Assess the AI project plan and scope in detail — Thoroughly calculate staff resources and all other costs, collaborating with business leaders, technical teams, and financial experts to estimate expenses and align expectations
Monitor and update costs continuously throughout the project to prevent overruns and ensure alignment with the budget, anticipating scaling costs
Be realistic about the cost of talent and expertise — Factor in the cost of hiring, training and retaining AI, data, technical, and other professionals
Factor in ongoing and maintenance costs — Include IT, data acquisition, data preparation, model updates, storage, software, integration and iteration costs
Break down the project into phases and tangible pieces — Start with pilot projects, identify challenges and improve cost estimation before scaling
Make sure to consider all related costs across all project phases, including support, training, adoption, potential disruption, and opportunity costs
