Simor Consulting

Category: Organizational Design

Should every company build their own LLM? A contrarian view
Should every company build their own LLM? A contrarian view
03 Aug, 2026 | 05 Mins read

A pharmaceutical company I consulted for was three months into a project to fine-tune a large language model on their internal research corpus. The project had a team of four engineers, a budget of $8

The gender gap in AI: what the data actually shows
The gender gap in AI: what the data actually shows
29 Jul, 2026 | 05 Mins read

The headline numbers are familiar. Women represent roughly a quarter of AI and data science professionals globally. At senior levels, the proportion drops to the low teens. At the C-suite level of AI-

What ancient engineering principles teach us about AI architecture
What ancient engineering principles teach us about AI architecture
20 Jul, 2026 | 05 Mins read

The Pont du Gard in southern France has carried water across the Gardon river valley for two thousand years. It was built without steel reinforcement, without concrete, and without computer-aided stru

Building an AI Center of Excellence: Structure, Mandate, and Success Metrics
Building an AI Center of Excellence: Structure, Mandate, and Success Metrics
05 Jul, 2026 | 11 Mins read

Most organizations have attempted some form of AI initiative. Some succeeded and delivered measurable business value. Many failed and produced results that were technically interesting but did not mov

The paradox of AI automation: more tools, less productivity?
The paradox of AI automation: more tools, less productivity?
01 Jun, 2026 | 05 Mins read

A data engineering team I worked with had adopted six AI-powered tools in twelve months. An automated code reviewer, a data quality scanner, a pipeline orchestrator with intelligent retry, a natural l

What we can learn from the DevOps revolution applied to AI
What we can learn from the DevOps revolution applied to AI
04 May, 2026 | 04 Mins read

In 2009, deploying software to production was an event. It involved a change request, a maintenance window, a runbook, and a prayer. Developers wrote code, then threw it over the wall to operations, w

Why most AI transformations fail (it's not the technology)
Why most AI transformations fail (it's not the technology)
20 Apr, 2026 | 04 Mins read

The CTO of a mid-size financial services firm told me they had spent $4 million on AI tooling in eighteen months. They had three large language model providers under contract, a vector database cluste