The Hardware Asset Reality Check
A company must separate reusable foundations from the new capacity needed for a shared AI knowledge service.
Scenariet
Teaching composite — not a claim about a named organisation or measured outcome. A 350-person engineering company wants an internal assistant that summarises maintenance manuals and drafts work-order notes. The IT team says there is already a virtualisation cluster, a 10 Gb network, identity management, backups and unused rack space. A business sponsor therefore assumes that 'we already have the infrastructure' and asks procurement to buy a GPU.
The infrastructure lead finds a more nuanced picture. Identity, network monitoring and document storage may be reusable, but the candidate server has no suitable accelerator, the rack's power and cooling headroom are unverified, and the backup route was designed for office systems rather than a shared model service. The assistant also needs to handle long manuals during the morning planning peak. The decision is not whether existing assets have value; it is which parts actually meet the proposed service requirement and which create a hidden bottleneck or operating obligation.
The CIO asks for a one-page asset-and-gap view before approving any purchase: user journey, permitted data route, existing components, constraints, incremental additions, recurring operation, and the representative test that would prove the design is adequate.
Sådan kommer AI ind i arbejdsgangen
Frame the decision
MenneskeThe accountable leader defines the outcome, constraints and what must remain human.
Prepare evidence
AIAI organises the relevant material, assumptions and options with sources where available.
Test the workflow
Menneske + AIA small team tests the proposed workflow on representative work and records failures.
Make the call
MenneskeA named person approves the decision, boundaries and measure of success.
Learn and improve
Menneske + AIResults, feedback and exceptions feed the next review rather than disappearing in a project report.
Spørg om workflowet
ADA, taskforcens næstkommanderende, forklarer præcis, hvordan menneske og AI deler arbejdet — spørg om hvad som helst.
Taskforcen: menneske + agenter
Teamleder — godkender hvert resultat
Teamleder — godkender hvert resultat

PRISM
Readiness & Assessment Agent

FORGE
Engineering Agent

Kuni
AI Learning Companion

ATLAS
Strategy Agent

ORION
Infrastructure Agent

NOVA
Intelligence & Industry Research Agent
BRIDGE
Change Management & Adoption Agent
Agenter foreslår og udfører. Den menneskelige leder godkender altid det endelige resultat.
Resultater
| Metrik | Før | Efter |
|---|---|---|
| Time to a defensible first decision | Fragmented | Visible and repeatable |
| Human accountability | Implicit | Named at each hand-off |
| Learning signal | Anecdotal | Reviewed every cycle |
Vigtigste pointer
- Start with a bounded business decision, not a technology demonstration.
- Make the human owner, evidence and escalation route visible before scaling.
- Treat feedback as a design input: it improves the system and the team's judgment.
Relaterede koncepter
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