Insights
Frameworks, cost models and documented industry examples for deciding where AI is worth the investment — and where it is not.
Updated 3 September 2026
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A practical hub on finding AI opportunities in a real business: discovery methods, scoring models, prioritization frameworks and department-level opportunity maps.
Explore hub →How to calculate AI ROI honestly: cost models, value drivers, payback periods, business case structure and the measurement discipline that keeps the number credible.
Explore hub →Enterprise and mid-market AI strategy: a workable framework, readiness assessment, operating model choices, governance and a sequenced implementation roadmap.
Explore hub →Department-level AI use cases with the detail that matters: where AI helps, complexity, data requirements, risks, KPIs and ROI considerations for each workflow.
Explore hub →ai opportunities
A repeatable method for finding AI opportunities: start from workflows and cost, not from technology. Includes signals to look for, a discovery sequence and disqualifiers.
ai opportunities
What an AI opportunity assessment covers, how it differs from an AI readiness assessment, the method behind it, and what a credible output document contains.
ai opportunities
A transparent scoring model for prioritizing AI opportunities across value, confidence, effort, risk and readiness — plus how to sequence the first twelve months.
ai roi
A complete method for calculating AI ROI: value drivers, the full cost model, a worked example, payback period and the measurement discipline that keeps the number honest.
ai roi
A section-by-section AI business case structure: problem baseline, proposed change, value range, cost model, risk, governance, measurement plan and decision request.
ai roi
The real cost structure of an AI implementation — build, integration, evaluation, change management, inference, human review and maintenance — and how each line behaves over time.
ai strategy
A five-part AI strategy framework — economic thesis, portfolio, operating model, governance and measurement — designed for mid-market companies rather than global enterprises.
ai strategy
The dimensions of AI readiness — data, process, systems, skills, governance and change capacity — how to score them, and how readiness should influence sequencing.
ai strategy
A twelve-month AI implementation roadmap for mid-market companies: what happens in each quarter, what gates each stage, and the signals that you are moving too fast.
The Merjora assessment maps your workflows, scores each opportunity and quantifies the value range.
Discover your AI opportunitiesEditorial standard. Merjora publishes analysis, frameworks and publicly documented examples. We do not publish invented statistics, unattributed benchmarks or unverified customer stories.