How to Use AI for Real Supply Chain Results

🚀 Discover the latest trending topics in AI Agents for 2025! Key developments include: 1. **Specialized AI Agents**: Tailored for specific tasks like customer support and financial planning. 2. **Multimodal Capabilities**: Processing text, voice, and images for richer interactions. 3. **Autonomous & Proactive Agents**: Moving towards self-decision making and task execution. 4. **Ethical AI & Transparency**: Prioritizing fairness and clear explanations in AI-driven decisions. 5. **Integration with IoT**: Seamless control in smart environments. 6. **Open-Source AI Models**: Democratizing AI development. 7. **Human-AI Collaboration**: New roles emerging to bridge human and artificial intelligence. These trends highlight the dynamic evolution and growing integration of AI agents in business and daily life. #AI #AIAgents #ArtificialIntelligence #TechTrends #Innovation #FutureOfWork

🚀 The evolution of voice recognition technology is nothing short of extraordinary. Remember when talking to your device felt like speaking to a brick wall? Now, we’re on the cusp of a revolution. 🔹 Accuracy improvements are at an all-time high. Using advanced AI algorithms and deep learning, today’s voice recognition can understand accents, dialects, and even contextual nuances—making it more human than ever. 🔹 Integration is seamless. From customer service to personal assistants, businesses are leveraging voice tech to enhance user experiences. Less friction, more connection. 🔹 Applications are expanding. Healthcare, automotive, and IoT are just a few sectors that harness voice technology to streamline processes and boost productivity. As someone who follows trends closely, I can’t help but wonder: What does this mean for the future of work? Are we ready to hand over tasks to our speaking counterparts? 🤖 👇 Let me know your thoughts on the future of voice recognition! #VoiceRecognition #AI #Innovation #FutureOfWork

🚀 AI is reshaping the future of commercial real estate — and Scenera is leading the way. Join us on September 17 at 10:00 am ET for an exclusive CREtech webinar featuring Dr. Patryk Laurent of Scenera in conversation with Michael Beckerman. Discover how Scenera is transforming building operations to be safer, more cost-effective, and better for tenant retention. Key topics include: 🔒 Solving the Paradox of Privacy – How BlindEye delivers powerful video intelligence with a 100% privacy guarantee 💡 Low-Cost, High-Accuracy AI – The edge + cloud combination that makes advanced video AI affordable 📊 From Data to Dollars – Case studies on real ROI from video AI and IoT data 📜 A New Paradigm for AI Ownership – Why AI models trained for customers become their royalty-free IP 👉 Don’t miss this chance to learn from an AI innovator driving real estate’s next big leap. Register Here: https://lnkd.in/g5XznHX8 #CREtech #Webinar #AI #PropTech #CommercialRealEstate #Innovation

🚀 Latest Trends in AI Agents (September 2025): 1. Specialized AI Agents: Tailored for specific domains like healthcare and finance, delivering accurate and efficient results. 2. Autonomous Decision-Making: Evolving from reactive to proactive systems, capable of independent decisions and iterative task execution. 3. Multimodal AI Integration: Processing text, voice, and images for more interactive user experiences. 4. Multi-Agent Collaboration: Systems where multiple AI agents work together to achieve complex goals, inspired by swarm intelligence. 5. Ethical & Transparent AI: Prioritizing fairness, accountability, and transparency with a focus on Explainable AI (XAI). 6. Integration with the Physical World: Connecting with IoT devices for applications in smart environments. 7. Open-Source AI Models: Democratizing AI development by allowing companies to build and fine-tune their own agents. 8. Human-AI Collaborative Teams: Emerging roles like AI Trainers and Ethicists to bridge human and artificial intelligence. These trends highlight the rapid evolution and growing impact of AI agents across industries. Stay ahead of the curve! #AI #AIAgents #ArtificialIntelligence #TechTrends #Innovation #FutureOfWork

🤖 AI Development Trends: The Transition from Tool to Ecosystem Artificial intelligence has moved from the lab to the masses, from a "trial" for businesses to a "must." In 2025, several key trends in AI development are accelerating: 1️⃣ Multimodal AI: The integrated application of text, voice, image, and video will enable AI to move beyond just "talking" to "seeing," "hearing," and "understanding." 2️⃣ Industry-Specific Models: Smaller, more accurate models are emerging in fields such as healthcare, finance, and manufacturing, helping businesses implement applications more quickly. 3️⃣ AI + Automation: From code generation to process optimization, AI is gradually becoming the "second engine" of business operations. 4️⃣ Edge AI: AI no longer relies on the cloud; more computing will be performed locally on devices, empowering IoT, wearables, and smart devices. 5️⃣ Responsible AI: With stricter regulations, transparent, explainable, and fair AI systems will become a must-have for businesses. 🌍 AI is not just a technological trend; it's also a core force for organizational transformation and the reshaping of competitiveness. Whether a company can seize this wave of trends will determine its competitive position over the next 5–10 years. 👉 What changes has AI already brought to your industry? #AI #Artificial Intelligence #FutureTrends #EnterpriseStrategy #DigitalTransformation

#BOI published an interesting article about "The future of AI-driven insights - From understanding consumers to enabling intelligence" (link in comments). A few reflections that stood out to me if we apply this to digital (IoT) products: 1. Personalization as perceived value Users feel “seen & listened to” when the surroundings adapt to them, based on their interactions. It’s not just functionality, it’s about that next level of personalization where the product’s system learns from your personal usage and preferences, possibly even adapting the interface accordingly, creating an exclusive experience. The additional value of that sense of uniqueness often outweighs the actual technological complexity behind it, making it at least worthwhile to investigate. I believe in the future, AI will be an integral part of UX. 2. Dynamic contextual information “Understanding who someone is right now” sounds extremely powerful, but I wonder if there’s appetite for the level of data-sharing this would require. Continuous emotional/event tracking feels like a red line for many users. Data can be used for good or bad. Just like technology isn’t inherently good or bad, it depends how you use it. The risk of sharing data is that it could contain information, not directly clear/sensible to the human eye, but extrapolatable by AI, that could be taken advantage of. I’ll elaborate this with an example in the comments. I do believe some contextual insights can be used for the right use case, especially when they rely on non-intrusive or less personal data. Perhaps in the (far) future, the world collectively has decided how to ethically go about this. For now that zone seems gray, knowing Belgium is currently undecided about the new EU legislation proposal about mandating the scanning of all private communications. 3. Orchestrated intelligence & closed-loop engines To differentiate your product or service, embedded intelligence in the backbone is a must. Architecting systems that continuously learn and accelerate decision-making, without manual reconfiguration, will be key for the next generation of intelligent products. For IoT products, that requires both software and hardware development expertise. Not an easy task, as they require different development methodologies. 💡 I’m curious how others building digital platforms and innovative software see this: → Where do you draw the line between personalization and privacy? → How do you think orchestrated intelligence should be embedded into product architectures today? Let’s discuss in the comments or send me a DM!

From Data to Decisions: The 5 Key Steps of Data Analysis Data is everywhere and but insights only emerge when we follow a structured process. Figure 1: Steps of Data Analysis reminds us how to turn raw numbers into real impact: 🔹 1. Define the Problem → Every analysis starts with clarity. What challenge are we solving? What decision do we want to improve? 🔹 2. Collect the Data → Relevant, quality inputs matter. From sales records to customer interactions, the right data sets the foundation. 🔹 3. Clean & Prepare → Raw data is messy. Removing errors, duplicates, and gaps ensures accuracy and reliability. 🔹 4. Analyze → This is where the magic happens and using techniques like statistical models, machine learning, and visualization to uncover hidden patterns. 🔹 5. Interpret & Act → Insights only matter when they drive action. Translate results into strategies that improve operations, decisions, and outcomes. 📊 These steps aren’t just a cycle and they’re a mindset for making smarter, evidence-based decisions in business, research, and beyond. As AI, IoT, and cloud technologies evolve, these principles remain the core of data-driven transformation. The real advantage? Organizations that can move seamlessly from data collection to action will lead in tomorrow’s competitive landscape. #Analytics #DataScience #AI #DecisionMaking #Innovation #FutureOfWork

AI in Supply Chain: Revolutionizing Efficiency Over a Decade With over 10 years in AI, I’ve watched it reshape supply chain management from reactive to proactive. In the early days, supply chains relied on manual forecasting with limited accuracy. Now, AI-driven demand forecasting models achieve up to 85% accuracy, minimizing overstock and shortages. Reinforcement learning optimizes logistics routes, cutting transportation costs by 20%. Digital twins, powered by AI, simulate supply chain scenarios in real-time, enhancing resilience. The rise of AI-integrated IoT ensures end-to-end visibility, from warehouse to delivery. As sustainability becomes critical, AI is paving the way for greener supply chains. How has AI transformed your supply chain operations? Read more about AI in supply chains: MIT Sloan - AI in Supply Chain Management #MultimodalAI #HealthcareAI #InsuranceTech #AIinHealthcare #DataIntegration #PersonalizedMedicine #AIforInsurance #DigitalHealth #HealthTech #TechInInsurance #AIApplications #FutureOfHealthcare #InnovationInInsurance #DataScience #MachineLearning #AI #ArtificialIntelligence #DigitalTransformation #TechTrends #ML #DeepLearning #Automation #AIInBusiness #DataScience

“95% of AI investments fail. But 92% of Gen AI pioneers are already seeing ROI.” A recent MIT report highlighted that 95% of AI investments have yet to deliver results. In contrast, our latest research shows a more encouraging picture: 92% of early adopters say their generative AI investments have already paid for themselves, with an average ROI of 41% for those who have measured the impact. This raises an important question for every business leader: which camp will you be in? In manufacturing, the opportunity is clear. The industry is advancing rapidly through automation, smart technologies, and sustainability efforts. But the real differentiator lies in harnessing data + AI across IT, OT, and IoT systems to: - Optimize business planning and supply chains - Enable smart manufacturing at scale - Unlock more value from connected products Surveyed manufacturers are already leading the way — 71% are deploying Gen AI in production and supply chain management, compared to just 45% across other industries. They’re also applying it in inventory management and quality inspection protocols. The message is clear: AI impact is not a matter of if but how effectively data foundations are mobilised. 📖 Learn more in The Ultimate Guide to Data & AI for Industries (link in comments)