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01 · Use cases— The evidence

Philips

8 documented AI deployments at Philips, across 1 industry. Each one links to the public source it was taken from.

Amsterdam, Netherlands · Founded 1891 · philips.com · WikipediaSource: Wikidata, 2026-11-01

8
deployments
on record
1
industry
Healthcare
0%
use AI agents
0 of these
11 May 2026
latest source date
2 report a measured outcome
§ 1

Public AI record

Philips ranks 8th of 13 healthcare companies on the hub with a public AI record score of 62. It is ahead of 89% of companies on breadth, but behind most on sophistication. Patient engagement and healthcare workflow automation are common among peers but not yet documented at Philips.

Medium confidenceBased on 8 public cases · updated 10 Nov 2026
62
Record score
Out of 100; 50 is typical on the hub
8th of 13
Healthcare companies
Peer median 63

Nearest peers: Amazon Pharmacy 6th, 63 · Availity 7th, 62 · NHS 9th, 61 · Northwestern Medicine 10th, 59

  1. BreadthHow many different kinds of use case, across how many business areas
    89
  2. DepthShare running in production or at scale rather than pilots
    54
  3. SophisticationAgentic share and innovativeness rating
    17
  4. EvidenceShare backed by the company's own sources and measured results
    69
  5. MomentumHow recent the cases are; older cases count less
    82
How the score works
Each bar is a percentile against every company page on the hub: 70 means a stronger record than 70% of them. The score is the average of the five. It measures the public record we can document, not the quality of the company's AI.

First documented case Feb 2011, latest May 2026. Cloud providers named: AWS, Microsoft.

§ 2

Compared with peers

Against 39 other healthcare companies on the hub.

What peers document

  1. Clinical documentation20 of 39 peers · here too
    51%
  2. Patient engagement14 of 39 peers
    36%
  3. 28%
  4. AI development platform8 of 39 peers · here too
    21%
4 of 6 patterns

Gaps against the industry

Signature use cases

No peer on the hub documents data platform modernization.

Stack and approach vs peers
  • Peer cases name Microsoft 77%, AWS 16%, GCP 8%.
  • AI agents: 0% of Philips's cases vs 46% for peers.
  • Cases from the last 12 months: 50% vs 21% for peers.
§ 3

Deployments

8 deployments at Philips, newest first.

  • 11 May 2026
    Healthcare

    Philips HealthSuite Platform Delivers Insights at Scale on AWS

    Philips · Data platform modernization · AWS

    Philips enables customers to unlock insights at scale from their data by using cloud health applications running on HealthSuite Platform built on AWS. The platform consolidates patient records, wearable data, remote medical-monitoring equipment data, and information from insurance companies or healthcare organizations.

    Scaled Production

  • 29 Apr 2026
    Healthcare

    Philips Accelerates AI-Driven Healthcare Innovation with AWS

    Philips · AI development platform · AWS

    Philips, a healthcare technology company headquartered in the Netherlands, partnered with AWS to accelerate AI model training, improve healthcare solutions innovation, and maintain compliance and security. They utilize Amazon SageMaker ToolSuite, AWS Skill Builder, AWS IoT, and Amazon EKS to develop AI-driven healthcare applications, medical imaging acceleration, and system integration.

    Production

    −80%
    time
  • 29 Apr 2026
    Healthcare

    Philips on AWS: Accelerating AI Innovation for Healthcare

    Philips · Medical imaging · AWS

    Philips uses AWS to accelerate AI solution development and reduce model training time, delivering faster innovation and improved patient outcomes. Collaborated with AWS to upskill over 5,000 employees through AWS Skill Builder for AI capabilities. Leveraged Amazon SageMaker AI ToolSuite to speed up ML development from weeks to days and integrated AI across healthcare workflows. Implemented data privacy automation and portable medical imaging solutions on AWS cloud, significantly improving operational efficiency and reducing MRI scan time. Deployed medical image analysis with AWS IoT and EKS enabling real-time processing and cost reductions.

    Production

    −67%
    time
  • 29 Apr 2026
    Healthcare

    AWS Healthcare & Life Sciences Generative AI Use Cases and Customer Implementations

    Pfizer · Drug discovery · AWS

    AWS supports healthcare and life sciences organizations in deploying generative AI to accelerate drug discovery, improve clinical trial development, enhance medical imaging and pathology analysis, automate clinical documentation, and streamline regulatory compliance. Customers such as Pfizer, Natera, Clario, Aetion, Sanofi, Philips, Hippocratic AI, Solventum, Amazon Pharmacy, and Radboud University Medical Center use AWS technologies to enhance research, care delivery, and compliance workflows. AWS technologies employed include Amazon Bedrock, Amazon SageMaker, AWS HealthScribe, Amazon Textract, and Amazon Comprehend. Applications include rapid drug candidate screening, protocol generation, synthetic defect image generation, compliant content creation, real-world evidence analysis, sales team compliance improvement, clinician task automation, call center productivity, prior authorization automation, and compliance reporting.

  • 18 Mar 2025
    Healthcare

    Philips enhances neurological diagnosis and monitoring for Alzheimer’s and MS patients

    Philips · Medical imaging · Microsoft

    Philips, leveraging a partnership with icometrix, has integrated AI-driven imaging and reporting solutions into its latest BlueSeal MR scanners and healthcare informatics platform to address the growing demand for neurological diagnosis and monitoring in the Netherlands and beyond. The solution employs icometrix’s AI-powered quantitative reporting software and Philips’ cloud-based AI Manager running on Microsoft Azure. With the introduction of novel Alzheimer’s therapies and an expanding patient population, the automated platform delivers fast, accurate, and scalable MRI analysis for Alzheimer’s and multiple sclerosis (MS). High diagnostic consistency and automation ease the burden on neuroradiologists and enable personalized treatments. The platform integrates into radiology workflows, supports FDA/CPT III reimbursement in the US, and features protocols to automate labor-intensive evaluation steps, allowing clinicians to address both Alzheimer’s and MS with improved confidence and efficiency.

    Production

5 of 8 deployments
§ 4

What it builds

AI development platform is the most common pattern in these deployments: 2.

§ 5

Cloud providers named

AWS is named in 5 of these deployments.

  1. AWS63% of these
    5
  2. Microsoft38% of these
    3
§ 6

Industries

All of these deployments are in Healthcare.

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