Are you curious about the true costs and potential return on investment (ROI) of implementing AI in your organization? In this we do a deep dive deep into one of the most common hurdles companies face when starting an AI project: forecasting costs and calculating ROI. As AI adoption continues to accelerate—thanks in part to decreasing costs and accessible tools like Microsoft 365 Copilot —understanding the financial impact of your AI initiatives has never been more critical. This video breaks down the complexity, providing practical insights to help you plan and budget effectively for your AI projects.
This video also explores the variety of AI solutions available, from out-of-the-box agents to fully custom models, and explains how to approach implementation, operational costs, and ongoing maintenance. By the end, you’ll have a clearer understanding of the financial considerations involved and how to evaluate the ROI of your AI initiatives, so your projects deliver measurable business value.
In this video you’ll learn:
How to estimate AI project costs: Discover a structured approach to calculate costs using prototyping exercises, tokenization, and infrastructure considerations.
How to evaluate ROI effectively: Learn to apply frameworks like ICE (Impact, Confidence, Ease of Implementation) to prioritize AI initiatives with the highest potential impact.
Best practices for implementation and scaling: Understand key factors like data quality, maintenance, training, and avoiding common pitfalls that can affect project costs and outcomes.
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