An executive stopped a sales meeting to ask whether Krista would do a better job for his competitor than for him. Not a naïve question. The natural conclusion for someone whose only AI reference point is ChatGPT, a public model that answers the same way for everyone. He generalized from the only evidence he had. …
by Scott King 
To build an enterprise brain, connect your meetings, emails, tickets, and systems of record into one shared memory that remembers, reasons, and acts. Start with understanding, because understanding is what lets AI act on your behalf. Your company does not think today. It reacts. Every meeting gets recorded, every transcript gets filed, and every summary …
by Scott King 
The model you choose today is a liability tomorrow. Most companies are currently making the single most expensive mistake in their AI journey: they are treating LLM selection like a popularity contest. They choose the “celebrity” models, the ones with the loudest CEOs and the most tabloid-style hype, and they hard-code them into their business …
by Scott King 
Boards are pressuring every CIO to do something with AI this quarter. The wrong answer is to buy more agents. Most companies are signing up for 30 specialized agents from 15 vendors. Each one carves off data its own way. Each one runs in isolation. Six months in, nothing reasons across them. Call it what …
by Scott King 
Why Companies Struggle to Capture Value from GenAI Generative AI is everywhere, from boardrooms to headlines. Yet the deployment reality is sobering. A recent MIT report, The GenAI Divide, State of AI in Business 2025, found that only 5 percent of pilots deliver measurable ROI. The remaining 95 percent fail to scale or make a dent in profit …
by Scott King 
The race to adopt AI has flooded enterprises with chatbots, copilots, and isolated agents. What began as innovation is now sprawling into disconnected tools that fail to produce real outcomes. In a recent conversation with John Michelsen and Chris Kraus, we outlined the key findings from the report “Choosing the Right Agentic Platform.” The report …
by Scott King 
AI That Never Learns Many people fear having AI train on their data because they don’t want to lose proprietary data in public LLMs. So they say, “I don’t want AI training on my data.” But that’s exactly what they want—they just don’t realize what they’re saying. What they mean is they don’t want to give up …
by Scott King 
The Hidden Power of Your Meetings It’s Monday, and your inbox is clogged with meeting summaries—Zoom calls, Teams updates, customer huddles. Your team records everything, but the data scatters across silos, leaving action items untracked and insights buried. For operations executives, this is a familiar frustration. Recording tools capture discussions, yet their potential stays locked …
by Scott King 
When Anthropic introduced the Model Context Protocol (MCP) in November 2024, it triggered a wave of hype. YouTube videos, blogs, and tweet threads all chimed in to say: this is the future of AI integration. And in many ways, it is. But in our latest conversation, I wanted to step beyond the hype and ask: What …
by Scott King 
The Sticker Shock of OpenAI’s AI Agents OpenAI recently announced that its specialized AI agents could cost $2,000 to $20,000 per month.¹ For businesses eager to adopt AI, this triggers immediate sticker shock. Spending up to a quarter-million dollars per year for a single AI agent seems excessive—especially when today’s AI still struggles with basic reasoning tasks. Naturally, many …
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