AI Accelerates Supply Chain Execution with 41% Adoption

📰 Supply Chain News: Logistics IT Perspectives 2026: Future Trends Unveiled The 'Logistics IT Perspectives 2026' report by Inbound Logistics outlines the technological advancements anticipated to transform logistics operations. Key trends include AI adoption, enhanced data analytics, and greater automation, which promise to streamline supply chains and improve efficiencies. Source: Inbound Logistics Read our analysis: https://lnkd.in/g6_S5ZC3 #SupplyChain #AI #DemandPlanning #InventoryOptimization #ForecastWorx

AI adoption is accelerating and governance is still catching up.    AI agents are moving from concept to real-world deployment, now acting within workflows and making decisions on behalf of organizations. As their role expands, clarity around authority and oversight is becoming essential.    Our latest report with the World Economic Forum introduces the Agent Capability and Authorization Profile (ACAP): a framework to bring structure and consistency to how AI agents are deployed and governed.    It enables organizations to make delegated action explicit, auditable, and scalable, moving from isolated pilots to more controlled, enterprise-wide adoption.    The question is no longer what AI can do, it’s how we govern it at scale.    Read ‘AI Agents in Action: A playbook for trusted adoption, authorization and scaling’: https://bit.ly/3PYasLv    #WEF #MakeItReal

#MakeItReal with AI trusted adoption, authorization and scaling. Check the latest report from Capgemini and the World Economic Forum introducing the ACAP Framework: Agent Capability and Authorization Profile 💡

Exciting to see the focus shifting from experimentation to structured, governed AI adoption. The real differentiator will be how well we manage control and accountability.

AI stalls when it runs through operating models that were never designed for it.   Across ADAPT’s Data & AI Edge discussions, the challenge is no longer access to AI tools, but whether organisations can operate at the speed AI now demands.   Many AI programs generate activity without changing performance because they are built on slower, linear, human-led workflows.   Scaling AI forces a redesign of how the organisation runs:   ⚡ Machine-speed coordination, where decisions move without bottlenecks 🎯 Distributed accountability, with business owners responsible for outcomes 🔁 Continuous adaptation, as workflows, roles, and processes evolve with the technology   Learn from more key takeaways at #DataAIEdge:https://lnkd.in/giDQcdNr

Most enterprises still treat AI implementation as a capital expenditure decision, not an operational one.❗ That single framing is why so many AI initiatives stall in procurement for nine months before a line of code is written. Zero Upfront Deployment is not a discount - It is a different business model. Let me explain what I mean. When you remove implementation fees, capital expenditure, and the multi-quarter buildout, AI stops being a board-level capex case and starts being a monthly operating decision. The risk profile changes. The approval path changes. The speed-to-value changes. This is the principle our entire company is built on: No implementation fees. No capital expenditure. Fully deployed AI systems from day one, on an all-inclusive monthly subscription.✅ We made this the structural foundation rather than a promotional offer because the barrier was never the technology. It was the commercial model wrapped around it. Every business deserves access to powerful AI without the barriers. The deployment model should reflect that. 🔗www.gmdautomation.ai #AI #AIVoiceAgents #AIAutomation #FutureOfWork #DigitalTransformation

AI is reshaping technical service operations—and the organizations leading the way are already seeing gains in efficiency and service excellence. In their latest analysis, deborah hawkins and Rachel Dean explore how AI is being used in service today, what separates market leaders, and what it will take for businesses to close the maturity gap. Download the report: https://hubs.li/Q04h5Fcb0 #AI #TechnicalService #ServiceExcellence #DigitalTransformation #FieldService #Automation #KeypointIntelligence

Most logistics AI still depends on centralized systems.  That’s where the delay begins.  Edge AI enables faster routing decisions closer to real-world operations, helping firms reduce costs and improve delivery performance in real time. #EdgeAI #LogisticsTech #SupplyChainAI #EnterpriseAI #WerqLabs 

Most logistics AI still depends on centralized systems.  That’s where the delay begins.  Edge AI enables faster routing decisions closer to real-world operations, helping firms reduce costs and improve delivery performance in real time. #EdgeAI #LogisticsTech #SupplyChainAI #EnterpriseAI #WerqLabs 

Deloitte predicts agentic AI adoption in manufacturing will jump from 6% to 24% this year. Here’s what that means for people on the floor: AI isn’t coming for your job. It’s coming for the parts of your job that slow you down. Predictive maintenance. Demand forecasting. Automated shift handover reports. Real-time inventory tracking. These aren’t sci-fi. They’re being deployed right now across the industry. But here’s what nobody talks about: AI only works if the data is clean. And the data is only clean if the people on the ground — the ones doing the counts, the receiving, the kitting — are doing it right. 94% of manufacturers report using some form of AI already. The question isn’t if it’s coming. It’s whether your operation is ready for it. The future of AI in manufacturing starts with operational discipline. That starts with us. #AI #Manufacturing #SupplyChain #Operations #SmartManufacturing