Automation provider aims to debunk myths still obstructing adoption of AI

Fears about the impact of artificial intelligence (AI) in automation will prove as unfounded as fears about robotics a few years ago, says Fanuc.

The company quotes an Institute of Labor Economics study from 2022 on the effect of robots on the European labour market, which concluded that robot adoption actually increased employment and reduced unemployment in most of the 16 European markets it examined.

Countering the similar myth that AI will take away jobs, Fanuc recommends instead thinking of AI as a tool for individuals to use – rather than to replace them.

AI can help people to do their jobs more efficiently by automating repetitive and mundane tasks, Fanuc explains, generating insights and intelligence that can inform decision making, accelerating lengthy testing and design processes, and making predictions that can eliminate risks.

Of course, where there are labour shortages and an ageing workforce means that skills are being lost, then the manufacturing sector can harness AI to supplement and bolster scarce expertise, it adds.

A second persistent myth, says Fanuc, is that AI will put the company’s data at risk. As with any data-based technology, there is a requirement to protect AI models, the data they process, and the broader systems they integrate with against cyber threats. It is also true that information inputted into free AI models can become public training data, leading to corporate secrets or personal data being exposed. But Fanuc emphasises that these are not the types of AI system that are going to add value in industrial settings.

Keeping it local and using internal GPU (Graphics Processing Units) and servers to run AI models offers maximum data privacy, says the company, ensuring that no sensitive data is used for external training or leaked to third-party cloud providers. On-device AI is also a high-security option, as the data is processed on user devices rather than in the cloud.

The company highlights a third myth, which assumes that AI is moving so fast that any system will quickly become obsolete. It is true that the pace of development is rapid, it says, but certain measures can be taken to avoid obsolescence. Open ecosystems and standardised, open-source platforms help in futureproofing, particularly with the shift from generative to agentic AI. MCP (an open-source protocol that allows AI assistants to interact with external data sources and software tools) is one standard interface of such systems and OPC Unified Architecture (OPC UA) is another secure standard.

024 7605 3000
www.fanuc.eu