Artificial intelligence is increasingly becoming a routine part of how women‑led businesses operate, according to new data from Network Ireland released ahead of its national International Women’s Day event at the Limerick Strand Hotel this Saturday.
The survey of 1,400 members of the country’s largest business networking organisation for women shows that 68% of respondents now use AI in some form, most commonly in marketing, finance or HR. The trend is set to continue, with 72% planning to increase their use of the technology this year, despite two out of three respondents saying they are worried about regulatory or ethical issues linked to AI.
Rising operational pressures are also evident. 76% say costs have increased this year, driven primarily by labour (32%), energy (17%), taxation/compliance (15%), supply‑chain input (13%), insurance (4%) and commercial rates (3%).
Inflation pressures (38%) remain the biggest risk for 2026, followed by a domestic economic slowdown (29%), global instability (21%) and access to finance (5%). Customer demand trends are mixed, with 47% reporting stronger customer demand than in 2025, 31% saying it is unchanged and 22% reporting weaker demand.
LinkedIn and Instagram remain the most important platforms for business growth, with eight in ten business owners posting regularly. The main objectives for social media use are brand awareness (42%), lead generation (30%), community building (14%), direct sales (12%) and recruitment (2%).
Network Ireland’s International Women’s Day event will be headlined by entrepreneur and social innovator Sonya Lennon, who will join speakers from fashion, global sport and enterprise to discuss what it takes to build resilient brands in competitive markets. The programme will also explore the concept of brand wellness, ensuring that as organisations scale, the people behind them remain supported.
The event is supported by AIB, Limerick City and County Council and Enterprise Ireland. Down Syndrome Limerick, the President’s chosen charity partner, will be represented by speaker Annie Conway.
Karen Ronan, Network Ireland President and CEO of Galway Chamber, said the survey findings underline the importance of this year’s International Women’s Day theme.
“Building bridges is about creating access to opportunity, to confidence and to leadership,” she said. “Women are adapting to new technologies and new market realities at pace. Our role is to make sure they have the networks and support to grow with confidence.”
Mayor of Limerick, John Moran, commented, “International Women’s Day urges us to turn celebration into action, ensuring that equality, respect and opportunity are not aspirations, but realities for all. Network Ireland continues to champion women who lead, innovate and uplift others. I particularly want to commend Limerick native Karen Ronan for her work as President of Network Ireland, while wishing Barbara MacCarthy the very best of luck in her term as Limerick branch President throughout 2026.”
Geraldine Casey, Managing Director of Retail Banking at AIB, said, “At AIB, we believe that when women in business thrive, our communities and our economy thrive with them. International Women’s Day is a powerful reminder that progress happens when ambition is supported by access to finance, to networks and to opportunity. AIB plays a vital role in creating those connections, and we look forward to continuing to champion female entrepreneurship, leadership and sustainable growth across Ireland.”
Sarah Walker, Senior Executive, Enterprise Ireland, said, “Enterprise Ireland is focused on increasing the number of women who start, lead and grow businesses, and we are delighted to support Network Ireland in hosting this year’s International Women’s Day event. Through our investments and initiatives, including the Going for Growth, NextWave, WeBuild, WeGrow and WeScale Shared Island programmes, we aim to give women the skills, networks and funding routes they need to scale. When women succeed in business, the benefits are felt across communities and the wider economy.”
Established in 1983, Network Ireland supports more than 1,400 female entrepreneurs, SME owners and senior professionals across sectors ranging from multinational business to non-profits, the arts and the public sector. Visit networkireland.ie for more.
Computer vision is powering everything across Ireland’s fast-growing tech ecosystem, from advanced manufacturing and smart retail to fintech security. Data annotation sits at the core of these intelligence systems. Keep reading to understand how Irish tech companies are improving accuracy and accelerating model training as AI-powered annotation systems become scalable and precise.
Data Annotation Trends in Irish Tech Companies
Many Irish tech companies in the early computer vision development relied on small teams, mostly in-house, to label videos and images manually. These processes were inconsistent, slow and expensive, especially during scaling or when datasets reach the millions. Now, companies are relying on AI-powered data annotation to reshape their workflow. By combining human validation with automated pre-labelling, providers like theoWorkers team offer support in handling large-scale datasets with great precision and speed. This is a hybrid approach that allows both established businesses and startups to train their vision models with great efficiency without compromising quality.
Data annotation plays an essential role in system training, since even the most sophisticated AI model is as accurate as the data it trains from. Irish companies are taking advantage of well-annotated datasets for different sectors like retail analytics, fintech, health tech and smart cities to power fraud prevention, facial recognition, predictive maintenance and object detection. AI-powered tools are gaining popularity since they reduce human errors, speed up turnaround and guarantee consistent labelling standards across different projects. Because of that, organisations can scale their computer vision solutions confidently, improve model performance and shorten development cycles in competitive global markets.
How AI-Powered Annotation Elevates Models Accuracy
Companies cannot achieve accurate computer systems by chance; they should build them on precisely labelled data. Improving model accuracy and developing AI-driven platforms for Irish tech organisations is directly tied to the consistency and quality of annotation processes.
Machine Learning Pre-Labelling
Machine learning models are used by AI-powered annotation tools to automatically create initial labels for videos and image frames. This pre-labelling technique helps companies reduce workloads and accelerate dataset preparation. The only work annotators have is to review and refine already generated tags, segmentation masks and/or bounding boxes instead of starting from scratch. For Irish companies working under pressure, this means quicker deployment and faster iterations of computer vision solutions.
Human Validation (In the Loop)
Human experience and expertise remain vital even though automation alone speeds up workflows. Human-in-the-loop validation guarantees that any AI-generated annotation is checked for edge cases, context and nuance. Skilled reviewers in this approach handle complex scenarios, correct inaccuracies and maintain dataset consistency. This is a perfect combination of precision and speed, which results in a stronger model performance and reliable training data.
Bias Reduction and Feedback Loops
AI-assisted annotation systems “grow” over time through a well-structured feedback loop. This means that corrections made by human annotators are returned to the systems to refine future output. Because of that, companies can boost efficiency while identifying and minimising bias in datasets. Reducing bias, especially for Irish tech companies like healthcare, finance and smart cities, is vital for fairness, long-term trust and compliance.
Conclusion
AI-enhanced data annotation is taking centre stage in computer vision innovation in Ireland‘s tech companies. These organisations can develop reliable, scalable and more accurate AI systems by combining human expertise with intelligent automation.
The gap between AI adoption and teacher preparedness in Irish schools is striking. Recent research from Microsoft and 3Gem found that 83% of Irish teachers lack formal training in AI, yet 72% support increased use of AI tools in their classrooms. This disconnect leaves thousands of educators wanting to use AI but uncertain where to start. The good news: you don’t need formal certification to begin using AI tools effectively in your teaching. What you need is a practical framework, sensible boundaries, and the confidence to learn alongside your students.
Irish classrooms are already among Europe’s most digitally advanced, with Ireland’s digital education transformation positioning schools ahead of many European counterparts. Teachers already use digital technologies to improve productivity and personalise learning—87% report using digital tools to optimise classroom time. AI represents the next step in this progression, not a complete departure from existing practice.
Why Formal Training Isn’t Always Necessary
Waiting for formal AI training before using these tools means missing opportunities that benefit students right now. AI tools designed for education are increasingly intuitive, with interfaces built for users without technical backgrounds. The same teachers who learned to use interactive whiteboards, learning management systems, and video conferencing during the pandemic can learn AI tools through similar approaches: experimentation, peer support, and gradual integration.
The Microsoft research reveals an interesting pattern: schools that adopt AI quickly report less concern about training gaps than slower-adopting schools. In fast-adopting institutions, only 32% cite insufficient training as a major barrier, compared to 67% in schools slower to adopt. This suggests that hands-on experience reduces perceived training needs—teachers who start using AI tools build confidence through practice rather than waiting for formal instruction.
“Technology in education should support teachers rather than replace their expertise,” notes Michelle Connolly, founder of LearningMole and former teacher with over 15 years of classroom experience. “The best approach is starting with simple applications that solve real classroom problems, then building from there.”
Starting Points for AI in Irish Classrooms
The most effective entry point for AI in teaching isn’t the most sophisticated application—it’s the one that saves you time on tasks you already do. Begin with administrative and planning tasks before moving to student-facing applications.
Lesson Planning and Resource Adaptation
AI tools can generate lesson plan outlines, suggest differentiation strategies, and adapt existing resources for different ability levels. A teacher preparing a history lesson on the Great Famine might use AI to generate discussion questions at varying complexity levels, create simplified text versions for struggling readers, or suggest extension activities for advanced learners.
The key is treating AI output as a starting point rather than a finished product. Review everything, adjust for your specific class, and add the contextual knowledge only you possess about your students. AI doesn’t know that Seán struggles with reading but excels in oral discussion, or that your Third Class has particular interest in local history. You add that expertise.
Feedback and Assessment Support
Writing individualised feedback consumes enormous teacher time. AI tools can help generate initial feedback drafts that you then personalise and refine. For a set of 30 creative writing pieces, AI might identify common issues across the class, suggest specific praise points, and flag pieces needing closer attention—reducing a three-hour task to one hour of focused work.
This application works particularly well because you remain in control of final communication with students and parents. AI handles the time-consuming initial analysis while you make professional judgements about what feedback each student actually needs.
Differentiated Resource Creation
Creating multiple versions of worksheets and activities for mixed-ability classes traditionally requires significant preparation time. AI can generate variations of resources at different reading levels, with varied scaffolding, or with alternative question formats—all from a single source document.
For Irish teachers managing classes with wide ability ranges, this capability transforms planning. Instead of choosing between teaching to the middle or spending hours creating differentiated materials, you can generate appropriate resources for each ability group efficiently.
AI Tools Suitable for Irish Primary Classrooms
Not all AI tools suit educational contexts. Teachers need applications that are age-appropriate, safe for school use, and aligned with Irish educational values around child protection and data privacy.
Text-Based AI Assistants
General AI assistants like ChatGPT and Claude can support lesson planning, resource creation, and administrative tasks. These work best for teacher-facing applications rather than direct student use in primary settings. Use them to generate quiz questions, explain difficult concepts in child-friendly language, or brainstorm creative approaches to teaching challenging topics.
When using these tools, avoid inputting student names, personal information, or sensitive data. Frame requests around general classroom scenarios rather than specific children.
Educational Platforms with Built-In AI
Some educational resource platforms now incorporate AI to personalise learning pathways and provide adaptive practice. LearningMole offers curriculum-aligned video content and teaching resources that teachers can use to supplement AI-assisted planning, providing quality-assured materials that work alongside AI tools.
These platforms offer safer environments for student interaction because they’re designed with educational safeguarding in mind. Content is curated, age-appropriate, and aligned with curriculum expectations.
Image and Presentation Tools
AI image generators can create custom illustrations for teaching materials, though teachers should review all output for appropriateness. Presentation tools with AI features can help structure content logically and suggest visual improvements.
For Irish teachers, these tools prove particularly useful for creating materials with local relevance—images depicting Irish landscapes, historical scenes, or cultural contexts that generic stock imagery often misses.
Practical Implementation Framework
Moving from occasional AI experimentation to systematic integration requires a structured approach. This framework helps teachers build AI use gradually without overwhelming themselves or their students.
Week One: Personal Productivity
Start with applications that don’t involve students at all. Use AI to draft parent communications, generate meeting agendas, or summarise long documents. This builds familiarity with AI interaction patterns—how to phrase requests effectively, how to evaluate output, how to iterate toward better results.
Keep a simple log of what works and what doesn’t. Note which types of requests produce useful output and which need significant revision. This personal experience base informs later classroom applications.
Weeks Two and Three: Planning Support
Expand to lesson planning support. Use AI to generate activity ideas, discussion questions, or assessment criteria. Compare AI suggestions against your professional judgement and existing resources. You’ll quickly identify where AI adds value and where it falls short for your specific teaching context.
Try having AI adapt existing resources for different ability levels. Take a worksheet you’ve used successfully and ask for simplified and extended versions. Evaluate whether these adaptations actually suit your students’ needs.
Week Four and Beyond: Selective Student Applications
Only after building personal confidence should you consider student-facing applications. Start with highly structured uses where you control the interaction—perhaps displaying AI-generated discussion prompts or using AI-created differentiated materials.
For older primary students, supervised AI use might include generating research questions, creating writing prompts, or exploring “what if” scenarios in history or science. Always preview AI outputs before student exposure and frame AI as a tool that makes mistakes, requiring critical evaluation.
Addressing Common Concerns
Teachers hesitating to use AI often cite specific concerns that, once addressed, become manageable rather than prohibitive.
Data Protection and Privacy
Irish schools operate under GDPR and specific DES guidance on data protection. AI tools raise legitimate questions about where data goes and how it’s used. The practical response: never input personal student data, names, or identifying information into AI tools. Frame all requests around anonymous, general classroom scenarios.
For teacher-facing applications, this restriction rarely limits usefulness. You can ask AI to help plan a lesson on fractions without mentioning any student names. You can generate differentiated resources for “a mixed-ability Third Class” without identifying specific children.
Academic Integrity
Concerns about students using AI to complete work dishonestly require age-appropriate responses. In primary settings, direct AI misuse is less common than in secondary and higher education. Focus instead on building critical evaluation skills—teaching children that AI can be wrong, that it doesn’t understand context, and that human judgement matters.
When students do use AI-supported tools, frame this as appropriate use of available technology rather than cheating. The goal is developing skills to work effectively with AI, not pretending it doesn’t exist.
AI tools produce confident-sounding output that may contain errors, outdated information, or cultural assumptions that don’t fit Irish contexts. Teachers must review all AI-generated content before use, just as they would review any external resource.
This requirement isn’t unique to AI—textbooks contain errors, websites become outdated, and imported resources assume different educational systems. The teacher’s professional role includes evaluating and adapting all materials, regardless of source.
Over-Reliance
Some teachers worry that AI will deskill the profession or make teaching impersonal. The opposite proves true when AI is used appropriately: by reducing time on administrative tasks, AI frees teachers to focus on the relational, creative, and responsive aspects of teaching that no technology can replicate.
AI cannot read the mood of a classroom, notice that a child seems withdrawn, or adjust a lesson because the energy is different today. These human skills become more valuable, not less, as AI handles routine tasks.
Building Confidence Through Peer Learning
Formal training programmes exist—the Microsoft Dream Space Teacher Academy offers free AI skills development for Irish teachers—but peer learning often proves more immediately useful. Teachers learn best from colleagues who’ve solved similar problems in similar contexts.
Staffroom Sharing
Informal conversations about AI successes and failures accelerate collective learning. When one teacher discovers an effective way to use AI for report writing, sharing that approach benefits the whole staff. Schools might designate brief time in staff meetings for AI tool sharing, creating space for practical exchange without requiring extensive formal development.
School-Based Champions
Some teachers naturally embrace new technologies and can support colleagues’ learning. Without creating additional workload, schools might recognise these informal champions and create opportunities for them to share expertise. A ten-minute demonstration of AI-assisted planning might inspire colleagues to experiment independently.
Online Communities
Irish teacher communities on social media and professional networks increasingly discuss AI applications. These spaces offer access to broader experience than any single school provides, with teachers sharing specific prompts, workflows, and cautionary tales from their own practice.
Curriculum Connections
AI integration works best when aligned with existing curriculum goals rather than added as separate technology instruction. The Irish Primary Curriculum’s emphasis on skills development provides natural connections.
Critical Thinking
Evaluating AI output develops critical thinking skills explicitly valued in the curriculum. When students assess whether an AI-generated text is accurate, well-written, or appropriate, they practice analysis and evaluation skills transferable across subjects.
Communication
Using AI effectively requires clear communication—precise requests produce better output. Students learning to interact with AI develop skills in clarity, specificity, and iterative refinement that support writing and speaking development.
Creativity
AI tools can support creative work by generating starting points, suggesting alternatives, or providing constraints that spark imagination. A student stuck on a story opening might use AI-generated prompts as inspiration while maintaining ownership of their creative choices.
The Role of Quality Teaching Resources
AI tools work best alongside high-quality teaching resources rather than replacing them. AI can generate rough content quickly, but polished, curriculum-aligned, pedagogically sound resources require human expertise and careful development.
Platforms offering structured educational content complement AI tools by providing reliable starting points that AI can help adapt and extend. When planning a science unit, a teacher might use video resources from established educational platforms for core instruction, then use AI to generate extension activities, differentiated worksheets, and assessment questions aligned with that content.
This combination—curated resources for core content, AI for adaptation and extension—offers efficiency without sacrificing quality. Teachers maintain professional control over what students learn while reducing time spent on routine resource creation.
Moving Forward Responsibly
AI in Irish education will continue developing regardless of individual teachers’ choices. The question isn’t whether to engage with AI but how to do so in ways that benefit students while maintaining professional standards and educational values.
Starting small, maintaining critical oversight, and building gradually from personal productivity to classroom application provides a manageable pathway. Teachers who begin this journey now, even without formal training, position themselves and their students well for an educational landscape where AI literacy becomes increasingly expected.
The 83% of Irish teachers lacking formal AI training aren’t failing—they’re facing a professional development system that hasn’t kept pace with technological change. By taking initiative to learn through practice, these teachers demonstrate exactly the adaptability and commitment to improvement that makes Irish education strong.
Frequently Asked Questions
Do I need formal AI training before using AI tools in my classroom? No. Many AI tools are designed for users without technical backgrounds. Start with simple applications for personal productivity, build familiarity through practice, and expand gradually. Hands-on experience often reduces perceived training needs more effectively than formal courses.
What AI tools are safe for use in Irish primary schools? Teacher-facing tools like ChatGPT and Claude work well for planning and resource creation when you avoid inputting student personal data. Educational platforms with built-in AI features designed for school use offer safer options for student-facing applications, as they’re built with appropriate safeguards.
How can I use AI without compromising student data protection? Never input student names, personal information, or identifying details into AI tools. Frame all requests around anonymous, general scenarios. For example, ask for resources suitable for “a mixed-ability Third Class” rather than naming specific children or their characteristics.
Will using AI make me a less effective teacher? Used appropriately, AI makes teachers more effective by handling routine tasks and freeing time for the relational, creative, and responsive work that defines excellent teaching. AI cannot replace professional judgement, classroom presence, or understanding of individual students.
How do I evaluate whether AI-generated content is suitable for my classroom? Review all AI output before use, checking for accuracy, age-appropriateness, and alignment with Irish curriculum expectations. Apply the same critical evaluation you’d use for any external resource. AI content is a starting point for professional refinement, not a finished product.
What’s the best way to start using AI as a teacher? Begin with personal productivity tasks that don’t involve students: drafting communications, generating meeting agendas, or summarising documents. Build familiarity with AI interaction patterns before moving to planning support and eventually selective student-facing applications.
Conclusion
Irish teachers don’t need to wait for formal training to begin benefiting from AI tools. The practical framework outlined here—starting with personal productivity, expanding to planning support, and eventually incorporating selective student applications—provides a manageable path for any teacher willing to experiment and learn.
The gap between AI enthusiasm and training provision in Irish education creates an opportunity for teachers to lead their own professional development. By engaging thoughtfully with AI tools now, building critical evaluation skills, and maintaining focus on educational values, teachers prepare themselves and their students for an educational future where AI literacy matters increasingly.
Quality teaching resources, professional judgement, and human relationships remain at the heart of excellent education. AI tools enhance rather than replace these fundamentals—when used by teachers confident enough to experiment, critical enough to evaluate, and focused enough to keep student benefit central to every decision.
A Growing Number of Business Decisions Now Start With an AI Query – Not a Google Search
Something fundamental has shifted in how businesses and consumers find service providers. When a procurement manager needs to shortlist software vendors, when a marketing director researches agency options, when a business owner looks for specialist expertise – increasingly, the first question goes to an AI assistant rather than a search engine.
ChatGPT, Google’s AI Overviews, Perplexity, Microsoft Copilot – these tools now handle a growing proportion of “who should I hire?” and “which company should I use?” queries. The businesses appearing in those AI-generated answers get considered. Those invisible to AI don’t even know they’ve been excluded from the conversation.
ProfileTree, the Belfast-based digital agency that works with tech companies across Ireland and the UK, has been tracking this shift since AI search tools gained mainstream adoption. The pattern emerging is clear: Irish tech companies with strong products and genuine expertise are losing visibility to competitors who’ve adapted their digital presence for how AI systems evaluate and recommend businesses.
This isn’t a distant future concern. It’s happening now, and most Irish tech companies haven’t recognised the shift – let alone responded to it.
The Shift from Rankings to Recommendations
Traditional search worked on a simple model: optimise your website, build backlinks, rank higher, get more clicks. Companies invested in SEO, achieved good rankings for target keywords, and generated steady organic traffic. This model still functions – but it’s no longer the complete picture.
AI recommendation operates differently. When someone asks an AI assistant “Who are the best cybersecurity firms in Ireland?” or “Which agencies handle B2B tech PR in Dublin?”, the AI doesn’t return a list of ten blue links to evaluate. It synthesises information from across the web and recommends two or three companies it deems most credible – often explaining its reasoning.
The implications are significant. In traditional search, appearing on page one meant visibility alongside nine competitors. In AI recommendation, appearing at all often means being one of just a handful of mentioned options. And not appearing means complete exclusion – prospects never learn your company exists.
Gartner and other analyst firms have projected that up to 25% of organic search traffic could migrate to AI-powered interfaces in the coming years. For B2B tech companies, where purchase decisions often begin with research queries, the shift may be more pronounced.
Why Strong SEO Doesn’t Guarantee AI Visibility
Irish tech companies that invested heavily in SEO over the past decade often assume those efforts protect them. They rank well for target keywords, generate steady organic traffic, and see their brand appear in traditional search results. This creates dangerous complacency.
AI recommendation rewards different signals than traditional SEO. Search engine optimisation focuses on technical factors, backlink profiles, and keyword targeting. AI recommendation focuses on clarity, consistency, credibility signals, and the breadth of your digital footprint across multiple sources.
A company might rank first on Google for “Dublin fintech development” through solid SEO work, yet never appear when someone asks ChatGPT the same question. The AI isn’t simply replicating Google’s rankings – it’s forming its own assessment of which companies are credible enough to recommend based on information synthesised from across the web.
This explains an emerging pattern: established players with strong SEO being overlooked while smaller competitors with clearer digital positioning appear in AI recommendations. The smaller company might have inferior backlink profiles but superior clarity – consistent descriptions everywhere, reviews on multiple platforms, clear statements of expertise. AI systems find them easier to understand and trust.
The pattern parallels other marketing blind spots in Irish tech. As explored in TechBuzz Ireland’s analysis of why Irish tech companies are failing at sustainability marketing, the sector repeatedly demonstrates strong operational capabilities but poor communication of those capabilities. AI visibility is the latest manifestation: companies doing excellent work that AI systems can’t identify or recommend because the digital signals are missing or muddled.
Clarity of identity and offering. AI systems need to understand precisely what a company does, who it serves, and where it operates. Vague descriptions like “innovative technology solutions” or “digital transformation partner” give AI nothing concrete to work with. Specific statements – “enterprise software development for financial services companies across Ireland and the UK” – are far more useful for AI trying to match queries to recommendations.
Consistency across sources. AI cross-references multiple sources when assessing a business. If your website describes you as a “software development agency,” your LinkedIn says “technology consultancy,” and your Google Business Profile lists “IT services,” the inconsistency reduces AI confidence. Companies with identical core descriptions across every platform signal reliability.
Third-party validation. AI systems weight independent sources heavily. Review profiles on platforms like Trustpilot, Google, Clutch, and industry platforms create external validation AI can reference. Press coverage, industry awards, directory listings, and professional body memberships all contribute. Companies relying solely on their own website claims lack the corroborating evidence AI needs to recommend with confidence.
Breadth of digital presence. Appearing across multiple credible platforms – industry directories, review sites, professional networks, local business listings – creates the distributed footprint AI trusts. A company with strong presence only on their own website appears less established than one appearing consistently across relevant platforms.
Specificity of proof. AI favours concrete, verifiable information over vague claims. Statements like “12 years in operation,” “worked with over 1,000 clients,” or “5-star rating across 450 reviews” give AI something to reference confidently. “Extensive experience” and “trusted by many clients” cannot be verified or cited.
ProfileTree, for example, has built the kind of distributed digital presence AI systems can assess: founded in 2011, over 450 five-star reviews on Google, 60+ five-star reviews on Trustpilot, presence on industry platforms, and consistent service descriptions across sources. These signals create the clarity AI needs when recommending digital agencies for Belfast and Northern Ireland queries.
The Sectors Facing Greatest Risk
Certain Irish tech sectors face disproportionate exposure to AI invisibility.
B2B SaaS companies depend on being discovered during research phases of purchasing decisions. When procurement teams and department heads increasingly use AI assistants for initial research, companies invisible to AI miss the shortlist entirely. Unlike consumer products where existing brand awareness might carry through, B2B tech purchases often begin with open-ended queries where AI invisibility can be fatal.
Professional services firms – consultancies, development agencies, managed service providers – compete in categories where AI recommendations carry particular weight. Queries like “best IT consultancies in Dublin” or “top software development agencies in Ireland” produce AI answers that directly influence which companies get contacted.
Emerging technology specialists in AI, cybersecurity, fintech, and medtech face intense competition where differentiation matters. These sectors attract new entrants constantly, and AI systems may recommend newer companies with clearer digital positioning over established players with stronger track records but weaker digital signals.
Regional tech companies outside Dublin face compounded challenges. AI systems drawing on web-wide data may default to Dublin-centric recommendations unless companies in Cork, Galway, Limerick, and elsewhere have explicitly clear geographic signals. A Galway software company with ambiguous location information might never appear in “tech companies in the West of Ireland” queries.
The Measurement Problem
Most Irish tech companies can’t quantify their AI visibility because they’ve never measured it. Traditional analytics track website visits, keyword rankings, and conversion rates – none of which capture whether you’re being recommended by AI assistants.
This measurement gap allows the problem to grow undetected. Companies continue investing in SEO and paid advertising while a growing channel – AI recommendation – delivers enquiries to competitors. Without tracking, the lost opportunities remain invisible.
Basic measurement requires regularly testing how AI systems respond to queries your customers might ask. What happens when you ask ChatGPT, Perplexity, or Google’s AI Overview “Who are the best [your category] companies in Ireland?” Does your company appear? How is it described? Which competitors show up instead?
Companies that conduct these audits often discover uncomfortable gaps between their perceived market position and their AI visibility. Testing takes minutes and costs nothing – yet most companies have never done it.
What’s Actually Required
Fixing AI invisibility isn’t about gaming algorithms or implementing quick tricks. It requires fundamental clarity about how you present your business across the digital landscape.
Audit your current state. Test AI responses to relevant queries. Document where you appear and where you don’t. Identify competitors who appear when you don’t and analyse what makes their digital presence more AI-friendly.
Establish consistent identity. Ensure your business name, description, location, and service offerings are identical across your website, Google Business Profile, LinkedIn, industry directories, and every other platform where you appear. Eliminate variations that create confusion.
Build distributed credibility. Develop presence across relevant platforms beyond your website. Industry directories, review sites, professional networks, local business listings, and sector-specific platforms all contribute to the breadth of footprint AI systems evaluate.
Accumulate third-party validation. Systematically build reviews across multiple platforms – not just Google. Pursue press coverage, industry recognition, and directory inclusions that create independent corroboration of your credibility.
Create AI-friendly content. Ensure your website contains clear, specific, factual statements about your expertise, experience, and credentials. AI systems need quotable information they can reference with confidence. Marketing language designed to sound impressive but say little gives AI nothing useful to work with.
Maintain and update. AI systems favour current information. Outdated content, old team information, and stale descriptions signal neglect. Regular updates demonstrate active, credible operation.
The Window of Opportunity
The current period represents an unusual opportunity for Irish tech companies willing to adapt quickly. AI search is growing but hasn’t yet become universal. Most competitors haven’t recognised the shift or taken action. Companies that establish strong AI visibility now build advantage before the market catches up.
This mirrors patterns from early SEO adoption. Companies that invested in search optimisation in the early 2000s built positions that later entrants struggled to displace. AI visibility may follow similar dynamics – early movers establishing presence that becomes difficult for latecomers to challenge.
The risk of inaction compounds over time. As AI assistants become more prevalent, the proportion of opportunities influenced by AI recommendations grows. Companies invisible to AI today lose a small percentage of potential business; the same companies invisible to AI in two years may lose dramatically more.
Ciaran Connolly, founder of ProfileTree, puts it directly: “Irish tech companies have spent years building products, expertise, and reputations that genuinely deserve recognition. The frustration is watching them miss opportunities because AI systems can’t find or understand them. AI visibility isn’t about being the best – it’s about being clear enough that AI can see what you offer.”
The Broader Context
AI invisibility connects to broader challenges in how Irish tech companies communicate their value. Strong operational capabilities paired with weak external communication is a recurring pattern – evident in sustainability marketing challenges, employer branding struggles, and now AI search visibility.
The common thread is a gap between what companies actually do and what the outside world – including AI systems – can perceive and understand. Closing that gap requires treating external communication with the same rigour applied to product development and operations.
For Irish tech companies, the immediate priority is clear: assess your current AI visibility, identify gaps, and begin building the digital presence that AI systems can understand and trust. The companies taking action now will capture opportunities; those waiting will wonder why enquiries are going elsewhere.
Frequently Asked Questions
How do I check if my company appears in AI recommendations?
Test the AI assistants your customers might use – ChatGPT, Google’s AI Overview, Perplexity, Microsoft Copilot. Ask questions like “Who are the best [your service] companies in Ireland?” or “Which [your category] providers should I consider in [your city]?” Note whether you appear, how you’re described, and which competitors are recommended instead. Repeat monthly to track changes.
Does Google ranking still matter if AI is becoming important?
Traditional Google rankings still matter significantly – AI hasn’t replaced conventional search, and won’t entirely. However, AI recommendation is growing as an additional channel. Companies need both: strong SEO for traditional search visibility and clear digital presence for AI recommendation. The clarity that helps AI visibility often improves traditional SEO performance too.
How long does it take to improve AI visibility?
Meaningful improvement typically takes three to six months of consistent effort. Some elements – fixing inconsistencies, updating content – can be addressed quickly. Others – building reviews, accumulating press coverage, establishing directory presence – require sustained activity over time.
Is this relevant for smaller companies or mainly large enterprises?
AI visibility may actually benefit smaller companies more than large ones. AI systems don’t automatically favour market leaders – they favour clarity and credibility signals. A focused smaller company with clear positioning, strong reviews, and consistent presence can appear in AI recommendations ahead of larger competitors with muddled digital footprints.
What’s the single most important thing to fix first?
Consistency. Ensure your business description, services, and location are identical across your website, Google Business Profile, LinkedIn, and any directories where you appear. Inconsistencies are a common reason AI systems lack confidence to recommend businesses. This fix requires no budget – just attention to detail across platforms you already control.
ProfileTree is a Belfast-based digital agency working with tech companies across Ireland and the UK on web design, SEO, content strategy, and AI visibility. The agency holds 60+ five-star reviews on Trustpilot and over 450 five-star reviews on Google, demonstrating the distributed review presence that influences AI recommendation.
AI-powered visuals are reshaping how songs come to life on screen. A few clicks can now do the work of an entire film crew. Analysts value the generative-AI-in-music market at about $643 million in 2024 and project it to top $3 billion by 2030, a 29% yearly climb. With that growth comes an overcrowded toolbox, so we spent three weeks pressure-testing 18 platforms and ranked the seven that deliver the best results for your budget and your audience.
How We Picked The Winners
We didn’t rely on flashy promo reels or influencer hype. We spent three solid weeks hammer-testing every major AI music-video platform we could access, 18 tools in total, then scored each one on six make-or-break factors.
Visual quality came first. If footage looked blurry, glitchy, or flat, it was out. A music video should turn heads, not spark a Reddit roast.
Next was synchronization. A clever algorithm that hits the downbeat is worth more than a thousand stock clips. We checked whether each tool sensed tempo shifts, verse breaks, and subtle vocal swells.
Neuralframes.com is a prime example.
According to Neural Frames’ ai music video generator Autopilot page, a three-minute song renders in about five minutes while the engine locks every cut to the track’s kicks, snares, and vocal peaks using audio-reactive keyframes.
That real-time sync became our benchmark during testing, and the free 20-credit sandbox lets you verify the precision before opening your wallet.
Ease of use mattered. You deserve speed, not a night class in node-based compositing, so clear menus and one-click workflows earned big points.
Feature depth followed. Can you storyboard multiple scenes, swap models mid-track, and export vertical plus widescreen in the same session? The richer the toolbox, the higher the score.
Speed and stability sat close behind. We timed every render and noted crashes. If a platform stalled longer than the song itself, we docked it.
Finally, we checked pricing and rights. Transparent plans, fair credit models, and clear commercial licenses separated serious players from quick cash grabs.
Each factor carried its own weight, yet visual polish and beat accuracy led the pack. After testing, only seven tools cleared our high bar, and together they cover creative needs from rooftop lyric videos to cyberpunk epics.
Scan The Field At A Glance
Before we explore each platform, here’s the overview.
Spend thirty seconds with the scorecard below and you’ll see which tools meet your top priorities, whether that is razor-sharp 4K footage, one-click beat-sync, or a price that keeps the merch budget intact.
Tool
Visual punch
Beat accuracy
Ease of use
Creative control
Render speed
Value
Neural Frames
★★★★☆
★★★★★
★★★☆☆
★★★★☆
★★★★☆
★★★★★
LTX Studio
★★★★★
★★★☆☆
★★☆☆☆
★★★★★
★★★☆☆
★★★☆☆
Runway ML
★★★★★
★★☆☆☆
★★☆☆☆
★★★★☆
★★★☆☆
★★☆☆☆
Kaiber
★★★★☆
★★★★☆
★★★★☆
★★★☆☆
★★★★☆
★★★☆☆
Revid AI
★★★☆☆
★★★★☆
★★★★★
★★☆☆☆
★★★★★
★★★★★
PlazmaPunk
★★★★☆
★★★★☆
★★☆☆☆
★★★★★
★★★☆☆
★★★★☆
Shai Creative
★★★☆☆
★★★★★
★★★★☆
★★★☆☆
★★★★★
★★★★☆
Stars compare the tools within this list, not the entire industry. Treat them as pointers to each platform’s strongest lanes and skip what you don’t need.
1. Neural Frames: Autopilot Videos That Hit Every Beat
Imagine handing your song to an editor who instantly feels its groove, slices footage to every snare, and nails the drop without a single note from you. That is Neural Frames, an ai music video generator that nails the drop without a single note from you.
Upload the track, choose Autopilot, and the engine dissects tempo, stems, and emotional contour. In about the time it takes to refill your mug, you get a full-length video whose cuts land right on the one.
Prefer more control? Switch to the timeline view. Your waveform appears like a DAW session. Drag markers, assign fresh prompts to choruses, swap visual models on the bridge, and let the system handle the transitions.
Neural Frames Autopilot and beat-synced timeline interface screenshot.
Quality matches creativity. Multiple backend models, such as Runway Gen-3 and custom Stable Diffusion forks, render up to true 4K. Character-consistency tools carry a logo or mascot from verse to verse, so branding never wanders.
Plans start at $19 a month, with a free 20-credit sandbox to test the waters. Credits roll over, so if you start on the starter plan at Neuralframes.com, you can carry unused minutes into the next month. For musicians who want pro-level sync without touching a timeline, Neural Frames is a reliable set-and-forget option.
2. Ltx Studio: Cinematic Control Without The Crew
If your song needs a mini-movie, LTX Studio is the place to start.
You storyboard in plain language. “Neon skyline at dusk, singer on a rooftop.” The platform turns that line into a fully lit, camera-tracked shot. Add another prompt and it builds the next scene while keeping characters and colors consistent.
Quality stands out. Footage lands in true 4K, faces stay consistent, and even wind-whipped hair looks natural. Because you adjust camera angles, lighting, and pacing inside the browser, the process feels closer to directing than prompting.
Expect a learning curve. You pay with “compute seconds,” and early sessions vanish quickly while you experiment. Once you find a groove, a one-minute concept video can finish in less time than it takes to brew coffee.
Pricing starts at $15 a month with a free trial. That tier covers personal releases, so indie artists can drop a film-grade clip on day one without draining the gas fund.
3. Runway Ml: The Vfx Playground In Your Browser
Runway feels less like an app and more like a box of cinematic superpowers.
Fire up Gen-3 or Gen-4, type “slow-motion rain on neon streets,” and 10 seconds of moody footage appears. Want something wilder? Feed the same clip into Motion Brush and paint movement onto a static skyline. Effects that once needed a blockbuster budget now sit in your browser.
Runway ML Gen-3 and Motion Brush VFX editor screenshot.
Because each generation tops out at about 10 seconds, you stitch clips on the built-in timeline. That extra step rewards planners: map chorus hits to new prompts, fade bridges with soft bokeh, and your 3 minute video snaps together like Lego.
Runway does not auto-sync. You drag clips until snare drums land on clean cuts, just like in Premiere. Editors enjoy that freedom. Newcomers may groan, yet the payoff is precision.
Credits power everything. The starter plan supplies enough to create a 30 second teaser in 4K. Bigger visions call for tiers of $15 and up, or single credit packs. Even a long night on Runway costs less than renting one fog machine.
4. Kaiber: Art-School Flair At Streaming Speed
Kaiber doesn’t just animate your song; it turns it into a moving canvas.
Drop an image, paste a prompt, and the platform breathes life into the artwork, timing scene flips to kick drums and vocal peaks. Picture watercolor wolves dissolving into cosmic dust on the bass drop. Most renders finish before the chorus ends.
Three modes keep sessions fresh: Flipbook adds hand-drawn jitter, Motion provides smooth pans and zooms, and Transform remolds existing footage into bold new styles. The new Storyboard feature chains prompts, so entire verses evolve instead of looping five-second segments.
Exploration costs $29 a month because there is no permanent free tier. The upside is unlimited experimentation within your credit pool, with no daily caps or watermarks. For visual originality per dollar, Kaiber delivers strong value.
The tool is not surgical. You can nudge intensity or color but cannot fine-tune every frame. Embrace the spontaneous brushstrokes, and you will leave with videos vibrant enough for a Spotify Canvas or a full stage backdrop.
5. Revid Ai: Social-Ready Videos In One Coffee Break
Need a vertical clip for tomorrow’s release blitz? Revid is the fastest option in this group.
Drop your song, pick a vibe—bright pop, gritty noir, glitchcore—and the engine assembles stock footage, AI loops, and kinetic text, all sliced to tempo and syllable. Verse lines flash as you sing them, and hooks land right on the beat.
Revid AI vertical social video templates and kinetic text editor screenshot.
Because templates drive the experience, results look polished from the first render. Adjust a color accent, swap a clip, then export. Most projects finish in under two minutes, with no watermark on the paid tier.
Visual depth is lighter than the artsier tools above. Think polished TikTok, not Blade Runner. For teaser trailers, lyric shorts, and sponsor shout-outs, Revid meets the brief.
Pricing starts with a free tier, but HD downloads live behind a $19 monthly plan. That fee undercuts a freelance editor and unlocks unlimited, no-queue exports, ideal for artists who post content as often as they release singles.
6. Plazmapunk: Open-Source Power For The Mad Scientist
PlazmaPunk feels like stepping into a secret lab where every knob invites a twist.
The app listens to your track, maps peaks and lulls, then routes those pulses through open-source models such as SDXL and Kandinsky. You decide which model drives each section, how color histograms carry over, and the exact prompt switch at bar 64.
Daily generation limits keep GPU bills sane. The free tier grants 20 seconds. €5 buys a full minute each day, and €12 buys five. Because seconds reset at midnight, you iterate in steady bursts instead of burning through credits overnight.
Outputs lean experimental: ideal for live VJ loops, psychedelic interludes, or any genre that thrives on visual chaos. If you need polished narrative, look elsewhere. If your brand celebrates glitch art, chromatic melt, and happy accidents, PlazmaPunk is your playground.
Developers take note: an API lets you auto-generate visuals for an entire catalog. Imagine every back-catalog track receiving beat-synced art while you sleep. That is the kind of tinkering this punk lab was built for.
7. Shai Creative: Lyric-First Visuals For Storytellers
Some songs live and die by their words, and Shai turns those syllables into storyboards before adding motion to every line.
Paste your lyrics or let the platform auto-transcribe. In seconds, it generates a reel of AI-illustrated frames, each aligned to its timestamp. The process feels as if a director mapped your entire narrative overnight.
Select “Animate” and the stills gain gentle pans, zooms, and light particle movement. Captions arrive pre-synced, so a polished lyric video sits one export away. If a frame misses the mood, tweak the prompt and regenerate only that slice—no need to redo the whole song.
Resolution tops out at 1080p on the $9 plan, which also adds vertical and square formats for Shorts and Reels. Character consistency can wobble on longer stories, yet for single-verse videos or social snippets, the subtle shifts add charm rather than chaos.
Bottom line: if your lyrics deserve a spotlight, Shai gives them a stage without demanding an editing degree.
Rights, Licensing, And Platform Policies
Great visuals mean nothing if you cannot legally post them.
Most AI video platforms now grant full commercial rights to your downloads as long as you own the underlying music. Read the fine print before you hit upload, especially if you plan to run ads or sell the video as an NFT.
Platform rules matter too. On July 18, 2025, YouTube announced that it would demonetize “inauthentic, repetitive” AI uploads that flood the feed. Artist-driven clips remain safe, but spammy loops risk yellow-dollar status. Keep edits fresh and add human touches such as captions, b-roll, or behind-the-scenes footage to stay compliant.
Copyright law is catching up as well. An August 2025 report from the U.S. Copyright Office confirmed that AI-assisted works qualify for protection when meaningful human input exists. Your prompt choices, scene edits, and color tweaks count, so document your process and save drafts in case of disputes.
Bottom line: own your audio, choose tools with clear licenses, and avoid low-effort spam. Do that and your AI video can stream, sell, and scale without legal headaches.
Choose The Right Tool For Your Next Release
Start with the outcome.
If you crave cinematic storytelling and have time to tweak, LTX or Runway will reward your patience with frame-perfect drama.
Need trippy art that drops tomorrow? Spin up Kaiber and let Autopilot ride the beat.
Want a full-length video in minutes, synced tighter than a session drummer? Neural Frames is the fast lane.
If social speed matters most, think vertical teasers or daily Reels; Revid edits itself while you refill the coffee.
Tinkerers and live-show VJs should keep PlazmaPunk in their back pocket for nightly experiments, while lyric-focused writers will find Shai’s storyboard flow tough to top.
Match your priority, whether quality, speed, narrative, or price, to the column that shines in our table. Pick one platform and dive deep. Mastery of a single tool outperforms dabbling in five. Your audience will notice the focus.
New research from Indeed shows that one in ten (11%) job postings in Ireland mention AI, leading ahead of the US, UK, France and Germany. This trend is reflective of the tech sector’s sizable footprint in the Irish economy.
Job postings which mention AI are most frequently seen in tech-related categories, led by data & analytics (56%). That’s followed by software development (48%), IT systems & solutions (37%) and IT infrastructure, operations & support (29%). However, several non-tech categories also have significant shares of AI postings, including arts & entertainment (24%), human resources (20%) and sales (19%).
The research also shows that remote and hybrid work mentions have reached a new high of 19.4% by the end of December 2025 – more than four times higher than pre-pandemic levels. The occupations with the highest share of remote or hybrid mentions include software development (47%), media & communications (44%) and data & analytics (43%).
Indeed’s report shows that while job postings in Ireland are well down from peaks seen in early 2022, they still remain 7% above their pre-pandemic baseline as of January 2026. The level of postings has also remained relatively stable since May.
Other key findings in the report include:
Salary transparency growth has stalled: The share of Irish job postings which include salary information has dipped recently to around 34%, its lowest since late-2022. The report highlights how the Irish Government’s transposing of incoming EU legislation will result in increased transparency.
Benefit offerings have levelled off: The share of Irish job postings mentioning at least one benefit has levelled off over the past 18 months, after rising steadily since 2018. Standing at 48% in November, the share was unchanged from its level in May 2024.
Foreign interest in Irish jobs remains high: The Irish labour market remains attractive to foreign workers. On average in 2025, around 13% of searches for Irish jobs on Indeed originated outside Ireland. That was broadly in line with 2024 and higher than seen in recent years since at least 2017.
Posted wage growth remains solid: Tight labour-market conditions continue to translate into strong pay pressures in Ireland. At 4.1% in December (on a three-month average basis), wage growth as measured by theIndeed Wage Tracker remains well above the euro area average (2.5%).
Commenting on the report, Jack Kennedy, senior economist at Indeed, said:
“Ireland enters 2026 with the economy in good shape. Growth is set to slow slightly after a strong 2025, but lower interest rates and continued government spending mean the outlook remains broadly positive: jobs are still being created, unemployment remains low, but pay pressures haven’t gone away. For workers and employers alike, this year’s labour market story is one of ongoing change and adaptability.
For jobseekers, AI is rapidly reshaping how work gets done, with a clear expectation emerging for workers across all sectors to be comfortable using AI tools, even in roles that aren’t traditionally tech-focused. Those who adapt to these skills will have a competitive edge, as employers increasingly seek ways to integrate AI into their processes.
From an employer perspective, hybrid and flexible working have moved from a perk to an expectation in 2026, and they will need to keep this in mind when recruiting. The organisations that will stand out will be those offering not just competitive salaries, but transparency, flexibility and support for employees navigating a rapidly changing work environment.”
Kerry is to showcase the latest science underpinning advances in sustainable nutrition at this year’s Stripe Young Scientist & Technology Exhibition.
The company, a global leader in specialist ingredients for the food and beverage sector, is a Silver Sponsor of the event and will present the Kerry Sustainable Nutrition Award, recognising outstanding student projects that demonstrate scientific innovation in sustainable nutrition.
From January 7–10 at the RDS, Kerry experts will be on hand to provide key insights on pressing global food challenges, from coffee and chocolate supply issues to sodium reduction and AI-driven food safety solutions.
Attendees will have a chance to step into the world of sustainable nutrition at Stand 113, where Kerry brings science to life through five interactive experiences, showing how innovation creates real-world impact for consumers and the planet.
Great taste with less salt
With global sodium intake exceeding twice the WHO recommendation, reducing salt without compromising on taste remains a significant industry challenge. Kerry will showcase how its TasteSense™ Salt technology enables up to 60% sodium reduction while maintaining flavour and food safety. Visitors can experience a live tasting demo comparing standard crisps with reduced-salt alternatives – seeing first-hand how healthier snacks can still taste great.
Improving Human Healthspan
Healthspan is about living better, not just longer – at Kerry’s stand attendees will see how science can provide dietary solutions to proactively boast wellness over a lifetime. Kerry experts will highlight science-backed solutions supporting stress reduction, immune health, gut health, and skin wellness, tailored to age and gender needs. The showcase will feature clinically validated ingredients including Sensoril® Ashwagandha, Wellmune®, BC30™, and Plenibiotic™, which support energy, resilience, and long-term wellbeing.
AI- Powered Food Safety
Unsafe food remains a global health challenge. Kerry will demonstrate how its AI-driven predictive model analyses thousands of data points to anticipate food safety risk, reduce analysis time by 80%, accelerate development by up to 10 months, and deliver safer food solutions to market, faster.
4. Cracking the Cocoa Crisis
Chocolate is a timeless favourite, but cocoa supply is under threat from crop disease, climate change, and soaring prices. Visitors will discover how Kerry’s Cocoa Boosters enable up to 50% cocoa powder reduction without compromising an indulgent taste. These solutions help manufacturers manage costs and deliver the chocolate experience consumers love, sustainably.
(Still) Getting the Caffeine Kick
Coffee lovers expect rich flavour, but roasting can create acrylamide, a potential carcinogen. Kerry’s Acrylerase® enzyme reduces acrylamide in target applications by up to 90% post-roast, without changing production processes. The result: advanced consumer health, regulatory compliance, and sustainability. Kerry’s interactive experience on this issue – close to any coffee lover’s heart – will highlight how innovation can protect both taste and wellbeing.
Catherine Keogh, Chief Corporate Affairs Officer at Kerry said: “Kerry’s partnership with the Stripe Young Scientist & Technology Exhibition is both an exciting initiative and a natural fit. Science and technology are at the heart of everything we do. From our roots in Irish dairy to leading the way in sustainable taste and nutrition, our 1,200 scientists are creating innovations that make food healthier, tastier, and more sustainable. This sponsorship is about inspiring the next generation of innovators who will tackle some of the world’s biggest food challenges.”
The Kerry Sustainable Nutrition Award aligns with Kerry’s Beyond the Horizon sustainability strategy and its ambition to deliver sustainable nutrition solutions to more than two billion people by 2030.
Core42, a G42 company specializing in sovereign cloud and AI infrastructure, today announced the establishment of its European headquarters in Dublin, Ireland. The news was shared at Investopia, the UAE’s global investment platform, which is hosting its global dialogue series in Dublin this week. The new headquarters strengthens Core42’s ability to serve European enterprises and governments seeking secure, high-performance infrastructure to scale AI adoption.
Core42 was founded in 2023 by G42 to build globally relevant infrastructure for large-scale AI. The company focuses on sovereign cloud, advanced compute platforms, and hyperscale AI environments that support production-grade AI across sectors. Core42 partners with Microsoft, NVIDIA, AMD, Cerebras, and other global ecosystem leaders to ensure customers have access to the latest accelerators, models, and architectures.
Through its AI Cloud platform, Core42 provides fast, self-service access to high-performance compute for training, inference, and large-scale experimentation. Its services portfolio, managed delivery functions, and AI solutioning capabilities support customers through cloud modernization, data readiness, and the full AI adoption lifecycle.
Since 2024, Core42 has expanded its European presence through a series of large-scale sovereign compute initiatives. In France, Core42 partnered with Data One and Oreus to deliver a national-scale AI infrastructure deployment in Grenoble that supports high-performance enterprise and public sector workloads. In Italy, the company collaborated with Domyn to build Europe’s largest AI compute cluster, creating a strong foundation for an AI-first economy and accelerating the region’s ability to scale advanced AI solutions.
Establishing the European headquarters in Dublin marks the next phase of this expansion. The office will act as the regional hub for customer delivery, engineering leadership, regulatory engagement, and ecosystem partnerships. It positions Core42 to work more closely with European institutions and industry leaders as demand for scalable AI infrastructure accelerates across key sectors.
Commenting on the milestone, Talal M. Al Kaissi, Interim CEO of Core42, said: “Europe is a central part of Core42’s global expansion strategy. Establishing our headquarters in Dublin gives us the operational base to support growing demand for high-performance AI infrastructure and to work more closely with customers and partners as they scale production-grade AI across key sectors.”
Also at Investopia, Core42 together with Emerging Markets Intelligence and Research (EMIR), released a report that explores the infrastructure, policy, and investment conditions required for Europe to accelerate its AI capabilities. The report draws on comparative insights from the rapid AI scale-up in the UAE and provides practical guidance for governments, investors, and enterprises developing sovereign-aligned AI ecosystems. To download the report, click here.
Core42 will begin formal operations in Dublin in early 2026, with plans to expand engineering, customer success, and partner ecosystem teams throughout the year.
The gerotor tooth profile is crucial for determining hydraulic system performance in automotive engineering. In a new development, researchers from Pusan National University have leveraged conditional generative adversarial networks for machine learning-driven gerotor profile synthesis and optimization. The novel approach has remarkably produced designs that outperform human efforts and lead to 32% more efficient hydraulic pumps, potentially revolutionizing the automotive industry.
Gerotor pumps for oil circulation and lubrication are crucial components in automotive and hydraulic systems. They possess a compact design, excellent flow rate per rotation, and high suction capability. The gerotor tooth profile plays a significant role in determining the overall performance of hydraulic systems for engine lubrication and automatic transmission. Unfortunately, conventional design methods leverage predefined mathematical curves and iterative adjustments, which compromises their optimization flexibility.
In an innovative breakthrough, a team of researchers from the School of Mechanical Engineering at Pusan National University, led by Professor Chul Kim, has proposed a new design methodology. Their findings were made available online on 10 October 2025 and have been published in Volume 162, Part D of the journal Engineering Applications of Artificial Intelligence on 24 December 2025.
The key point of this study is the use of AI, specifically, a conditional generative adversarial network, as a design tool. Instead of relying on the traditional approach of using predefined mathematical curves, the researchers trained an AI to automatically generate new gerotor profiles. The AI learned from a dataset linking specific, high-performance profile geometries to their actual performance data. This innovation allowed it to understand why certain shapes perform better than others, and then generate new, highly-optimized geometries that substantially outperform traditional designs.
The team demonstrated that their novel AI-generated design exhibits substantial performance gains in simulation validation via computational fluid dynamics. Compared to a traditional ovoid profile, the proposed design achieved a 74.7% reduction in flow irregularity. This means the pump’s output is significantly more stable and consistent. It also shows a 32.3% increase in average flow rate, which indicates better volumetric efficiency, as well as a 53.6% reduction in outlet pressure fluctuation, which directly contributes to quieter operation and reduced vibration.
The most direct real-life applications of the present work are in the automotive industry. The reduction in pressure fluctuation and flow irregularity is highly beneficial here. It can lead to transmission systems that operate more quietly and could potentially improve component reliability by reducing vibration and unstable hydraulic stress. Furthermore, the 32.3% increase in average flow rate allows for more efficient oil circulation throughout the engine. This contributes to better lubrication and cooling of engine components, which is critical for engine durability.
Prof. Kim remarks: “The same principles demonstrated in our study are applicable to various hydraulic pumps used in industrial machinery, where efficiency, low noise, and reliability are important factors, making our technology highly lucrative for real-life adoption.”
In the next 5 to 10 years, methods like this could become a standard tool for engineers. It represents a move toward “inverse design,” where an engineer can specify the desired performance targets, such as “minimize pressure fluctuation,” and the AI assists in generating an optimal geometry to meet those targets. Moreover, this approach can speed up the research and development cycle for complex mechanical components. It allows for the exploration of a much wider design space than is possible through traditional manual iteration.
“Crucially, for the public, the adoption of more optimal components can mean the machines we use daily become quieter and more reliable. In the automotive sector, this translates to vehicles with more efficient and durable hydraulic systems like transmissions and oil pumps,” concludes Prof. Kim.
Reference
Title of original paper: Machine learning-driven gerotor profile synthesis and optimization using Conditional Generative Adversarial Networks
Journal: Engineering Applications of Artificial Intelligence
