February 11, 2025 AI Competition Unleashed: Effects on Manufacturing

New AI models offer manufacturers efficient, low-compute tools, but challenges around scalability, security, and reliability remain.

By Jan Burian

DeepSeek AI’s recent unveiling of its open-source, low-compute, and faster large language model (LLM) has raised a host of questions across the tech and industrial sectors. The model is built using open-source software, making it available for expert examination and providing insight into its code. One key innovation in DeepSeek AI’s R1 LLM is the compression of large AI models into smaller, more efficient versions. This approach allows the models to run on less powerful infrastructure without sacrificing performance, and some experts argue that it could rival OpenAI’s ChatGPT in capabilities.

In the manufacturing sector, OpenAI’s technology has become the dominant choice for applications like knowledge management, code generation, and AI copilots. But with the emergence of faster and more efficient models, many are asking: What’s next for manufacturers? How can they benefit from these innovations, and what use cases will emerge?

Industrial AI: A Leap Toward Innovation

A key question is whether manufacturing organizations can harness these faster, more efficient models for their operations. While DeepSeek AI’s technology and its potential to scale for industrial use cases are still being explored, there is growing excitement among industrial AI professionals about the possibilities it presents. Experts are eager to see how these innovations could be applied to industrial use cases like predictive maintenance, supply chain optimization, and enhancing manufacturing automation.

However, the real challenge will be determining if DeepSeek AI’s models can meet the robustness criteria needed for such demanding applications. Manufacturers will need to carefully evaluate the models’ stability, accuracy, and ability to handle the complexities of real-world industrial environments.

Data Security and Geopolitical Concerns

While the potential benefits are clear, there are significant concerns surrounding data security. According to DeepSeek AI’s privacy policy, all data is stored on servers in China. This raises an important question for manufacturing companies—especially those in the U.S.: Can they trust a Chinese-based company with their sensitive data?

Geopolitical tensions further complicate the issue. Despite the promise of ‘outside the US’ technology, many companies in the U.S. may hesitate to adopt it due to concerns about data privacy and the safety of their intellectual property. As regulations on data sovereignty become stricter and restrictions on cross-border data flow evolve, the challenges of adopting foreign AI technology could become a major barrier in some regions.

A Changing Global Landscape

The Chinese market’s role in the industrial AI conversation should be taken into consideration. With Chinese regulations requiring that AI technology used within the country be developed domestically, the global AI landscape is shifting. For organizations targeting the Chinese market, there is a clear need for locally developed solutions. This means global companies may need to develop their industrial AI solutions with Chinese-specific requirements in mind—whether they choose to work with DeepSeek AI or other Chinese AI firms.

As AI continues to advance, manufacturers will need to stay ahead of the curve by leveraging the most effective and secure technologies. Whether it’s DeepSeek AI’s innovations or those from major U.S. tech companies, the race for AI supremacy is likely to result in better-performing models and expanded opportunities across industries worldwide. Manufacturers will need to keep a close eye on developments, evaluate their options carefully, and above all, prioritize security as they implement these transformative technologies.

About the Author:
Jan Burian, a global analyst, author, and speaker, serves as the Head of Industry Insights at Trask. His expertise spans digital transformation, management, leadership, and the geopolitical influences shaping manufacturing and global supply chains. Prior to his role at Trask Solutions, Jan led Manufacturing Insights Europe at IDC and held consulting positions at EY and Deloitte.

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