{"id":6460,"date":"2025-11-21T11:49:27","date_gmt":"2025-11-21T11:49:27","guid":{"rendered":"https:\/\/www.goodcore.co.uk\/blog\/?p=6460"},"modified":"2026-05-19T06:54:46","modified_gmt":"2026-05-19T06:54:46","slug":"goodcore-google-roundtable","status":"publish","type":"post","link":"https:\/\/www.goodcore.co.uk\/blog\/goodcore-google-roundtable\/","title":{"rendered":"The Realities of AI Adoption: 8 Takeaways From the GoodCore x Google Roundtable"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">AI is shaping every conversation in tech right now, but the reality on the ground is far more complex than the headlines suggest. At our GoodCore x Google AI Roundtable, we brought together 12 founders and CEOs, plus Google\u2019s AI GTM lead, for a candid discussion about what it really means to build with AI in 2025.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The excitement was there, but so were the frustrations, the tradeoffs, and the quiet worry that some teams are trying to run before they can walk. What followed was a refreshingly honest look at the pressures leaders feel, the guardrails slowing them down, and the gaps that keep even the smartest teams from moving faster.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The discussion surfaced 8 big themes that kept coming up in different ways. If you are building anything AI-related, these insights will feel very familiar.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">1. The 10-year truth nobody wants to tell the board<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Everyone wants AI transformation now. But real, structural change, the kind that rewires how a business makes decisions, allocates resources, and serves customers, is a decade-long rebuild, not a quarterly initiative.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The uncomfortable truth is: individual incentives are misaligned with organisational transformation. As one founder put it, people want wins they can take back to their teams and leaders; something that gets them noticed, rewarded, or promoted. It\u2019s human. It\u2019s career survival (especially in this market). That\u2019s why teams chase quick wins: a pilot here, an \u201cAI-powered\u201d feature there, that makes leadership nod approvingly. These projects do add value, but they\u2019re almost always surface-level.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">What\u2019s missing is vision, not in the inspirational sense, but in the very real architectural sense. Transformative AI isn\u2019t about stitching models into today\u2019s workflows; it\u2019s about rethinking the workflows themselves. It requires:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Rebuilding data foundations<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Redesigning operational processes<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Shifting decision rights<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Reskilling teams\u00a0<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Those changes don\u2019t produce slide-worthy wins in Q1, they take years of sustained cultural, technical, and organisational refactoring. The truth is, no board wants to hear that.\u00a0<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-6469 size-full\" src=\"https:\/\/www.goodcore.co.uk\/blog\/wp-content\/uploads\/2025\/11\/GoodCore-Roundtable.png\" alt=\"\" width=\"2048\" height=\"1536\" srcset=\"https:\/\/www.goodcore.co.uk\/blog\/wp-content\/uploads\/2025\/11\/GoodCore-Roundtable.png 2048w, https:\/\/www.goodcore.co.uk\/blog\/wp-content\/uploads\/2025\/11\/GoodCore-Roundtable-300x225.png 300w, https:\/\/www.goodcore.co.uk\/blog\/wp-content\/uploads\/2025\/11\/GoodCore-Roundtable-1024x768.png 1024w, https:\/\/www.goodcore.co.uk\/blog\/wp-content\/uploads\/2025\/11\/GoodCore-Roundtable-150x113.png 150w, https:\/\/www.goodcore.co.uk\/blog\/wp-content\/uploads\/2025\/11\/GoodCore-Roundtable-768x576.png 768w, https:\/\/www.goodcore.co.uk\/blog\/wp-content\/uploads\/2025\/11\/GoodCore-Roundtable-1536x1152.png 1536w\" sizes=\"(max-width: 2048px) 100vw, 2048px\" \/><\/p>\n<h2><span style=\"font-weight: 400;\">2. UK innovation is stuck in slow motion<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Founders compared notes on fundraising and frustration. The consensus was blunt: the UK is structurally misaligned with the pace of modern innovation.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Capital doesn\u2019t flow into productive assets; it flows into property. Decades of treating real estate as a national savings account has created a system where money chases house-price inflation instead of high-growth companies.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This is the same reason the UK lost DeepMind. Before Google bought it, DeepMind spent months trying to raise locally, but no one in the UK could write the cheque. What could have been Britain\u2019s \u201cOpenAI moment\u201d became another American victory, and that same dilemma still stands.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Today, even Series A and B rounds drag on for six months. Diligence is slow, bureaucracy is heavy, and new tax policies push founders to look elsewhere. Many simply leave, to the US for speed, or to Dubai for friendlier tax regimes. British and European funds can\u2019t currently match the urgency or the scale AI startups need, so if we want to avoid the brain drain, something needs to change.\u00a0<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">3. The compliance trade-off: safety vs performance<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Early research from DeepMind, Anthropic, and others shows the uncomfortable truth: when you strip away guardrails, remove the filters, and tell the model it\u2019s allowed to be biased, violent, or even racist \u2013 performance skyrockets. With zero filter, models are sharper and more decisive.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">So enterprises, especially those in regulated environments, are stuck choosing between \u201cexcellent but risky\u201d or \u201ccompliant but mediocre\u201d models. Most choose safety, not because they lack ambition, but because regulators can\u2019t keep pace with what the technology can actually do. <\/span><span style=\"font-weight: 400;\">Interestingly, some firms are already experimenting with a middle path:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Dual constitutions (a general one and an industry-specific one),<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Fewer guardrails but stricter domain constraints,<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Specialised models instead of general-purpose giants,<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Abandoning zero-shot generality in favour of deeply specialised, role-specific AI.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">And the results are often significantly better. A model designed to do one job, with a constitution tailored to a single industry\u2019s risk profile, can outperform safer general models without wandering into dangerous territory.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">4. Exec dreams vs engineering reality<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">The gulf between C-suite expectations and technical reality has never been wider. Executives return from conferences high on narratives like \u201cAI will do half our company\u2019s work.\u201d Engineers return to decade-old codebases, broken data pipelines, and systems held together by inheritance and hope.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Engineering teams tend to be cautious by nature and training. They operate in binary truth: it works or it doesn\u2019t, the data is clean or it isn\u2019t, the system scales or it fails. And right now? Most AI initiatives live in the messy \u201cin-between\u201d, promising but brittle, powerful but dependent on fragile foundations.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This gap can&#8217;t be closed by better communication alone. It requires education, empathy, and updated roadmaps, where executives understand the constraints, and engineers understand the strategic urgency.\u00a0<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">5. The big blocker: outdated service design<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Several guests noted that companies are trying to layer AI on top of unclear data strategies, fragmented workflows, and decades-old system design. LLMs can make this mess look functional; they\u2019re brilliant at smoothing over unstructured, inconsistent inputs, but they don\u2019t repair the underlying business logic.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The deeper issue is inertia. Leaders know what their tech strategy should be. They just also know that ripping out core systems will cost three, five, even ten years of disruption. So they don\u2019t do it. AI becomes a workaround: plug models directly into data, bypass the rigid middle, and hope it holds.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">As one guest explained, \u201cFinance is simple: data \u2192 software \u2192 decision. If the software layer is dead, people try to connect decisions straight to the data.\u201d It works for now, but it\u2019s not transformation. It\u2019s coping.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The result? Organisations keep hitting the same bottlenecks. AI speeds up one stretch of the motorway, but the red lights; the workflows, the approvals, the data inconsistencies, the human processes, remain in place.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">6. Who\u2019s really benefiting from AI\u2019s productivity gains?<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">AI is automating repetitive work, but here\u2019s the uncomfortable question: are we reinvesting that saved time into higher-value work, or quietly converting it into cost savings?<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Right now, it feels like most organisations are doing the latter. Efficiency becomes justification for headcount reduction, not a catalyst for reinvention.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The narrative many organisations use is that AI will free people to do more strategic, fulfilling work, that jobs will evolve, not vanish. And that\u2019s the right aspiration. But it collides with a deeper truth: no one can clearly articulate what those \u201cnew roles\u201d look like. So workers are being told to embrace the future\u2026while staring into a fog.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This creates a dangerous transition gap: efficiency gains arrive before new career paths are defined. Companies risk reducing headcount faster than they can redesign roles, upskill teams, or create new forms of contribution.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The organisations that will win aren\u2019t the ones who simply save money with AI, they\u2019re the ones who convert efficiency into empowerment, turning reclaimed time into innovation. Everyone else will unknowingly trade long-term resilience for short-term savings.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">7. The market bubble that\u2019s heading for burst<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Several guests predicted an AI \u201ccorrection\u201d within the next 18 months, not a crash, but a reality check. The current market resembles the late-90s internet boom: ballooning valuations, rushed product launches, and promises that only work in slide decks.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">As one participant put it, \u201cAI hasn\u2019t had its browser moment yet.\u201d We\u2019re still waiting for the equivalent of the technology that makes the value obvious, mass-adoptable, and indispensable. Until that moment arrives, the gap between what\u2019s promised and what\u2019s actually achievable will keep widening.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">8. The bigger picture: AI is a mirror, not a miracle<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Across every discussion, one truth stood out: AI isn\u2019t creating new problems; it\u2019s exposing the ones companies have avoided for years. Data silos, slow governance, outdated workflows, unclear ownership, and incentives that reward activity over impact. These are the real bottlenecks, and AI simply makes them impossible to ignore.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">When a model struggles, it\u2019s usually not the model. It\u2019s the process wrapped around it. AI becomes a mirror held up to the organisation: revealing where data is broken, where decisions are slow, where compliance blocks creativity, and where teams aren\u2019t aligned on what \u201cgood\u201d even looks like.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The companies that win the long game will be the ones willing to confront these structural issues head-on: rebuilding workflows, redesigning roles, and fixing the organisational plumbing that AI currently has to work around. Everyone else will keep layering new tools onto old foundations and wondering why transformation feels so slow.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Honest conversations matter<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">This roundtable was the first in a series designed to strip away the noise and talk about what\u2019s <\/span><i><span style=\"font-weight: 400;\">really<\/span><\/i><span style=\"font-weight: 400;\"> happening in AI, not the press release version. To everyone who joined us: thank you for your candour, humour, and willingness to speak truthfully.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you\u2019d like to join a future session, drop us a message. We\u2019re keeping the table small, but the conversations big.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI is shaping every conversation in tech right now, but the reality on the ground is far more complex than the headlines suggest. At our GoodCore x Google AI Roundtable, we brought together 12 founders and CEOs, plus Google\u2019s AI GTM lead, for a candid discussion about what it really means to build with AI [&hellip;]<\/p>\n","protected":false},"author":18,"featured_media":6467,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[116],"tags":[],"class_list":{"0":"post-6460","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-ai"},"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>8 Takeaways From the GoodCore x Google Roundtable<\/title>\n<meta name=\"description\" content=\"Founders and guest speaker from Google share real insights on building with AI, the pressures teams face, and the gaps slowing adoption. 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