From readiness to measured results
Three connected frameworks take an organisation from "are we ready?" to "is each agent earning its place?", with responsible delegation in between.
Diagnose → Quantify → Govern → Measure
AI readiness → value opportunity → responsible delegation → measured financial outcomes.
- Stage 1
Diagnose
Kiros AI Readiness & Value Index
Determines organisational capability and the readiness gaps that would stop value being captured.
Assessed readinessDetails → - Stage 2
Quantify
Agent Value Ledger
Identifies financial value opportunities across revenue, operating costs, capital and risk.
Estimated opportunityDetails → - Stage 3
Govern
AI Delegation Map
Defines decision authority, human oversight and accountability for each agent.
Designed controlsDetails → - Stage 4
Measure
Financial and operational outcomes
Tracks verified performance against the agreed baseline, and reports it to the board.
Realised resultsDetails →
Three connected tools
- 1AI readiness
- 2Value opportunity
- 3Responsible delegation
- 4Measured financial outcomes
Kiros AI Readiness & Value Index
Is the organisation ready to create value from AI?
Explore →Value opportunity · Measured outcomesAgent Value Ledger
Which lines in the accounts can AI move, and at what full cost?
Explore →Responsible delegationAI Delegation Map
Which decisions may AI make, recommend, or never touch?
Explore →How the frameworks are used in an engagement
- 01K-ARVI
AI readiness
We score readiness across six dimensions and identify the capability gaps that would stop value being captured.
- 02Agent Value Ledger
Value opportunity
We read the accounts, map value levers and build a case for each candidate agent across revenue, cost, capital and risk.
- 03AI Delegation Map
Responsible delegation
We place each agent's decisions into one of three categories and design the controls each needs.
- 04Agent Value Ledger
Measured financial outcomes
We measure results against the baseline with evidence an auditor would accept, and report to the board.
Readiness is not return
The readiness index measures whether the organisation can capture value. The ledger estimates and then measures the value itself. We keep the two apart, so a high readiness score is never presented as a forecast of financial return.
Rules we hold to
Capacity is not a saving
Freed hours count only when they are redeployed to revenue work or replace hiring that would otherwise happen.
Count the full cost
Model usage, integration, data work, human oversight, validation and assurance all go on the ledger.
No baseline, no agent
If a result cannot be measured before deployment, it cannot be claimed after.
Risk benefits wait for evidence
Lower losses or fewer incidents are counted only once there is enough history to show them.
Roles kept separate
Our advisory work is independent. Where we also lead delivery, or use technology from a company in which we hold an interest, we say so in writing and never assure our own work.
What we publish, and how to read it
We distinguish clearly between research, methodology, experience, portfolio activity, client work and hypothetical illustrations.
Research and publications
Peer-reviewed and academic work by our people. Cited as research, not as client results.
Advisory methodology
Our frameworks: K-ARVI, the Agent Value Ledger and the AI Delegation Map. Proprietary methods, not regulatory standards.
Professional experience
The prior careers and qualifications of our people, described as their experience, not the firm's.
Interests
Where we hold an interest in a company whose technology a client may use, we name it on this site and disclose it in writing.
Client engagements
Our client work is confidential. We do not publish client names or results without permission.
Hypothetical illustrations
Worked examples and scenarios are clearly labelled as hypothetical. They are not case studies.
See the frameworks applied to your business
The Enterprise AI Value Creation Assessment applies all three frameworks in four weeks.