8 areas that define your
agent's operating environment.
Before we build Agent_8, we map. The 8-Area Scope reveals where your organisation's readiness is strong, where it is fragile, and which layers to build first. It does not prescribe solutions. It scopes the build.
Every dimension AI touches.
Scored. Prioritised. Sequenced.
The 8-Area Scope maps every dimension that determines whether Agent_8 deployment holds. Most programmes address two or three dimensions. The agent requires all eight — because gaps in any one area create failure points across every system the agent operates.
The foundation of Scope Area M1. Every decision in your organisation belongs in one of three tiers.
Automated
AI acts without human review. Low stakes, high frequency, well-defined rules.
Assisted
AI recommends. Human decides. High-value, moderate complexity decisions.
Reserved
Human only. AI provides no recommendation. Judgment, ethics, accountability.
Decision Architecture
How decisions flow through your organisation. Who has authority at each tier. Where AI is authorised to act autonomously.
Can you map every major decision to an owner and a process?
Do you have a defined framework for Automated vs. Assisted vs. Reserved decisions?
When AI makes a decision, how is it logged, audited, and reversed if needed?
Three-Tier Decision Framework installed
Decision ownership mapped across all major workflows
AI authority boundaries defined and documented
Authority & Governance
The policy layer. Who governs the AI systems. How accountability is structured. What guardrails prevent drift.
Is there a named AI governance owner in your organisation?
Do you have published policies on AI use, data, and decision rights?
How are edge cases escalated and resolved?
AI Governance Stack designed and installed
Policy framework with clear accountability lines
Escalation protocols for AI decision errors
Knowledge & Memory
How institutional knowledge is captured, stored, and made accessible to both humans and AI systems.
Where does tribal knowledge live? Who would lose it if they left?
Is your documentation structured for machine retrieval?
Do your AI systems have access to the context they need to act correctly?
Knowledge architecture designed (vector DB, taxonomy, retrieval logic)
Documentation structured for AI-native access
Memory systems that retain organisational context
Talent & Role Design
How roles are redefined when intelligence becomes infrastructure. Who builds, governs, and evolves your AI systems.
Which roles in your org will be fundamentally changed by AI in 18 months?
Do you have an AI Steward — a named person who owns AI operations?
Is your hiring and performance framework updated for intelligence-era expectations?
Role redesign for key AI-impacted positions
AI Steward model and governance staffing plan
Competency frameworks updated for intelligence-era skills
Revenue & Value Architecture
Pipeline, forecasting, pricing, and go-to-market — redesigned for AI-native velocity and intelligence-era buying dynamics.
Is your RevOps stack integrated or fragmented across tools?
Are your reps spending more time in CRM or doing actual selling?
Does your pricing model reflect the intelligence-era value you deliver?
RevOps architecture built on AI-native foundations
Pipeline intelligence with predictive scoring
GTM redesigned for intelligence-era buyer behaviour
Technology & Infrastructure
Your AI ecosystem. Integration architecture. The gap between tools you own and intelligence you actually operate.
Have you mapped every AI tool in use across your organisation?
Are your systems integrated enough for AI to act across them?
Do you have a data strategy that enables AI to read and write reliably?
Full AI ecosystem map and integration architecture
Data infrastructure assessment and remediation plan
Stack rationalisation with implementation roadmap
Culture & Adaptability
Change tolerance, AI literacy, and the human side of transformation. The layer most programmes underestimate.
What percentage of your leadership team has hands-on AI proficiency?
Is there visible resistance or enthusiasm toward AI adoption?
Does your culture reward experimentation or penalise failures?
AI literacy programme for leadership and teams
Change management architecture for transformation rollout
Culture assessment with adoption acceleration plan
External Positioning & Moat
How you are perceived in a market where AI capability is becoming table stakes. Where your defensible advantage lives.
Can you articulate your AI differentiation to a sophisticated buyer?
Is your competitive moat dependent on information or intelligence?
How are you narrating your AI transformation to the market?
AI narrative framework for market positioning
Competitive intelligence model built into your GTM
Moat analysis: what AI makes defensible vs. commoditised
Where do you score
across all eight areas?
You leave with a scored readiness map and a build plan for Agent_8.
Book a Scoping Call →