Lars Leipson
Lars Leipson
Data · AI · Operations

I build the data engines AI products run on, and the organizations behind them.

VP Data Production & Acquisition and Deputy CDO at Statista, leading a ~150-person organization that produces data across 170+ industries. Co-founder of Lit-X, an AI company for book publishing, built from zero. Trained in strategy at BCG and Roland Berger.

See the work Get in touch
~150
people across six departments, from data engineering to operations
~20m
data points produced per month, steered by value
170+
industries covered, for tens of thousands of corporate customers
0 → 1
Lit-X, from zero to enterprise customers in production
What I do

Where I create the most value

01

Run production at scale

Built Statista's data production operating system: AI-first production lines, value-based steering of ~20m data points a month, and dedicated quality and architecture functions. Consolidated production capacity from across the company into one organization.

02

Make data AI-ready

Made a platform asset consumable by AI: richer metadata, context, harmonized taxonomies and structured delivery via API and MCP. The shift from platform to headless. Statista data now reaches users inside Microsoft Copilot and Perplexity.

03

Build from zero

Co-founded Lit-X with one technical co-founder, bootstrapped and part-time. Built a proprietary data layer and AI tools on top of it, and closed every customer personally, in a vertical openly skeptical of AI.

04

Turn strategy into decisions

Six-plus years at BCG and Roland Berger: portfolio decisions with top management, operating models that make strategy executable, a major corporate venture capital vehicle. At Statista: rebuilt data acquisition on a revenue-share model and led M&A evaluation of data companies.

Selected work

From zero to enterprise customers

Lit-X · Co-founder since 06.2023

Lit-X

An AI and data platform for book publishers, organized around how editorial, marketing and sales teams actually work: title scouting, manuscript checks, bookfluencer matching, campaign tracking, Amazon ads optimization.

2M+
book titles
12,800+
bookfluencers tracked
2.4M+
social posts, text, audio and visual
4
enterprise publishers live in production

What it shows. Data layer first, AI tools on top, every customer closed personally: Bonnier, Carlsen, Piper and ars edition. Bootstrapped to low six-figure recurring revenue.

lit-x.com →
How I think

Data production is a discipline. Few companies run it like one.

AI makes it easy to get any data, and harder to get the right data. The Data Production Framework is how I decide what to produce, for whom, and how to run it at scale. It applies to classic data providers and to data operations inside AI companies.

  1. 01 Customer & use case orientation Who is the data for, and which decisions does it serve?
  2. 02 Data portfolio What to produce, and what to stop producing.
  3. 03 Production engine How to organize and produce at scale, with AI where it pays and humans where it matters.
  4. 04 Quality & customer signal How good is good enough, and how do you know?
  5. 05 Commercial connection Data, insights or software: what you sell, and how it reaches the market.
Explore the framework →
Writing
23.03.2026 · 12 min read
What 'Data Production' Actually Means
The core capability of every data provider, why it is neither data engineering nor data science, and how to organize authority over it.
Read →
Also: jury member, AI BEAVERS founder hackathon, House of AI Hamburg, 2026. More notes on LinkedIn →
Track record
08.2020 to today
Statista
VP Data Production & Acquisition, Deputy CDO (since 01.2025) · Senior Director Market Insights (2022 to 2024) · Director B2C Market Insights (2020 to 2022)
06.2023 to today
Lit-X
Co-founder. Bootstrapped AI and data company for book publishing.
09.2017 to 08.2020
Boston Consulting Group
Strategy Consultant. Corporate strategy, organizational design, corporate venture building.
02.2014 to 08.2017
Roland Berger
Management Consultant. Transformation, market entry, operational restructuring.
Full profile on LinkedIn →
Contact

Let's talk.

I enjoy conversations with founders, operators and investors about data for AI, scaling operations, and building data businesses.

LinkedIn