AI predictions for the year 2026

AI has been developing rapidly for several years and is constantly making new advances. Language models are getting smaller and better. Companies and tech-savvy individuals are paying more attention to what happens to their data. A forecast for developments and AI trends in 2026.

Introduction

A prediction for a one-year period was already made here for the year 2025. The forecasts were fulfilled to a rather high extent. So, the development of LLMs regarding their size and performance capabilities was well predicted. However, this is not really a surprise for all those who intensively deal with AI technology.

As predicted, agent systems are also increasingly finding their way into the everyday lives of some AI-savvy individuals. However, there is no sign of a triumphant advance: AI agents can not only be powerful, but also dangerous. At the same time, they often fail.

Autonomous systems were on the rise in 2025. However, their breakthrough is yet to come, with the exception of war scenarios (drones).

What will happen in 2026? Where will AI develop? What new things will happen?

The following is a forecast.

Forecasts for the development of AI

The individual forecasts are presented in loose order. They will be evaluated towards the end of 2026.

The rise of open source

Recent advancements in AI have been rapid, bringing new breakthroughs every year. Language models are becoming smaller and more efficient. Companies and tech-savvy individuals are increasingly concerned about what happens to their data. A forecast for developments and AI trends in 2026. Open-source AI models and methods have been improving for a while now. For example DeepSeek. DeepSeek, as a Chinese startup, even made it into the evening news on ARD. Recently, DeepSeek has brought innovative methods to improve AI models through previously unknown training methods.

Meta has decided as of December 2025 to withdraw from Open-Source. However, this shouldn't be of interest to anyone, because it will also continue without Meta. It would actually be best if Meta disappeared off the face of the earth: Its transgressions against humanity are too significant and numerous .

As before, LLMs and image models will become smaller and smaller or better. ChatGPT will not only have a problem with Google's AI dominance, but also with free AI, which everyone will soon be able to operate to some extent on their own computer system (or powerful smartphone).

Security requirements

People and companies will pay more attention to data protection and data security. Not that companies in Europe need to place particular emphasis on compliance with the GDPR: supervisory authorities are still a toothless tiger. Rather, companies are worried that their trade secrets or other sensitive data will fall into the wrong hands.

It is well known that AI systems are processing more data than ever before in human history. So it's no wonder that some people are worried. It starts with AI training to create cloud AI models such as ChatGPT or Gemini. Many billions of texts are collected from the internet for this purpose (you could also leave out the "b" here).

Three types of views on data security can be identified:

1. The first group are the Acceptors and Reality Deniers. They have resigned themselves to their supposed fate: control over their own data and that in the company is not possible. But that's not so bad, because Microsoft is certainly safe anyway. Spoiler: Microsoft is not safe. But fortunately, nothing ever happens. Espionage has the task of remaining unnoticed.
2. The second group are the alleged risk reducers. They think that with a ChatGPT filter or anonymizer everything will be fine. Spoiler: Such data filters do not work. This leads to an even bigger problem than before: As soon as the privacy filter is installed, some people think everything is safe now. Therefore, sensitive documents are uploaded to the chat even more recklessly.
3. The third group are the Innovators and Free Spirits. They don't want to be suppressed by the US and data giants like Microsoft or Google. The solution is being sought out and utilized. Spoiler: There have been local AI as a safe and affordable alternative for several years now. The basis for this is open-source models. The application scenarios are diverse. The answer quality is often better than with ChatGPT for specific use cases.

Cyber security is becoming increasingly important. Why shoot down a missile when you can paralyze an entire country easily and almost untraceably with malware?

Thanks to Microsoft, the malware named Copilot is now frequently landing in German companies and inviting others to be exploited by villains. Fortunately, that only happens in other companies. Yours is definitely safe ([1]) !

Multimodal systems will become the standard

It all started with ChatGPT as a language model. There were also image-only models. For some time now, there have been models that combine text and images or even speech.

These models are called multimodal: They support multiple types of data.

How DeepSeek has shown with DeepSeek OCR, a machine learning model that interprets a scanned text as an image (rather than trying to extract the text directly from the image) can develop a significantly better understanding of the text. At the same time, the information content of the text can be expressed with a fraction of the tokens previously used (compression).

So in the future, we may still say language model or LLM, but mean "AI for whatever".

Enterprise AI faces the "scale or fail" moment

Many companies believe that a chatbot is a savior. It is true that chatbots are very suitable for general questions and answers. Chatbots are the wrong choice for specific applications in companies.

A specific problem requires a specific solution.

Universal systems can only solve specific problems to a limited extent. In any case, their answers are unreliable, non-transparent and, at the end of the day, uneconomical.

Those who believe they can succeed by taking the easy route will only succeed with general problems. For example, chatbots for world knowledge, or AI assistants in software development.

Business problems will be solved correctly with preconceived AI systems. This is the somewhat more difficult path that has no shortcuts. Fortunately, this is not a problem, because thanks to AI, AI apps can be produced faster and better (and with a nicer look) than ever before.