Chelsea AI Ventures
KI-Schulung für Führungskräfte Leiter Lernpfad 2 Day Intensive (In-Person, London) or 1 Week Accelerated (Virtual Cohort)

AI Due Diligence: Evaluating High-Growth AI Ventures

A rigorous framework for decision-makers to accurately assess an AI company's technology, team, and true market value

Zielgruppe

The Capital Allocator

Kernnutzen

Accurately assess the technology, team, and true market value of any AI company

Alleinstellungsmerkmal

Built around a proprietary, field-tested evaluation framework

Lernziele

  • Apply a structured framework to systematically evaluate an AI company's technology, team, and market position
  • Assess the defensibility of an AI company's intellectual property, including algorithms and data assets
  • Identify critical red flags related to model performance, scalability, ethical bias, and regulatory compliance
  • Evaluate the true caliber and expertise of a technical team beyond academic credentials
  • Incorporate AI-specific risks and opportunities into valuation models and deal structuring

Voraussetzungen

Professional experience in corporate finance, venture capital, or corporate strategy.

Kursaufbau

Module 1: The Due Diligence Framework - Technology & IP

Assess core algorithms, code quality, architecture scalability, and technical debt. Analyze the company's data moat and defensibility.

Aktivitäten:

  • Technical deep dive exercise on sample AI startup
  • Data moat evaluation workshop

Module 2: The Due Diligence Framework - Team & Talent

Go beyond resumes to assess practical expertise. Structure technical interviews and evaluate execution capability versus research ability.

Aktivitäten:

  • Team assessment role play
  • Technical interview design session

Module 3: The Due Diligence Framework - Performance, Ethics & Risk

Critically analyze model performance beyond accuracy. Assess robustness, identify bias risks, and evaluate regulatory exposure.

Aktivitäten:

  • Red flag identification exercise
  • Regulatory risk assessment

Module 4: Valuation & Deal Structure for AI Companies

Factor AI-specific elements into financial models. Structure deals to mitigate technical and execution risks.

Aktivitäten:

  • AI company valuation workshop
  • Term sheet structuring exercise

Behandelte Themen

Proprietary evaluation framework
Technical due diligence for AI
Algorithm and model assessment
Data asset valuation
IP defensibility analysis
Team capability evaluation
Performance metrics beyond accuracy
Bias and fairness assessment
Regulatory compliance evaluation
AI-specific valuation models
Risk-adjusted deal structuring
Red flag identification

Abschlussprojekt

Conduct rapid due diligence on a mock AI startup using the course's structured framework and present your recommendation to the group.

Why This Course Matters

The AI venture landscape is littered with the wreckage of due diligence failures. Sophisticated firms have allocated millions to companies whose “proprietary AI” turned out to be clever wrappers around open-source models, whose “data moats” evaporated under scrutiny, and whose “world-class teams” couldn’t ship production code.

In this gold rush, the ability to distinguish genuine innovation from well-packaged hype is essential for survival. This course provides the systematic framework you need to make strategic allocation decisions based on evidence, not assertions.

What Makes This Course Different

Unlike generic tech due diligence, this program addresses the unique challenges of evaluating AI companies. We teach you to look past the code and identify whether an AI company’s technology is a genuine breakthrough or sophisticated marketing.

The centerpiece is our proprietary evaluation framework, a comprehensive system developed through analyzing hundreds of AI companies. This isn’t theoretical; it’s a field-tested framework used to evaluate potential partners and technologies. You’ll apply it to real-world scenarios to build practical, repeatable skills.

Course Philosophy

We believe effective AI due diligence requires both technical literacy and commercial acumen. You don’t need to code, but you do need to understand what questions to ask and what the answers really mean.

Throughout this intensive workshop, we focus on finding the truth beneath the pitch deck. Every module is designed to reveal the hidden risks and opportunities that determine whether a capital allocation succeeds or fails.

Who Should Take This Course

This course is essential if you:

  • Evaluate AI companies for funding or acquisition
  • Need to validate technical claims in pitch decks
  • Want to understand AI-specific valuation factors
  • Must assess technical team quality beyond credentials
  • Are responsible for identifying hidden risks in AI ventures
  • Need a repeatable process for AI due diligence

If you’re allocating capital to AI companies, this framework provides the systematic approach you need to proceed with confidence.

Bereit, Ihr Team weiterzuentwickeln?

Kontaktieren Sie uns für maßgeschneiderte Schulungen oder Gruppenanmeldungen.

Schulungsbedarf besprechen
Ben Auffarth, Chief Data Officer at Chelsea AI Ventures

Ihr Gespräch ist mit
Ben Auffarth, Chief Data Officer