Healing Green: Sustainable AI Transforming Healthcare
By Dr. Hernani Costa — May 22, 2025
How energy-efficient AI is revolutionizing patient care while shrinking medicine's carbon footprint
Good morning and welcome to First AI Movers Pro! Today, we will start with the news and save the main story for last, as it is a bit long, and you might not have the time right now. We will delve into how companies are deploying AI ethically and sustainably. Our lead story examines energy-efficient AI in healthcare—why power use matters, what industry leaders are doing to shrink AI's carbon footprint, and how smarter energy choices can lead to better patient outcomes. Let's get into it.
Quick Takes about Recent AI News You Should Know
- Google's AI Assistant Gets Proactive: At Google I/O 2025, the company unveiled Project Astra, an AI assistant that "decides for itself when to speak" by observing context and can proactively help users (for example, correcting a student's homework mistake in real time). Google's push into omnipresent, proactive AI underscores how our digital helpers are becoming more autonomous – and raises new questions about AI etiquette and trust.
- Startup's AI 'Employees' Do 80% of Work: Belgian startup Ravical secured €7.3 million in funding to deploy AI agents as "virtual employees" in tax, legal, and insurance firms. The CEO claims these agents handle up to 80% of routine tasks – from retrieving data to reading regulations – allowing human experts to focus on complex counsel. Notably, Ravical insists no jobs will be lost; the goal is to free up humans for higher-value work, highlighting a collaborative vision for AI in professional services.
- ASUS Bets Big on Health AI: At Computex 2025, ASUS announced a suite of AI-driven healthcare tools. One highlight is the HealthAI Genie for its VivoWatch, a generative AI wellness coach that analyzes your vitals twenty-four seven and gives personalized health tips. ASUS also debuted an AI-powered handheld ultrasound that can automatically measure organs and cut scanning time, and an endoscopy AI system already in use across dozens of hospitals. It's a glimpse of AI making medical devices smarter, from wearables to clinical imaging.
- Robotaxis Gain Speed: Autonomous driving firm WeRide and Uber announced plans to expand their robotaxi services to 15 new cities worldwide. After successful trials in Abu Dhabi (and an upcoming launch in Dubai), Uber is investing $100 million more in WeRide to scale self-driving rides via the Uber app. With a fleet of 1,200+ autonomous vehicles already, WeRide's global push shows how quickly driverless tech is moving from pilot to mainstream – though each new city will test local regulatory and safety readiness.
- AI Aids Epilepsy Surgery: New research suggests large language models like ChatGPT might help pinpoint the origin of epileptic seizures in the brain. Identifying this epileptogenic zone is key for surgical cures, but currently has only a ~50–60% success rate. LLMs could analyze complex patient data and seizure descriptions to predict the exact spot more accurately, potentially boosting surgery success for the ~30% of epilepsy patients who don't respond to meds. It's an exciting example of AI's pattern-recognition prowess being applied in high-stakes medicine.
Now to the …
Lead Story: Greener AI in Healthcare – Ethically Powering Innovation
AI is transforming healthcare from diagnostics to hospital operations – but it comes with an environmental price tag. Training a single large AI model can emit as much CO₂ as five cars driven for 12 years. That's alarming for healthcare, a sector already responsible for 4.4% of global greenhouse gases. In short, if healthcare AI is to do no harm, it must mind not just patients, but the planet. As one research team put it, "the healthcare industry continues to embrace AI… it is imperative to prioritize sustainability and environmental responsibility". Ethically, AI's use now needs to align with broader corporate climate goals, mainly when our health institutions' mission includes safeguarding public health from climate change.
Why energy use matters: Power-hungry AI systems can undermine sustainability efforts and even budgets. Consider generative AI: A single query to an AI like ChatGPT guzzles enough electricity to charge a smartphone 11 times, plus ~20 milliliters of cooling water. In fact, ChatGPT consumes ~15× more energy per query than a Google search. Its daily CO₂ emissions equal those of 400–800 U.S. homes. Now, imagine deploying similar AI across hospitals – the carbon footprint could be enormous. Moreover, strict privacy means many healthcare AI models run locally (not just in hyper-efficient cloud data centers), potentially increasing energy use. All this adds up to a new ethical mandate for corporate healthcare leaders: use AI responsibly by keeping its energy appetite in check.
Industry response – doing more with less: The good news is that companies and researchers are taking action to build "energy-efficient AI models" for healthcare through AI automation consulting and operational AI implementation strategies. This means redesigning algorithms and systems to do the same work with fewer computations. Techniques like model compression, quantization, and pruning are being adopted to slim down AI models without sacrificing accuracy. Smaller, task-specific models (so-called narrow AI) are favored over giant general ones to cut power draw. A recent study advises hospitals to always ask: Do we really need a huge model like an LLM? Often, a smaller fine-tuned model will do, and "smaller, finely tuned LLMs can outperform larger ones" while using far less resources. Developers are also optimizing code and even tweaking how prompts are used (e.g., shorter, more focused prompts) to reduce unnecessary computation. In short, a culture of AI energy diligence is taking hold, with teams treating computing power like a precious resource.
Greening the infrastructure: Beyond the code itself, corporate IT departments are overhauling infrastructure to reduce AI's footprint through workflow automation design and AI tool integration. Data centers are being retrofitted or relocated to use renewable energy sources. Tech giants like Google and Microsoft have pledged to run their cloud regions on 100% carbon-free power by 2030, which will benefit any healthcare AI hosted there. Hospitals and AI vendors are also embracing "green computing" practices – deploying energy-efficient hardware (think next-gen low-power AI chips and servers) and intelligent power management in off-peak times. Some imaging equipment makers are innovating for efficiency: for example, Philips introduced helium-free MRI scanners that reduce resource use and energy for cooling. Even healthcare facilities themselves are going green: the UK's NHS aims for net-zero emissions by 2040, pushing its tech suppliers to deliver low-carbon solutions. All these steps ensure the backend running AI – from server racks to MR machines – sips power instead of guzzling it.
AI as part of the solution: Ironically, AI can help save energy while it consumes energy, and smart healthcare companies are leveraging that through business process optimization. Optimizing operations via AI can yield net energy gains. For instance, operating rooms are notorious energy hogs (lights, ventilation, equipment running regardless of need). By using AI to analyze schedules and adjust settings on the fly, some hospitals cut OR energy use by 25% in a pilot study. Remarkably, the energy saved by AI-driven efficiency far outweighed the energy the AI itself used – a net win for the environment. From smart building systems that dial down HVAC when not needed, to AI systems that streamline patient flow (reducing idle scanner time and paper waste), data-driven optimizations can "flip the script" for hospital energy use. This means an ethical AI deployment isn't just about minimizing harm – it can actively do good by cutting waste elsewhere.
Why it improves outcomes at scale: Done right, sustainable AI lets healthcare organizations scale innovations without guilt or breaking the bank through AI readiness assessment and digital transformation strategy. When each model is leaner and each server greener, you can deploy AI across many clinics and tasks affordably and within carbon limits. That translates to more lives saved and better care delivered. Doctors get AI assistance everywhere – reading scans, triaging patients, monitoring vitals – not just at flagship centers that can pay huge cloud bills. Crucially, these environmental efforts often dovetail with clinical gains. Efficient AI tends to be faster and more accessible, meaning quicker decisions and broader reach. And hospitals reinvesting energy cost savings into patient services improve care quality. As the World Economic Forum observed, it's a positive feedback loop: "better data leads to better care, better outcomes, and a more sustainable use of resources." In other words, green AI is good medicine. By prioritizing sustainability and building trust in AI through AI governance & risk advisory, healthcare leaders are redefining what's possible – delivering high-tech care that heals patients and protects our shared world.
Thanks for reading First AI Movers Pro! If you found value in today's edition, please share it with colleagues or friends who care about the future of AI. Do you have thoughts on sustainable AI or examples from your organization? Hit reply and let me know. I love hearing from our community. Stay tuned for more AI insights in your inbox, and let's keep driving innovation responsibly. Until next time, stay curious and stay green!
Written by Dr. Hernani Costa and originally published at First AI Movers. Subscribe to the First AI Movers Newsletter for daily, no‑fluff AI business insights and practical automation playbooks for EU SME leaders. First AI Movers is part of Core Ventures.
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