AI @ McKesson
Summary
- McKesson has progressively increased its adoption of AI technologies from 2019 to 2025, focusing on healthcare data management, predictive analytics, and automation to improve operational efficiency and customer engagement.
- Key AI initiatives include collaboration with Google Cloud and Microsoft for cloud-based AI solutions, implementation of large language models in oncology data via the Ontada platform, and the use of virtual assistants and machine learning models to streamline healthcare supply chains and logistics.
- By 2025, McKesson is leveraging AI for both internal operational efficiencies and external customer-facing solutions, particularly in specialty pharmacy, oncology data processing, and supply chain optimization, driving outcomes such as cost reduction, risk mitigation, improved customer experience, and revenue growth.
VIBE METER
3 AI Use Cases at McKesson
Data Extraction2024
Predictive Analytics2024
Virtual Assistants2022Customer Facing
Timeline
2025 Q4: no updates
2025 Q3
McKesson's AI strategy leverages logistics scale and Rx technology innovation to dominate healthcare supply chain, distribution, and medication management.
2025 Q2
McKesson highlights logistics innovation and AI potential in healthcare, launching specialty pharmacy solutions and exploring machine learning to tackle cost challenges.
2025 Q1
McKesson focused on designing and implementing AIOps solutions, and Ontada used Microsoft Azure OpenAI to analyze over 150 million unstructured oncology records to enhance insights.
2024 Q4
Ontada, a McKesson company, partnered with Microsoft to transform unstructured oncology data using Azure OpenAI technology and the Genuity platform.
2024 Q3: no updates
2024 Q2
McKesson scaled AI capabilities and predictive analytics to anticipate supply disruptions and optimize the healthcare supply chain.
2024 Q1
McKesson continued revolutionizing healthcare through innovative AI applications improving efficiency and care delivery.
2023 Q4
McKesson leveraged partnerships, acquisitions, and investments to implement three AI use cases enhancing healthcare operations.
2023 Q3
McKesson's Director of Enterprise Analytics highlighted the use of supervised and unsupervised machine learning models as core to analytics work.
2023 Q2
AI applications in nuclear medicine poised to automate routine tasks, enhancing physician productivity.
2023 Q1: no updates
2022 Q4: no updates
2022 Q3
Reported use of interactive virtual assistants, chatbots, and agent assistance technology to enhance organizational efficiencies.
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
McKesson focused on building internal digital infrastructure and investing in AI to facilitate healthcare advancements.
2019 Q2
McKesson chose Google Cloud to centralize data management and began applying AI to healthcare predictions, initiating its AI journey.