AI Value Assessment

10 lessons on measuring and valuing AI investments as intangible assets. Follow NovaTech AI — a £30M B2B SaaS company — as your worked example, from the AI measurement problem to board-level strategy.

The Assessment Journey

From understanding why AI is hard to measure, through a 4-layer ROI framework, to presenting AI value at board level. Each lesson builds on the last, with practical scenarios using NovaTech AI — a mid-market B2B SaaS company using AI for product recommendations and internal operations.

Attribute Detail
CompanyNovaTech AI Ltd
Revenue£30M ARR
SectorB2B SaaS (AI-powered product recommendations)
Employees180
AI Investments£4.2M annually across 6 initiatives
AI AssetsProprietary ML models, 8-year transaction dataset, AI talent
ScenarioMeasuring AI ROI for board reporting and potential acquisition

AI ROI Layer Builder

See how AI value stacks across four layers. Each bar represents a layer of the 4-layer AI ROI framework, building from the most measurable (cost reduction) to the most strategic (positioning).

AI maturity stage: Exploring
Cost Reduction
£0.3M
Revenue Growth
£0.1M
Competitive Adv.
£0.1M
Strategic Position
-
Total measurable AI value: £0.5M

Your Lessons

10 lessons. Scroll to explore, or jump to the topic that matters most to you.

The AI Measurement Problem
1
Foundations

The AI Measurement Problem

Why traditional ROI metrics fail for AI investments. The gap between AI spending and measurable outcomes, and why a new framework is needed.

ROI limitations, AI investment gaps, traditional metrics failure Start Lesson
AI Investments Create Intangible Assets
2
Foundations

AI Investments Create Intangible Assets

How AI spending creates intangible assets under IAS 38 and the CHS framework. Classifying AI investments as computerised information, innovative property, and economic competencies.

IAS 38, CHS framework, AI asset classification, capitalisation Start Lesson
The 4-Layer AI ROI Framework
3
Frameworks

The 4-Layer AI ROI Framework

Introducing the 4-layer AI ROI framework: cost reduction, revenue growth, competitive advantage, and strategic positioning. Each layer builds on the last.

Cost reduction, revenue growth, competitive advantage, strategic positioning Start Lesson
AI and Cost Reduction: Measurement and Verification
4
Measurement

AI and Cost Reduction: Measurement and Verification

Measuring and verifying AI-driven cost reductions. Before/after methodology, control group design, and avoiding attribution errors in operational savings.

Before/after analysis, control groups, process efficiency, FTE savings Start Lesson
AI and Revenue Growth: Attribution and Sizing
5
Measurement

AI and Revenue Growth: Attribution and Sizing

Attributing revenue growth to AI initiatives. Multi-touch attribution models, A/B testing frameworks, and isolating AI-driven revenue uplift from organic growth.

Attribution modelling, A/B testing, uplift measurement, revenue decomposition Start Lesson
AI and Competitive Advantage: Optionality and Risk
6
Measurement

AI and Competitive Advantage: Optionality and Risk

Quantifying the competitive advantage layer of AI ROI. Real option valuation, defensibility assessment, and measuring AI-driven switching costs and network effects.

Real options, competitive moats, switching costs, network effects Start Lesson
AI and Strategic Positioning: Goodwill vs Expense
7
Measurement

AI and Strategic Positioning: Goodwill vs Expense

Distinguishing between AI investments that create strategic goodwill and those that are pure operating expenses. How AI capability affects M&A multiples.

Goodwill creation, strategic value, M&A premium, expense vs asset Start Lesson
Building Your AI ROI Dashboard
8
Application

Building Your AI ROI Dashboard

Designing and building a comprehensive AI ROI dashboard for executive reporting. Selecting KPIs across all four layers, leading vs lagging indicators, and dashboard architecture.

KPIs, executive reporting, visualisation, leading indicators Start Lesson
AI ROI in Practice: Three Case Studies
9
Application

AI ROI in Practice: Three Case Studies

Three detailed case studies applying the 4-layer AI ROI framework: NovaTech AI (B2B SaaS), a manufacturing firm, and a financial services company.

B2B SaaS, manufacturing, financial services, real-world examples Start Lesson
From Measurement to Board Strategy
10
Application

From Measurement to Board Strategy

Translating AI ROI measurement into board-level strategy. Structuring AI investment committees, governance frameworks, and strategic recommendation templates.

Board reporting, strategic recommendations, investment governance, AI roadmap Start Lesson
Scroll to see all 10 lessons →

From Measurement Problem to Board Strategy

Each lesson builds on the last — starting with why AI is hard to measure, through the 4-layer framework, to presenting AI value to your board.

Foundations

Why AI is hard to measure and how AI creates intangible assets

Lessons 1-2
Framework

The 4-layer AI ROI framework: cost, revenue, advantage, positioning

Lessons 3
Measurement

Deep-dive into measuring each layer with worked examples

Lessons 4-7
Application

Building dashboards and real-world case studies

Lessons 8-9
Strategy

From measurement to board-level AI investment strategy

Lessons 10

AI Value IQ

Complete the quiz at the end of each lesson to track your AI Value IQ. Score 0/40

Lesson 1
Measurement
Lesson 2
AI as Asset
Lesson 3
ROI Framework
Lesson 4
Cost Layer
Lesson 5
Revenue Layer
Lesson 6
Advantage Layer
Lesson 7
Strategy Layer
Lesson 8
Dashboard
Lesson 9
Case Studies
Lesson 10
Board Strategy

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