
Strategy & evaluation
How to Calculate Business AI ROI: Example and Calculator
Estimate AI pilot ROI using task time, human review, implementation, and operating costs. Explore KODE’s example and open calculator.
Read guide →AI strategy
AI consulting to assess data readiness, prioritize use cases, and plan implementation. KODE supports businesses from Jakarta, Indonesia.
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Clear priorities. Measurable next steps.
Map the need
Set priorities
Build a roadmap
For teams ready to begin but unsure which use case deserves priority.
Prepare together
Bring a process owner, a sample workflow, and an overview of data sources. Sensitive data is not needed for the initial conversation.
Strategy starts with work that needs improvement. We assess processes, data, ownership, and change costs. Agreed outputs may include prioritized use cases, a readiness assessment, a business case, and a pilot scope with success criteria. Business and IT teams review assumptions before choosing the next step.
Cost is determined after discussing goals, scope, data readiness, integrations, and support needs. Describe the process and intended outcome; confidential data is not required for the first conversation.
How to choose an AI consultant →Your next step
Tell us which process takes up your team’s time. We’ll explore the need, data readiness, and a practical first step.

Strategy & evaluation
Estimate AI pilot ROI using task time, human review, implementation, and operating costs. Explore KODE’s example and open calculator.
Read guide →
Budget & decisions
Understand business AI implementation costs: data preparation, integrations, testing, model usage, and support after launch.
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Budget & decisions
Choose ready-made AI software, integrations, or a custom system based on workflows, data, operating costs, and ownership.
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Data & implementation
Prepare reporting automation with clear KPI definitions, data sources, calculation rules, corrections, and human review.
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Training & adoption
A sample business AI training syllabus covering literacy, data, instructions, output review, role-based practice, and follow-through.
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Open checklist
An open checklist for goals, data, access, evaluation, budget, and operational ownership before starting an AI project.
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