, clinicians, and regulators must have confidence that AI solutions are safe, transparent, and equitable. Building this trust requires more than meeting regulatory standards. It demands robust governance frameworks, ongoing monitoring and active engagement with all stakeholders.
Client success story: A healthcare payments organization collaborated with us to automate prior authorization. By embedding governance frameworks into the solution, the organization ensured compliance, equity and fostered long-term trust in the system.
4. Solutions and innovation: From pilots to outcomes
AI’s promise lies in practical solutions that address clinical and operational needs. For many organizations, the greatest challenge is scaling those solutions from pilots to production systems that seamlessly integrate into everyday workflows.
Client success story: We partnered with Boneprox to apply AI to dental X-rays for early osteoporosis detection. By combining advanced imaging with a secure cloud platform, the solution helps identify risk before fractures occur, enabling preventive care at scale and demonstrating how innovation translates into measurable outcomes.
5. People and services: Empowering the human-AI partnership
AI will not replace clinicians, researchers, or administrators. But those who embrace and use it responsibly will transform healthcare and life sciences. Success depends on cultivating a human-AI partnership in which technology augments expertise rather than replacing it. This requires sustained investment in digital skills, AI literacy, and thoughtful change management to ensure people remain at the center of transformation.
Client success story: A global life sciences company collaborated with us to implement a people-centric change management program. The initiative equipped employees with new operating models, process frameworks, and cultural enablers, allowing them to adapt successfully during a period of significant organizational transformation.
Connecting the five pillars across our health and life sciences offerings
These five pillars are more than guiding principles. They directly reinforce our broader health and life sciences service offering. Together, they establish the foundation for data and transformation readiness, helping us guide organizations to have the infrastructure, trusted data, governance, solutions, and people to achieve their AI ambitions.
At the same time, each pillar aligns with broader market demands: governance safeguards trust at every stage of innovation, people and services build workforce resilience, and solutions and innovation deliver real-world outcomes. In this way, these five pillars serve as a practical framework for how we continuously enhance our industry offerings to help clients achieve measurable value.
From backbone to bedside to bench: building a strategy that delivers patient outcomes
Across payers, providers, government, and life sciences, the message is clear: AI success doesn’t emerge from any single dimension. It is achieved when organizations strengthen all five pillars and weave them into a coherent, enterprise AI strategy. We are uniquely positioned to help clients deliver on this vision. From modernizing infrastructure to responsibly governing AI models and embedding solutions into daily workflows, our focus is on ensuring that AI delivers outcomes.
Connect with me to explore how we can work together to strengthen health systems, accelerate scientific innovation, and enhance patient outcomes, moving confidently from backbone to bedside to bench.
About this author
Ben Goldberg
Global Industry Lead, Health and Life Sciences
Ben Goldberg is the Global Industry Lead for Health and Life Sciences at CGI, where he engages with teams around the world to help define, develop, and foster our role as technology partner for health and care organizations.
