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Articles

Written pieces from our work: how AI moves from pilot to measurable operation, where it typically stalls, and what has proven itself across more than 30 mid-market engagements. If you would rather listen, the same topics run in the podcast.

Format All Article Podcast Newsletter Paper Event

Topic All AI Operations AI tools & models Governance & Compliance Digital strategy GEO

Article · 9/28/2026

What companies actually pay for AI: spending data instead of surveys

Surveys measure intent, transactions measure decisions. What payment data reveals about AI budgets, and why it only goes so far for European mid-market firms.

Articles

All articles

What companies actually pay for AI: spending data instead of surveys

The end of AI magic: why companies need to know their human share

The Most Expensive Mistake in AI Adoption: Old Workflows, New Tool

Allowed but Not Provided: Where Shadow AI Actually Starts

88% or 20%? The Number Everyone Cites

440 Billion on the Table: The Business Case for AI in Germany

Enterprise Means Automation: What Usage Data Reveals About Real AI Value

The Sandwich Trap: Why Germany's Classic Mid-Market Falls Behind on AI

Fascination Meets Fear of Losing Control: What AI Skepticism Means for Companies

AI Agents Beyond the Experiment: Governance as the Lever for Scale

47% Direct AI Instead of Doing the Work: The Tool-Stacking Trap

Inaccuracy Becomes the Top Risk: Why Data Quality Now Outranks Cybersecurity

Measuring AI ROI: Why Broad Adoption in Germany Does Not Prove Value Yet

Self-Hosting an LLM: What It Costs, What It Takes and When It Pays Off

Open Source LLMs Explained: DeepSeek, Qwen, Llama & Mistral

Digital Sovereignty with AI: How European Companies Stay in Control

AI Content Disclosure: What Article 50 of the AI Act Requires Since 2 August 2026

AI & Data Privacy: The Overview for Businesses

How We Produce Our Content: Hybrid Division of Labour in Live Operations

Microsoft Copilot: AI Woven Deep Into Microsoft 365

Google Gemini: AI from the search engine giant

OpenAI and ChatGPT: the market leader under the microscope

Anthropic and Claude: what's behind the safest AI model?

Claude, ChatGPT, Gemini, Copilot & Co.: AI tools compared

Developing an AI Strategy for the Organization

Token-Smart: Cutting AI Costs Without Losing Quality

Managed Machine Mode: AI Running Autonomously, Under Control

Configure AI for Data Privacy: Settings, Org Level & Common Traps

Governance, Control, Autonomy: Who Gets to Decide What?

The Dual Leadership Challenge in AI Transformation

Data Quality: Why AI Fails on Bad Data

What AI Providers Do With Your Data: Privacy Terms Compared

We Build the Machine, Not the Output

Expense or Asset: What's Left of the AI Budget at Year-End

The People-Process Gap: When AI Is Ready but the Team Is Not

AI & Data Privacy: Which Risks Really Count and Which Are Overrated

AI Takes Over Tasks, Not Roles: Why AI Is an Organizational Question

Getting Found When Nobody Searches Anymore: From SEO to GEO to AEO

Built with the Team: AI Systems People Actually Use

More Than Automation: How AI Reorders Organization and Visibility

AI Isn't the Problem: Why More Tools Don't Mean More Productivity

The AI Operations Framework: Five Areas That Must Work Together

Building the Business Case: ROI of AI Operations

Getting Started Without Risk: From Self-Check to AI Operations Partnership

The Trillion-Dollar Paradox: Why AI Explodes on the Stock Market and Never Reaches the P&L

The Pilot Graveyard: Why AI Pilots Fail

Production from Day One: Getting AI into Real Operations

What is AI Operations? Definition, Concept and Strategic Importance

Workflow-First, Not Tool-First: How to Adopt AI