4 Themes for Sustainable AI Adoption in Life Sciences

What does it take to create sustainable #AI adoption in life sciences? After attending the 2026 ISPE AI in Life Sciences Summit, Clarkston's Anna Ivashko shares four themes that surfaced across conversations with industry leaders: https://hubs.ly/Q04nl8jx0 → Build trust by upskilling users for AI adoption -- not forgetting the #HumanScience that is necessary for success. → Keep #HumansInTheLoop with clear oversight, training, and accountability. → Make AI #explainable for auditors, governance boards, and other stakeholders. → Prioritize data and process #readiness to create scalable, practical use cases. Continue the conversation with our team here: https://hubs.ly/Q04nl2yF0 #LifeSciences #ArtificialIntelligence

🔄 What happens when AI reviews its own work? One of the fastest-growing ideas in AI is the concept of **self-improving loops**. In healthcare analytics, the workflow can look like this: 📊 Generate insight ✅ Validate insight 📈 Compare with historical outcomes 🔁 Refine automatically The objective isn't to remove humans from the process. 🎯 The objective is to continuously improve the quality, accuracy, and reliability of recommendations while keeping human oversight at the center. The most impactful AI systems won't be the ones that generate the first answer. They'll be the ones that learn, evaluate, and improve with every cycle. 🏥 That's where the future of healthcare analytics is headed. #SelfImprovingAI #LoopEngineering #HealthcareInnovation #HealthcareAI #AgenticAI #DataAnalytics #AITransformation #DigitalHealth

🧠 🤖 The ‘Med AI’ Capsule Newsletter — New Edition Out Now! This issue simplifies Synthetic Data in Healthcare with a 5‑QnA primer: what it is, why it’s attracting attention, where it fits into AI development and clinical workflows, and the key risks and limitations you need to keep in mind before trusting synthetic‑data–driven results. ✨ Plus this month’s Med AI gems: - 4 research picks - 3 learning resources - 2 worth‑attending events - 1 industry spotlight If you’ve been hearing about synthetic data and wondering how it might impact AI research, education, or quality‑improvement projects—this edition is for you. Explore the full edition here 👇 https://lnkd.in/gRmGHGUx #SyntheticData #ClinicalAI #MedicalAI #AIinHealthcare #DigitalHealth #HealthTech #ResponsibleAI #ClinicalWorkflows #DecisionSupport #HealthInnovation

It's #AIAppreciationDay, and we’re reflecting on how healthcare AI is evolving from prediction to partnership. The greatest opportunity is not replacing clinicians and researchers. It is expanding what they can see, accelerating discovery, and giving them more time to focus on judgment, care, and the questions that matter most. Our latest perspective from Chief AI Officer Anand Oka explores how agentic AI, real-world data, rigorous evaluation, and human expertise can work together to support better science, better decisions, and better health outcomes: https://tr.vet/4pl0XDe

As AI moves beyond standalone applications towards networks of agents operating across healthcare, finance, public services, and research, understanding these collective dynamics is becoming increasingly important. At our workshop on multi-agent AI systems, researchers from across disciplines are exploring some of the field's most pressing questions: 🔹 What happens when autonomous agents have conflicting goals? 🔹 How might agent interactions shape markets, trust, and decision-making? 🔹 What governance frameworks can ensure these systems remain safe and aligned with human values? As multi-agent AI systems become embedded across sectors, what do you think is the most important challenge we need to solve now to ensure they deliver positive outcomes for society? #AI #ArtificialIntelligence #MultiAgentSystems #ResponsibleAI #ResearchCollaboration #FutureOfAI #UniversityOfWarwick #DDSAISpotlight #interdisciplinary Long Tran-Thanh Jason Snow

Great work Mats! The biggest challenge facing Life Sciences today? Accelerating innovation without losing sight of compliance. Mats Govaerts, AI Lead Life Sciences & Healthcare at Sopra Steria, works at the crossroads of AI, regulation and digital transformation. Discover how he helps organisations adopt innovative technologies while meeting the industry's strict regulatory requirements. 👉 Read Mats' full interview:https://lnkd.in/dkKVgndg #LifeSciences #AI #Compliance #Innovation #DigitalTransformation #SopraSteria

"The integration of artificial intelligence is not just a possibility; it is an inevitability." - Edward Marx Healthcare isn't preparing for a distant future, it's navigating it today. In the foreword to ‘Generative AI: Unlocking the Next Chapter in Healthcare,’ Edward Marx frames AI as a transformational force that will redefine how care is delivered, decisions are made, and innovation is accelerated. Whether you're a healthcare executive, clinician, innovator, or digital health leader, this book offers practical insights to help you lead with confidence in the era of Generative AI. 📖 Discover how AI can enhance healthcare while keeping people at the center. 👉Order your copy now: https://hubs.la/Q04pjg2K0 Rohit M. Ritu M Uberoy M. Uberoy #GenerativeAI #HealthcareAI #DigitalHealth #HealthIT #HealthcareInnovation #TheBigUnlock

Mats is not only a great guy to work with, he breathes innovation and AI and applies this as efficiently as possible in his field of expertise, Life Science. The biggest challenge facing Life Sciences today? Accelerating innovation without losing sight of compliance. Mats Govaerts, AI Lead Life Sciences & Healthcare at Sopra Steria, works at the crossroads of AI, regulation and digital transformation. Discover how he helps organisations adopt innovative technologies while meeting the industry's strict regulatory requirements. 👉 Read Mats' full interview:https://lnkd.in/eha9DqEx #LifeSciences #AI #Compliance #Innovation #DigitalTransformation #SopraSteria

If your clinical AI investments aren't hitting the mark, don't blame the algorithm. The industry has made a massive bet on artificial intelligence to solve site selection, feasibility predictions, and protocol design. Yet, many clinical operations teams are still missing forecasts and dealing with misaligned site recommendations. The natural instinct is to swap vendors or look for a more sophisticated model. But the truth is much simpler: Your AI is only as good as the data feeding it. To get real value out of clinical AI, we have to look past the algorithm and focus on data foundation. Read the full breakdown on why clinical ops teams are rethinking their AI strategies: https://ow.ly/iqf750ZebZv #ClinicalAI #ClinicalOperations #HealthTech #AIinHealthcare #DataDriven #ClinicalTrials #FeasibilityStudies #ProtocolDesign #MedicalInnovation

https://lnkd.in/dS36NPB9 The post about Claude shows a key shift in AI: from isolated tools to systems that actually live inside workflows. Features like Projects (memory, structure, continuity) make AI less about one-off answers and more about ongoing context. In medicine, this matters even more — clinical work is continuous, not fragmented. We’re moving from asking AI questions → to working with AI that understands context over time. #AI #Claude #HealthcareAI #DigitalHealth #MedicalInnovation #FutureOfWork #management #technology #innovation #goals #future #Humanresources #creativity #futurism #socialmedia #marketing