Keynote-Roy Jakobs
19 Feb 2026 14:00h - 14:15h
Keynote-Roy Jakobs
Summary
The session featured Roy Jacobs, CEO of Philips, outlining how artificial intelligence is poised to become the most transformative technology in healthcare [5-7][8-11]. He argued that mounting pressures from rising demand, chronic disease, workforce strain and patient expectations are accelerating the adoption of data-driven AI solutions [16-20]. Jacobs described the first wave of AI as focused on eliminating friction by automating repetitive tasks, streamlining documentation and prioritising worklists, thereby giving clinicians back valuable time [36-42]. He illustrated this with an autonomous MRI workflow in which AI positions the patient, selects optimal protocols and continuously monitors image quality, resulting in faster, more consistent scans and earlier diagnoses [46-66]. A second illustration showed a “smart healing environment” where AI aggregates data from multiple devices, reduces false alarms and provides predictive alerts to nurses and physicians, enabling proactive care while remaining under human oversight [80-87]. Jacobs emphasized that trust, transparency and continuous regulatory validation are essential for AI adoption, noting that clinicians must understand recommendations and patients must see their data protected [87]. Turning to India, he highlighted the country’s robust digital health infrastructure, such as the Ayushman Bharat Digital Health Mission, which creates high-quality longitudinal data crucial for AI training [88-95]. He further noted that India’s diverse and complex care settings-from urban hospitals to rural primary centres-serve as a unique testbed for scalable, resilient AI solutions that can be exported globally [96-115]. Philips has invested heavily in Indian R&D, manufacturing and AI engineering, with more than 4,000 engineers developing algorithms and platforms that feed into worldwide product offerings [104-112]. Jacobs stressed that success will be measured not by the number of algorithms deployed but by outcomes such as earlier disease detection, reduced complications, shorter wait times and increased clinician capacity [116-121]. Survey data from the Philips Future Healthcare Index showed that 76 % of Indian health professionals and 79 % of patients are optimistic that AI will improve outcomes, indicating strong readiness for these technologies [122]. He concluded that AI’s greatest impact will be realized through tangible health improvements for billions, and that Philips is committed to building this future together with partners in India and beyond [123-125].
Keypoints
Major discussion points
– AI will fundamentally transform healthcare by relieving clinician workload and improving efficiency.
Jacobs stresses that AI’s biggest impact will be in health because “healthcare needs it” and that the “first wave of AI is about removing friction, automating repetitive steps, reducing clicks, supporting documentation, making systems more intuitive” – giving clinicians back precious time [11-14][20-26][30-36].
– Autonomous MRI scanning illustrates how AI can streamline diagnostics and expand access.
He describes a scenario where AI positions the patient, selects optimal protocols, continuously monitors image quality, and delivers precise, consistent scans, thereby reducing back-logs and enabling deployment of MRI units outside traditional hospitals [46-66].
– AI-driven smart hospital rooms turn data overload into actionable insights, improving patient safety.
Jacobs envisions a “smart healing environment” where AI continuously analyses vital signs, suppresses false alarms, flags subtle deterioration hours before it becomes visible, and alerts staff within context, thus preventing crises [80-87].
– Trust, transparency, and continuous regulatory oversight are essential for AI adoption.
He warns that “Healthcare runs on trust” and that AI systems must be transparent, continuously validated, and operate within evolving regulatory frameworks; otherwise adoption will stall [87].
– India is positioned as a global AI-healthcare innovation engine and test-bed.
The speech highlights India’s digital health infrastructure, diverse care settings, and large engineering workforce, arguing that solutions built for India’s scale can inform worldwide models and that Philips’ R&D hubs in Bengaluru and Pune are central to this effort [89-103][116-124].
Overall purpose / goal
The discussion aims to persuade stakeholders-clinicians, policymakers, partners, and the broader public-that AI is already delivering tangible benefits in healthcare, that Philips is leading this transformation, and that India’s unique ecosystem makes it an ideal launchpad for scalable, trustworthy AI solutions that will improve outcomes for billions worldwide.
Tone of the discussion
The tone begins enthusiastic and visionary, celebrating AI’s potential and Philips’ leadership. It then shifts to a practical, evidence-based description of concrete technologies (autonomous MRI, smart rooms). Mid-speech it adopts a cautious, responsible tone emphasizing trust and regulatory alignment. Finally, it moves to an optimistic, collaborative tone, highlighting India’s role and a future defined by measurable health outcomes. Throughout, the speaker maintains a confident and forward-looking demeanor, with the only notable shift being the insertion of a more sober, trust-focused segment.
Speakers
– Roy Jacobs
– Role/Title: President and Chief Executive Officer, Royal Philips (CEO of Philips)[S1]
– Area of Expertise: Healthcare technology, artificial intelligence in healthcare, medical imaging, digital health innovation[S1][S2]
– Speaker 1
– Role/Title: Event moderator/host introducing the keynote speaker[S4]
– Area of Expertise:
Additional speakers:
– (none identified beyond the listed speakers)
Speaker 1 opened the session by thanking Mr Alexander Wang for his remarks and by linking Philips’ AI-driven transformation to “the visionary path of the Prime Minister” for health innovation in India [1-7][8-10]. He then introduced Roy Jacobs, CEO of Philips, as the leader of a storied healthcare-technology company that is placing AI diagnostics and patient monitoring at the core of its mission.
Jacobs asserted that artificial intelligence will have its greatest impact in healthcare because the sector “needs it” and acknowledged the skepticism that can accompany bold promises [11-13]. He outlined the mounting pressures accelerating AI adoption: rising demand for services, a surge in chronic disease, stretched workforces and ever-higher patient expectations [16-20].
He described the “first wave of AI” as a set of friction-reducing technologies that automate repetitive steps, cut unnecessary clicks, support documentation and make systems more intuitive. By listening to clinical conversations, drafting structured notes and prioritising work-lists so urgent cases rise to the top, AI quietly returns valuable time to clinicians without replacing their judgement [30-42].
To illustrate the transformative potential of AI-enabled imaging, Jacobs presented an autonomous MRI scenario. A patient checks in at a regional hospital, and her clinical data are already available to the scanner. AI positions the patient, selects the optimal protocol and continuously monitors image quality, adjusting parameters in real time. The result is a fast, consistent scan that delivers clear, precise images; radiologists receive AI-driven insights and quantitative biomarkers that enable earlier diagnosis, expanded capacity, reduced variability and lower cost. Philips supports this vision through advanced automation, integrated MRI workflows, a dedicated AI engine and helium-free MRI hardware that can be installed outside traditional hospitals, increasing resilience and patient reach [55-78].
Jacobs then moved to the “smart-healing” hospital room, where a unified platform funnels the overload of device data. Agentic AI continuously analyses vital signs, suppresses false alarms and flags subtle deterioration hours before it becomes clinically visible, alerting nurses and physicians with contextual, actionable information while operating within defined guardrails under human oversight [85-89].
He emphasized that “healthcare runs on trust” and warned that trust and the speed of regulatory approval must move in alignment; if they diverge, confidence erodes and adoption stalls. Accordingly, AI systems must be transparent, continuously validated and compliant with evolving regulatory frameworks, providing explainability for clinicians and data protection for patients [87-92].
Turning to India, Jacobs highlighted the country’s robust digital-health infrastructure, notably the Ayushman Bharat Digital Health Mission, which is creating interoperable health records, longitudinal patient data and unique health registries that enable continuity of care at population scale. The mix of urban and rural settings, public and private providers, and high-end tertiary centres alongside primary health centres offers an unparalleled test-bed for scalable, resilient AI solutions that can inform global models [89-103].
Jacobs noted that Philips has been in India for 97 years and that its Innovation Campus in Bengaluru and Healthcare Innovation Centre in Pune host more than 4 000 engineers developing AI algorithms, software platforms and clinical-workflow solutions for both local and global markets. He pointed to significant investments in R&D, manufacturing, digital platforms, AI engineering and clinical collaboration that underpin this work [104-115].
He described the resulting “distributed innovation model”: AI algorithms trained on diverse Indian data improve robustness across geographies, while software platforms engineered in India connect ecosystems in multiple markets, linking local insights with global impact [113-115].
Looking ahead, Jacobs argued that success will be measured not by the number of algorithms deployed but by tangible health outcomes-earlier disease detection, fewer avoidable complications, shorter waiting times and increased clinician capacity [116-121].
He cited the Future Healthcare Index, one of the world’s largest recurring health-research initiatives, which shows that 76 % of Indian clinicians and 79 % of patients are optimistic about AI’s ability to improve outcomes [122-124].
Jacobs concluded with a forward-looking vision: healthcare will move from reactive to predictive, from fragmented to connected and from episodic to continuous, and the systems built today will shape the health of billions tomorrow [125-130]. He reiterated that AI’s greatest legacy will be the billions of lives improved rather than screen-based metrics and pledged Philips’ continued commitment to building an intelligent, trustworthy and predictive care system together with partners in India and around the world [131-135].
Thank you, Mr. Alexander Wang. Our heartfelt gratitude to you for your remarks, for sharing your findings as well. And well, your vision for AI and innovation, it does inspire many of us. Well, ladies and gentlemen, please join me now in welcoming Mr. Roy Jacobs, CEO of Philips. Mr. Jacobs leads one of the world’s most storied healthcare technology companies through a pivotal transformation, putting AI diagnostics and patient monitoring at the center of Philips’ mission. His work sits at the critical intersection of AI and human health, where the stakes could not be higher. Ladies and gentlemen, please welcome CEO of Philips, Mr. Roy Jacobs.
Thank you so much. Good afternoon. It’s a true honor to be here among so many brilliant minds and very bold ambitions. and building of the visionary path of the Prime Minister, I want to share how we are walking that path, designing and developing in India and delivering to the world. And since I have your attention, let me share something that I want to leave behind. We believe that artificial intelligence will have its biggest impact in healthcare. Because healthcare needs it. And maybe some of you are skeptical, but let me try to convince you otherwise. For decades, healthcare has been adopting technology cautiously. And there are different reasons for this. For today, something fundamental has changed in healthcare.
Healthcare systems are under immense pressure. Rising demand. chronic disease, stretched workforces, and high expectations of patients and society. The pressure is only accelerating, and that will also accelerate the adoption of data and AI -driven innovation. AI is already today helping to provide better access to care. It’s embedded in clinical workflows. It’s augmenting human expertise. It’s improving imaging precision. It’s enabling earlier detection. It’s extending care beyond walls. And so the task now is, how do we build an intelligent care system that is predictive, trusted, more effective, and accessible for people everywhere? Thank you. Because ultimately, it’s not about AI or technology. It’s about the people that are served by technology and AI. Just consider for a moment the pressure care teams are under.
If you ask clinicians what they lack most, the answer is almost always time. Time to think. Time to explain. Time to connect with patients. In many health systems, nurses and physicians spend hours on documentation and administrative tasks. Hours not spent on the patient. AI has the full potential to change that equation. The first wave of AI is about removing friction, automating repetitive steps, reducing clicks, supporting documentation, making systems more intuitive. The first wave of AI is about making systems more intuitive. This may not be flashy, but it is transformative and it does generate huge impact. When AI listens to a clinical conversation and drafts structured documentation in the background that is not replacing a clinician, it’s giving time back to the clinician.
When AI prioritizes worklists so that the most urgent cases rise to the top, it’s not making decisions independently. It’s supporting better clinical judgment. This is AI working quietly in the background so clinicians can focus on what matters most. And this is real today. Let me make it even more tangible. Because AI is… is already reshaping what’s possible across healthcare. Imagine a patient in a regional hospital. She has been waiting for weeks for an MRI scan. The backlog is long. The technologists are stressed. Clinicians are not available to support. Traditionally, an MRI required significant manual setup, precise parameter selection, and highly specialized expertise to conduct a scan. Variability was inevitable and access was limited. Now imagine something completely different.
The patient arrives for her MRI and checks in smoothly. Her clinical information is already available to the system that will conduct the scan. AI helps position her first -time right accurately and selects the optimal scan protocol. It’s tailored to her autonomy. And as the scan runs, the image quality is continuously monitored and adjusted automatically. The scan is now able to see the scan. The scan is now able to see the scan. The scan is now able to see the scan. The scan is now able to see the scan. The scan is now able to see the scan. This is autonomous MRI scanning. The result? Clear, precise images, delivered efficiently and consistently. The radiologist receives AI -driven insights and quantitative biomarkers.
And Philips is working to make that a reality. It means more patients diagnosed earlier. Earlier detection of chronic and complex conditions. It expands capacity and access to care. It reduces variability. It scales expertise. And over time, it helps reduce the overall cost of care. And at Philips, we have been laying the groundwork for this future. Through advanced automation, integrated MRI workflows, and an AI engine, that scans faster while enhancing quality. We are also leaders in helium -free MRI systems. That’s a hardware breakthrough. And together, that does not only make it more sustainable, but it allows us to install MRI systems outside of the hospital, closer to patients, where it was previously not visible to go to.
That means even more access, more resilience, and more patients served. But diagnosis is not the only part of the story. Let’s enter a hospital room. There is no lack of data. Actually, there’s an overload of data. Many devices, alarms going off, dashboards to be read. Now image a hospital room transformed into a smart healing environment. Data from devices flow into a unified platform. Where AI continuously analyzes vital signs and clinical trends. False alarms are reduced True risks are elevated early A subtle deterioration pattern in patient is detected by AI hours before it comes visible The nurse is alerted within context, not with noise And the physician receives predictive insights Preventative action can and will be taken The true patient crisis never fully materializes That is the power of agentic AI Software that can perceive, reason and act within defined guardrails Always under human oversight It reduces burden It anticipates risks And it turns data into action That’s how we can give time back With all of this With all of this excitement We must be clear about one thing Healthcare runs on trust AI in healthcare needs to be transparent It must be validated continuously Not approved just once It must operate within regulatory frameworks And those evolve as the technology evolves Clinicians need to understand how systems arrive at their recommendations Patients need to know how their data is protected And regulators need confidence that safety and efficacy is rigorously monitored all the time Innovation and governance must advance together With speed Because trust determines adoption And adoption determines the success of valuable application of AI in healthcare If they move at different speeds Trust erodes If they move in alignment, adoption accelerates.
Now, I’m very happy to be back in India. India represents a remarkable opportunity in this transformation, standing at the intersection of skill, digital infrastructure, and ambition. The country’s digital infrastructure, including initiatives under the Ashman Bharat Digital Health Mission, is laying the foundation for interoperable health records and longitudinal patient data, the foundation for big data play. Unique health ideas and digital registries create the possibility for the continuity of care for population at scale. This matters enormously, as we have heard earlier today. AI systems thrive on structured, high -quality longitudinal data. When patients can be followed across settings, AI systems thrive on structured, high -quality longitudinal data. From primary care, to hospital, to diagnostics, and to the home, the power of predictive analytics increases dramatically.
But India also brings something else to the table. Real -world complexity at scale. Urban and rural settings. Public and private systems. High -end tertiary care systems and primary health centers. The diversity of care environments creates an unparalleled testbed for scalable, resilient solutions. Solutions built for India’s scale and constraints have the potential to inform global models of care. And at Philips, we see India as a global innovation engine. We are already here for 97 years. And through our Philips Innovation Campus in Bengaluru and the Healthcare Innovation Center in Pune, we have made significant investments in R &D, manufacturing, digital platforms, AI engineering and clinical collaboration. Our teams in India contribute to global development as much as to local development.
And they do that across imaging, monitoring and connected care. The work done here does not stay here alone. It shapes solutions deployed around the world. For example, AI algorithms developed and validated with diverse data sets here improve robustness across geographies. That’s done by more than 4 ,000 engineers that we have in India, developing for India and for the world. These software platforms, engineered here, connect ecosystems in multiple markets. Clinical workflow solutions co -created with Indian partners inform designs that scale globally, exactly as the Prime Minister says we are doing that today. And this is the kind of distributed innovation model that healthcare needs. Not isolated breakthroughs, but integrated, globally connected ecosystems. If we look ahead, in 10 years, success will not be defined by the number of algorithms deployed.
It will be defined by the outcomes they generate. Earlier detection of disease. Fewer avoidable complications. Shorter waiting times. Greater access. More times for clinicians, nurses, and technicians. The Philips Future Healthcare Index, one of the world’s largest recurring health research initiatives, tells a clear story. 76 % of Indian healthcare professionals are optimistic that AI can help them improve patient outcomes. 79 % of the Indian patients are optimistic that AI can improve their health. Their personal healthcare. This shows us that patients in India are ready for this And that Indian healthcare professionals are asking for this And so are policymakers and government as we heard today The promise is real It’s for today Healthcare will move from reactive to predictive From fragmented to connected From episodic to continuous The systems we build today will shape the health of billions tomorrow So let me return to where I started AI will have its greatest impact in healthcare for the world And when we look at this in a decade from now We will look at the outcomes and impact it has delivered It will look at the outcomes and impact it has delivered It will not be remembered for what is optimized on the screen but for the billions of lives that we could improve with it.
That’s the responsibility. That’s the exciting opportunity. And that’s the future that we are committed to building together with all our partners, together here in India and across the world. Thank you so much.
“Roy Jacobs is the President and Chief Executive Officer of Royal Philips (Philips).”
The knowledge base lists Roy Jakobs as President and Chief Executive Officer of Royal Philips, confirming his role. [S1]
“Philips’ AI work spans imaging, monitoring and connected care, with solutions deployed globally and validated with diverse data sets.”
The source notes that AI algorithms are developed and validated with diverse data sets and are applied across imaging, monitoring and connected care, shaping solutions deployed worldwide. [S2]
“India’s digital‑health infrastructure includes the Ayushman Bharat Digital Health Mission, which is creating interoperable health records and longitudinal patient data.”
The knowledge base explicitly mentions India’s digital infrastructure and initiatives under the Ayushman Bharat Digital Health Mission. [S45]
“India’s young demographic and entrepreneurial ecosystem are expected to produce global leaders addressing health‑AI challenges.”
The source adds that India’s youthful workforce and vibrant entrepreneurial ecosystem are seen as a source of future global leaders in health-AI innovation. [S57]
The discussion shows clear agreement that AI is a crucial, inspirational, and needed technology for healthcare transformation, with both speakers emphasizing its impact.
High consensus on AI’s significance, though the depth of agreement is limited to introductory statements; this suggests strong shared momentum for AI initiatives in health but leaves other issues (trust, governance, capacity) less jointly addressed.
The discussion shows strong alignment rather than conflict. Speaker 1’s introductory remarks and Roy Jacobs’s detailed presentation both champion AI as a transformative force, especially in healthcare. No substantive contradictions or opposing viewpoints emerge between the participants.
Minimal disagreement; the dialogue is largely consensual, indicating a unified stance on advancing AI in health and related development agendas.
The identified comments collectively shaped the discussion from an introductory celebration of AI potential to a nuanced, multi‑dimensional conversation. Early statements set an ambitious vision, while the focus on clinicians’ time constraints and the ‘first wave’ of AI grounded that vision in practical workflow gains. Concrete examples like autonomous MRI and smart healing environments turned abstract ideas into vivid possibilities, energizing the audience. The pivot to trust, governance, and outcome‑based success introduced necessary caution and a framework for sustainable adoption. Finally, positioning India as a global testbed broadened the scope to include strategic, infrastructural, and collaborative dimensions. Together, these pivotal remarks guided the flow, deepened analysis, and balanced optimism with responsibility, steering participants toward a holistic view of AI’s role in transforming healthcare.
Disclaimer: This is not an official session record. DiploAI generates these resources from audiovisual recordings, and they are presented as-is, including potential errors. Due to logistical challenges, such as discrepancies in audio/video or transcripts, names may be misspelled. We strive for accuracy to the best of our ability.
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