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rise of the Agentic Enterprise: AI’s role in business transformation",[207,210],{"path":203,"langcode":208},{"id":209},"en",{"path":211,"langcode":212},"\u002Fde\u002Finsights\u002Fder-aufstieg-des-agentic-enterprise-die-rolle-der-ki-bei-der-unternehmenstransformation",{"id":213},"de",{"id":215,"sharedMediaLegend":204,"mediaImage":216,"name":239},"172891",{"url":217,"width":218,"height":219,"alt":220,"title":204,"size":221,"mime":222,"variations":204,"headerMinimalVariations":223},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fimages\u002Fagentic_enteprise_main.jpeg",1280,720,"Abstract digital illustration of flowing, translucent ribbon-like waves in blue, teal, and purple, overlaid with faint lines of code and small glowing points, suggesting agentic AI enteprise.",113166,"image\u002Fjpeg",[224,229,230,235,238],{"name":225,"url":226,"width":227,"height":228},"FOCAL_POINT32_SMALL","https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_3_2_small\u002Fpublic\u002Fimages\u002Fagentic_enteprise_main.jpeg.webp?itok=B8PTWlcS",800,533,{"name":225,"url":226,"width":227,"height":228},{"name":231,"url":232,"width":233,"height":234},"FOCAL_POINT169_MEDIUM","https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_16_9_medium\u002Fpublic\u002Fimages\u002Fagentic_enteprise_main.jpeg.webp?itok=oDpn3fCg",1200,675,{"name":236,"url":237,"width":218,"height":219},"FOCAL_POINT169_LARGE","https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_16_9_large\u002Fpublic\u002Fimages\u002Fagentic_enteprise_main.jpeg.webp?itok=sBxB1O7Q",{"name":236,"url":237,"width":218,"height":219},"agentic_enteprise_main.jpeg",{"processed":241},"\u003Cp>Discover how agentic AI is reshaping business transformation, and what it takes to scale AI with trust, governance and real value in the Agentic Enterprise.\u003C\u002Fp>",{"id":215,"sharedMediaLegend":204,"mediaImage":243,"name":239},{"url":217,"width":218,"height":219,"alt":220,"title":204,"size":221,"mime":222,"variations":204},[245,252,259,264,269,275,280,311,353,384],{"__typename":246,"id":247,"ctaLink":204,"pgSharedText":248,"pgSharedTitle":204,"pgSharedCtaLink":204},"ParagraphPgText","34065",{"value":249,"processed":250,"format":251},"\u003Cp>Although AI has moved fast, many organisations haven’t. Most leaders we speak to aren’t short on ideas, proofs of concept, or vendor demos. The challenge is turning AI into something repeatable \u003Cspan>—\u003C\u002Fspan> a capability you can trust, scale, and steer without creating new risks or bottlenecks.\u003C\u002Fp>\u003Cp>That gap is the starting point for this conversation between Romano Roth, Prof. Dr. Oliver Gassmann, and moderator Prof. Dr. Naomi Haefner. They explore what \u003Ca href=\"\u002Fnode\u002F26055\" target=\"_blank\" data-entity-type=\"node\" data-entity-uuid=\"7513e074-abbb-4a04-9a33-e6f832a08cd7\" data-entity-substitution=\"canonical\">agentic AI\u003C\u002Fa> actually means for the enterprise, where it works today, and what organisations need to change before they can scale it.\u003C\u002Fp>\u003Cp>The discussion surfaces a productive tension. Oliver, drawing on his research article \"\u003Ca href=\"https:\u002F\u002Fcmr.berkeley.edu\u002F2025\u002F10\u002Fthe-non-human-enterprise-how-ai-agents-reshape-organizations\" title=\"Read the research article The Non-Human Enterprise\">The Non-Human Enterprise\u003C\u002Fa>\", pushes the idea of fully autonomous, agent-driven organisations as a radical thought experiment. Romano argues that real enterprises are socio-technical systems that need human-led steering, feedback loops and continuous adaptation. Where they converge is just as revealing as where they disagree.\u003C\u002Fp>","\u003Cp>Although AI has moved fast, many organisations haven’t. Most leaders we speak to aren’t short on ideas, proofs of concept, or vendor demos. The challenge is turning AI into something repeatable \u003Cspan>—\u003C\u002Fspan> a capability you can trust, scale, and steer without creating new risks or bottlenecks.\u003C\u002Fp>\u003Cp>That gap is the starting point for this conversation between Romano Roth, Prof. Dr. Oliver Gassmann, and moderator Prof. Dr. Naomi Haefner. They explore what \u003Ca href=\"\u002Fen\u002Finsights\u002Fagentic-ai-risks-rewards-of-adaptive-ai\" target=\"_blank\" data-entity-type=\"node\" data-entity-uuid=\"7513e074-abbb-4a04-9a33-e6f832a08cd7\" data-entity-substitution=\"canonical\" title=\"Agentic AI: the rewards & risks of adaptive AI\">agentic AI\u003C\u002Fa> actually means for the enterprise, where it works today, and what organisations need to change before they can scale it.\u003C\u002Fp>\u003Cp>The discussion surfaces a productive tension. Oliver, drawing on his research article \"\u003Ca href=\"https:\u002F\u002Fcmr.berkeley.edu\u002F2025\u002F10\u002Fthe-non-human-enterprise-how-ai-agents-reshape-organizations\" title=\"Read the research article The Non-Human Enterprise\">The Non-Human Enterprise\u003C\u002Fa>\", pushes the idea of fully autonomous, agent-driven organisations as a radical thought experiment. Romano argues that real enterprises are socio-technical systems that need human-led steering, feedback loops and continuous adaptation. Where they converge is just as revealing as where they disagree.\u003C\u002Fp>","full_html",{"__typename":253,"id":254,"title":204,"media":255,"text":204,"primaryImage":204,"pgSharedTitle":258},"ParagraphPgContentVideoHighlight","34163",{"id":256,"mediaOembedVideo":257},"172889","https:\u002F\u002Fyoutu.be\u002FS1SHHIGyCjI?si=9GAk6fsgExlWCV48","Watch the conversation",{"__typename":246,"id":260,"ctaLink":204,"pgSharedText":261,"pgSharedTitle":263,"pgSharedCtaLink":204},"34070",{"value":262,"processed":262,"format":251},"\u003Cp>Romano Roth is the Global Chief of Cybernetic Transformation and a Partner at Zühlke. Romano shapes Zühlke’s global strategy for cybernetic transformation, platform engineering and AI integration.\u003C\u002Fp>\u003Cp>Prof. Dr. Oliver Gassmann is a \u003Ca href=\"https:\u002F\u002Fwww.unisg.ch\u002Fen\u002Funiversity\u002Fabout-us\u002Forganisation\u002Fdetail\u002Fperson-id\u002Fe6425bfe-0dad-44bd-a417-20749b911b52\u002F\" title=\"View the profile of Prof. Dr. Oliver Gassmann\">Professor of Technology Management at University of St. Gallen\u003C\u002Fa> and Vice Chairman and Partner at Zühlke. He brings deep expertise in innovation management and the leadership required to make transformation stick.\u003C\u002Fp>\u003Cp>Prof. Dr. Naomi Haefner is an \u003Ca href=\"https:\u002F\u002Fwww.unisg.ch\u002Fen\u002Funiversity\u002Fabout-us\u002Forganisation\u002Fdetail\u002Fperson-id\u002Fdc42b915-ff4f-4a99-b463-5909f0b1b503\u002F\" title=\"View the profile of Prof. Dr. Naomi Haefner\">Assistant Professor of Technology Management at University of St. Gallen\u003C\u002Fa>. Naomi researches how emerging technologies reshape organisations, decision-making and management practices.\u003C\u002Fp>","Meet the speakers",{"__typename":246,"id":265,"ctaLink":204,"pgSharedText":266,"pgSharedTitle":268,"pgSharedCtaLink":204},"34071",{"value":267,"processed":267,"format":251},"\u003Cp>Oliver defines the agentic enterprise as the ultimate vision of a fully automated organisation \u003Cspan>—\u003C\u002Fspan> AI agents with described goals and tools that plan, execute and collaborate, much like the “dark factories” we already see in manufacturing. He deliberately pushes this to its extreme saying, 'If we would design a global insurance company on a green field with only five people, how would it look?' \u003C\u002Fp>\u003Cp>Romano brings the counterpoint. While you could build an agentic enterprise for an online shop that sells black socks, a global insurance provider is a different matter entirely. Real enterprises are complex socio-technical systems with feedback loops, regulatory constraints and human judgement at their core. Today’s AI agents reliably handle five to seven steps autonomously, but then a human needs to step in.  \u003C\u002Fp>\u003Cp>This tension between radical automation as a thought experiment and pragmatic, human-led transformation runs through the entire discussion and is what makes it valuable.\u003C\u002Fp>","The agentic enterprise: a radical thought experiment",{"__typename":246,"id":270,"ctaLink":204,"pgSharedText":271,"pgSharedTitle":274,"pgSharedCtaLink":204},"34072",{"value":272,"processed":273,"format":251},"\u003Cp>Oliver shares a compelling example from the telecom industry. Autonomous network agents monitor radio access networks and respond to unplanned events — a festival, a traffic jam, a demonstration — in real time:  \u003C\u002Fp>\u003Cul>\u003Cli data-list-item-id=\"e7a954e9a174ec2c091fd5563794af0c7\">An \u003Cstrong>event agent \u003C\u002Fstrong>scrapes social media data every 15 minutes to detect gatherings.  \u003C\u002Fli>\u003Cli data-list-item-id=\"ed2deaf933a5eab5a60f75652a3272c7a\">A \u003Cstrong>remediation agent \u003C\u002Fstrong>automatically re-segments the network.  \u003C\u002Fli>\u003Cli data-list-item-id=\"e35943a6b022666ad016dae99fed81fdc\">A \u003Cstrong>guardian agent \u003C\u002Fstrong>monitors performance KPIs and rolls back changes if they don’t improve the situation.\u003C\u002Fli>\u003C\u002Ful>\u003Cp>This innovative approach means that what previously took a team of engineers one hour now happens autonomously in eight minutes and with better performance.  \u003C\u002Fp>\u003Cp>These are what both speakers call “agentic islands”: bounded, well-understood domains where automation delivers clear, measurable gains. The challenge is connecting these islands into end-to-end value streams.\u003C\u002Fp>","\u003Cp>Oliver shares a compelling example from the telecom industry. Autonomous network agents monitor radio access networks and respond to unplanned events — a festival, a traffic jam, a demonstration — in real time:  \u003C\u002Fp>\u003Cul>\u003Cli>An \u003Cstrong>event agent \u003C\u002Fstrong>scrapes social media data every 15 minutes to detect gatherings.  \u003C\u002Fli>\u003Cli>A \u003Cstrong>remediation agent \u003C\u002Fstrong>automatically re-segments the network.  \u003C\u002Fli>\u003Cli>A \u003Cstrong>guardian agent \u003C\u002Fstrong>monitors performance KPIs and rolls back changes if they don’t improve the situation.\u003C\u002Fli>\u003C\u002Ful>\u003Cp>This innovative approach means that what previously took a team of engineers one hour now happens autonomously in eight minutes and with better performance.  \u003C\u002Fp>\u003Cp>These are what both speakers call “agentic islands”: bounded, well-understood domains where automation delivers clear, measurable gains. The challenge is connecting these islands into end-to-end value streams.\u003C\u002Fp>","Where AI agents deliver value today",{"__typename":246,"id":276,"ctaLink":204,"pgSharedText":277,"pgSharedTitle":279,"pgSharedCtaLink":204},"34073",{"value":278,"processed":278,"format":251},"\u003Cp>Both speakers are blunt about why so many organisations struggle: they add AI onto existing processes and expect magical results.\u003C\u002Fp>\u003Cp>According to Romano, the current focus on generative AI tools (which vendor, which LLM) distracts from the real work. 'Go away from the tool itself. Think about identifying processes and bottlenecks.' His recommended method is value stream mapping, a technique from the Toyota Production System. This means mapping every step, and analysing process time, lead time, percentage complete and correcting it; and only then designing the future state. Sometimes that future doesn’t even involve AI.\u003C\u002Fp>\u003Cp>As Oliver points out, most European companies still think of hardware-era strategy cycles. The automotive industry plans around SOP minus three — three years before starting production. But AI frameworks change every three to four months and inference costs drop by 900x per year. Strategy as a plan has to be replaced with creating strategic flexibility.\u003C\u002Fp>","Why most AI initiatives disappoint",{"__typename":281,"id":282,"caption":283,"imageRight":284,"pgSharedTitle":285,"pgSharedCtaLink":204,"textMedia":286,"pgSharedText":308},"ParagraphPgTextMedia","34075","Human Distribution of Work - AI",false,"A framework for deciding what to transform",{"id":287,"sharedMediaLegend":283,"mediaImage":288,"name":307},"172890",{"url":289,"width":290,"height":291,"alt":292,"title":204,"size":293,"mime":294,"variations":204,"textMediaVariations":295},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fimages\u002Fagentic_cybernetic_enterprise.png",1070,853,"A four-quadrant matrix with a purple cross-shaped set of arrows. The vertical axis runs from “Humans work together with AI” at the bottom to “Humans hand over their work to AI” at the top. The horizontal axis runs from “Work stays the same, powered by AI” on the left to “Work is transforming” on the right. The quadrants are labelled: top-left “Automate & Orchestrate”, top-right “AI-First”, bottom-left “Augmenting & Scaling”, and bottom-right “Co-Create on the Frontier”.",89483,"image\u002Fpng",[296,301,302,303,306],{"name":297,"url":298,"width":299,"height":300},"FIXED_WIDTH_SMALL","https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffixed_width_small\u002Fpublic\u002Fimages\u002Fagentic_cybernetic_enterprise.png.webp?itok=z3byZ1MW",900,717,{"name":297,"url":298,"width":299,"height":300},{"name":297,"url":298,"width":299,"height":300},{"name":304,"url":305,"width":290,"height":291},"FIXED_WIDTH_MEDIUM","https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffixed_width_medium\u002Fpublic\u002Fimages\u002Fagentic_cybernetic_enterprise.png.webp?itok=D1Y2vRzA",{"name":304,"url":305,"width":290,"height":291},"agentic_cybernetic_enterprise.png",{"value":309,"processed":310,"format":251},"\u003Cp>Romano uses a practical two-axis framework when advising companies:  \u003C\u002Fp>\u003Cul>\u003Cli data-list-item-id=\"e035bb7f95a6c6dd2344e2c6b0e73b3f7\">\u003Cstrong>Horizontal axis: \u003C\u002Fstrong>How much do we need to transform the work itself — adapt processes or redesign them entirely?  \u003C\u002Fli>\u003Cli data-list-item-id=\"e226a44eb7d17df8f2d4db3c09410c672\">\u003Cstrong>Vertical axis: \u003C\u002Fstrong>How much do we delegate to AI, co-create with AI, or keep with humans?  \u003C\u002Fli>\u003C\u002Ful>\u003Cp>This produces four quadrants that help teams map their current work and decide where to move. The thinking itself — examining every process step and deciding whether to change it, automate it, or leave it — is what most organisations haven’t done yet. Without it, AI is just an expensive addition to a broken process.\u003C\u002Fp>","\u003Cp>Romano uses a practical two-axis framework when advising companies:  \u003C\u002Fp>\u003Cul>\u003Cli>\u003Cstrong>Horizontal axis: \u003C\u002Fstrong>How much do we need to transform the work itself — adapt processes or redesign them entirely?  \u003C\u002Fli>\u003Cli>\u003Cstrong>Vertical axis: \u003C\u002Fstrong>How much do we delegate to AI, co-create with AI, or keep with humans?  \u003C\u002Fli>\u003C\u002Ful>\u003Cp>This produces four quadrants that help teams map their current work and decide where to move. The thinking itself — examining every process step and deciding whether to change it, automate it, or leave it — is what most organisations haven’t done yet. Without it, AI is just an expensive addition to a broken process.\u003C\u002Fp>",{"__typename":312,"id":313,"title":314,"lead":204,"tabs":315},"ParagraphTab","34086","Highlights from the conversation",[316,323,330,338,346],{"infoText":317,"pgSharedParagraphs":318},"Human-led, AI-enabled",[319],{"id":320,"ctaLink":204,"pgSharedText":321,"pgSharedTitle":317,"pgSharedCtaLink":204},"34076",{"value":322,"processed":322,"format":251},"\u003Cp>A consistent theme is that AI can enhance judgement and execution, but it can’t compensate for missing clarity. If the goals aren’t defined, accountability is unclear, or teams don’t have the encouragement to act, AI alone won’t be able to fix it.\u003C\u002Fp>\u003Cp>Romano illustrates this with a cautionary story. A bachelor thesis student delivered polished, AI-generated slides on Kubernetes certificate management, but couldn’t explain any of the solutions or why one built on another. 'Use AI, absolutely, but you need to own the work. You need to understand it,' says Romano. This is a leadership responsibility \u003Cspan>—\u003C\u002Fspan> ensuring that people take ownership of AI-generated output.\u003C\u002Fp>",{"infoText":324,"pgSharedParagraphs":325},"Start with strategy, not technology",[326],{"id":327,"ctaLink":204,"pgSharedText":328,"pgSharedTitle":324,"pgSharedCtaLink":204},"34078",{"value":329,"processed":329,"format":251},"\u003Cp>'Start with strategy, tech comes second,' insists Oliver. There are several questions that must be asked before going into the tech, such as: Where do we differentiate? What’s our positioning from a customer perspective?\u003C\u002Fp>\u003Cp>AI is the second or third step, but it should never be the first. Oliver adds two more preconditions: break down silos into cross-functional teams (because end-to-end solutions require it) and build genuine AI literacy (not just rolling out Copilot and counting logins).  \u003C\u002Fp>\u003Cp>The AI literacy point is practical. Oliver sees executives excited about high adoption numbers, but the actual usage is basic. Real productivity gains require understanding what AI can and can’t do and measuring outcomes instead of only activity.\u003C\u002Fp>",{"infoText":331,"pgSharedParagraphs":332},"Trust becomes non-negotiable",[333],{"id":334,"ctaLink":204,"pgSharedText":335,"pgSharedTitle":331,"pgSharedCtaLink":204},"34080",{"value":336,"processed":337,"format":251},"\u003Cp>When systems move from assisting to acting, trust can’t be an afterthought. You need explicit boundaries: what the AI can decide, what must be escalated, what gets logged, and how you detect drift.\u003C\u002Fp>\u003Cp>In practice, \u003Ca href=\"\u002Fnode\u002F7862\" title=\"Discover our framework for responsible AI\" data-entity-type=\"node\" data-entity-uuid=\"19fe309b-e7b8-445c-a515-c581ba0b5e23\" data-entity-substitution=\"canonical\">responsible AI\u003C\u002Fa> becomes less of a policy slide and more of an operating discipline, needing guardrails, monitoring, and clear ownership.\u003C\u002Fp>\u003Cp>\u003Ca href=\"\u002Fnode\u002F26816\" title=\"Read our guide to digital sovereignty\" data-entity-type=\"node\" data-entity-uuid=\"5288f1e3-ef0c-4090-8bcd-416bb43f98f9\" data-entity-substitution=\"canonical\">Data sovereignty\u003C\u002Fa> adds another layer. Romano reports increasing C-level concern about where company data resides, especially in the current geopolitical environment. European cloud and AI platform providers are stepping into this gap. For sensitive domains like patent litigation, organisations are choosing on-premise deployments with smaller, more focused language models, accepting some performance trade-offs for control.\u003C\u002Fp>","\u003Cp>When systems move from assisting to acting, trust can’t be an afterthought. You need explicit boundaries: what the AI can decide, what must be escalated, what gets logged, and how you detect drift.\u003C\u002Fp>\u003Cp>In practice, \u003Ca href=\"\u002Fen\u002Finsights\u002Fresponsible-ai-framework-for-ethical-applications\" title=\"Discover our framework for responsible AI\" data-entity-type=\"node\" data-entity-uuid=\"19fe309b-e7b8-445c-a515-c581ba0b5e23\" data-entity-substitution=\"canonical\">responsible AI\u003C\u002Fa> becomes less of a policy slide and more of an operating discipline, needing guardrails, monitoring, and clear ownership.\u003C\u002Fp>\u003Cp>\u003Ca href=\"\u002Fen\u002Finsights\u002Fdigital-sovereignty-guide\" title=\"Read our guide to digital sovereignty\" data-entity-type=\"node\" data-entity-uuid=\"5288f1e3-ef0c-4090-8bcd-416bb43f98f9\" data-entity-substitution=\"canonical\">Data sovereignty\u003C\u002Fa> adds another layer. Romano reports increasing C-level concern about where company data resides, especially in the current geopolitical environment. European cloud and AI platform providers are stepping into this gap. For sensitive domains like patent litigation, organisations are choosing on-premise deployments with smaller, more focused language models, accepting some performance trade-offs for control.\u003C\u002Fp>",{"infoText":339,"pgSharedParagraphs":340},"Feedback loops beat big-bang transformation",[341],{"id":342,"ctaLink":204,"pgSharedText":343,"pgSharedTitle":339,"pgSharedCtaLink":204},"34082",{"value":344,"processed":345,"format":251},"\u003Cp>Rather than multi-year programmes, both speakers lean into short, instrumented loops. This is the core of the \u003Ca href=\"\u002Fnode\u002F26876\" title=\"Discover the Cybernetic Enterprise\" data-entity-type=\"node\" data-entity-uuid=\"c947819e-d3a5-4562-b751-e4fe05e21778\" data-entity-substitution=\"canonical\">Cybernetic Enterprise\u003C\u002Fa> concept. Organisations that sense, learn, and continuously adapt, using the data they already have, outperform those that plan in annual or multi-year cycles.  \u003C\u002Fp>\u003Cp>“You need to become a company which senses and learns and continuously adapts. You can't do any more one-year or two-year or five-year plans”, says Romano.  \u003C\u002Fp>\u003Cp>Oliver agrees and reframes it – the ultimate goal is becoming a truly data-driven company. But he’s also realistic – he believes many “AI-first” initiatives quickly turn into data integration projects, because the data simply isn’t there in the right quality.\u003C\u002Fp>","\u003Cp>Rather than multi-year programmes, both speakers lean into short, instrumented loops. This is the core of the \u003Ca href=\"\u002Fen\u002Finsights\u002Fbenefits-of-becoming-cybernetic-enterprise\" title=\"Discover the Cybernetic Enterprise\" data-entity-type=\"node\" data-entity-uuid=\"c947819e-d3a5-4562-b751-e4fe05e21778\" data-entity-substitution=\"canonical\">Cybernetic Enterprise\u003C\u002Fa> concept. Organisations that sense, learn, and continuously adapt, using the data they already have, outperform those that plan in annual or multi-year cycles.  \u003C\u002Fp>\u003Cp>“You need to become a company which senses and learns and continuously adapts. You can't do any more one-year or two-year or five-year plans”, says Romano.  \u003C\u002Fp>\u003Cp>Oliver agrees and reframes it – the ultimate goal is becoming a truly data-driven company. But he’s also realistic – he believes many “AI-first” initiatives quickly turn into data integration projects, because the data simply isn’t there in the right quality.\u003C\u002Fp>",{"infoText":347,"pgSharedParagraphs":348},"The exponential horizon",[349],{"id":350,"ctaLink":204,"pgSharedText":351,"pgSharedTitle":347,"pgSharedCtaLink":204},"34084",{"value":352,"processed":352,"format":251},"\u003Cp>Oliver puts a number on the pace of change – even assuming a modest 10x improvement per year in AI capabilities, that’s 10,000x in four years. For any company thinking on a five-year horizon, the implications are enormous. ‘We will see radically new solutions, things we couldn’t have thought of’, he says.\u003C\u002Fp>\u003Cp>Romano’s vision for the near future is equally bold – AI will work directly on data, making middleware, APIs, and traditional user interfaces unnecessary. Interaction will be conversational (by either typing or speaking), and the AI will operate on the data directly. ‘The whole thing about user interfaces, apps, middleware; all this will be gone’.\u003C\u002Fp>\u003Cp>Both speakers compare this moment to the 1990s, when no one predicted the app economy that would follow. The opportunity space is real, but so is the disruption, particularly for inexperienced workers entering the job market.\u003C\u002Fp>",{"__typename":354,"id":355,"columns":356,"listItems":357,"text":204,"title":382,"variant":383},"ParagraphPgContentList","34090","3col",[358,368,375],{"id":359,"icon":360,"link":204,"logo":204,"media":204,"text":364,"title":367},"34087",{"id":361,"file":362},"170294",{"url":363},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002F2024-07\u002Fdouble-arrow-right-icon.svg",{"value":365,"processed":365,"format":366},"\u003Cp>Pick one end-to-end flow. Use value stream mapping to identify bottlenecks. process time, lead time, percentage complete and correct. Design the future state. AI may or may not be part of the solution. Start with efficiency gains; move to the customer journey once you’ve proven the approach.\u003C\u002Fp>","content_list","1. Map a value stream before you add AI",{"id":369,"icon":370,"link":204,"logo":204,"media":204,"text":372,"title":374},"34088",{"id":361,"file":371},{"url":363},{"value":373,"processed":373,"format":366},"\u003Cp>Be explicit about decision boundaries, escalation paths, monitoring and rollback. The telecom example shows that a guardian agent is essential infrastructure, not an optional add-on.\u003C\u002Fp>","2. Design guardrails before you scale autonomy",{"id":376,"icon":377,"link":204,"logo":204,"media":204,"text":379,"title":381},"34089",{"id":361,"file":378},{"url":363},{"value":380,"processed":380,"format":366},"\u003Cp>Standardise patterns for secure data access, model integration, deployment and observability. Build governance into the AI platform so teams can move fast without breaking trust. This is what separates companies that scale from companies that accumulate demos.\u003C\u002Fp>","3. Invest in the platform, not a pile of pilots","Three practical moves leaders can make now","icon",{"__typename":385,"id":386,"pgTitle":387,"text":388,"link":389,"coloredBackground":7,"compactMode":7,"actionVariant":26,"buttonText":204,"pgEmbededCode":392},"ParagraphPgCtaDefault","34164","Ready to move beyond pilots?","AI value doesn’t come from deploying models. It comes from designing an organisation that can learn and deliver in real time, with the right feedback loops, foundations, and governance in place. \r\n\r\nIf you’d like to explore what the Cybernetic Enterprise could mean for your organisation — from operating model to engineering platform — we’d be happy to talk.",{"title":390,"url":391,"internal":7},"Get in touch","\u002Fen\u002Fcontact",{"value":393,"processed":393,"format":394},"","code",[396],{"id":397,"name":398},"855","All industries",[400],{"id":401,"name":402},"110","AI",{"processed":404},"\u003Cp>AI is moving fast, but turning it into repeatable, measurable value is still a challenge. In this conversation, Prof. Dr. Naomi Haefner (University of St. Gallen) hosts Romano Roth (Zühlke) and Prof. Dr. Oliver Gassmann (University of St. Gallen) to explore the rise of the Agentic Enterprise and what it takes to scale AI responsibly for real business transformation.\u003C\u002Fp>\n",{"timestamp":406},1772020800,[408,430],{"status":7,"contactName":409,"contactProfession":410,"contactLinkedinUrl":411,"sharedEmail":413,"sharedRefMedia":414},"Romano Roth","Chief AI Officer & Partner",{"title":393,"url":412,"internal":284},"https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fromanoroth\u002F","romano.roth@zuehlke.com",{"id":415,"sharedMediaLegend":204,"mediaImage":416,"name":429},"4009",{"url":417,"width":418,"height":418,"alt":419,"title":204,"size":420,"mime":222,"variations":204,"authorVariations":421},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fimages\u002Fromano_roth_0.jpg",500,"Romano Roth, Thought Leader DevOps",67675,[422,425,426,427,428],{"name":423,"url":424,"width":418,"height":418},"FOCAL_POINT11_SMALL","https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_1_1_small\u002Fpublic\u002Fimages\u002Fromano_roth_0.jpg.webp?itok=kxFcWKun",{"name":423,"url":424,"width":418,"height":418},{"name":423,"url":424,"width":418,"height":418},{"name":423,"url":424,"width":418,"height":418},{"name":423,"url":424,"width":418,"height":418},"romano_roth_0.jpg",{"status":7,"contactName":431,"contactProfession":432,"contactLinkedinUrl":433,"sharedEmail":204,"sharedRefMedia":435},"Oliver Gassmann","Vice Chairman & Partner",{"title":393,"url":434,"internal":284},"https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Folivergassmann\u002F",{"id":436,"sharedMediaLegend":204,"mediaImage":437,"name":449},"172042",{"url":438,"width":439,"height":439,"alt":440,"title":204,"size":441,"mime":222,"variations":204,"authorVariations":442},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fimages\u002FOliver-Gassmann-1000x1000px.jpg",1000,"Oliver Gassmann, Zühlke",256173,[443,445,446,447,448],{"name":423,"url":444,"width":227,"height":227},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_1_1_small\u002Fpublic\u002Fimages\u002FOliver-Gassmann-1000x1000px.jpg.webp?itok=rdW5u9nH",{"name":423,"url":444,"width":227,"height":227},{"name":423,"url":444,"width":227,"height":227},{"name":423,"url":444,"width":227,"height":227},{"name":423,"url":444,"width":227,"height":227},"Oliver-Gassmann-1000x1000px.jpg",[451,480,506,537],{"id":452,"path":453,"sharedTeaserTitle":454,"sharedTeaserRefMedia":455,"sharedTaxrefIndustries":473,"sharedTaxrefExpertises":475},"25818","\u002Fen\u002Finsights\u002Ffrom-code-to-conversation-the-new-era-of-digital-interaction","Digital interaction: the role of LLMs in personalising experiences",{"id":456,"sharedMediaLegend":204,"mediaImage":457,"name":472},"169796",{"url":458,"width":459,"height":460,"alt":461,"title":204,"size":462,"mime":222,"variations":204,"relatedContentVariations":463},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fimages\u002Fai-touch-screen_1.jpg",1920,1617,"\"\"",333374,[464,466,467,470,471],{"name":225,"url":465,"width":227,"height":228},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_3_2_small\u002Fpublic\u002Fimages\u002Fai-touch-screen_1.jpg.webp?itok=ftqe8Ug0",{"name":225,"url":465,"width":227,"height":228},{"name":468,"url":469,"width":233,"height":227},"FOCAL_POINT32_MEDIUM","https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_3_2_medium\u002Fpublic\u002Fimages\u002Fai-touch-screen_1.jpg.webp?itok=UGyvSLba",{"name":468,"url":469,"width":233,"height":227},{"name":468,"url":469,"width":233,"height":227},"ai-touch-screen.jpg",[474],{"id":397,"name":398},[476,477],{"id":401,"name":402},{"id":478,"name":479},"129","Experience design",{"id":481,"path":482,"sharedTeaserTitle":483,"sharedTeaserRefMedia":484,"sharedTaxrefIndustries":500,"sharedTaxrefExpertises":504},"26501","\u002Fen\u002Finsights\u002Fcomputer-vision-in-retail","Computer vision in retail: How AI-enabled video is giving retail stores a new set of eyes",{"id":485,"sharedMediaLegend":204,"mediaImage":486,"name":499},"171760",{"url":487,"width":218,"height":219,"alt":488,"title":204,"size":489,"mime":222,"variations":204,"relatedContentVariations":490},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fimages\u002FDigital%20eye%20representing%20computer%20vision%20in%20retail.jpg","Digital eye representing computer vision in retail",172163,[491,493,494,497,498],{"name":225,"url":492,"width":227,"height":228},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_3_2_small\u002Fpublic\u002Fimages\u002FDigital%20eye%20representing%20computer%20vision%20in%20retail.jpg.webp?itok=eueU9Zdp",{"name":225,"url":492,"width":227,"height":228},{"name":468,"url":495,"width":496,"height":219},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_3_2_medium\u002Fpublic\u002Fimages\u002FDigital%20eye%20representing%20computer%20vision%20in%20retail.jpg.webp?itok=uAMr89Ui",1080,{"name":468,"url":495,"width":496,"height":219},{"name":468,"url":495,"width":496,"height":219},"Digital eye representing computer vision in retail.jpg",[501],{"id":502,"name":503},"9","Commerce & retail",[505],{"id":401,"name":402},{"id":507,"path":508,"sharedTeaserTitle":509,"sharedTeaserRefMedia":510,"sharedTaxrefIndustries":528,"sharedTaxrefExpertises":532},"348","\u002Fen\u002Finsights\u002Freclaiming-your-healthcare-data","Reclaiming your healthcare data",{"id":511,"sharedMediaLegend":204,"mediaImage":512,"name":527},"278",{"url":513,"width":514,"height":515,"alt":516,"title":204,"size":517,"mime":222,"variations":204,"relatedContentVariations":518},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fimages\u002Freclaiming_healthcare_data.jpg",693,520,"Healthcare data on iPad",180148,[519,522,523,525,526],{"name":225,"url":520,"width":514,"height":521},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_3_2_small\u002Fpublic\u002Fimages\u002Freclaiming_healthcare_data.jpg.webp?itok=rXgthDSh",462,{"name":225,"url":520,"width":514,"height":521},{"name":468,"url":524,"width":514,"height":521},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_3_2_medium\u002Fpublic\u002Fimages\u002Freclaiming_healthcare_data.jpg.webp?itok=BsCTECtr",{"name":468,"url":524,"width":514,"height":521},{"name":468,"url":524,"width":514,"height":521},"reclaiming_healthcare_data.jpg",[529],{"id":530,"name":531},"12","Pharma",[533,534],{"id":401,"name":402},{"id":535,"name":536},"19","Digital strategy",{"id":538,"path":539,"sharedTeaserTitle":540,"sharedTeaserRefMedia":541,"sharedTaxrefIndustries":556,"sharedTaxrefExpertises":558},"26789","\u002Fen\u002Finsights\u002Fwill-the-next-biotech-breakthrough-be-digital-before-its-biological","Will digital come before biology in biotech’s next leap?",{"id":542,"sharedMediaLegend":204,"mediaImage":543,"name":555},"172502",{"url":544,"width":218,"height":219,"alt":545,"title":204,"size":546,"mime":294,"variations":204,"relatedContentVariations":547},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fimages\u002FThumbnail_Episode_4_Bibi_Ephraim.png","A promotional graphic for the podcast “Tech Tomorrow with David Elliman.” On the left, there’s a portrait of a man wearing glasses and a maroon academic-style gown with a white shirt and matching tie. A label below the image reads “Bibi Ephraim.” The background features a dynamic blue and purple gradient design with abstract wave-like patterns.",2052664,[548,550,551,553,554],{"name":225,"url":549,"width":227,"height":228},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_3_2_small\u002Fpublic\u002Fimages\u002FThumbnail_Episode_4_Bibi_Ephraim.png.webp?itok=Hne72IDN",{"name":225,"url":549,"width":227,"height":228},{"name":468,"url":552,"width":496,"height":219},"https:\u002F\u002Fcms.zuehlke.com\u002Fsites\u002Fdefault\u002Ffiles\u002Fstyles\u002Ffocal_point_3_2_medium\u002Fpublic\u002Fimages\u002FThumbnail_Episode_4_Bibi_Ephraim.png.webp?itok=DH3u-OnL",{"name":468,"url":552,"width":496,"height":219},{"name":468,"url":552,"width":496,"height":219},"Thumbnail_Episode_4_Bibi_Ephraim.png",[557],{"id":530,"name":531},[559],{"id":401,"name":402}]