Dispositions • Enterprise Si & Agents • Actionable Signal
Superintelligence Production Readiness
Source: MIT Sloan Management Review. Source published .
These are historical survey findings reported in January 2024, not current adoption estimates. The AWS and Wavestone surveys measured different stages of deployment.
The analysis date above is the date of James's commentary.
James's take
Davenport and Bean's January 2024 article reported two distinct findings: 6% of companies in the AWS survey had a generative application in production, while 5% in the Wavestone survey had deployed the technology at scale. Those historical findings inform my current superintelligence implementation work. I look at how a proposed workflow accepts incomplete inputs, handles exceptions, connects to business tools, and tells a person when review is needed. A useful pilot needs evidence from the complete workflow before a team depends on it in production.
Questions for your team
- Which messy inputs must the workflow accept, and what will happen when an input is incomplete or unexpected?
- Which exceptions need deterministic handling, and who will own escalation when the automation cannot proceed?
- Which core business tools must receive the output, and how will you verify that the write-back succeeded?
- What evidence from the end-to-end workflow will show that it is ready for production rather than still a pilot?