The new ADIPEC Global Energy Report 2026 caught my attention: 22% of oil and gas insiders name AI-driven efficiency as a top commercial opportunity today, versus 27% in ten years. A signal of changing business priorities. Join > adipec.com @ADIPECOfficial Partner. Another finding adds context: 81% of energy insiders expect AI-driven electricity demand to exceed current forecasts. This creates a closer relationship between the energy and technology industries. Energy companies need to understand how computing demand will evolve, and technology companies must understand the capacity and operating requirements of energy systems. I find this mutual dependency particularly interesting because investment decisions in one industry will increasingly affect the other. ADIPEC 2026, taking place from 2-5 November in Abu Dhabi, offers an opportunity to examine how these developments will shape the energy business. Energy. Intelligence. Impact. #ADIPEC2026 #ADIPEC #Energy #AI

AI creates business value when strategy, workflows, and execution work together. Leaders need to connect these layers, redesign how work gets done, and build the skills that turn AI capabilities into measurable outcomes. Source @McKinsey Link mck.co/4hVixKN v @antgrasso

Two patients have the same diagnosis. Would the same treatment be right for both? Clinical decision support helps clinicians examine the differences. Patient information supplies the context. Medical knowledge helps interpret it before a decision is made. Microblog @antgrasso Consider a clinician preparing to prescribe a medication. The patient record contains kidney function results that may affect the appropriate dose. A clinical decision support system can combine that information with medical references and flag a possible dosing concern for review. Now the clinician has something to examine. Are the patient data current? Does the recommendation make sense in this particular care situation? The software can bring relevant evidence to the attention of the clinician while the decision is being considered. The clinician interprets that evidence and decides how to proceed. The purpose is to make medical knowledge available in the context of the patient, without transferring clinical judgment to the software. #ClinicalDecisionSupport #DigitalHealth