The History of AI, Part 4: AI Becomes Infrastructure (2024–2025)

From Novelty to Infrastructure

2024 and 2025 marked the transition: AI was no longer an experiment, it became infrastructure. Like electricity or the internet – something that's simply there and on which everything else is built.

2024: The Year of Consolidation

Multimodal Models Become Standard

GPT-4V, Gemini, Claude 3 – all major models became multimodal. They could handle not just text, but also:

• Analyze and describe images
• Understand documents and charts
• Process audio (GPT-4o)
• Understand video (Gemini)

This changed how people use AI: no longer just "write me a text," but "look at this dashboard and tell me what stands out."

AI Agents: The Next Level

2024 saw the shift from chatbots to agents. The difference:

Chatbot	Agent
Answers questions	Completes tasks
Needs precise prompts	Plans steps independently
Single interaction	Multi-step workflows
Passive	Proactive

Tools like Devin (AI Software Engineer), AutoGPT, and soon monday AI Agents showed where things are heading: AI as a team member, not as a tool.

Reasoning Models

OpenAI's o1 (September 2024) introduced a new category: models that "think" before they answer. Chain-of-thought reasoning was integrated directly into the model. The result:

• Significantly better performance in math and logic
• More reliable complex analyses
• More transparent thinking processes

Open Source Catches Up

LLaMA 3, Mistral Large, and Qwen 2 proved: open-source models can keep up with closed-source models. The community developed:

• Specialized models for medicine, law, code
• Efficient models for local use (Ollama, LM Studio)
• Fine-tuning pipelines anyone can use

2025: AI in Everyday Work

Enterprise AI Becomes Real

2025 was the year AI truly arrived in enterprises – not as a pilot project, but as standard:

• Microsoft Copilot became an Office 365 standard feature
• monday AI integrated Sidekick, Workflows, and Agents directly into the platform
• Salesforce Einstein became the standard AI in CRM
• SAP integrated AI into the Business Suite

AI-Native Workflows

The decisive shift: AI was no longer bolted onto existing processes, but processes were built around AI:

• Automatic lead qualification and enrichment
• AI-powered project planning with dynamic adjustment
• Predictive analytics as standard in business intelligence
• Automated documentation and reporting

Vibe Coding and AI Development

A new development philosophy emerged: Vibe Coding. Tools like Lovable, Cursor, and Replit made it possible to create complete applications through natural language.

• Non-technical people can build software
• Developers become 10x more productive
• Prototyping in hours instead of weeks

Regulation Takes Shape

The EU AI Act came into effect and set the global standard:

• Risk-based classification of AI systems
• Transparency requirements for generative AI
• Bans on certain applications (social scoring, real-time biometrics)
• Europe positions itself as a regulatory pioneer

The Working World Changes Fundamentally

By the end of 2025, it was clear: AI doesn't just change individual tasks, it changes entire job profiles:

• Marketing: From content creation to content curation and strategy
• Development: From writing code to system design and AI orchestration
• Consulting: From analysis to strategic interpretation and execution
• Management: From reporting to AI-powered decision-making

What We Learn from This Era

1. Integration beats innovation – Not the best model wins, but the best integration
2. AI is a skill – Those who can't use AI fall behind
3. Regulation is necessary – Europe leads, the world follows
4. People First – The most successful AI implementations put people at the center

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Continue with the finale, Part 5: Outlook 2026 – What Comes Next?