How do newer AI/data-driven valuation approaches differ from traditional consultant valuation reports in power markets?

I’m curious about how different valuation approaches are used in energy market analysis, especially when it comes to long-term outlooks. From what I’ve seen, some methodologies rely on fundamentals (supply-demand, cost curves, policy assumptions) and statistical/AI-based extrapolation, while traditional consultant reports tend to use expert judgment, scenario tables, and proprietary assumptions. For people who work with valuation models or long-term forecasts: * How do these newer data-driven approaches compare with more traditional consultant valuation reports in practice? * In what situations would you trust one method over the other? * Do they tend to produce similar results, or do they diverge significantly on key assumptions like capacity prices, merchant revenues, or compliance markets? I’m interested in practitioner perspectives on the differences in methodology and use cases, not specific tool recommendations. Thanks!