The Five Pillars of AI Capability
The Question AISA Doesn’t Answer
When I introduced the AI Stages of Adoption, the most common follow-up question was immediate and practical: “How do we know when we’re truly ready to move from one stage to the next?”
It’s a crucial question. I’ve seen organisations celebrate early pilot successes and immediately attempt to leap from Experimenting straight to Optimising, only to encounter significant challenges. The reality is that AI adoption isn’t merely about completing pilots or deploying new technologies - it’s about developing fundamental organisational capabilities that enable sustainable progress.
The Five Pillars framework answers this question by identifying the capability domains that determine whether stage transitions succeed or fail.
Five Domains, One System
Through my earlier work on the AWS Cloud Adoption Framework, I knew that explaining progression through capability domains was the right approach. For AI adoption, I’ve identified five capability domains that cut across every level of maturity:
Governance & Accountability ensures AI initiatives operate within safe and legal boundaries while maintaining clear human oversight. This pillar addresses who decides and who is responsible - questions that become increasingly critical as AI takes on more autonomous decision-making.
Technical Infrastructure provides the foundational technology elements that support AI systems - the platforms, data architecture, and compute resources that enable development and deployment at scale.
Operational Excellence focuses on running AI systems reliably in production. It covers MLOps practices, model monitoring, data quality processes, and the day-to-day management that determines whether sophisticated AI solutions actually deliver sustained value.
Value Realisation & Lifecycle Management ensures organisations capture measurable business value from AI investments across the full lifecycle - from identifying high-value use cases through to measuring ROI and managing the model portfolio.
People, Culture & Adoption addresses the human dimension - change management, skills development, and cultural readiness. This pillar determines whether sophisticated AI systems get used effectively or actively circumvented.
Why Balance Matters
These pillars work as a system, not a checklist. Weakness in one undermines progress in all others.
I regularly encounter organisations with considerable strength in technical foundations but significant weaknesses in governance or culture. The tension between these strengths and weaknesses often determines whether a transition to the next adoption stage will be smooth or painful.
Strong technical infrastructure without operational excellence creates impressive demos that never reach production. Comprehensive governance without technical capability produces innovation paralysis. Enthusiastic teams without adequate infrastructure drive shadow AI proliferation. Value frameworks without people capabilities generate plans that never materialise.
This explains why many AI initiatives fail despite sophisticated technology. Organisations invest heavily in one or two pillars while neglecting others, creating imbalances that block progress regardless of individual pillar strength.
Matching Capabilities to Stage
Different AISA stages require different maturity levels across the Five Pillars. The capability requirements for a function that’s Experimenting differ vastly from one that’s Transforming.
Moving from Experimenting to Adopting demands strength in Governance & Accountability and Technical Infrastructure. Without sufficient governance maturity, organisations face proliferating shadow AI initiatives creating significant risk exposure. Without adequate infrastructure, they can’t move beyond isolated experiments.
The leap from Adopting to Optimising requires strength in Technical Infrastructure, Operational Excellence, and Value Realisation. Organisations often stall at this transition when they lack the operational discipline to monitor value outcomes or the processes to consistently measure business impact.
Optimising to Transforming is where AI evolves from an operational tool to a driver of business model innovation. Success depends heavily on People, Culture & Adoption - transformation requires widespread AI literacy and cultural acceptance of AI-driven change.
Transforming to Scaling extends AI beyond organisational boundaries to broader ecosystems. This requires excellence across all pillars, with particular emphasis on governance mechanisms that can span partner networks and infrastructure that supports ecosystem-wide integration.
Assessing Your Capability Balance
The AI CoE Simulator visualises your pillar maturity for each business function, showing where capability investment should focus. It reveals patterns that inform where your AI Centre of Excellence needs to concentrate effort.
Functions with strong technical capabilities but weak governance are prime candidates for risk exposure. Areas with high governance maturity but low technical infrastructure might be over-controlling innovation. These patterns become visible when you assess pillars systematically rather than relying on general impressions of AI readiness.
Related Articles
Foundational
- Increasing AI Maturity: The Five Pillars - The original framework introduction explaining how to assess readiness for stage transitions
Integration
- A Complete AI Adoption Framework - How AISA, Five Pillars, and Well-Advised work together as a unified governance system
Practical Application
- AI CoE Capabilities: Building the Five Pillars - How to systematically develop capabilities across all five domains
- AI Business Case: Implementation Feasibility - Using Five Pillars assessment to evaluate initiative readiness
Governance Context
- Why Boards Need an AI Centre of Excellence - Why AI governance requires Board-level authority across all five pillars
- AI Centre of Excellence: The Eighteen Functions - The specific functions that build Five Pillars capabilities
Tools
- AI CoE Simulator - Visualise your pillar maturity gaps across business functions and identify where capability investment should focus
