April 14, 2026

AI Projects Are Failing | Here's What Everyone Gets Wrong

Show Notes

Most AI projects fail because of messy data, not the LLM models everyone blames.

In this episode of An Hour of Innovation, Vit Lyoshin speaks with Max Vermeir, VP of AI Strategy at ABBYY, about why AI and LLM implementations fail in real business environments. They break down how unstructured data, document processing, and real-world constraints impact AI systems far more than the models themselves. This conversation goes beyond AI hype to explore what actually works when building AI products in production.

They discussed:

* Why most AI projects fail in enterprise environments

* The real challenge of unstructured data for LLMs

* How document AI impacts business automation and workflows

* Deterministic vs probabilistic AI systems explained simply

* Why LLMs always return answers, even when incorrect

* Hidden costs of using AI models in production systems

* Why simple solutions often outperform complex AI models

* What product managers misunderstand about AI implementation

* Framework for building reliable AI products in production

* Future of AI agents and engineering productivity shifts

Max Vermeir is the VP of AI Strategy at ABBYY, where he focuses on applying AI to real-world business problems, especially around document processing and automation. He works at the intersection of AI technology and enterprise systems, helping organizations turn unstructured data into usable insights. Max is known for his practical, no-hype perspective on AI, focusing on what actually works in production rather than demos. His experience gives him a unique view into why many AI projects fail and how to build systems that deliver real value.

Timestamps

00:00 Introduction

01:35 AI in Business Operations

03:56 Understanding Document AI

06:57 Challenges in Document Processing

10:15 The Importance of Data Accuracy

11:59 Deterministic vs. Probabilistic AI

16:38 High ROI Use Cases for Document AI

18:50 Common Underestimations in AI Product Development

21:48 Engineering Challenges in AI Projects

25:26 Implementing AI Feature as a Product Manager

27:36 Frameworks for AI Implementation