Don't Feed AI Outdated Info, Fix Your Knowledge Base First

Everyone wants AI agents. Very few companies are actually ready for enterprise AI. There’s a massive difference between: using AI tools and running an AI-driven organization. 𝐄𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐀𝐈 is not ChatGPT or Claude subscriptions for employees. It is AI becoming part of: → operations → workflows → decisions → customer experience → risk management → internal systems And this is where most companies fail. They scale AI before they build: → governance → ownership → accountability → operational clarity So instead of scaling productivity… they scale confusion. More tools. More dashboards. More automation. More noise. Not better execution. The companies winning with AI right now are not the ones experimenting the fastest. They are the ones redesigning how work actually happens. Because scaling AI without operational clarity only scales chaos. 𝐀𝐫𝐞 𝐲𝐨𝐮 𝐭𝐫𝐮𝐥𝐲 𝐫𝐞𝐚𝐝𝐲 𝐟𝐨𝐫 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐀𝐈, 𝐨𝐫 𝐚𝐫𝐞 𝐲𝐨𝐮 𝐬𝐭𝐢𝐥𝐥 𝐢𝐧 𝐭𝐡𝐞 𝐦𝐨𝐫𝐞 𝐭𝐨𝐨𝐥𝐬 𝐩𝐡𝐚𝐬𝐞? #AI #EnterpriseAI #Leadership #DigitalTransformation #AIStrategy

AI is not a software upgrade. It is an operating model test. After reading the world Economic Forum and Accenture's report on organizational transformation in the age of AI, my biggest takeaway was simple: The real AI divide will not be between companies that use AI and companies that do not. It will be between companies that redesign around AI and companies that simply add AI on top of old workflows. Many organizations are still treating AI like a productivity layer. A faster report. A smarter dashboard. A more efficient customer service tool. A better assistant for existing teams. Useful, yes. But that is not transformation. The deeper question is whether a company is willing to rethink how work actually flows. Who makes decisions? Where does accountability sit? How quickly can the organization learn from signals? How are people, data and intelligent systems coordinated around outcomes? This is where the real gap begins. If a company has fragmented data, unclear ownership and slow decision cycles, AI will not magically make it intelligent. It will simply expose the friction faster. The companies that benefit most from AI will not necessarily be the ones with the most pilots. They will be the ones with the courage to redesign workflows, governance, talent systems and leadership rhythms around continuous learning. To me, the new competitive moat is not just model capability. It is organizational learning speed. Because AI can accelerate insight. But leaders still own direction, trade offs and outcomes. Do not just collect AI pilots. Redesign how work flows. #AI #BusinessTransformation #Leadership #Strategy #FutureOfWork #DigitalTransformation

Everyone wants AI. Almost no one is ready for it. But the opportunity is real. After navigating IT transformation across multiple markets, I see the same pattern everywhere. Executives rush to implement AI tools. 🤖 Budgets get approved. Pilots get launched. And then… nothing works as expected. But here's the thing: the technology isn't the problem. It's actually an opportunity in disguise. The companies hitting a wall aren't failing at AI. They're discovering, faster than ever, that their data foundations need work. And that's valuable information. Teams working off multiple versions of the same file. Systems that don't talk to each other. Data that looks clean. Until you actually try to use it. Fixing this isn't a setback. It's the real transformation. The question I now ask before any AI conversation: "Can we actually trust our data?" Because the organizations that answer that question seriously, and act on it, are building something that lasts. Cleaning. Structuring. Governing. Aligning. Repeat. Unglamorous work. But the work that creates lasting competitive advantage. AI is just the reward for doing it well. Where do you start? From what I've seen, it comes down to 4 steps. 1. Audit what you have. Honestly. 2. Define what "good data" looks like for your business. 3. Break the silos. One integration at a time. 4. Build governance before you build dashboards. 📊 It's not glamorous. But it's the work that makes everything else possible. AI isn't the transformation. It's the proof that your transformation worked. The organizations that understand this today are the ones that will lead tomorrow. 🚀 #DigitalTransformation #DataStrategy #ArtificialIntelligence #ITLeadership #DataGovernance

🚀 AI-first “Frontier Firm”: a look at how #BNY is redesigning work with #AI—as a transformation engine: 🧠 AI is for everyone: Every employee is trained to design work, not just do it 🤖 Digital employees: 140+ AI agents operate like team members with roles, managers, KPIs ⚡ Massive efficiency gains: Tasks go from mins → secs 🔄 Shift from repetitive → strategic work: humans move up value chain (analysis, strategy, design) 🧩 New org model: from pyramid → diamond (less repetition, more creativity and judgment) 🎓 AI upskilling at scale: thousands trained, with real prototypes built by employees 🔐 Trust-first AI with governance, compliance, and observability built into every step ⚙️ AI building AI: workflows can now be captured and turned into automated agents in hours 💡 Takeaway: This isn’t about doing less work — it’s expanding what humans are capable of doing. Learn more: https://msft.it/6046vr0Bq #FutureOfWork #DigitalTransformation #Copilot #Leadership #Innovation #FinancialServices #AgenticAI #WorkplaceEvolution #FrontierFirms #MicrosoftAI

🚀 AI-first “Frontier Firm”: a look at how #BNY is redesigning work with #AI—as a transformation engine: 🧠 AI is for everyone: Every employee is trained to design work, not just do it 🤖 Digital employees: 140+ AI agents operate like team members with roles, managers, KPIs ⚡ Massive efficiency gains: Tasks go from mins → secs 🔄 Shift from repetitive → strategic work: humans move up value chain (analysis, strategy, design) 🧩 New org model: from pyramid → diamond (less repetition, more creativity and judgment) 🎓 AI upskilling at scale: thousands trained, with real prototypes built by employees 🔐 Trust-first AI with governance, compliance, and observability built into every step ⚙️ AI building AI: workflows can now be captured and turned into automated agents in hours 💡 Takeaway: This isn’t about doing less work — it’s expanding what humans are capable of doing. Learn more: https://msft.it/6043vTVWT #FutureOfWork #DigitalTransformation #Copilot #Leadership #Innovation #FinancialServices #AgenticAI #WorkplaceEvolution #FrontierFirms #MicrosoftAI

Over the last two weeks I've had 50+ conversations on AI adoption with CHROs, Heads of Talent and Learning from Fortune 1000 orgs. Of those 50+ conversations: 🔵 100% believe AI will have a massive impact on jobs (both size and nature of workforce) 🔵 100% are actively working on C-level initiatives to shepherd said impact ⁉️ 0% are able to demonstrate measurable progress aside from "pilots launched" and other anecdotal feedback What's the deal? Three things stand out 1️⃣ I believe we are wrongly characterizing AI as a tech thing rather than a human and talent thing 2️⃣ Much of the conversation today is speculative (read: not based on data, actual business outcomes, or reality) and we have few case studies of widespread enterprise application 3️⃣ I believe we are grossly underestimating what I'm calling the "iceberg" dynamic in that much of the public discourse is related to the tip of the iceberg - what models we are encouraging employees to engage (if any), how they are engaging, how we are thinking about cost, etc What I believe we are underestimating is the foundation that makes the iceberg so strong and ensures AI scales across an enterprise, namely 🧊 Governance 🧊 Security 🧊 Compliance 🧊 Change management 🧊 Business process 🧊 Data Without proper investment in these areas Enterprise AI will fail. Unsexy topics for sure and unlikely to sell newspapers or excite dining companions, but IMHO the most underreported chapter in the enterprise AI story to date

Enterprise AI adoption just hit 87% according to the latest McKinsey report. But here's what the numbers don't show: Most teams are still treating AI like a magic black box. They're frustrated when it doesn't read their minds or deliver perfect results on the first try. The companies winning with AI? They've invested in prompt engineering skills across their workforce. It's not about knowing every AI model feature. It's about communicating clearly with AI systems using frameworks like R-C-T-O: • Role: Who is the AI in this scenario? • Context: What background info does it need? • Task: What exactly should it do? • Output: How should it format the response? We're seeing this pattern everywhere — from marketing teams cutting campaign creation time by 70% to finance departments automating complex analysis workflows. The skill gap isn't technical knowledge. It's structured thinking and clear communication with AI. What's your team's biggest challenge with AI adoption right now? #AISkills #PromptEngineering #EnterpriseAI #FutureOfWork #AITraining

🚀 AI-first “Frontier Firm”: a look at how #BNY is redesigning work with #AI—as a transformation engine: 🧠 AI is for everyone: Every employee is trained to design work, not just do it 🤖 Digital employees: 140+ AI agents operate like team members with roles, managers, KPIs ⚡ Massive efficiency gains: Tasks go from mins → secs 🔄 Shift from repetitive → strategic work: humans move up value chain (analysis, strategy, design) 🧩 New org model: from pyramid → diamond (less repetition, more creativity and judgment) 🎓 AI upskilling at scale: thousands trained, with real prototypes built by employees 🔐 Trust-first AI with governance, compliance, and observability built into every step ⚙️ AI building AI: workflows can now be captured and turned into automated agents in hours 💡 Takeaway: This isn’t about doing less work — it’s expanding what humans are capable of doing. Learn more: https://msft.it/6040vrDGg #FutureOfWork #DigitalTransformation #Copilot #Leadership #Innovation #FinancialServices #AgenticAI #WorkplaceEvolution #FrontierFirms #MicrosoftAI

🚀 AI-first “Frontier Firm”: a look at how #BNY is redesigning work with #AI—as a transformation engine: 🧠 AI is for everyone: Every employee is trained to design work, not just do it 🤖 Digital employees: 140+ AI agents operate like team members with roles, managers, KPIs ⚡ Massive efficiency gains: Tasks go from mins → secs 🔄 Shift from repetitive → strategic work: humans move up value chain (analysis, strategy, design) 🧩 New org model: from pyramid → diamond (less repetition, more creativity and judgment) 🎓 AI upskilling at scale: thousands trained, with real prototypes built by employees 🔐 Trust-first AI with governance, compliance, and observability built into every step ⚙️ AI building AI: workflows can now be captured and turned into automated agents in hours 💡 Takeaway: This isn’t about doing less work — it’s expanding what humans are capable of doing. Learn more: https://msft.it/6042vrG9y #FutureOfWork #DigitalTransformation #Copilot #Leadership #Innovation #FinancialServices #AgenticAI #WorkplaceEvolution #FrontierFirms #MicrosoftAI