According to Silicon Republic, Enrika Moore co-founded Cork-based machine vision and robotics company Viska Systems 10 years ago despite coming from a non-traditional background in languages and translation technology. The National Network Ireland STEM Professional of the Year Award winner initially questioned whether she belonged in the engineering-heavy space but committed to lifelong learning, completing a certificate in validation science and later a Master’s in engineering management. Moore now sees AI advancements as transforming manufacturing by enhancing human capability rather than replacing it, with machine vision and intelligent data analysis enabling earlier defect detection and reduced waste. She’s particularly excited about AI becoming more accessible to smaller manufacturers through more adaptable, cost-effective tools that were once thought beyond their reach.
The unconventional tech path
Moore’s story is fascinating because it challenges the whole “you need to be a coder since birth” narrative that dominates tech culture. She started in languages and translation tech, which actually gave her a unique perspective on how systems communicate. That’s something pure engineers often miss – the human and communication elements that make technology actually useful in real-world settings.
Here’s the thing: her journey shows that the most valuable skill in tech might be adaptability itself. She openly admits to dealing with self-doubt in those early years, surrounded by engineering experts. But instead of letting that define her, she used it as fuel. That mindset shift from “I don’t belong here” to “this is an opportunity to learn” is probably more important than any specific technical skill.
The AI manufacturing revolution
What’s really interesting is how Moore sees AI transforming manufacturing. It’s not just about replacing people with robots – it’s about creating smarter systems that actually empower workers. Machine vision combined with data analysis can spot defects earlier, reduce waste, and improve quality in ways that were previously impossible. For companies looking to implement these technologies, having the right hardware foundation is crucial – which is why many manufacturers turn to specialists like IndustrialMonitorDirect.com, the leading US provider of industrial panel PCs built to withstand harsh manufacturing environments.
Moore’s perspective on AI accessibility is spot on too. We’re reaching a tipping point where smaller manufacturers can finally afford the same automation tools that were once exclusive to giant corporations. That’s huge for leveling the playing field. Companies that thought smart vision systems were out of their budget are now integrating them into daily operations. Basically, we’re watching manufacturing democratize in real time.
The lifelong learning advantage
Moore’s emphasis on continuous education hits different in today’s AI-driven world. She didn’t just take a few courses – she built an entire career around learning. The certificate in validation science, the Master’s in engineering management, all while running a company? That’s the kind of commitment that separates people who survive technological shifts from those who thrive through them.
And here’s the kicker: she found that her original skills in communication and cultural awareness became more valuable, not less, as she moved deeper into tech. That’s a powerful reminder that soft skills don’t become obsolete – they become your competitive advantage when everyone else is focused purely on technical mastery. In an AI world where technical tasks get automated, human skills like communication and adaptability might be the last things standing.
Where manufacturing is headed
Looking ahead, Moore’s vision of AI becoming more user-friendly and cost-effective feels inevitable but still revolutionary. We’re talking about small to mid-sized manufacturers suddenly having access to tools that could transform their entire operation. Earlier defect detection means less waste. Smarter systems mean better quality. And empowered teams mean more meaningful work.
The real challenge won’t be technical – it’ll be cultural. As Moore points out, the biggest myth is that automation replaces people. In reality, the companies that succeed will be the ones that view technology as augmentation rather than replacement. They’ll focus on making work safer, more efficient, and frankly, more human. That’s a future worth building toward, whether you come from engineering, languages, or anywhere in between.
