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Thinkers360’s Top 10 Education Thought Leaders recognise experts who shape how learning evolves in organisations and society. Their work focuses on areas such as AI in education, leadership development, digital learning models, and future skills, helping institutions and professionals adapt to changing knowledge and work environments. The work contributes clear ideas on how organisations and leaders should understand and apply learning in the context of AI and organisational

AI Orchestration: Coordinating Intelligence at Scale Artificial intelligence is entering organisations through many separate tools, models, and platforms. Marketing teams use generative AI, operations deploy automation, and data teams develop predictive systems. The challenge is no longer access to AI but coordination across these capabilities. AI orchestration refers to the structured coordination of models, data flows, human oversight, and governance so that multiple AI sys

Human-centred AI is no longer about fancy tools. It reshapes roles, power, and responsibility. The real test now is leadership: when to slow decisions, protect judgement, and keep accountability human. #leadershipresponsibility; #aigovernance; #decisionaccountability; #humanintheloop; #trustinai; #responsibleautomation; #futureofwork; #managementandai Article Link

𝐘𝐨𝐮 𝐝𝐨𝐧’𝐭 𝐧𝐞𝐞𝐝 𝐭𝐨 𝐥𝐞𝐚𝐫𝐧 𝐏𝐲𝐭𝐡𝐨𝐧 𝐭𝐨 𝐠𝐨𝐯𝐞𝐫𝐧 𝐀𝐈 You didn't need to learn COBOL to manage the mainframe, and you don't need to learn Python to govern AI in ServiceNow. AI risk is a business process issue, not a coding bug. Driving Business Process Evolution requires AI Governance and Risk Stewardship.( Linda Restrepo ) ☺️ Why are we still trapping cross-functional accountability in technical silos? #aigovernance #businessprocessevolution #riskstew

AI is becoming more capable but harder to understand. Decisions are automated, yet humans remain accountable. This is why explainability must move beyond models and outputs, toward helping people keep clarity, confidence, and judgement when working with AI systems over time. 💁 #explainableAI #AIgovernance #AIleadership #HumanCenteredAI full article

One Year Later: What We Actually Learned This year does not start with a new promise. It starts with unfinished work. The question is no longer whether AI can be tested, but whether organisations can judge what those tests really showed. 2026 opens as a year of choices: what to close, what to fix, and what deserves the discipline of staying power rather than another experiment. One year later, the main lesson is simple. Learning did not come from more pilots or smarter tools.