In Industry 4.0 and 5.0 discussions, a common argument appears: AI models reach around 90% accuracy, and in industrial environments a 10% error can cost millions. The reasoning sounds compelling because it is framed numerically and linked to operational risk. However, this argument assumes something critical — the existence of a fully digitized factory. In reality, across many manufacturing plants in Poland and Europe — especially in the SME sector — that level of digital maturity simply does not exist.

Picture a warehouse robot navigating the aisles at full speed, or a port crane stacking containers with millimeter-level precision. These aren't machines running pre-written scripts — they're AI systems making decisions in real time. This is what the era of Physical AI looks like. Physical AI refers to intelligent systems capable of sensing, interpreting, and acting in the real world. Autonomous vehicles weaving through city traffic, robotic arms assembling components with surgical accuracy, smart energy grids responding instantly to load changes — these are just a few examples.

January 2026 marked a pivotal turning point in the development of artificial intelligence. AI is evolving from an “interactive tool” into a “physical entity” capable of fundamentally transforming all industrial sectors—especially manufacturing. Physical AI and the Robotics Era Jensen Huang, CEO of NVIDIA, announced at CES 2026 that “the ChatGPT moment for robotics has arrived,” signaling a mass transition of AI from the virtual space into the physical world. NVIDIA introduced a series of open models for physical AI, including the Cosmos models capable of understanding the world and generating action plans, as well as Isaac GR00T N1.6, dedicated to humanoid robots. The new Jetson T4000 module, based on the Blackwell architecture, delivers four times higher energy efficiency and AI compute performance compared to the previous generation, priced at USD 1,999 (for orders of 1,000 units). Global companies such as Boston Dynamics, Caterpillar, Franka Robotics, LG Electronics, and NEURA Robotics presented a new generation of robots powered by NVIDIA technologies.

Why data sovereignty is no longer a technical detail — but a strategic advantage As factories accelerate digital transformation, cloud platforms are often presented as the foundation of innovation. But for manufacturing environments, where every second of downtime translates directly into financial and operational losses, dependency on external cloud services introduces real risk. Data sovereignty — the ability to control where industrial data is processed, who can access it, and how it is governed — is becoming one of the most important pillars of modern manufacturing architecture. This is not a trend. It is the foundation of operational resilience, industrial AI, and competitive advantage.

For more than a decade, industrial digitalization has set new directions in manufacturing. The term Industry 4.0 became a symbol of the Fourth Industrial Revolution – the era of automation, robotics, and the Internet of Things (IoT). Today, Industry 5.0 is gaining traction. It does not replace 4.0 but builds on it, adding a new dimension: the integration of humans and technology in a sustainable and responsible way.

ROI: up to 15% efficiency gains and 10–20% better energy storage performance – this is the real power of AI in modern energy. In the era of Industry 5.0, where technology merges with a human-centric approach, the renewable energy sector is growing at an unprecedented pace – with 18.6 GW of additional solar capacity installed in the first nine months of 2024. Manufacturing Execution Systems (MES) enhanced with machine learning are becoming a cornerstone of this transformation, delivering both business and technical benefits.

Industry is on the brink of a new revolution. Industry 5.0 marks an era of human–machine collaboration that prioritizes sustainability, where AI is not merely a tool but a strategic enabler of transformation. Unlike Industry 4.0, which focused on automation and digitalization, Industry 5.0 emphasizes human–machine collaboration, sustainable development, and the integration of ESG (Environmental, Social, Governance) principles with advanced technologies.

The Ollama project is an open, free software that allows running local AI models, specifically large language models (LLMs), on your own computer or server. Due to its low hardware requirements, this software is accessible to medium and small businesses, providing access to 93 AI models without significant limitations.

Learn how to integrate the GPT-4 API with a web application step by step to leverage advanced data analysis features. Example in Python and Flask, along with settings and data security.