Rudy Lai

AI @ McKesson

Pharmaceutical distributor
Industry
Last updated
July 3, 2025 at 10:44 AM

Summary

  • McKesson's AI strategy shows a clear progressive adoption and expansion from initial data centralization and AI integration for healthcare predictions in 2019, to advanced AI-powered oncology data solutions and supply chain optimizations by 2025-2026.
  • Key initiatives include partnerships with Microsoft (notably Azure OpenAI), deployment of AI for supply disruption prediction, oncology data processing via large language models, and automation of customer service functions using interactive virtual assistants and chatbots, reflecting a maturing AI ecosystem within McKesson.
  • Leadership roles such as Director of Enterprise Analytics (e.g., Lawhead) and AI product management indicate internal drive towards supervised/unsupervised machine learning applications that enhance operational efficiency, reduce prior authorization burdens, and improve patient outcomes, underlining both internal process improvements and customer-facing impacts.

VIBE METER

More AI announcements = more VIBE
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5 AI Use Cases at McKesson

Provider Burden Reduction
2026
Traditional
Generative
Agentic
Outcome
The US Oncology Network uses AI to extract clinical data and streamline workflows, reducing provider workload while enhancing patient outcomes in community oncology settings. [1]
Prior Authorization
2025
Traditional
Generative
Agentic
Outcome
Costs
Deployment of AI platforms designed to reduce prior authorization processes, decreasing administrative burden and accelerating patient access to therapies. [1]
Oncology Data Processing
2025
Traditional
Generative
Agentic
Outcome
Using Microsoft Azure OpenAI and large language models, McKesson's Ontada transforms vast amounts of unstructured oncology data into actionable clinical insights that improve patient care and research. [1][2]
Supply Forecasting
2024
Traditional
Generative
Agentic
Outcome
Risk
McKesson employs AI and predictive analytics to anticipate supply chain disruptions and shortages, enabling proactive management of healthcare supply inventories. [1]
Customer Support Automation
2022
Customer Facing
Traditional
Generative
Agentic
Outcome
Integration of interactive virtual assistants (IVAs), chatbots, and agent assistance technologies to automate customer interactions, improving service efficiency and responsiveness. [1]

Timeline

2026 Q1

2 updates

McKesson continues AI product strategy with roles focused on data and AI products; US Oncology Network uses AI to reduce provider burden and improve outcomes; AI adoption extends to automation and customer service.

2025 Q4

1 updates

McKesson advances access to quality cancer care by leveraging cutting-edge AI technology and forging strategic partnerships.

2025 Q3

1 updates

Analysis reveals McKesson's AI strategy leveraging logistics scale and Rx technology innovation to dominate healthcare supply chain and medication management.

2025 Q2

1 updates

McKesson emphasizes AI in logistics innovation, specialty pharmacy solutions, and tackles cost and prior authorization challenges; new roles like AI Integration Architect highlight AI's growing role internally.

2025 Q1

1 updates

Using Microsoft Azure OpenAI Service, Ontada processes 150 million oncology data points deploying large language models; McKesson continues building AI leadership roles and focuses on AI adoption in the healthcare space.

2024 Q4

2 updates

Ontada, a McKesson company, collaborates with Microsoft and Datavant leveraging Azure OpenAI technology to transform unstructured oncology data into actionable real-world insights.

2024 Q3: no updates

2024 Q2

1 updates

McKesson scales AI and predictive analytics technologies to anticipate supply disruptions and shortages within the healthcare supply chain.

2024 Q1

1 updates

Revealed multiple AI use cases driving healthcare efficiency and delivery improvement in 2024, continuing McKesson’s AI advancement trajectory.

2023 Q4

1 updates

McKesson showcases three key AI use cases, emphasizing partnerships, acquisitions, and corporate investments to implement AI solutions.

2023 Q3

1 updates

McKesson's Director of Enterprise Analytics, Lawhead, describes deployment of supervised and unsupervised machine learning models as foundational for analytics and AI work.

2023 Q2

1 updates

Exploration of AI applications in nuclear medicine to automate routine tasks, aiding physicians and enhancing medical workflows.

2023 Q1: no updates

2022 Q4: no updates

2022 Q3

1 updates

Adoption of AI-driven interactive virtual assistants and chatbots to enhance organizational efficiency, highlighting customer communication improvements.

2022 Q2: no updates

2022 Q1: no updates

2021 Q4: no updates

2021 Q3: no updates

2021 Q2: no updates

2021 Q1: no updates

2020 Q4: no updates

2020 Q3: no updates

2020 Q2: no updates

2020 Q1: no updates

2019 Q4: no updates

2019 Q3

1 updates

Focused investment in building new digital infrastructure to facilitate healthcare AI as McKesson initiates internal AI programs.

2019 Q2

1 updates

McKesson began its AI journey by choosing Google Cloud to centralize data management and start making healthcare predictions leveraging artificial intelligence.