About Us

Introduction

AI CATCH addresses the problems of traditional approaches to improve national statistical organizations. It combines generative AI with structured problem-solving workshops, focusing on co-creation and real organizational dynamics. While AI is useful for simple tasks, AI CATCH integrates robust methodologies and human insights to solve complex issues, ensuring sustainable change by overcoming organizational barriers. See detailed background below.

Our Mission

To empower National Statistical Organizations to navigate complex change by combining Generative AI with expert-led, structured problem-solving workshops—ensuring quality, efficiency, and sustainability.

Our Vision (2028)

To be a globally recognized catalyst for innovation in official statistics, known for translating dense standards into practical improvements while operating as a small, sustainable team.

Founders

Mogens Grosen Nielsen

Mogens Grosen Nielsen

  • Expert in managing change in statistical organizations supported by AI.
  • 30+ years at Statistics Denmark and global NSO consulting across multiple continents.
  • Specialist in quality assurance, metadata alignment, and organizational systems change.
  • Deep interest in sociological dynamics within statistical systems.
  • Published international conference papers on quality frameworks with Lars.
  • Get details: LinkedIn and Website

Lars Thygesen

Lars Thygesen

  • Over 30 years advising top management in 25+ NSOs including Statistics Denmark and OECD.
  • Led register-based census designs, metadata systems, and quality frameworks.
  • Strong interest in official statistics and user-driven quality approaches.
  • Co‑authored international papers on statistical quality and metadata with Mogens.
  • Expert in strategy, standards, dissemination, and advisory services for NSOs.
  • Get details: LinkedIn and Website

The Main Ideas Behind AI‑CATCH

AI‑CATCH bridges high-level theory and real-world implementation:

  • Change as strucured problem solving: Use a clear, step-by-step path from current to desired situation. The includes a guide to describe current situation and issues, based on how NSO subsystems interact
  • Generative AI: Converts complex guidelines and contextual data into actionable, tailored scenarios.
  • Co‑creation: Workshop-based collaboration ensures stakeholder ownership and practical outcome design.
  • Standards Integration: Aligns with frameworks like GSBPM, GAMSO, and UN NQAF to guide quality and process consistency.
  • Sustained Change: Embedded documentation, decision logs, and feedback loops create organizational memory, not just one-time fixes.

Lars and Mogens launched AI‑CATCH to offer a framework that combines structured methodologies with analytic innovation— turning theory into durable practice for statistical agencies worldwide.

Detailed background

AI CATCH was founded on a simple observation: many efforts to improve national statistical organizations—whether led by external consultants or through complex international manuals (e.g., UN, Eurostat)—fail to bring lasting change. These approaches often overlook organizational factors like siloed production systems, and internal and external power dynamics, which inhibit coordination and ownership. Despite comprehensive global guidelines and numerous advisory missions, statistical systems often remain fragmented. Large-scale change fails when drive comes from the outside and the system’s internal realities aren't addressed. AI CATCH instead focuses on co creation, pairing generative AI with structured problem-solving workshops that align with real organizational dynamics.

“Simple use of AI is great for instrumental use finding alternative problem-solution combinations, where AI dives into the global sea of knowledge (e.g., writing polite emails, analysing x-ray for cancer etc). But AI can be dangerous if we use simple AI to deliver solutions to complex organizational and societal problems, e.g. preparing strategy in organizations and decisions on how statistical organizations provide reliable information based on dialogue with all sectors in society. For complex problems we must build AI-solutions with proper methodology and proper knowledge bases and ensure that humans are included”

We designed AI CATCH to navigate this complexity—integrating theory and methodology, AI, and stakeholder engagement into a unified process. Building on decades of firsthand experience, Lars Thygesen and Mogens Nielsen co-created a tool that recognizes real-world organizational barriers and makes change genuinely stick.