Methodologies
Every Dodone model is a published, versioned method. You can see every formula, default and limitation before you rely on a result.
Dodone — AI Engineering ROI v1
One-year economic effect of a new AI coding tool on an engineering workforce, valued two alternative ways.
New to the model? How Dodone works — a five-step guide
AI Customer Support ROI
Not yet specified. No calculations are offered until an independent methodology exists.
AI Knowledge Work ROI
Not yet specified. No calculations are offered until an independent methodology exists.
Enterprise Agent ROI
Not yet specified. No calculations are offered until an independent methodology exists.
Third-party methodologies
For reference, here are other published ways to assess the return on AI. Each PDF is an independent summary written by Dodone of a method published by another organisation, based only on public material available up to 31 October 2026. The original publishers have not reviewed or endorsed these summaries, and they are not used by Dodone's calculator. Always read the original source.
Download the overview of all 14 (PDF, 64 KB)
Forrester — Total Economic Impact (TEI)
EXT-001 · General technology investment methodology · Undated methodology page; accessed 31 October 2026
Reproducibility from public sources: Partial. An independent reader can verify the published conceptual dimensions, but cannot reconstruct a universal TEI calculation from this policy page alone.
Download review (PDF, 72 KB) of Forrester — Total Economic Impact (TEI)Original source: Forrester Methodologies: Total Economic Impact (opens in a new tab)
Google Cloud / DORA — ROI of AI-Assisted Software Development
EXT-002 · Public interactive engineering ROI calculator · Report version v.2026.1; report page updated 22 April 2026
Reproducibility from public sources: Partial from the public inputs and displayed outputs. The full official report is linked through a separate report request/page; only the accessible calculator and public landing information were relied on here.
Download review (PDF, 74 KB) of Google Cloud / DORA — ROI of AI-Assisted Software DevelopmentOriginal source: DORA ROI calculator (opens in a new tab)Original source: DORA ROI report landing page (opens in a new tab)Original source: DORA report version checker (opens in a new tab)
McKinsey / QuantumBlack — The AI Value Curve
EXT-003 · Proprietary bottom-up task economics opportunity analysis · 14 October 2026
Reproducibility from public sources: Partial at the logic level. The article gives the aggregation chain, but not enough source data or proprietary transformations to reproduce its full global result independently.
Download review (PDF, 73 KB) of McKinsey / QuantumBlack — The AI Value CurveOriginal source: The AI value curve: The economics of applying AI to existing work (opens in a new tab)
Microsoft Copilot Studio — Measuring the Business Value of Agents
EXT-004 · Operational agent outcome/value measurement guidance · Guidance page last updated 4 June 2026
Reproducibility from public sources: Strong for the published Agent Assisted Hours/Value worked example; partial for complete agent business ROI across all four value drivers.
Download review (PDF, 74 KB) of Microsoft Copilot Studio — Measuring the Business Value of AgentsOriginal source: Measure the impact of your agents (opens in a new tab)
McKinsey Global Institute — The Economic Potential of Generative AI
EXT-005 · Bottom-up global use-case and work-activity opportunity sizing · 14 June 2023
Reproducibility from public sources: Partial. Published activity categories and high-level opportunity outputs can be inspected, but the underlying global research aggregation cannot be rebuilt solely from the public article.
Download review (PDF, 73 KB) of McKinsey Global Institute — The Economic Potential of Generative AIOriginal source: The economic potential of generative AI: The next productivity frontier (opens in a new tab)
Kanuri, Pattabhiramaiah & Sridhar / Journal of the Academy of Marketing Science — Return on AI (RoAI)
EXT-006 · Academic marketing AI investment economic framework · 21 October 2026
Reproducibility from public sources: Strong for the published expression and explanatory example; a company application still requires independently established benefit, value-share, durability and cost inputs.
Download review (PDF, 73 KB) of Kanuri, Pattabhiramaiah & Sridhar / Journal of the Academy of Marketing Science — Return on AI (RoAI)Original source: Return on AI (RoAI): A framework for assessing AI investments in the marketing organization (opens in a new tab)
IDC — Business Value Research Methodology
EXT-007 · Customer-research-driven technology business value study · 12 February 2026 explanation
Reproducibility from public sources: Partial process transparency, low numerical reproducibility from the public overview alone.
Download review (PDF, 71 KB) of IDC — Business Value Research MethodologyOriginal source: A closer look at how an IDC Business Value project unfolds (opens in a new tab)
Amazon Web Services — Agentic Value Model for Automation
EXT-008 · Agentic workflow business-case methodology · 7 October 2026
Reproducibility from public sources: Strong for the published illustrative cost examples and overall value-pool logic; partial for a universal agent model because operational inputs are workflow-specific.
Download review (PDF, 72 KB) of Amazon Web Services — Agentic Value Model for AutomationOriginal source: Beyond hours saved: Building the business case for agentic automation (opens in a new tab)
Workhelix — Task-Based Enterprise AI ROI Measurement
EXT-009 · Proprietary task-level opportunity and causal measurement system · Undated FAQ and methodology descriptions; accessed 31 October 2026
Reproducibility from public sources: Limited. The core task-centric measurement logic is public, but proprietary coefficients, data and implementation are not.
Download review (PDF, 72 KB) of Workhelix — Task-Based Enterprise AI ROI MeasurementOriginal source: Workhelix FAQ (opens in a new tab)Original source: Workhelix AI information and methodology description (opens in a new tab)
Gartner — How to Calculate Business Value and Cost for Generative AI Use Cases
EXT-010 · Restricted analyst research framework · 25 March 2025
Reproducibility from public sources: Not possible from the public abstract. This is a documented access limitation, not a claim that Gartner did not produce such detail.
Download review (PDF, 68 KB) of Gartner — How to Calculate Business Value and Cost for Generative AI Use CasesOriginal source: Gartner research listing (document 6294515) (opens in a new tab)
Amazon Web Services — Calculating the ROI of AI: Cost per Outcome
EXT-011 · AI cost allocation and unit-outcome economics · 10 August 2026
Reproducibility from public sources: High for Cost per Outcome given measured costs and an outcome denominator; partial for financial ROI because outcome valuation is use-case-specific.
Download review (PDF, 71 KB) of Amazon Web Services — Calculating the ROI of AI: Cost per OutcomeOriginal source: Calculating the Return on Investment (ROI) of AI (opens in a new tab)
McKinsey / QuantumBlack — From Promise to Impact: Five-Layer AI Measurement
EXT-012 · Enterprise operating and impact-measurement framework · 24 April 2026
Reproducibility from public sources: High for the five-layer taxonomy and ownership mapping; not applicable for a single numeric ROI because no universal formula is defined.
Download review (PDF, 71 KB) of McKinsey / QuantumBlack — From Promise to Impact: Five-Layer AI MeasurementOriginal source: From promise to impact: How companies can measure and realize the full value of AI (opens in a new tab)
Deloitte — AI ROI Performance Index
EXT-013 · Comparative AI performance research index · 22 October 2025
Reproducibility from public sources: Partial conceptual reproducibility for the four dimensions and top-20% rule; numerical score reconstruction is not possible from the reviewed public paper.
Download review (PDF, 71 KB) of Deloitte — AI ROI Performance IndexOriginal source: AI ROI: The paradox of rising investment and elusive returns (opens in a new tab)
Atlassian Teamwork Lab — Enterprise AI ROI Value Framework
EXT-014 · Four-stage qualitative maturity and measurement framework · 24 March 2026
Reproducibility from public sources: High for conceptual four-stage framework and KPI examples; numeric ROI reproducibility not applicable.
Download review (PDF, 69 KB) of Atlassian Teamwork Lab — Enterprise AI ROI Value FrameworkOriginal source: Stop guessing at AI ROI: A four-stage framework for real results (opens in a new tab)