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Getting started and measuring results

How to start an AI project in the company and how to measure if it works: pilot project, KPI, mistakes to avoid.

11 guides in this category

A Copilot pilot for SMEs compares quality, net time, cost and capacity allocationCopilot for SMEs: pilot project, adoption and ROIEvaluate Copilot in an SME with role-based tasks, quality checks, net time savings and costs. Pilot budget examples distinguish capacity from cash.
Calculation of the return on investment of an artificial intelligence projectROI of an AI project: how to calculate itCalculate an AI project's return: what to include, what to leave out and why you need baseline measurements before starting.
Integration of an AI system with existing business management softwareIntegrating AI into the systems you already haveConnect AI to existing business software, CRM and archives: requirements, complications and how to assess feasibility.
Indicators to monitor in an artificial intelligence projectAI project KPIs: what to measureWhich indicators to track in an AI project: process, quality and adoption metrics. Which to ignore and why.
Structure of an AI pilot project with defined success criteriaAI Pilot Project: How to Set It UpSet up an AI pilot with scope, duration and predefined success criteria. Prevent it from becoming an endless prototype.
Criteria for choosing an AI project providerHow to choose an AI providerChoosing an AI project provider: questions to ask, signals to check and what makes a credible quote.
Points to check in a contract for an artificial intelligence projectContract with an AI provider: what to checkAI project contracts: what to clarify about code ownership, data, support, liability and compliance before signing with your technology supplier.
Training of the company team on the use of artificial intelligenceTraining the team on AI: what worksTrain staff to use AI: what they need, what does not work and how to measure whether training delivered results.
The real causes of failure of artificial intelligence projectsWhy AI Projects FailWhy AI projects fail: the causes are rarely technological. What happens in practice and how to prevent each type of failure.
Steps to start an artificial intelligence project in the companyAI project in the company: how to really get startedStart an AI project in your business: where to begin, what to measure first, mistakes to avoid and how to protect your initial investment.
Difference between proof of concept, prototype and AI pilot projectProof of concept AI: what it is for and how long it lastsWhat an AI proof of concept is, when it helps and when it wastes time. Differences from prototypes and pilots, typical duration and exit criteria.

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