Valuation with AI: Fundamental Analysis and Company Valuation in the Age of Large Language Models

A practical guide to fundamental analysis and company valuation using artificial intelligence in 2026.

Ten chapters cover the complete analytical workflow: the four financial statements and their interpretation, the regulatory sources where filings live (SEC EDGAR, ESEF in Europe, equivalents in Latin America and Asia), data extraction with large language models and traditional scrapers, AI-assisted reading of the financial statements (trend analysis, ratio computation, red-flag detection, segment analysis, qualitative interpretation of the MD&A and risk factors), discounted cash flow valuation with AI support, valuation by multiples and sum-of-the-parts methodology, practical workflows and advanced prompting techniques, integrated case studies (a US technology company, a European bank, an emerging-markets conglomerate), risks and verification practices (hallucinations, knowledge cutoff, legal and ethical considerations, fiduciary obligations), conclusions and outlook for the analyst working with AI in 2026 and beyond. Written for educated readers with some background in finance who want to incorporate AI tools as productivity amplifiers in their analytical work, with rigorous attention to verification and to the limits of what the tools can and cannot do.

The analyst's job just changed. This is the field manual.

For two centuries the only real productivity tool the financial analyst had was the spreadsheet. Then large language models stopped being a curiosity and became a serious instrument of the trade. The moment you could feed a 200-page filing to an AI and get back a coherent summary in under a minute, the conditions of analytical work changed for good.

This book is about that change—written for the reader who is past believing AI will replace the analyst, and equally past dismissing it as a passing fashion. Both phases were short and unproductive. What remains is the substantive question: how do you actually integrate these tools into the work an analyst really does?

Following the natural arc of an analysis, Valuation with AI takes you from the financial statements and regulatory sources (SEC EDGAR, ESEF, Companies House, and the major Latin American and Asian regulators) through automated data extraction, the analytical reading of the statements, and the two core valuation methodologies—discounted cash flow and market multiples—with AI applied at every step where it genuinely helps.

Inside you'll learn to:

Reduce a 300-page annual report to a structured, verifiable summary in seconds

Build reusable analytical workflows instead of one-off exercises

Apply LLMs to DCF and multiples valuation without losing analytical rigor

Exploit XBRL and structured reporting to analyze thousands of companies at scale

Integrate ESG and sustainability disclosure into the financial picture

Recognize—and defend against—hallucinations and the other failure modes

This is not a book that promises magic. The tools are useful for some tasks, dangerous for others, and never a substitute for judgment. The verification discipline is the price of using them productively. But for any analyst with a substantial career still ahead, the math is clear: the AI-assisted competitor is getting more capable every quarter.

Used properly, these tools amplify. Used improperly, they substitute. This book is written to put you firmly on the amplifying side—and to make that investment efficient.

Welcome to the present condition of the financial analyst's working life, where the difference between productive and unproductive practice is now measured in months, not years.