Enterprise AI Planner

Work In Progress

AI Use Case Modelling, Cost Visibility, and ROI Planning

A web-based planning and modelling tool designed to help organisations evaluate and operationalise AI initiatives responsibly.

Why This Matters

Most AI tools sell you optimism. The AI Planner sells you realism. Enterprise AI adoption fails not because models are bad, but because organisations buy blanket licences without matching tools to tasks. This planner helps you see the real numbers - grounded in published research, not vendor marketing.

Focus Areas

AI use case modellingOperational cost at scaleLocal vs cloud deployment strategyMeasurable ROI frameworks

AIEnterpriseStrategyROICost Modelling

Try It Now →

The Enterprise AI Planner is a free, open web tool that helps organisations model where, how, and at what cost they can deploy AI across their business. No sign-up required.

The Problem

Most enterprises know they should be "doing AI" but lack a structured way to evaluate the opportunity. Where are the high-value use cases? Should models run locally or in the cloud? What will it actually cost? What's the realistic ROI? Without clear answers, organisations either over-invest in pilots that don't scale or under-invest and fall behind.

What It Does

The AI Planner gives technology and business leaders a practical modelling tool to work through these questions systematically:

36 use cases across 9 business functions - Pre-built templates covering everything from L1 ticket automation to contract review, each with researched adoption rates and task success data
Org-size defaults - Select your company size and employee count to get realistic starting assumptions, then customise from there
Deployment modelling - Compare enterprise licences (M365 Copilot, Claude Enterprise, ChatGPT Enterprise, Gemini), cloud APIs, and local GPU inference for each use case
4 automation levels - From manual AI-assisted to fully autonomous, with deployment constraints and capability requirements enforced automatically
Data classification enforcement - Confidential and regulated data is automatically routed to enterprise-grade deployments
Cost analysis - Model the true costs including compute, API calls, integration, licensing seats, and local GPU infrastructure
ROI projection - Period-based ROI over 1, 3, 5, or 10 year horizons with research-grounded rework factors
Scenario comparison - Compare "The Copilot Blanket" (one tool for everyone) against "Right-sized AI" (matched tools per use case) to see the ROI difference
Portfolio view - See total monthly costs, savings, one-off investment, break-even, and ROI across your entire AI portfolio

Research-Grounded

All assumptions are backed by real enterprise data from Microsoft Inside Track, GitHub Research, Deloitte State of AI 2026, and McKinsey. The model reflects 10-15% real-world productivity gains - not the 55% from controlled lab studies.

Core Principles

Realistic over optimistic - data beats narrative
Cost transparency by default - every calculation is visible
One ecosystem per company - no mixing licence ecosystems
Free and open - no sign-up, no paywall, no data collection

Part of mattcoppinger.com

The AI Planner lives as a tool within this site, freely available to technology leaders evaluating their AI strategy.