The future of workplace learning is no longer a distant vision—it is already shaping how organizations grow. This week, I revisited The Future of Learning at Work by Frédérique Bergeron. AI. Neuroscience. Personalization. What impressed me most were the case studies from Unilever, AT&T, and Walmart, showing how these trends are being embedded into scalable L&D strategies. As the founder of an L&D company, my key reflection is that future‑ready organizations will move beyond traditional training toward adaptive ecosystems that continuously engage, personalize, and prepare employees for rapid change. 👉 I’d love to hear from my network: How is your organization reimagining learning to stay future‑ready? #FutureOfWork #LearningAndDevelopment #AIinLearning #WorkforceTransformation #LeadershipDevelopment #PersonalizedLearning
How AI, Neuroscience, and Personalization are changing L&D strategies at Unilever, AT&T, and Walmart
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"...Actionable takeaway for leaders: When you build with AI agents, don’t just focus on intelligence (L1/L2). Ask: What does this agent care about? How does it decide what matters next? Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team..." #AI
#1 Top Voice in AI & Automation | Award-Winning Expert | Best-Selling Author | Recognized Keynote Speaker | Agentic AI Pioneer | Forbes Tech Council | 2M+ Followers ✔️
🧠 A massive paper dropped — 264 pages from researchers across 20 universities and AI labs (Stanford, Yale, CIFAR, DeepMind, Microsoft Research, MetaGPT…). It’s about what researchers now call “Foundation Agents.” And here’s the surprising part: their design is starting to look less like software… and more like a brain. 🧠 And it might be the most comprehensive roadmap yet on the future of AI agents. Look at this chart. It maps different human brain regions to their state of progress in AI. Some are already well-developed (like visual perception). Others are barely touched (like empathy, self-awareness, and emotional processing). 👉 Here’s the insight most people miss: AI agents don’t fail because they’re weak at logic or memory. They fail because they’re missing the “L3” regions — the emotional, contextual, and motivational layers that guide human decisions every second. That’s why many AI pilots collapse in business: we deploy “brains” with strong vision and reasoning, but no motivation or empathy. In practice, it means brilliant outputs with no sense of priority, context, or trust. 💡 Actionable takeaway for leaders: When you build with AI agents, don’t just focus on intelligence (L1/L2). Ask: What does this agent care about? How does it decide what matters next? Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team. Because in the end, the future of agents won’t just be about smarter brains. It will be about brains with values. PS: The irony? We might be building empathy into machines before mastering it ourselves. 👉 Would you trust a system that thinks more like a brain — or do you prefer AI to stay purely mechanical? Paper link: https://zurl.co/PkJGs #AI #AgenticAI #FutureOfWork #Neuroscience #FoundationAgents
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We can no longer continue to think in terms of software-based applications. A good start might be Hume's solution: placing feelings (which can be experienced and which we have experience of) as an epistemological source in relation to morality and the arts. AI will be different when it becomes part of a group.
#1 Top Voice in AI & Automation | Award-Winning Expert | Best-Selling Author | Recognized Keynote Speaker | Agentic AI Pioneer | Forbes Tech Council | 2M+ Followers ✔️
🧠 A massive paper dropped — 264 pages from researchers across 20 universities and AI labs (Stanford, Yale, CIFAR, DeepMind, Microsoft Research, MetaGPT…). It’s about what researchers now call “Foundation Agents.” And here’s the surprising part: their design is starting to look less like software… and more like a brain. 🧠 And it might be the most comprehensive roadmap yet on the future of AI agents. Look at this chart. It maps different human brain regions to their state of progress in AI. Some are already well-developed (like visual perception). Others are barely touched (like empathy, self-awareness, and emotional processing). 👉 Here’s the insight most people miss: AI agents don’t fail because they’re weak at logic or memory. They fail because they’re missing the “L3” regions — the emotional, contextual, and motivational layers that guide human decisions every second. That’s why many AI pilots collapse in business: we deploy “brains” with strong vision and reasoning, but no motivation or empathy. In practice, it means brilliant outputs with no sense of priority, context, or trust. 💡 Actionable takeaway for leaders: When you build with AI agents, don’t just focus on intelligence (L1/L2). Ask: What does this agent care about? How does it decide what matters next? Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team. Because in the end, the future of agents won’t just be about smarter brains. It will be about brains with values. PS: The irony? We might be building empathy into machines before mastering it ourselves. 👉 Would you trust a system that thinks more like a brain — or do you prefer AI to stay purely mechanical? Paper link: https://zurl.co/PkJGs #AI #AgenticAI #FutureOfWork #Neuroscience #FoundationAgents
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🧠 A massive paper dropped — 264 pages from researchers across 20 universities and AI labs (Stanford, Yale, CIFAR, DeepMind, Microsoft Research, MetaGPT…). It’s about what researchers now call “Foundation Agents.” And here’s the surprising part: their design is starting to look less like software… and more like a brain. 🧠 And it might be the most comprehensive roadmap yet on the future of AI agents. Look at this chart. It maps different human brain regions to their state of progress in AI. Some are already well-developed (like visual perception). Others are barely touched (like empathy, self-awareness, and emotional processing). 👉 Here’s the insight most people miss: AI agents don’t fail because they’re weak at logic or memory. They fail because they’re missing the “L3” regions — the emotional, contextual, and motivational layers that guide human decisions every second. That’s why many AI pilots collapse in business: we deploy “brains” with strong vision and reasoning, but no motivation or empathy. In practice, it means brilliant outputs with no sense of priority, context, or trust. 💡 Actionable takeaway for leaders: When you build with AI agents, don’t just focus on intelligence (L1/L2). Ask: What does this agent care about? How does it decide what matters next? Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team. Because in the end, the future of agents won’t just be about smarter brains. It will be about brains with values. PS: The irony? We might be building empathy into machines before mastering it ourselves. 👉 Would you trust a system that thinks more like a brain — or do you prefer AI to stay purely mechanical? Paper link: https://zurl.co/PkJGs #AI #AgenticAI #FutureOfWork #Neuroscience #FoundationAgents
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🧠 A massive paper dropped — 264 pages from researchers across 20 universities and AI labs (Stanford, Yale, CIFAR, DeepMind, Microsoft Research, MetaGPT…). Pascal BORNET
#1 Top Voice in AI & Automation | Award-Winning Expert | Best-Selling Author | Recognized Keynote Speaker | Agentic AI Pioneer | Forbes Tech Council | 2M+ Followers ✔️
🧠 A massive paper dropped — 264 pages from researchers across 20 universities and AI labs (Stanford, Yale, CIFAR, DeepMind, Microsoft Research, MetaGPT…). It’s about what researchers now call “Foundation Agents.” And here’s the surprising part: their design is starting to look less like software… and more like a brain. 🧠 And it might be the most comprehensive roadmap yet on the future of AI agents. Look at this chart. It maps different human brain regions to their state of progress in AI. Some are already well-developed (like visual perception). Others are barely touched (like empathy, self-awareness, and emotional processing). 👉 Here’s the insight most people miss: AI agents don’t fail because they’re weak at logic or memory. They fail because they’re missing the “L3” regions — the emotional, contextual, and motivational layers that guide human decisions every second. That’s why many AI pilots collapse in business: we deploy “brains” with strong vision and reasoning, but no motivation or empathy. In practice, it means brilliant outputs with no sense of priority, context, or trust. 💡 Actionable takeaway for leaders: When you build with AI agents, don’t just focus on intelligence (L1/L2). Ask: What does this agent care about? How does it decide what matters next? Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team. Because in the end, the future of agents won’t just be about smarter brains. It will be about brains with values. PS: The irony? We might be building empathy into machines before mastering it ourselves. 👉 Would you trust a system that thinks more like a brain — or do you prefer AI to stay purely mechanical? Paper link: https://zurl.co/PkJGs #AI #AgenticAI #FutureOfWork #Neuroscience #FoundationAgents
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Interesting study: AI increasingly resembles humanlike neural networks. It lacks the chemical interference, though. Interesting, that human and artificial intelligence become more similar - hopefully, they do balance - and not compound - their weaknesses ...
#1 Top Voice in AI & Automation | Award-Winning Expert | Best-Selling Author | Recognized Keynote Speaker | Agentic AI Pioneer | Forbes Tech Council | 2M+ Followers ✔️
🧠 A massive paper dropped — 264 pages from researchers across 20 universities and AI labs (Stanford, Yale, CIFAR, DeepMind, Microsoft Research, MetaGPT…). It’s about what researchers now call “Foundation Agents.” And here’s the surprising part: their design is starting to look less like software… and more like a brain. 🧠 And it might be the most comprehensive roadmap yet on the future of AI agents. Look at this chart. It maps different human brain regions to their state of progress in AI. Some are already well-developed (like visual perception). Others are barely touched (like empathy, self-awareness, and emotional processing). 👉 Here’s the insight most people miss: AI agents don’t fail because they’re weak at logic or memory. They fail because they’re missing the “L3” regions — the emotional, contextual, and motivational layers that guide human decisions every second. That’s why many AI pilots collapse in business: we deploy “brains” with strong vision and reasoning, but no motivation or empathy. In practice, it means brilliant outputs with no sense of priority, context, or trust. 💡 Actionable takeaway for leaders: When you build with AI agents, don’t just focus on intelligence (L1/L2). Ask: What does this agent care about? How does it decide what matters next? Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team. Because in the end, the future of agents won’t just be about smarter brains. It will be about brains with values. PS: The irony? We might be building empathy into machines before mastering it ourselves. 👉 Would you trust a system that thinks more like a brain — or do you prefer AI to stay purely mechanical? Paper link: https://zurl.co/PkJGs #AI #AgenticAI #FutureOfWork #Neuroscience #FoundationAgents
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Interesting post. The author asks whether we would trust Agentic AI more if built like a brain, and makes some very good points why it should be. AI agents with no Empathy, Cognitive Flexibility, Inhibitory Control, Self Awareness, Emotional Processing etc, does seem psychopath-like in human terms. However, I can't help feeling uneasy, as (like with humans) these things are difficult to define and the learning outcomes hard to predict. Which leads me to another question - is predictable better, or has the predictability ship already sailed (and docked)? If so, perhaps there's no other choice. Thoughts?
#1 Top Voice in AI & Automation | Award-Winning Expert | Best-Selling Author | Recognized Keynote Speaker | Agentic AI Pioneer | Forbes Tech Council | 2M+ Followers ✔️
🧠 A massive paper dropped — 264 pages from researchers across 20 universities and AI labs (Stanford, Yale, CIFAR, DeepMind, Microsoft Research, MetaGPT…). It’s about what researchers now call “Foundation Agents.” And here’s the surprising part: their design is starting to look less like software… and more like a brain. 🧠 And it might be the most comprehensive roadmap yet on the future of AI agents. Look at this chart. It maps different human brain regions to their state of progress in AI. Some are already well-developed (like visual perception). Others are barely touched (like empathy, self-awareness, and emotional processing). 👉 Here’s the insight most people miss: AI agents don’t fail because they’re weak at logic or memory. They fail because they’re missing the “L3” regions — the emotional, contextual, and motivational layers that guide human decisions every second. That’s why many AI pilots collapse in business: we deploy “brains” with strong vision and reasoning, but no motivation or empathy. In practice, it means brilliant outputs with no sense of priority, context, or trust. 💡 Actionable takeaway for leaders: When you build with AI agents, don’t just focus on intelligence (L1/L2). Ask: What does this agent care about? How does it decide what matters next? Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team. Because in the end, the future of agents won’t just be about smarter brains. It will be about brains with values. PS: The irony? We might be building empathy into machines before mastering it ourselves. 👉 Would you trust a system that thinks more like a brain — or do you prefer AI to stay purely mechanical? Paper link: https://zurl.co/PkJGs #AI #AgenticAI #FutureOfWork #Neuroscience #FoundationAgents
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💡 Actionable takeaway for leaders: When you build with AI agents, don’t just focus on intelligence (L1/L2). Ask: What does this agent care about? How does it decide what matters next? Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team. Because in the end, the future of agents won’t just be about smarter brains. It will be about brains with values. PS: The irony? We might be building empathy into machines before mastering it ourselves.
#1 Top Voice in AI & Automation | Award-Winning Expert | Best-Selling Author | Recognized Keynote Speaker | Agentic AI Pioneer | Forbes Tech Council | 2M+ Followers ✔️
🧠 A massive paper dropped — 264 pages from researchers across 20 universities and AI labs (Stanford, Yale, CIFAR, DeepMind, Microsoft Research, MetaGPT…). It’s about what researchers now call “Foundation Agents.” And here’s the surprising part: their design is starting to look less like software… and more like a brain. 🧠 And it might be the most comprehensive roadmap yet on the future of AI agents. Look at this chart. It maps different human brain regions to their state of progress in AI. Some are already well-developed (like visual perception). Others are barely touched (like empathy, self-awareness, and emotional processing). 👉 Here’s the insight most people miss: AI agents don’t fail because they’re weak at logic or memory. They fail because they’re missing the “L3” regions — the emotional, contextual, and motivational layers that guide human decisions every second. That’s why many AI pilots collapse in business: we deploy “brains” with strong vision and reasoning, but no motivation or empathy. In practice, it means brilliant outputs with no sense of priority, context, or trust. 💡 Actionable takeaway for leaders: When you build with AI agents, don’t just focus on intelligence (L1/L2). Ask: What does this agent care about? How does it decide what matters next? Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team. Because in the end, the future of agents won’t just be about smarter brains. It will be about brains with values. PS: The irony? We might be building empathy into machines before mastering it ourselves. 👉 Would you trust a system that thinks more like a brain — or do you prefer AI to stay purely mechanical? Paper link: https://zurl.co/PkJGs #AI #AgenticAI #FutureOfWork #Neuroscience #FoundationAgents
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💡 Actionable takeaway for leaders: “When you build with AI agents, don’t just focus on intelligence (L1/L2). Ask: What does this agent care about? How does it decide what matters next?” “Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team”
#1 Top Voice in AI & Automation | Award-Winning Expert | Best-Selling Author | Recognized Keynote Speaker | Agentic AI Pioneer | Forbes Tech Council | 2M+ Followers ✔️
🧠 A massive paper dropped — 264 pages from researchers across 20 universities and AI labs (Stanford, Yale, CIFAR, DeepMind, Microsoft Research, MetaGPT…). It’s about what researchers now call “Foundation Agents.” And here’s the surprising part: their design is starting to look less like software… and more like a brain. 🧠 And it might be the most comprehensive roadmap yet on the future of AI agents. Look at this chart. It maps different human brain regions to their state of progress in AI. Some are already well-developed (like visual perception). Others are barely touched (like empathy, self-awareness, and emotional processing). 👉 Here’s the insight most people miss: AI agents don’t fail because they’re weak at logic or memory. They fail because they’re missing the “L3” regions — the emotional, contextual, and motivational layers that guide human decisions every second. That’s why many AI pilots collapse in business: we deploy “brains” with strong vision and reasoning, but no motivation or empathy. In practice, it means brilliant outputs with no sense of priority, context, or trust. 💡 Actionable takeaway for leaders: When you build with AI agents, don’t just focus on intelligence (L1/L2). Ask: What does this agent care about? How does it decide what matters next? Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team. Because in the end, the future of agents won’t just be about smarter brains. It will be about brains with values. PS: The irony? We might be building empathy into machines before mastering it ourselves. 👉 Would you trust a system that thinks more like a brain — or do you prefer AI to stay purely mechanical? Paper link: https://zurl.co/PkJGs #AI #AgenticAI #FutureOfWork #Neuroscience #FoundationAgents
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"When you build with AI agents, don’t just focus on intelligence. Ask: What does this agent care about? How does it decide what matters next? Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team" Interesting (and unexpected IMO)
#1 Top Voice in AI & Automation | Award-Winning Expert | Best-Selling Author | Recognized Keynote Speaker | Agentic AI Pioneer | Forbes Tech Council | 2M+ Followers ✔️
🧠 A massive paper dropped — 264 pages from researchers across 20 universities and AI labs (Stanford, Yale, CIFAR, DeepMind, Microsoft Research, MetaGPT…). It’s about what researchers now call “Foundation Agents.” And here’s the surprising part: their design is starting to look less like software… and more like a brain. 🧠 And it might be the most comprehensive roadmap yet on the future of AI agents. Look at this chart. It maps different human brain regions to their state of progress in AI. Some are already well-developed (like visual perception). Others are barely touched (like empathy, self-awareness, and emotional processing). 👉 Here’s the insight most people miss: AI agents don’t fail because they’re weak at logic or memory. They fail because they’re missing the “L3” regions — the emotional, contextual, and motivational layers that guide human decisions every second. That’s why many AI pilots collapse in business: we deploy “brains” with strong vision and reasoning, but no motivation or empathy. In practice, it means brilliant outputs with no sense of priority, context, or trust. 💡 Actionable takeaway for leaders: When you build with AI agents, don’t just focus on intelligence (L1/L2). Ask: What does this agent care about? How does it decide what matters next? Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team. Because in the end, the future of agents won’t just be about smarter brains. It will be about brains with values. PS: The irony? We might be building empathy into machines before mastering it ourselves. 👉 Would you trust a system that thinks more like a brain — or do you prefer AI to stay purely mechanical? Paper link: https://zurl.co/PkJGs #AI #AgenticAI #FutureOfWork #Neuroscience #FoundationAgents
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I like the point of this post. I've been preaching that humanity remains the owner of a final judgement call -- only we can be the wise "Oracle" with the vision to make important decisions. We trust AI and agents as long as there is Human-in-the-Loop (HITL) or Human-on-the-Loop (HOTL). I've said "the combination of biological plus artificial intelligence lead to better outcomes." However, if we enable agents with vision, motivation, empathy, and the ability to build trust over time (i.e., L3 levels), do we become comfortable with more AI-only judgement calls? Are the recent announcements of e-commerce agents that can make purchasing decisions evidence of this?
#1 Top Voice in AI & Automation | Award-Winning Expert | Best-Selling Author | Recognized Keynote Speaker | Agentic AI Pioneer | Forbes Tech Council | 2M+ Followers ✔️
🧠 A massive paper dropped — 264 pages from researchers across 20 universities and AI labs (Stanford, Yale, CIFAR, DeepMind, Microsoft Research, MetaGPT…). It’s about what researchers now call “Foundation Agents.” And here’s the surprising part: their design is starting to look less like software… and more like a brain. 🧠 And it might be the most comprehensive roadmap yet on the future of AI agents. Look at this chart. It maps different human brain regions to their state of progress in AI. Some are already well-developed (like visual perception). Others are barely touched (like empathy, self-awareness, and emotional processing). 👉 Here’s the insight most people miss: AI agents don’t fail because they’re weak at logic or memory. They fail because they’re missing the “L3” regions — the emotional, contextual, and motivational layers that guide human decisions every second. That’s why many AI pilots collapse in business: we deploy “brains” with strong vision and reasoning, but no motivation or empathy. In practice, it means brilliant outputs with no sense of priority, context, or trust. 💡 Actionable takeaway for leaders: When you build with AI agents, don’t just focus on intelligence (L1/L2). Ask: What does this agent care about? How does it decide what matters next? Define motivations, guardrails, and context memory as deliberately as you would KPIs in a team. Because in the end, the future of agents won’t just be about smarter brains. It will be about brains with values. PS: The irony? We might be building empathy into machines before mastering it ourselves. 👉 Would you trust a system that thinks more like a brain — or do you prefer AI to stay purely mechanical? Paper link: https://zurl.co/PkJGs #AI #AgenticAI #FutureOfWork #Neuroscience #FoundationAgents
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