Tag: enterpriseai
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AI is valuable to the individual, less so to the organization
Ask an individual if AI made them more productive and about four in five say yes. Ask an organization if it moved EBIT and it’s fewer than two in five, and one in sixteen for anything you’d call real. A chart pulling three August surveys together, plus why the goal should be getting better at…
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One CEO in eight got what AI was sold as, survey
PwC asked 4,454 CEOs what AI did to their revenue and costs over the last twelve months. The biggest single box on the matrix, at 42%, is the one where nothing moved. One in eight got both benefits at once, and 13% came out worse.
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Relative to your interests, Friday
From: The adorable love story behind Wikipedia’s ‘high five’ photos ICYMI Original content published since last time. Shadow AI and Who Is Watching What the AI Bill Actually Looks Like People Actually Using It More Wastebook All things are possible, but this thing is more possible. AI Summaries I wanted to read these, but I…
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Relative to your interests, Thursday
From Marc Weidenbaum, June 22, 2026. ICYMI Original content published since last time. Where the Developer Day Actually Goes Theoretic charts: Only three of the eight bands move. Source: The AI productivity gap by Bjorn Roche. Juniors spend more of the day on the one thing AI speeds up, so they gain more, not less.…
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How people use AI in 2026: TV, homework, the DMV
Google looked at 15 million Gemini conversations and found people mostly asking about TV, homework, and government paperwork. Work is 13.5% of it, and almost none of that is trying to automate anything. Also: what the study leaves out, which is most of enterprise AI.
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Relative to your interests, Tuesday
I have been on vacation for a little while, in Finland for the third time. Finland feels different than the other parts of Europe I have been to. Perhaps it’s because I spent my time there in rural Finland. But it also feels like most of Finland is rural. In that way, it feels a…
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short feedback loops always works
Using short feedback loops to experiment and direct software development is always a good idea, especially with AI: What survives from Agile is the feedback logic. Short cycles still matter. Thin vertical slices still matter. Customer or stakeholder review still matters. Working software is still better than progress theater because agents can generate a lot…
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Employee avoiding AI, doing manual work instead
A new global survey of 3,750 executives and employees across 14 countries, conducted by SAP subsidiary WalkMe for its fifth annual State of Digital Adoption report, finds that more 54% of workers bypassed their company’s AI tools in the past 30 days and completed the work manually instead. Another 33% haven’t used AI at all.…
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Normie AI Usage: Figures & Findings
Programmers are still the dominant users of UI and, thus, drive AI use cases. The much larger market are “normies,” people outside of the IT department who are doing “knowledge work” and other tasks in organizations. I asked the AI to pull together a list of what those activities are and the momentum around them.…
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Enterprise Java apps are much more than just code, AI benchmarks don’t measure the Java SDLC enough
There’s countless dependencies in other frameworks and libraries, plus the build pipeline and even production platform are part of the app. Enterprise Java applications frequently span hundreds or thousands of modules connected through Maven or Gradle builds, Spring dependency injection, Jakarta EE services, annotation processors, generated code, legacy XML configuration, container orchestration, proprietary build plugins,…
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How NatWest is using AI
The NatWest CIO goes over how they’re using AI with some use cases. Some: “Today at NatWest, over 40% of all code is either AI-generated or AI-assisted.” AI use: “If you’re a relationship manager, if you’re a branch manager, or you’re sitting as a teller in the branch, whatever that role is, you’ve got better…
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Reducing token usage
Better Defaults (not Usage Caps) — Engineers can choose any model they want, but defaults matter. We’re experimenting with defaulting to open weight models like GLM 5.2 and Kimi 2.7 through our LLM gateway, while still encouraging engineers to choose the right model for the task. 91% of our employees were never hitting their usage…
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“this is the voice of American business that is being channeled through me”
“Livid” was the word he used to describe enterprise customers who are “paying for tokens that create no value,” while handing over their data to the major firms and, in the end, taxing the public who will end up paying for it in some form. The reason, he ventured, was the “models have completely… irresponsibly…
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Elusive Enterprise AI ROI: bring in the FDEs
Enterprise AI needs a lot of custom fitting and one off integration, so you need a lot of post-sales engineering. On the one hand, this is lock-in in the making, but lock-in to your own, stack. You build a stack that is unique to you. On the other hand, it means you get exactly what…
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How AI change your software development organization
A catch-up with Purnima Padmanabhan, GM of the Tanzu Division at Broadcom, on what her team has actually learned shipping enterprise software with AI for the last year and a half: code generation is the small part, beautiful code is the new uncanny valley, and you cannot solve the agent boundary problem from inside the…
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Enterprise AI on private cloud
Last year, 56 percent of enterprises used public cloud as the primary environment for production AI inference. This year, that figure has fallen 15 percentage points to 41 percent, while 56 percent of enterprises are now running or planning to run production inferencing in a private cloud. 🔗 The AI tipping point: where enterprise AI…
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“PE 2.0”
We are seeing a distinct movement where infrastructure is being reclaimed as a first-class platform concern. In the early days, platform engineering focused heavily on developer experience, often treating the underlying infrastructure as a utility that was managed separately. That is no longer sufficient. To succeed in the AI era, platform teams must have deep…
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“a staggering 3,611 active or planned use cases for AI across the federal government”
The office of management and budget (OMB) disclosed a staggering 3,611 active or planned use cases for AI across the federal government. The list has balloonedby 70% from the one published in the final year of the Biden administration, and includes many disturbing-seeming plans to hand over sensitive governmental functions to AI. Yes, but: While…
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When management is the bottleneck preventing enterprise AI ROI.
Right now, many companies already have the technology they need to go much faster. The blocker is company systems that are mostly designed to prevent things from happening. The power is centralized and all the team members are treated like a risk vector. Exhausting approval cycles, super tight boundaries on roles, unbreakable title-based hierarchies, and…
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