How to leverage AI in healthcare for success

We talk a lot about how AI will “save time” in healthcare. But maybe that’s not the right question anymore. Sure, automation helps with scheduling, notes, and paperwork. That’s valuable. But the AI systems now entering hospitals and clinics are doing something different — they’re interpreting, predicting, even prompting us to rethink decisions. And that takes time. What if the real value of AI isn’t speed, but pause? Not faster decisions, but smarter ones? If an AI alert makes you stop, reevaluate a diagnosis, or catch something early — is that a delay, or is that better medicine? This isn’t just about tools. It’s about how we define value in clinical care. So here’s the question we’re asking this week: Is time still the most important metric for judging AI in healthcare — or is it time we updated our thinking? What do you think?

MIT just published new research: 95% of AI pilots never reach production. Why? Because most AI solutions look promising in a pilot but collapse at scale. They aren’t fine-tuned, they don’t adapt to real-world processes, and they fail to integrate into existing workflows. MIT’s findings are striking: In-house AI projects succeed only ~33% of the time With specialized providers, success rates double to ~67% In healthcare, this gap is even sharper. Hospitals and clinics don’t run on generic workflows and that’s why generic tools rarely survive beyond pilots. By contrast, tailored, workflow-ready agents fine-tuned to healthcare use cases can reduce workload and deliver measurable ROI. Where most pilots stall, safe and our production-ready solutions move forward. And that is exactly where the market is shifting: from hype-driven pilots to trusted specialized providers who can scale AI safely and effectively. For healthcare leaders, the real question is no longer “Should we test AI?” It’s “Which workflows can we improve with AI and how do we get it into production safely and effectively?” BTW we’re hiring! If you’re passionate about building AI that makes a real impact in healthcare, apply through the link: https://lnkd.in/gXavDRrS

High-tech manufacturers are finding new ways to scale efficiency — combining real-time insights with intelligent capabilities that reduce planner strain. The latest installment in our high-tech blog series spotlights how decision intelligence helps planners manage rising decision volume with less manual effort, shifting their focus from firefighting to strategy. Leveraging specialized skills like the Dynamic Inventory Balancing and Reallocation Skill, Aera, the decision intelligence agent, streamlines shortage resolution, reduces exception handling, and keeps supply chains aligned with business priorities. Read the full post to learn how Aera applies real-time data, AI, and automation to ease planner workloads and improve efficiency at scale: https://lnkd.in/gX2UW9_d #DecisionIntelligence #SupplyChainInnovation #AgenticAI

MIT’s latest research shows that 95% of AI pilots fail. Not because the technology doesn’t work, but because of how organizations approach adoption. In his latest blog, Raheel Retiwalla explains why most pilots stall—and how healthcare leaders can beat the odds by focusing on governance, operational workflows, and agentic AI. https://hubs.li/Q03DSFCn0

AI isn’t magic. It’s 10 real-world use cases, the hidden tech in your voice assistant, and the rise of LLMs. We’ve explained all three, without the complex jargon. We focus on what leaders need to know: 1. Where AI is already transforming industries. 2. The technology is driving everyday tools like voice assistants. 3. Why LLMs are shaping the next generation of enterprise solutions. These aren’t abstract concepts. They’re the foundations of the AI systems businesses are adopting right now. We’ve put together a series of concise explainers in the comments below to help decision-makers move beyond jargon and into real-world application. Read more in the comments below

Doctor vs Data AI in healthcare isn’t “coming.” It’s already here. It knows patterns across millions of cases. It spots what even the sharpest eyes might miss. But here’s the catch: When AI says one thing and your doctor says another, WHO DO YOU TRUST? A doctor brings experience, intuition, and empathy. AI brings scale, speed, and global insight. One speaks from intuition. The other from information. And that’s the dilemma patients are about to face. In the end, trust might not lie in choosing one over the other, it might lie in how they work together.

Are concerns about operational efficiency and AI integration at the top of your agenda? It's crucial to stay ahead in healthcare management by understanding today's strategic challenges. In our latest white paper, we delve into how to optimize healthcare operations and leverage AI for improved outcomes. Uncover insights that can redefine your management approach and drive innovation. Follow the link : https://lnkd.in/gXk82xFB #B2BMarketing #StrategicROI #MarketingLeadership #DigitalMarketing #MarketingStrategy #CMOInsights

"A vendor we trust" is king! Specific priorities for selecting GenAI vendors are shown in the table below. Winning GenAI vendor examples highlight capabilities such as learning from feedback (66% of executives want this), retaining context (63% require this), and enabling deep customization to specific workflows - they start at workflow edges with significant tailoring, then scale into core processes. - from the new MIT "The GenAI Divide State of AI in Business 2025" report. #AI #Enterprise #GenAI

Why slog through data or wait weeks for consultants when AI delivers answers in seconds? In this excerpt from our webinar Cutting Healthcare Costs with Price Transparency Data we discuss the results of our experiment we ran in real-time, where Gigasheet AI analyzed millions of price transparency datapoints and produced a full form market analysis in minutes. With Gigasheet AI it's easy to verify the responses that the agent provides. Users can spot-check and ensure accuracy, as the same data is accessible via the UI for fact-checking. The potential for AI big data analysis in healthcare is massive. #AI #dataanalysis #businessintelligence #innovation #technology #pricetransparency #healthcare #healthinsurance

Yes, 𝟴𝟬% 𝗼𝗳 𝗺𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗲𝗿s are already exploring Generative AI, but adoption isn’t the same as success. The real impact lies in process optimisation, predictive maintenance, demand forecasting, and sustainable operations. 𝗕𝘂𝘁 𝗵𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲: pilots often fail when expectations don’t match reality. The key is:  • Choosing the right use cases  • Building a strong data foundation  • Scaling what works 𝗔𝘁 𝗨𝗦𝗠 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗦𝘆𝘀𝘁𝗲𝗺𝘀, we help manufacturers move from pilots to measurable ROI, transforming AI experiments into competitive advantages.  Where are you in your GenAI journey: piloting, scaling, or still exploring? https://lnkd.in/gTSHZK5r #GenerativeAI #ProcessOptimization #AILeadership #USM #SmartManufacturing #IndustryInnovation #IndustrialAI