Super to see GPT-5.6 with Work IQ come to Copilot Chat, Cowork, M365 apps, GitHub, and Foundry today. From multi-step agentic work to analysis and content creation, it brings stronger reasoning and…

Microsoft released GPT-5.6 with Work IQ across Copilot Chat, Cowork, M365 apps, GitHub, and Foundry, bringing stronger reasoning and multi-step agentic capabilities. The integration aims to embed advanced AI directly into enterprise workflows, shifting AI from a productivity tool to an operating layer for knowledge work.

Super to see GPT-5.6 with Work IQ come to Copilot Chat, Cowork, M365 apps, GitHub, and Foundry today. From multi-step agentic work to analysis and content creation, it brings stronger reasoning and higher-quality outputs without sacrificing efficiency. Try it out: https://lnkd.in/giKyzdFt https://www.linkedin.com/redir/redirect?url=https%3A%2F%2Flnkd%2Ein%2FgiKyzdFt&urlhash=OtvQ&trk=public post-text It’s great to see Microsoft moving so quickly with the integration into Copilot ... new models always bring new possibilities Even though I believe the technology is now far ahead of users’ mindset and readiness. We need to invest a lot of time and effort in ensuring it’s adopted and used properly to create added value. Everyone get's that there is value - but how to lift it? The question isn’t whether it’s Opus, FableGPT 5.5 or 5.6, but how I can make use of these incredible, complex and diverse possibilities in my day-to-day work. I’m looking forward to testing 5.6 Maya C. https://www.linkedin.com/in/maya-c-85829huk?trk=public post comment actor-name 16m The most compelling shift lies not merely in the enhancement of models, but in how advanced inference technologies are directly integrated into enterprise workflows. As artificial intelligence evolves from assisting in single tasks to coordinating multi-step processes, governance, integration, and measurable business outcomes will become true differentiators. We eagerly anticipate seeing how organizations translate these capabilities into lasting business value This is the real inflection point. The value is no longer just in model capability, but in how deeply it is embedded into the systems where knowledge work actually happens. When reasoning, content creation, and multi-step agentic work become native to Copilot, M365, GitHub, and Foundry, AI starts shifting from a tool people occasionally use to an operating layer people build around. What stands out most is the balance between stronger reasoning and efficiency. The next era of enterprise AI will not be defined by the biggest model alone, but by which systems can deliver reliable, high-quality output at scale without adding friction to daily work. Exciting to see this level of reasoning moving directly into the tools where real work already happens. The biggest shift is not just better answers, but better execution across context, documents, code, meetings, and workflows. This is where AI starts moving from assistant to actual work partner. One shift worth watching is that AI is moving beyond being a productivity tool and becoming part of the operating model. The competitive advantage won't come from having access to the latest model alone. It will come from how organizations redesign workflows, decision-making, and collaboration around it. Technology evolves quickly. Execution capability is what turns it into business value. The Work IQ integration across M365, GitHub, and Foundry is the detail that matters most for enterprise adoption. Most AI announcements focus on model capability. This one focuses on model placement — putting GPT-5.6 reasoning directly inside the workflows where enterprise knowledge already lives. That's a fundamentally different strategy. In 10 years of enterprise automation work, the tools that got adopted weren't always the most capable ones. They were the ones that appeared inside existing workflows rather than requiring people to leave them. The friction of switching context — even for a superior tool — is enough to kill adoption at enterprise scale. What's significant about offering GPT-5.6 Sol, Terra, and multiple Claude models inside Copilot is that Microsoft is solving for workflow continuity, not just intelligence. The model becomes ambient. The work stays central. That's the design philosophy that enterprise environments actually require — and it's been missing from most AI deployment strategies until now. The question for enterprise teams: are your workflows ready to absorb ambient AI reasoning, or will the intelligence arrive before the processes are prepared to use it? As always: Microsoft keeps up the speed and is faster than Lightning McQueen kachow ⚡️ Since the next best AI Model is coming like every other week, organizations need to speed up their employees as well. While ensuring the latest & greatest security & governance mechanism. exciting times for FY27 - Let‘s Copilot Your Day 🥳 Model version numbers are marketing. What actually matters is which math is running the business, not which LLM answers faster. A ledger has no room for "probably." An LLM does — 51% confidence is a fine answer for a chatbot and a fireable offense for an accounting entry. So the interesting question isn't GPT-5.6 vs whatever Copilot ran last month, its whether anything actually sits between the two math systems. Not a wrapper. Not a "trust score." A runtime gate that timestamps the request, snapshots the state before it touches the ledger, checks it against policy, and can kill the job mid-execution if it doesn't clear. Block first, document after — not the other way round. Swap the model tomorrow and none of that should move. If it does, you never had a gate. You had a camera. Edwin Uchman https://ch.linkedin.com/in/edwinuchman?trk=public post comment actor-name 3d AI is becoming the airplane of modern business. And many boards are still holding 50 meetings to study how the airplane works before deciding whether it is worth boarding. Meanwhile, their competitors are already in the air. Moving faster. Researching faster. Serving customers faster. Creating content faster. Analyzing markets faster. Testing ideas faster. Improving decisions faster. Of course, governance matters. Security matters. Data quality matters. Responsible implementation matters. But endless discussion is not strategy. At some point, leadership has to move. The companies that wait for perfect certainty may discover that the market did not wait with them. Less meditation. More execution. Because AI will not reward the companies that only talk about transformation. It will reward the companies that actually transform how work gets done. Edwin Uchman I THE MARGIN HEMORRHAGE Cecil Lacy https://www.linkedin.com/in/cecil-lacy-fossfnp?trk=public post comment actor-name 3d Here is the exact tragic flaw of Big Tech bureaucracy: They suffer from chronic sluggish implementation. Because they are so massive, turning the ship takes ages, and they get trapped in a perpetual loop of committee meetings, compliance reviews, and risk assessments before they can even test a disruptive concept. While they are slowly moving through their corporate red tape, the market doesn't stop. By being slow to look into a paradigm shift like this, they leave the door wide open for an agile player, a sector anchor, to jump in first. The moment a mid-market enterprise, a fast-moving AI startup, or a sharp cloud infrastructure provider locks down that license, they secure a massive competitive edge in data economics. They instantly reduce their overhead, drop their rack power constraints, and establish a leaner operation. By the time the legacy giants like Microsoft finally wake up, get past their internal friction, and try to jump, the landscape will have already shifted. They’ll be forced to play catch-up with an architecture that someone else has already weaponized as a sector anchor. 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