S. Shah’s Post

Your AI pilot in Customer Service looked great in the demo. Then reality hit. 🫣 Agents started bypassing the AI. Case summaries felt "off." Leaders stopped seeing the ROI. Sound familiar? We see the same three patterns repeat: fragmented data, AI applied to the wrong tasks, and foundations that were never built to scale. "AI doesn't fix a broken foundation. It amplifies what's already there." In our new article, we break down what goes wrong and what the organizations that actually make it work do differently. 👉 Read it here: https://lnkd.in/eDx_2Hbh #CustomerService #AI #ServiceManagement #DigitalTransformation

News | How can AI help to make it easier for individuals to share knowledge, and contribute know-how (such as precedents) to the knowledge library? Today (14th May) we have launched a powerful new AI-powered solution which reduces manual processes, with tags, fields, descriptions and more all automatically suggested by AI on behalf of the user — enriching documents seamlessly. Learn more via the press release (below). #knowledgemanagement #KM #AI #knowledge #legaltech

AI can do a lot, but it can’t do the thinking for us. The teams seeing the biggest impact aren’t the ones using AI the most - they’re the ones using it well. They have guardrails and a plan. They know when to trust the model and when to trust their gut. AI is powerful, but human intelligence is still the engine. Use both, and the results speak for themselves. #FridayThoughts #AIMarketing #ResponsibleAI #MarketingOps #DigitalStrategy #AIEnablement #FutureOfMarketing #WorkSmarter

AI doesn’t become reliable at scale just because it’s widely deployed. Reliability depends on whether the underlying enterprise structure is clear, governed, and accessible. My colleague Yannick Rudloff unpacks this well in his latest article for Business Reporter, especially the distinction between layering AI onto existing processes and designing the operating model with AI in mind. Read his full take here: https://okt.to/RIkOYS #AI #AINative #AgenticAI #Bizzdesign

Dive into the 𝗞𝗣𝗠𝗚 𝗠𝗮𝗻𝗮𝗴𝗲𝗱 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗢𝘂𝘁𝗹𝗼𝗼𝗸 𝗦𝘂𝗿𝘃𝗲𝘆 𝟮𝟬𝟮𝟲. Scaling AI is no longer optional - but complexity, legacy tech and governance challenges stand in the way. See how leading organisations are using modern managed services to accelerate AI and deliver outcomes that matter. Explore the full report: https://social.kpmg/452b1e #ManagedServices #AI #AIGovernance #LegacyTech #AIOutcomes

Dive into the 𝗞𝗣𝗠𝗚 𝗠𝗮𝗻𝗮𝗴𝗲𝗱 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗢𝘂𝘁𝗹𝗼𝗼𝗸 𝗦𝘂𝗿𝘃𝗲𝘆 𝟮𝟬𝟮𝟲. Scaling AI is no longer optional - but complexity, legacy tech and governance challenges stand in the way. See how leading organisations are using modern managed services to accelerate AI and deliver outcomes that matter. Explore the full report: https://social.kpmg/452b1e #ManagedServices #AI #AIGovernance #LegacyTech #AIOutcomes

The businesses using AI most effectively tend to have one thing in common: they knew what they were trying to achieve before they opened the tool. Not a vague intention. A specific outcome. Not "let's see what it comes up with." A defined brief. AI responds to the quality of the thinking brought to it. A clear input doesn't guarantee a perfect output - but a vague input almost guarantees a generic one. The thinking still has to happen first. AI just makes it faster to see whether it was right. #AIStrategy #AIBusinessStudioLondon #OperationalAI

AI doesn’t become reliable at scale just because it’s widely deployed. Reliability depends on whether the underlying enterprise structure is clear, governed, and accessible. My colleague Yannick Rudloff unpacks this well in his latest article for Business Reporter, especially the distinction between layering AI onto existing processes and designing the operating model with AI in mind. Read his full take here: https://okt.to/RrCFo8 #AI #AINative #AgenticAI #Bizzdesign

Most AI use cases shouldn't be built. Yours might be the exception. Everyone thinks theirs is the exception. That's the problem. The companies getting real outcomes from AI didn't start by asking 'how do we use AI?' They started with one question: Where does the work break, and what does that cost us every day? That question has an answer. The answer has a number. The number tells you where to build. Everything else is noise. Find your signal. The rest can wait. Browse the hub: https://lnkd.in/dAEWAVjz

Most people are waiting for someone else to build the tools they use. Meanwhile, we are entering a time where companies can build their own AI work harnesses around their own workflows, data, and operations using almost any model, including local ones. That changes everything! The power of owning the layer between your people, your processes, and AI cannot be understated. The companies that understand this early will move very differently over the next decade. We keep building! #WeBuild #BeTheChangeYouWantToSeeInTheWorld #AI #HarnessThePower