November 13, 2025
How Philips is scaling AI literacy across 70,000 employees
Philips is turning AI literacy into a company-wide capability that drives innovation and better care.
Results
AI literacy and hands-on use expanding across the organisation
Results
Executive leadership trained directly, modeling the change
Philips operates across personal health, diagnostics, image-guided therapy, and patient monitoring.
AI is not new to Philips—specialised AI and machine learning systems have been embedded in products for years. What’s new is the scale.
To fully realise the value of AI in healthcare, Philips is now working to make AI a capability that every employee can confidently use—not just specialised teams.
We sat down with Patrick Mans, Head of Data Science & AI Engineering, to hear how Philips is elevating AI literacy across the organisation, reinforcing its commitment to responsible AI, and advancing the age of intelligence to enable better care for more people.
“You start playing with it, then you start working with it—and from there, you start innovating with it.”
Inside the rollout
Philips already had strong, specialised AI teams working on traditional machine learning inside products.
But broad transformation required something different: AI literacy across everyone — not just experts.
OpenAI helps make that possible because the familiarity is already there.
“People were already using OpenAI tools privately—so the curiosity was there. We just needed to channel it into real work.”
Philips is intentionally moving employees along a curve: Toy → Tool → Transformation
And channelling curiosity into capability:
- Executives trained hands-on first to lead by example
- A company-wide challenge invited employees to propose use cases
- Access to ChatGPT Enterprise increased demand and momentum
This created momentum from both directions: leadership endorsement + grassroots pull.
As a 134-year-old healthcare technology company, Philips operates under strict safety, privacy, and regulatory expectations. Trust and responsible use of AI are foundational. “You can’t just implement AI as technology. You have to shift the culture—how people think, and how they trust,” says Patrick.
To build confidence:
- Philips began with low-risk internal workflows
- Teams were encouraged to experiment in controlled environments
- Responsible AI principles—transparency, fairness, human oversight—were formalised and adopted organisation-wide
- Confidence and skill grew before AI touched patient-impacting workflows
The priority now is reducing administrative burden—especially in clinical environments, where time is critical. Philips’ focus is clear: Give clinicians time back to care for patients.
“I was in a hospital where a clinician spent 15 minutes saving a life—and then had to spend 15 minutes documenting it. He could have saved two lives in that same time.”
Results at a glance
- AI literacy and hands-on use expanding across the organisation
- Executive leadership trained directly, modeling the change
- Bottom-up idea challenges accelerating experimentation
- Trust-building approach enabling movement into regulated workflows
- Strategic focus on reducing administrative burden in clinical environments to give back time to healthcare professionals
Leadership lessons from Philips
- Lead from the top: Train leadership hands-on so they model usage, not just mandate it.
- Fuel bottom-up momentum: Give people ways to propose, test, and own their use cases.
- Align early—AI moves faster than most organizations: Prepare stakeholders upfront so momentum becomes an advantage, not a blocker.
- Make responsible AI principles real: Transparency and human oversight are essential, especially in healthcare.
- Focus where time matters most: Administrative burden is the fastest path to meaningful impact.
What’s next
Philips is now moving from individual productivity gains to workflow-level automation and agent-supported processes—with a clear AI policy and responsible AI principles in place.
The goal is simple and human: giving back time to clinicians so they can spend time on what matters most; their patients.
“We want to deliver better care for more people. AI is one of the most powerful tools we have to do that.”
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