EPISODE · Jun 2, 2026 · 12 MIN
Is AI adoption now a bigger edge than the model itself?
from Fullstack HR · host Johannes Sundlo
Subscribe to the FullStack HR newsletter → https://fullstackhr.ioOpenAI just ran an event called Intelligence at Work, and the releases say a lot about where the world of work is going. Here is what dropped and why it matters for anyone leading AI adoption.In this episode:Why the bottleneck has shifted from model intelligence to a company's ability to absorb the techThe stat to sit with: 74% of AI's economic value is captured by 20% of companiesCodex moving into ChatGPT, and what that means if you are on ChatGPT EnterpriseSix role-specific agent plugins, including a data analytics agent that writes queries, builds charts, and produces a deckAnnotations: editing one piece of an output instead of regenerating the whole thing, and whether it solves the "last mile" problemSites: turning Codex outputs into shareable, live dashboards and internal apps (Lovable meets Artifacts)Why OpenAI keeps framing adoption as a human transformation, not an IT projectSam Altman on the next phase: proactive agents that fix things in the background before you askLinks mentioned:OpenAI Intelligence at Work (the event) → https://openai.com/sv-SE/business/intelligence-at-work/
What this episode covers
Subscribe to the FullStack HR newsletter → https://fullstackhr.ioOpenAI just ran an event called Intelligence at Work, and the releases say a lot about where the world of work is going. Here is what dropped and why it matters for anyone leading AI adoption.In this episode:Why the bottleneck has shifted from model intelligence to a company's ability to absorb the techThe stat to sit with: 74% of AI's economic value is captured by 20% of companiesCodex moving into ChatGPT, and what that means if you are on ChatGPT EnterpriseSix role-specific agent plugins, including a data analytics agent that writes queries, builds charts, and produces a deckAnnotations: editing one piece of an output instead of regenerating the whole thing, and whether it solves the "last mile" problemSites: turning Codex outputs into shareable, live dashboards and internal apps (Lovable meets Artifacts)Why OpenAI keeps framing adoption as a human transformation, not an IT projectSam Altman on the next phase: proactive agents that fix things in the background before you askLinks mentioned:OpenAI Intelligence at Work (the event) → https://openai.com/sv-SE/business/intelligence-at-work/
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Is AI adoption now a bigger edge than the model itself?
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