Stephen Padley’s Post

Insights leaders and procurement stakeholders working with AI suppliers are in a genuinely difficult position right now. They are expected to move quickly, demonstrate results, and integrate tools. At the same time, they carry the accountability for what those tools do with real consumer data. Governance frameworks have not caught up with advancements in AI, yet demand highest standards. Internal expertise is often thin. While most organizational leadership sat on the fence for a long time around AI adoption, they are now pressuring insights team to get on with it. However, this guidance and support fall short on ensuring the rigor and quality or understanding the consequences if its not done right. These are not small pressures. They are structural, and they deserve to be acknowledged. What most insights leaders are not given is a practical way to evaluate the suppliers they are being asked to work with. They get sales decks, case studies, and security questionnaires. What they rarely get is a clear framework for building trust where it matters. I think about AI supplier trust across three areas, somewhat inspired by ESOMAR's 20 questions. I call them the Trust Trinity: the company, the product, and the data. Each one represents a distinct set of questions.

🚨 Why Is Supply‑Chain AI Adoption Still So Low? Despite the AI Hype, Only 10% of Supply Chain Companies Use It A new report from Sage, highlighted in SupplyChain24/7 article, reveals most supply chain teams are still only testing AI tools (https://lnkd.in/gTK_m_ui) Despite the hype, only a small fraction of supply‑chain organizations have truly implemented AI at scale — and the reasons are clearer than ever. 🔹 Lack of a Real AI Strategy Most companies still operate through scattered pilot projects instead of building a cohesive, long‑term AI roadmap. Gartner reports that only 23% of supply‑chain leaders have a formal AI strategy, leading to fragmented “franken‑systems” that can’t scale. 🔹 Pressure for Quick Wins Leaders face heavy pressure to show immediate ROI, which keeps them locked into short‑term efficiencies rather than transformative initiatives. This slows progress and limits investment. 🔹 Legacy Systems + Data Fragmentation Outdated tech and siloed data make AI implementation notoriously difficult. Many professionals say they recognize AI’s importance, but only about 20% feel equipped to evaluate or deploy AI projects. 🔹 Still Stuck in Pilot Mode Research shows that only 11% of firms have moved beyond pilots and into full deployment — meaning most “AI programs” are still experiments, not operational solutions. 🔹 Shortage of Supply‑Chain‑Specific AI Tools Nearly half of supply‑chain professionals say the lack of tailored, industry‑ready AI tools is slowing adoption. 💡 The takeaway: The issue isn’t interest — it’s readiness. To unlock real value, organizations need strategy, alignment, clean data, and the courage to move beyond pilots. If your supply chain is exploring AI and these challenges feel familiar, you’re not alone — but the companies that break through will define the next decade of competitiveness. #SupplyChain #SupplyChainManagement #SupplyChainInnovation #AI #ArtificialIntelligence #GenerativeAI #DigitalTransformation #Logistics #Operations #Manufacturing #DataStrategy #FutureOfWork #Automation #Industry40 #SupplyChainTechnology #SupplyChainAnalytics #DigitalSupplyChain #SCM

💡 AI alone won’t transform your organisation - your people will. The Spring Statement highlighted something that should resonate strongly with UK Public Sector technology leaders: fiscal discipline and productivity are now front and centre, and technology investment needs to demonstrate measurable value. But as much as we talk about AI and automation, it’s not just about the technology. ISG’s latest article “AI Alone Won’t Transform Your Business - Your People Will” digs into a critical truth: transformation succeeds when technology and people evolve together. AI can boost efficiency, but it only delivers when staff are equipped, processes are ready, and culture supports change. 👉 https://lnkd.in/e7udXF_D That insight feels particularly relevant against the backdrop of the Spring Statement, where productivity not just spending is part of the fiscal narrative. For public sector organisations: 🤖 AI and automation should be tied to measurable outcomes, not just experimentation. 👥 Digital strategies must consider people, skills and organisational readiness. 🖥️ Legacy systems and capability gaps remain a barrier if not addressed in parallel with tech investment. In practice, that means technology leaders need to balance innovation with capability building ensuring people are part of the transformation equation, not an afterthought. Because at the end of the day, the impact of AI - especially in the Public Sector - is defined as much by the people who use it as the technology itself. #PublicSector #AI #Transformation #TechnologyLeadership #SpringStatement #DigitalStrategy #ISG #Productivity #Innovation

Working with clients every day, we’re seeing supply chain leaders move beyond isolated AI pilots toward enterprise‑scale AI that delivers measurable impact, higher margins, greater resilience and faster decision‑making. What’s standing out isn’t just AI’s potential, but where value is (and isn’t) being realized: ▸Procurement teams are applying AI to strengthen negotiations, improve supplier visibility, and respond faster to disruption ▸Many organizations still face a gap between executive ambition and workforce readiness ▸Closing that gap is critical , because the strongest outcomes come when human judgment works alongside intelligent systems, not when it’s replaced by them In this recent Procurement Magazine article, I share how leading organizations are scaling AI across procurement and supply chain operations, and what it takes to translate technology investment into real, sustained economic value. #Procurement #SupplyChain #AI #Leadership https://lnkd.in/ehfzkAkd

Business volatility is up 183% and leaders are responding by scaling AI — fast. According to Accenture’s latest research: • 86% of executives are increasing AI investment • 43% of supply chain work hours could be automated or augmented by GenAI • Companies with mature digital supply chains deliver 23% higher margins But there’s a problem. While 95% of leaders believe they’ve provided enough AI training, nearly 60% of employees say the technology is advancing faster than they can learn it. AI adoption is accelerating — but workforce readiness is lagging. For procurement leaders, closing that gap may determine who turns disruption into competitive advantage. Worth a read 👇 #Procurement #SupplyChain #ArtificialIntelligence #DigitalTransformation #AIinProcurement

How can organizations embed AI to drive impact at scale? Despite the hype, 86% of leaders say their organizations are not ready to adopt AI in day-to-day operations. In McKinsey & Company's 2026 State of Organizations report, Bettina Dietsche, Chief People and Culture Officer at Allianz shares how her company moved from experimentation to execution by integrating AI across underwriting, claims, and product design. Tools like AllianzGPT, now used by more than 60,000 employees, reduced manual workloads and improve efficiency at scale. Bettina emphasizes that technology alone is not enough. Upskilling, trust, and strategic workforce planning are critical to preparing for a future in which nearly two-thirds of required skills may change within the next five years. To learn more, read the full report, in which authors Alexis Krivkovich, Damian Klingler, Dana Maor, Michael Anzenhofer, and Patrick Guggenberger provide a holistic view of the nine most important shifts businesses are grappling with and what leaders and their teams can do about them: https://lnkd.in/ds_D2wwq McKinsey People & Organizational Performance #AI

Technology is only the accelerator. The real differentiators are #workforce #readiness, #trust, and intentional #upskilling. If nearly two-thirds of skills are set to shift, organizations that #proactively #invest in #people, not just tools, will be the ones that stay #competitive.

Operations leaders who still treat AI as a side project will lose on cost, speed, and resilience. I’m seeing a clear shift in operations: AI is no longer about experimentation. It is becoming the operating layer for how modern businesses plan, predict, and execute. Stanford HAI’s 2025 AI Index found that 78% of organizations reported using AI in 2024, up from 55% in 2023. It also found that 43% of companies using AI in supply chain management are already seeing cost savings. For me, that is the real signal: AI has moved from boardroom hype to shop-floor and back-office impact. McKinsey’s 2025 operations research adds another reality check: companies leading in AI adoption are now seeing a 3.8x performance gap versus laggards. That gap is not about better dashboards. It comes from embedding AI into workflows, decisions, and frontline execution. As an Operations Lead, I believe the priority is simple: stop chasing isolated pilots and start redesigning operations around intelligence. That means predictive maintenance instead of reactive fixes. Real-time visibility instead of fragmented reporting. Automation that removes friction instead of adding another layer of tools. I see the biggest wins happening where IT, OT, and AI work as one system, not in silos. That is where productivity compounds, downtime drops, and resilience becomes measurable. Are you using AI to optimize one process, or to redesign how your operations actually run? #OperationsLeadership #ArtificialIntelligence #DigitalTransformation #SmartOperations #PredictiveMaintenance #BusinessAutomation #FutureOfWork

--- *You bought the AI. Now you're trying to work out what it's for.* This is happening in organisations everywhere — and it's not stupidity. It's urgency. Boards want AI strategy. Competitors are making noise. Vendors are brilliant at creating fear of being left behind. So the technology gets procured. A team gets assigned. And everyone starts looking for problems that fit the solution they've already bought. Three things we've learned from watching this play out: 1. Most AI pilots succeed — that's part of the problem. It's not hard to impress stakeholders with curated data in a controlled environment. The gap isn't "can AI do this?" The gap is between a successful demonstration and sustained business value at scale. 2. The vendor's assumptions become your assumptions. When you start with the technology, you inherit their defaults, their training data, their idea of what "good" looks like. Generic tool. Specific context. Predictably generic results. 3. The diagnostic question is one sentence. Before the next vendor demo: "Can we articulate — in one sentence — the business problem this is supposed to solve?" Clear and specific? You're in good shape. "We need to be doing AI"? You're about to spend significant money finding out what your actual problem is — which you could have done for free. Context before technology. Less exciting. Considerably more effective. → Full article: https://lnkd.in/e52sHGH8 What's the worst "solution looking for a problem" AI procurement you've witnessed? #AIStrategy #AIImplementation #DigitalTransformation #Leadership #ContextIsEverything

AI can absolutely help reduce cost. But for most organisations, chasing the latest tool is not the real value. It is crucial to first address the fundamentals. Too many cost programmes focus on headcount, supplier cuts, or short-term savings targets. The problem is that these reoccurring inefficiencies are often missed because leaders are not joining the dots between technology spend, process performance, and business outcomes. That is where AI-enabled cost optimisation becomes a game changer. Used properly, AI helps leaders cut through the noise and see where money is being spent without enough return, where manual effort is driving avoidable cost, and where decisions could be made faster and better. But it is not just a tick-box exercise. AI on top of poor governance, fragmented data, and unclear ownership will not move the needle, as these issues can undermine the effectiveness of AI initiatives and lead to wasted resources and missed opportunities for improvement. The organisations seeing the strongest results are the ones combining AI with clear Technology Business Management (TBM) disciplines, which focus on aligning IT spending with business goals, better operating model design, and sharper performance visibility. This is where the real impact is felt. Cost optimisation should not solely focus on cost reduction. It should be about creating a leaner, smarter business that can reinvest in growth. #AI hashtag#CostOptimisation #BusinessTransformation #TechnologyStrategy #TBM #BusinessEfficiency #PerformanceImprovement Contact us at information@evangelize-consulting.com for further information on how we can drive business benefits for your organisation using the Evangelize Performance Framework.