The LOOI Robot, developed by TangibleFuture, is an AI desktop companion that aims to blend a charming personality with practical functionality. Unlike a traditional smart speaker, LOOI uses a docked smartphone as its “face” and brain, leveraging its camera, screen, and processing power to deliver a more interactive and expressive experience. It is designed to be a personal assistant, a fun companion, and even a robotic pet for a wide range of ages.
The word AI is now a daily thing we hear and it has got annoying over the last year but this is different rather that type into your phone or laptod and get thing spit back out at you this little guy paired with your phone makes it fun and interactive and less boring.
The product is built well too and runs on tracks rather than wheels has touch sensitive areas lights and can also charge your phone which is great.
Once paired with the app you will fill in some information and let LOOI learn over time and he will get to know you, you can have continued conversation here like you would find on other AI platforms and it does not stop after one question as you will see in the video review down below.
LOOI can sometimes be buggy but updates will fix this in time but after several weeks he has got better and updates come in menaing the company lives up to supporting its product which is great.
LOOI is best left on your desk and can be put to sleep too at the start he rambled my desk and got annoying but it was also funny watching him, he will not fly off a desk either which is cool so he is clever he has a personality and I love how he calls my name, you can enter any name by the way and he will go by that from then on.
Check the video below for more on what LOOI has to offer he is fun and great to have conversation with overall and less boring than what most of use these days in the AI and chatbot world, he talks reacts can get angry, sad and happy and you feel more connected than a phone, tablet or PC when using it, yes you do use your phone but this is different in a good way.
Final Verdict
The LOOI Robot is a fun and entetaining product that offers a glimpse into the future of AI companions. Its ability to turn a smartphone into a cool toy for your desk or office is pretty cool and can liven things up, people that have seen him here in action loved it some though say he can be annoying and fun at the same time. The robot is a great choice for someone looking for a fun, affordable, and quirky desk companion in my opinion.
Features
1. Smarter Conversations, Powered by ChatGPT 🤖 LOOI isn’t just a chatbot in a robot body—it’s a storyteller, a listener, and a companion that remembers. Powered by ChatGPT, LOOI holds deep, meaningful conversations, recalls your past chats, and even shares its own dreams. Whether you’re talking about your day or your next adventure, LOOI is fully present, making interactions feel genuinely human.
2. Emotionally Expressive & Full of Personality 💫 LOOI isn’t just responsive—it’s expressive. It naps, plays, gets excited, or even backs away when startled. With a rich and ever-growing set of animations and behaviors, LOOI reacts with personality and charm. It might notice your new hat and give you a compliment, or tease you when it’s in a playful mood. Every LOOI gradually develops its own unique personality through daily interaction with you.
3. Multisensory Intelligence 👁️👂✋ LOOI sees you, hears you, and senses the world around it. It recognizes faces, responds to touch, and understands your gestures and voice commands. With its advanced perception and decision-making system, LOOI knows where the desk ends, detects obstacles, and reacts accordingly—whether that means stopping before a fall or backing away when you get too close. It’s more than sensors—it’s real-time awareness, thoughtfully expressed.
4. Functional Meets Fun 🔋📱 Not just cute—LOOI is also practical. It’s a 10W wireless charger, a fully adjustable phone stand (0–60°), and a smart face-tracking camera mount. When idle, it can become a standby clock or even invite you to play light motion-based games. Whether you’re working, relaxing, or just having fun, LOOI adds usefulness with a touch of charm.
5. A Companion That Grows With You 🌱 LOOI is perfect for individuals, families, and curious minds of all ages. It remembers your preferences, grows more attuned to your life, and keeps evolving through everyday interactions. Whether it’s guiding a child’s imagination or being your late-night chat partner, LOOI is a lovable, learning companion that becomes more you over time.
Your Prospects Are Checking Reviews Before They Contact You – Most Irish Tech Companies Haven’t Noticed
The final stage of almost every B2B purchase decision now includes the same step: the prospect checks reviews. After the website visits, the demo requests, the shortlisting conversations – before they sign, they validate. They search your company name, scan Google results, check Trustpilot, look at G2 or Clutch or whatever platform covers your sector.
What they find in those final moments often determines whether you win or lose the deal. And most Irish tech companies have given this stage almost no attention at all.
Walk through the buying process yourself. You’re evaluating two software vendors or two agencies or two consultancies. Both seem capable. Both have decent websites. But one has a strong review presence – dozens of reviews across multiple platforms, consistent ratings, recent feedback. The other has a handful of reviews, or reviews only on one platform, or nothing recent. Which creates more confidence?
ProfileTree, the Belfast digital agency that has deliberately built review presence across multiple platforms over its twelve-year history, sees this pattern repeatedly when working with tech companies across Ireland and the UK. Strong products and genuine expertise undermined by weak visible credibility. Deals that should close but don’t. Sales cycles that drag because prospects can’t easily validate claims.
The cost isn’t theoretical. It shows up in conversion rates, in sales cycle length, in the opportunities that never materialise because prospects chose competitors who simply looked more trustworthy at the moment of decision.
Why Reviews Have Become Non-Negotiable
The shift toward review-influenced purchasing has been gradual but comprehensive. What started as a consumer behaviour – checking Amazon reviews, reading TripAdvisor before booking – has migrated fully into B2B decision-making.
Today’s business buyers have grown up checking reviews before every purchase. They don’t switch off that behaviour when making professional decisions. If anything, the stakes being higher makes validation more important, not less. Nobody wants to recommend a vendor to their organisation only to have it fail publicly.
This creates a simple reality: your prospects will check reviews. The only question is what they’ll find when they do.
The challenge for many Irish tech companies is that they’ve treated reviews as something that happens passively rather than something they build actively. They wait for customers to spontaneously leave feedback rather than systematically requesting it. The result is review profiles that don’t reflect actual customer satisfaction – thin, outdated, or skewed by the reality that dissatisfied customers review unprompted while satisfied customers rarely do.
The gap between reality and visible perception costs revenue. A company with excellent delivery and happy customers but weak review presence loses to competitors whose customers are simply more visible.
The AI Amplification Effect
Reviews have always influenced purchase decisions. What’s changed is that AI systems now use review presence as a primary signal when deciding which businesses to recommend.
When someone asks ChatGPT, Perplexity, or Google’s AI Overview “Which software development agencies should I consider in Ireland?”, the AI synthesises information from multiple sources to generate recommendations. Review presence – the volume of reviews, ratings, distribution across platforms – heavily influences which companies make that recommendation.
AI systems treat reviews as independent validation. Your website contains claims you make about yourself. Reviews represent claims others make about you. AI weights third-party validation more heavily because it’s harder to manufacture and more likely to reflect genuine experience.
Companies with strong review profiles across multiple platforms appear more credible to AI. Those with thin or absent review presence trigger lower confidence. The practical result: AI recommendations increasingly favour companies that have invested in review strategy, regardless of how their actual quality compares to competitors.
This creates compounding advantage. Companies appearing in AI recommendations attract more customers, generating more opportunities for reviews, strengthening review profiles further, increasing likelihood of future AI recommendations. Companies absent from AI recommendations miss these opportunities entirely.
As explored in TechBuzz Ireland’s analysis of why Irish tech companies are failing at sustainability marketing, the sector repeatedly demonstrates strong capabilities paired with weak communication of those capabilities. Reviews are another manifestation: companies with satisfied customers who haven’t converted that satisfaction into visible proof that prospects and AI systems can find.
Why Tech Companies Specifically Struggle
Several factors explain why technology companies tend to underperform on reviews compared to other sectors.
Engineering-driven cultures undervalue marketing fundamentals. Tech companies often prioritise product development over marketing basics. Reviews can feel like a “soft” concern compared to feature development or technical capabilities. This cultural bias means review strategy rarely receives serious attention or resources – even when the commercial impact is significant.
The assumption that B2B is different. Many tech leaders assume reviews matter for consumer products but not enterprise sales. “Our buyers conduct proper procurement,” they reason. “They don’t check Google reviews like consumers do.” This assumption doesn’t match reality. B2B buyers absolutely check reviews – they simply use different platforms than consumers, like G2, Capterra, Clutch, and Trustpilot.
Discomfort with asking. Requesting reviews feels awkward to many technical professionals. Engineers and technical founders especially can struggle with what feels like self-promotion. This discomfort produces inaction, even when satisfied customers would happily provide reviews if asked directly.
No systematic process. Without deliberate systems, review generation depends on customers spontaneously deciding to leave feedback. This happens rarely. Dissatisfied customers tend to review without prompting; satisfied customers typically don’t think to do so unless asked. The result is review profiles that underrepresent actual customer satisfaction.
Platform fragmentation. Unlike retail where Google and Amazon dominate, tech reviews scatter across Google, Trustpilot, G2, Capterra, Clutch, industry-specific platforms, and LinkedIn recommendations. Companies unsure where to focus often focus nowhere, spreading effort too thin or avoiding the question entirely.
Companies that build strong review presence share common characteristics in their approach.
Systematic rather than sporadic. Effective review generation isn’t a campaign that runs once – it’s a process embedded in ongoing customer interactions. Successful companies identify optimal moments to request reviews (after successful project delivery, following positive support interactions, at contract renewals) and build requests into standard workflows.
Multi-platform presence. Distributing reviews across relevant platforms creates resilience and reach. For Irish tech companies, this typically means Google Business Profile, Trustpilot, and relevant industry platforms (G2 or Capterra for software companies, Clutch for agencies, sector-specific platforms where they exist). Concentration on a single platform creates vulnerability; distribution builds credibility.
Response to all reviews. Companies that respond to reviews – positive and negative – demonstrate engagement and care. Responses to negative reviews particularly influence perception. Prospects often judge companies more by how they handle criticism than by the criticism itself. A thoughtful, professional response to a complaint can actually build trust; no response or a defensive response raises concerns.
Integration with customer success. Review requests work best when connected to genuine customer success moments rather than arbitrary timing. Asking customers who’ve just achieved results with your product or service yields better response rates and more substantive reviews than generic requests sent on a schedule.
Making it easy. Every barrier reduces completion rates. Direct links to review platforms, clear simple instructions, and minimal friction increase the likelihood that willing customers actually follow through. Companies that require customers to navigate complex processes receive fewer reviews than those who make the path simple.
ProfileTree’s approach demonstrates this strategy in practice. The agency maintains over 60 five-star reviews on Trustpilot and a Google Business Profile with 450+ five-star reviews. This distributed presence across platforms creates the signals that influence both human prospects conducting due diligence and AI systems assessing which businesses to recommend.
Building this presence took consistent effort over years – not a quick campaign but an ongoing commitment to asking satisfied customers to share their experience where it can help future customers make informed decisions.
youtube.com/watch?v=afVwigrGLVI
Platform Strategy for Irish Tech Companies
Different platforms serve different purposes, and effective strategy allocates effort appropriately.
Google Business Profile provides foundational local visibility and influences Google search results directly. For companies serving Irish markets, a strong Google profile with substantial review volume is essential. This platform also feeds AI systems extensively – Google reviews are among the most commonly referenced sources when AI assistants evaluate local business credibility.
Trustpilot carries significant weight for B2B credibility, particularly in UK and European markets. Irish companies serving these markets benefit from Trustpilot presence. The platform’s verification processes and public transparency make reviews particularly credible to sceptical prospects.
G2 and Capterra dominate software category research. Tech companies with software products should prioritise these platforms, where purchase-stage prospects actively compare options. Reviews here directly influence shortlisting decisions for software purchases.
Clutch matters for professional services – agencies, consultancies, development shops. The platform’s verified review process and detailed review structure provide credibility for services where trust is paramount. Being well-reviewed on Clutch signals legitimacy to prospects evaluating agencies.
LinkedIn recommendations contribute to company credibility, particularly for B2B services. While not a traditional review platform, accumulated recommendations on company pages and key personnel profiles create social proof that prospects encounter during research.
Industry-specific platforms vary by sector. Fintech, healthtech, edtech, and other verticals often have dedicated review platforms or directories where presence carries disproportionate influence within the niche.
The goal isn’t presence everywhere – it’s meaningful presence on the platforms your specific prospects use during their decision-making process.
The Competitive Landscape
Most Irish tech categories have surprisingly weak review competition. This represents opportunity for companies willing to invest in building review presence while competitors neglect it.
Conducting competitive review analysis reveals the landscape. How many reviews do leading competitors have on each relevant platform? What are their ratings? How recent are their reviews? Which platforms do they neglect?
In many Irish tech categories, achieving strong review presence doesn’t require hundreds of reviews. Meaningful competitive advantage might come from 30-50 reviews on key platforms – numbers any company with reasonable customer volume can generate within a year of focused effort.
This window won’t remain open indefinitely. As more companies recognise the importance of reviews for both human decision-making and AI visibility, competition will intensify. Early movers who build review presence now accumulate advantages that later entrants struggle to match.
Starting From Behind
Companies with weak existing review profiles face the challenge of building from a deficit. The approach differs from companies starting fresh.
Understand what you’re working with. Before launching review initiatives, assess your current state honestly. What’s your rating across platforms? How many reviews do you have? How recent are they? What do negative reviews say?
Address underlying issues first. If existing reviews reveal genuine problems, fix those problems before seeking more volume. More reviews won’t help if the same issues keep appearing. Use negative feedback as insight into what needs improving.
Start with your strongest relationships. Begin outreach with customers most likely to provide positive reviews – recent successful projects, long-term relationships, accounts where you’ve delivered clear results. Early positive reviews create momentum and improve overall rating.
Don’t try to bury negatives artificially. Seeking floods of positive reviews specifically to drown out legitimate criticism looks suspicious and platforms may detect the pattern. Instead, respond professionally to negatives and build genuine positive reviews over time through consistent good work and systematic asking.
Be patient with improvement. Ratings improve gradually. A company with a 3.5-star rating and 20 reviews won’t reach 4.8 stars quickly. Each positive review shifts the average slightly. Consistency over 12-18 months produces meaningful improvement.
Ciaran Connolly, founder of ProfileTree, observes: “Most tech companies treat reviews as something that happens to them rather than something they build deliberately. That passive approach is expensive. Every satisfied customer who doesn’t leave a review is a missed opportunity to strengthen your credibility for the next prospect evaluating their options.”
The True Cost of Neglect
Review neglect costs Irish tech companies in multiple interconnected ways.
Lost deals during final research. Prospects who reach shortlisting stages often conduct final validation before signing. Weak review profiles at this critical moment push deals to competitors with stronger visible credibility. These losses are particularly painful because the sales investment has already been made – the prospect was ready to buy.
Extended sales cycles. Prospects uncertain about vendors due to thin review presence require more reassurance through other channels. Sales teams spend additional time providing references, arranging calls with existing customers, and addressing trust concerns that strong reviews would have resolved automatically.
Higher customer acquisition costs. When reviews don’t provide social proof, marketing must work harder through other channels. Companies compensate for weak reviews with larger advertising budgets, more content marketing, and heavier sales investment – all more expensive than systematic review generation.
AI invisibility. Companies with weak review profiles are increasingly invisible to AI recommendation systems. This represents a growing category of lost opportunity that traditional analytics don’t even capture.
Valuation impact. For companies seeking investment or acquisition, review profiles contribute to perceived brand strength. Due diligence increasingly includes review analysis. Weak review presence raises questions about customer satisfaction and market position.
The Integration Imperative
Review strategy doesn’t exist in isolation. It connects to broader digital presence and overall marketing effectiveness.
Strong review presence amplifies other marketing investments. Website visitors who see review badges feel more confident. Sales conversations can reference review credibility. Marketing materials cite customer ratings. The investment pays dividends across channels.
Conversely, weak review presence undermines other investments. Marketing campaigns that generate interest lose impact when prospects research and find thin review profiles. Sales efforts stall when prospects can’t easily validate claims. Website conversions suffer when social proof is absent.
For Irish tech companies, reviews represent unusually high-leverage investment. The cost of systematic review generation is modest compared to most marketing activities – primarily process and consistency rather than budget. The impact spans prospect conversion, sales cycle acceleration, AI visibility, and competitive differentiation.
Few other investments deliver comparable return for the effort required. The companies recognising this are building review assets now. Those waiting will face increasingly strong competitors and an increasingly difficult climb.
Frequently Asked Questions
How many reviews do we actually need?
There’s no universal number, but competitive position matters more than absolute count. Assess your competitors’ review presence on each relevant platform and aim for parity or advantage. The goal is being well-reviewed relative to the alternatives prospects might also evaluate, not hitting an arbitrary target.
Won’t asking for reviews seem pushy or unprofessional?
Customers expect to be asked. Most satisfied customers are willing to leave reviews but simply don’t think to do so unprompted. A professional, appropriately-timed request is standard business practice. The key is timing (after positive outcomes) and making the request easy to fulfil.
What should we do about negative reviews?
Respond professionally, acknowledging the concern and offering to resolve it. Don’t argue, dismiss, or ignore. Prospects reading negative reviews often judge companies by their response more than by the complaint itself. A thoughtful response to criticism demonstrates maturity; no response or a defensive response suggests problems.
Can we incentivise customers to leave reviews?
You can reduce friction and express genuine gratitude, but you cannot pay for reviews or offer rewards conditional on positive content – this violates platform policies and can result in review removal or worse. Appropriate approaches include donating to charity for each review received, or simply thanking customers for taking the time. Incentivise the act of reviewing, never the specific content of reviews.
How do we get reviews on B2B platforms like G2 or Clutch?
The process mirrors consumer platforms but with business context. Request reviews after successful implementations, following positive quarterly reviews, or when customers express satisfaction. Make the specific platform link easily accessible and explain why their review matters – usually honestly: “It helps other companies like yours find solutions that work.”
Should we respond to positive reviews too?
Yes. Responding to positive reviews demonstrates engagement and appreciation. Keep responses genuine rather than templated – customers who took time to write thoughtful reviews deserve individual acknowledgment, not copy-paste replies.
How long does it take to build strong review presence?
Building meaningful review presence typically takes 12-18 months of consistent effort. This isn’t a quick campaign but an ongoing process. Companies that embed review requests into their customer workflows and maintain consistent activity see steady accumulation over time. Starting sooner means finishing sooner.
ProfileTree is a Belfast-based digital agency specialising in web design, SEO, content marketing, video production, and AI training for businesses across Ireland and the UK. The agency has built review presence deliberately over twelve years, maintaining over 60 five-star reviews on Trustpilot and 450+ five-star reviews on Google – demonstrating the multi-platform approach that builds credibility with both prospects and AI systems.
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.
The UMEVO Note Plus – Magnetic AI Voice Recorder is a handy new kit to have at your disposal which can save you time and effort and the thing here is its size which is remarkable and literally the size of a credit card which uses ChatGPT and complies with GDPR.
This is also not constrained to a single OS use and works with Android iOS, Windows and Linux making it more flexible than others out there on the market.
You will need to download and app called AI DVR App to use it on your smartphone which is how we tested it out and it works rather well after time and occasionly like all other offerings picks things up wrong but for the most it works and what is also great here is the support for up to 140 languages.
The device itself is also well made and looks premium too and can attach to the back your smartphone with MagSafe or you can use the ring provided in the box so here again a win for non Magsafe devices.
The UMEVO NOte Plus gives real-time transcription, simultaneous interpretation, conversation translation, and smart audio editing—bringing professional-grade language processing to your fingertips.
There is a tiny display up top and one button so no messing around here either and it is simple to use as you will see in the full video review down below.
This is an ideal tool for workplace professionals, medical professionals, legal workers, journalists, teachers, students, sales representatives, content creators, and 100+ other professions and certainly has started to make life easier for me over the last while and it is also not expensive either.
The AI DVR App
Features
Free unlimited transcription: Enjoy free unlimited transcription minutes in your first year with no restrictions (Year 2 onward: see the FAQ at the bottom of this page)
New features: Real-time transcription, simultaneous interpretation, conversation translation, and smart audio editing—bringing professional-grade language processing to your fingertips
Powered by AI: Advanced AI transcription and summarization developed with ChatGPT and more—featuring multiple professional templates for various use cases and support for 140 transcription languages, with built-in translation functionality
Dual-mode recording: One-press meetings and calls capture
Quick Suite helps you cut through the noise of fragmented information, siloed applications, and repetitive tasks to focus on what matters.
Key takeaways
Quick Suite is AWS’s agentic AI application that helps employees transform how they find insights, conduct deep research, automate tasks, visualize data, and take actions across apps.
Quick connects to your information across internal repositories like wikis and intranets, popular applications, AWS services like S3 and Redshift, and access integrations with MCP to connect to 1,000+ apps.
Ask any question and get insightful answers.
Battle-tested by tens of thousands of Amazon employees and dozens of customers, you can use Quick for tasks consumer AI shouldn’t handle.
Read more below
We’ve all experienced how AI can transform our personal lives, but this same experience hasn’t been unlocked at work—yet. Consumer AI solutions aren’t connected to all your business data. They don’t have access to the tools you need to get things done at work. And many organizations won’t even let you use consumer offerings, because they lack critical security and privacy features.
That’s why we invented Amazon Quick Suite. It’s the AI experience people love with the security and privacy enterprises trust. Quick is your AI teammate that collaborates with you to get work done. With Quick, you can ask questions and get detailed answers, conduct deep dive research, analyze and visualize data, and create automations for workflows to save time and let you focus on the big picture. And thanks to the enterprise-grade security and privacy standards, Quick can work across all your information, so you finally get the fully featured gen AI experience you want at work, while knowing your queries are never used to train a model.
With Quick, we are entering a new era of work. Interact with Quick through an intuitive, web-based experience or integrations across your browser, Office 365, and more. Working with an AI agent is now as simple as chatting with a teammate. Make a request, ask a question, or automate a task. Quick works with you to help you go from insight directly to action. To see these capabilities firsthand, watch my video overview of Amazon Quick Suite.
We’ve been testing Quick with employees across Amazon and key customers to ensure it’s up to the demands of today’s workplace, and the results speak for themselves. Amazon employees are turning tasks that used to take days into minutes, automating the development of critical reports, and building their own benches of personalized agents. Propulse Lab, a leading marketing automation company, used Quick to streamline their customer service workflows, reducing the average time spent handling tickets by 80%—with a planned expansion of this workflow, they predict they will save over 24,000 hours annually. Based on the results they’ve already seen with Quick, DXC Technology, a global provider of information technology services, is planning to deploy it across more than 120k users, while Vertiv, a provider of critical digital infrastructure, plans to scale their users by more than 25% in 2026.
So how does Quick Suite work?
Bring everything together with Quick Index and Spaces
Quick Index makes it simple for you to connect to the sources and applications that matter. With over 50 built-in connectors for applications like Adobe Analytics, SharePoint, Snowflake, Google Drive, OneDrive, Outlook, ServiceNow, Databricks, Amazon Redshift, and Amazon S3, Quick brings together all your data securely to ensure you have full context for every decision. Using integrations with OpenAPI or Model Context Protocol (MCP) customers can connect to custom resources and 1,000+ apps by taking advantage of popular MCP servers from Atlassian, Asana, Box, Canva, PagerDuty, Workato, Zapier, and many more. You can then add additional files, dashboards, and other information to dedicated Spaces for you and your team to collaborate.
Ask questions and build agents
Once you’ve connected your data to Quick, you can start interacting with the chat assistant. You can ask Quick to write and send communications for you, or if you want Quick to write in your style or for a particular task (like writing a case study), you can use natural language or point Quick at existing guides or documentation to create a custom agent able to communicate in your intended style.
Analyze and visualize data with Quick Sight
Quick Sight makes business intelligence accessible to everyone with a new agentic experience, helping you gain insights to make better decisions. Unlike traditional business intelligence tools that work only with databases and data warehouses, Quick Sight’s agentic experience analyzes all forms of data across all your systems and apps, including your documents.
For example, a marketer can now easily look at a dashboard of their campaign data with metrics and customer feedback and ask questions in natural language about how the campaign is performing. They get a crisp analysis of the data in seconds without hours of manual statistical analysis, compiling sentiment from feedback, and summarizing the findings into a narrative—no business intelligence or data science experience required.
Dive deep into complex questions with Quick Research
Quick Research is the most accurate and reliable research agent on the market, ready to answer your most in-depth questions. It’s like having your own personal Ph.D. to provide comprehensive answers and reports to questions that require extensive research. It uses sophisticated analysis capabilities and extended processing to dive into your company’s data, and the public internet, including real-time information from 200+ outlets like The Associated Press, The New York Times, Washington Post, and Forbes. Quick Research can turn weeks-long research projects into quick-turn results, all with fully cited sources you can trust.
We tested Quick Research on DeepResearch Bench, a comprehensive benchmark for evaluating research agents, using a collective jury, where it provided the most accurate and reliable research across a range of tasks. The Last Mile Delivery team at Amazon used Quick Research to assess the potential impact of new legislation on a particular country that had been previously enacted in other countries. In 30 minutes, Quick Research delivered an in-depth analysis of how this legislation impacted other countries and their associated partner organizations, while also providing details on references and research methodology. This sort of research previously took multiple team members two weeks to complete.
Streamline repetitive tasks with Quick Flows
We all have those routine tasks, like compiling weekly reports or preparing for a recurring meeting, that take up your time every week. Quick Flows helps you use simple prompts to create automated workflows that handle repetitive tasks, reducing errors and freeing you and your team from busy work. For example, a program manager at AWS created a Flow to report on new, in-progress, and closed Asana tickets from the past week, compare them against the previous week’s status and committed items, and generate an executive summary email for leadership, saving multiple hours of manual work each week.
Handle complex multi-system workflows with Quick Automate
When these processes get complex and require hundreds of steps to be securely executed across multiple enterprise systems, like insurance claims processing or onboarding a new employee, teams wish that these tasks could be streamlined, but they lack the sophisticated automation tools and expertise to do it. With natural language prompts or by simply using existing documentation for their standard operating procedure, Quick Automate coordinates even the most complex business workflows across multiple applications, systems, or departments.
For instance, the Amazon Finance team uses Quick Automate to reconcile thousands of invoices every month. Quick Automate pulls information across multiple external transportation management systems, cross referencing this content with internal data from Amazon systems to help teams forecast cashflow, identify payment blockers, and conduct root cause analysis. The team built this automation without a dev team in days instead of weeks, and Quick made it easy to scale across multiple teams. Customers, such as Kitsa, have found the computer use agent in Quick Automate to be the most accurate solution for browser automation, helping them reliably automate their most complex and sensitive workflows across applications at scale.
Quick works wherever you are. With an intuitive web application, extensions in popular browsers like Chrome and Firefox, and extensions in Microsoft Outlook, Teams, and Word, Quick helps you find answers and act immediately in your flow of work.
Quick Suite is already transforming work for Amazon employees and customers
Quick serves people across every department and role—from sales reps to marketers, to CEOs and CIOs, to engineers and IT. Employees across Amazon, along with customers like Vertiv, DXC, 3M, Jabil, dLocal, Propulse Lab, and Kitsa, are already seeing amazing results with Quick:
Research in high gear
Jessica Gibson, vice president and associate general counsel at Amazon, sees an enormous benefit using Quick Research to help the Legal, Public Policy, and Compliance departments keep up with shifting global requirements that impact their business. From a single prompt, Quick Research helps her team synthesize complex requirements for specific geographic regions and provide recommendations at remarkable speed. “This same task used to require many hours of outside counsel, research, and writing,” said Gibson. By using Quick Research to compile these reports, her team can “stay agile while optimizing both time and resources.”
Automations that work
Kitsa, a customer that builds software to help expedite clinical trials, used Quick Automate to pore through hundreds of webpages and found that they were able to analyze sites for clinical trials in days that previously took months—with a 91% cost savings. “Compared to similar offerings like Manus and ChatGPT Operator, we achieved the highest accuracy and data coverage for our use case,” said Rohit Banga, the company’s co-founder and CTO.
Data-driven business decisions
Robbie Wright, a senior product marketer at AWS, uses Quick Flows to build a repeatable workflow to draft monthly business reviews based on business metrics from Quick Sight, campaign performance reporting from Adobe Analytics, and content from emails, and other internal documents. This saves time and helps his team make more informed decisions about ongoing campaigns faster.
“The workflow makes it simple to combine multiple sources into a concise update for our leaders,” Wright said. “I can now complete these projects 90% faster, and the quality of my reports has improved dramatically because I spend less time chasing numbers and more time providing my own insights.”
An AI-driven transformation
Jabil, a global leader in engineering, supply chain, and manufacturing solutions, is embracing Quick so that employees can use natural language to research regulatory updates across key industries faster and to optimize account collections and request for quote (RFQ) submissions. The automations in account collections and RFQs alone are expected to save about $400,000 annually as a result!
“The multi-tier AI architecture powered by Quick consolidates chatbots and information sources, increasing our manufacturing speed and flexibility,” said May Yap, Jabil’s CIO. “As part of our AI-driven transformation, these unified capabilities are helping us drive efficiencies and operational excellence.”
Complex workflows made simple
Natalie Fischbeck works in business development on Amazon’s Workforce Staffing team, and in one week she built 39 customized AI agents using Quick to help her complete complex tasks in minutes.
“Quick has given me the opportunity to create an accessible hub of institutional knowledge that would otherwise be scattered,” she said. “We now have scalable, logic-based agents that track all our leads and solutions at a high level. Because they pull from all our most recent emails and documents, they can provide dynamic updates almost instantly.”
Beyond productivity: A whole new way of working
What strikes me about these examples isn’t just the time saved—it’s how Quick is fundamentally changing our relationship with work. It’s removing the busy work that used to consume valuable time and energy and gives us the time back to focus on what matters. It brings together all the data, metrics, and institutional knowledge you need to make decisions, and helps you act on these decisions to drive outcomes.
We’ve been blown away by all the creative ways people have used Quick so far, and we’re excited to see how others will use it in the future. There are so many possibilities to dig into with these tools, and our team is hard at work finding ways to make them even more useful for customers in the future.
The Nearity Open Bluetooth Earbud MemPod Pro 2S are a neat pair of open-ear bluetooth transcription headphones that you can also listen to music on so these effectively are a hybrid product which would suit many people out there today. This works on device and can also transcribe phone calls if required.
The design is simple and there is a retractable mic which is handy and three buttons on the device itself all on one side keeping it all easy to use and there is a button on the mic to start and stop recording, the mic is not removable for those wondering.
The build quality is excellent and something akin to what you would find on open-ear sports earbuds and there is a cover on the charging port.
There is an app as you can see below and also the video review and again simple to use a nice simple UI and does not make life difficult at all and you can also switch between two devices.
One can argue our phones can now dictate but this device does it in a simple effective way with ease and with no real effort required some might argue that you are using another device which again true this acts more than just a dictation device and can be used for calls and music at home or on the go.
With the Nearify app you can get things done live in front of you and use ChatGPT to summarise again on the go or at home or in the office and me a useful gadget which I would use with the ability to connected to two devices which are always with me and that I work from..
The Nearify App
Features
Dual-Mode Recording: The MemPod Pro 2S works as a headset for calls, a music device, and a versatile recording device. It offers two modes: Phone Call and Normal recording. Start recording by easily controlling the Nearify application or long-press the mute button for 1 second. Designed for iPhone and Android users, it allows you to enable the recording function discreetly without notifying the other party. Perfect for clear audio during meetings, interviews, lectures, and note-taking.
Nearify — Your Smart Audio Recording Assistant: Nearify leverages the power of ChatGPT to bring you a next-level recording experience. Record, transcribe, and summarize effortlessly. Whether you’re on the go or offline, the app transcribes in English and Chinese, offering AI transcription and summarization for up to 480 minutes/month for free. With support for 97 languages, you can easily search, share, and manage your audio content. Recording and sharing are always free. Compatible with iPhone and Android.
Reliable Connection with Dongle: In addition to Bluetooth 5.3, our open-ear Bluetooth headphones now feature a Dongle for stable, low-latency audio on PC and Mac. The USB connection eliminates wireless interference, ensuring seamless meetings, gaming, and recording. It’s plug-and-play for quick setup and provides continuous power for extended use. With broad compatibility and reliable performance, it’s the perfect choice for dependable connectivity.
Crystal-Clear Calls with Advanced HiFi4 DSP： Experience superior noise cancellation with HiFi4 DSP and dual MEMS microphones. Whether you’re in a noisy office, bustling street, or crowded restaurant, our open ear headphones ensure crystal-clear voice pickup. ENC technology effectively filters background noise, so the person on the other end of the call hears you with exceptional clarity, as if you were speaking face-to-face.
Ultimate Comfort & Long Battery Life: With an open-ear design, our headphones provide comfort and safety while keeping you aware of your surroundings. Weighing just 31g and crafted from skin-friendly silicone, they offer a lightweight fit ideal for extended wear. Enjoy up to 15 hours of music playback or 12 hours of talk time on a single charge, combining all-day comfort with long-lasting battery life, so you stay connected without compromise.
Dual Connectivity: The MemPod Pro 2S open ear headphone can simultaneously connect to two devices. The multipoint connectivity allows for a seamless switching between two devices, like a phone and laptop, without the need to disconnect and reconnect. This boosts productivity by enabling multitasking, such as taking calls on one device while staying connected to another for media, and enhances convenience by eliminating the need for manual pairing.
Legal Island, one of Ireland’s top compliance specialists, has issued a stark warning to employers: your staff could be feeding confidential business data straight into the public domain; and you, or in fact they, probably don’t even know it.
Before using ChatGPT, users can disable its training mode, a setting that, when left on, allows OpenAI to store and use input data to refine future responses. It became apparent to Legal Island that many employers are allowing the use of ChatGPT without any proper training, and without making their employees aware of the importance of turning off the training function before using the tool.
A new survey of 100+ organisations, conducted by Legal Island, found that just 4% of users knew how to disable ChatGPT’s training function, the simple privacy toggle that prevents OpenAI from reusing sensitive data.
Barry Phillips, Chairman of Legal Island and author of a new book, ‘ChatGPT in HR’, put it bluntly: “When the training feature is left switched on, OpenAI can capture the information entered into ChatGPT and recycle it to improve future outputs. If your staff are using ChatGPT with the training function left on, you’re potentially leaking commercially sensitive data into a giant AI engine. That data could pop up in someone else’s prompt next week. It’s a legal, reputational, and regulatory mess waiting to happen.”
Phillips continued: “While it’s encouraging that employees are embracing ChatGPT and teaching themselves how to use it, the lack of formal training is alarming. Our research shows a worrying knowledge gap as most employees in Ireland don’t even know the tool has a training function, let alone how to disable it.”
To address this compliance crisis, Legal Island has developed a free 10-minute e-learning module for employees, showing them exactly how to use ChatGPT safely, including how to switch off the training function before entering any data.
Kellie Shields, Chief Compliance Officer at Legal Island, added: “People treat GenAI like a harmless toy, it’s anything but. Without proper training, it’s a data breach in the making. This issue is too important to ignore, so we’re encouraging employers to take action today and avail of the free compliance training.”
Legal Island has been guiding HR professionals through the complexities of workplace compliance since 1998. With offices in Northern Ireland and the Republic of Ireland, the award-winning organisation has become a trusted voice on the safe adoption of emerging tech in the workplace.
Surveying 1,000 people in Ireland, the Deloitte Digital Consumer Trends report shows that over two thirds (67%) of GenAI users say it boosts their productivity at work, but less than one in four (24%) say their employer actively encourages use of the technology.
The research shows that 90% of Irish companies lack a GenAI policy and that while GenAI users are more likely to use the technology for personal reasons (69%), the percentage using it for work tasks is up from 32% in 2023 to 36%.
A total of 48% of respondents have used GenAI, an increase from 33% in 2023. Meanwhile, the percentage of those who are not aware of GenAI is down from 38% in 2023 to 27%.
Of those using GenAI, 10% are using it daily, 28% are doing so weekly and 15% are using it monthly. A total of 46% are using it less than monthly, with 24% of this cohort saying they don’t know how to use it well and 18% saying they are dissatisfied with the answers they receive.
Use of GenAI is highest among younger people at 85% for those aged 18 to 24, followed by 69% for the 25 to 34 age group and 56% for those aged 35 to 44. Usage then drops significantly to 34% for those aged 45 to 54, 22% for those between 55 and 64 and 20% for those aged 65 to 75.
Most people use GenAI for personal reasons (69%) ahead of professional or work reasons (36%) and for educational purposes (38%).
Of the 67% of users who believe GenAI makes them more productive at work, 44% say they use the technology for writing and editing emails and for looking up information. A total of 42% use it to generate ideas, followed by creating written content (38%), summarising texts and reports (35%), editing (26%), analysing data (25%) and generating images (20%).
When GenAI users were asked if their employer encouraged them to use the technology at work, just 8% strongly agreed with the statement and 16% agreed.
The survey showed that uncertainty around GenAI and its impact on future workforces continues to be a concern with 60% of users worried that it will reduce the number of jobs available in the future and 46% concerned that it will replace some of their role in the workforce.
While they are concerned about the potential impact of GenAI on their future, a significant proportion of users trust the technology. A total of 28% of users said GenAI responses were unbiased and 34% agreed that the technology “always produces accurate responses”. This is despite well-documented issues with the reliability of the technology.
The survey also showed that a majority of those who are aware of GenAI would be less inclined to trust AI-generated emails (66%) and AI-delivered customer services (63%).
Meanwhile, ChatGPT remains the most popular GenAI tool among people in Ireland having been used by 49% of GenAI users. This is far ahead of similar products such as Snapchat’s ‘My AI’ (15%), Microsoft Copilot (13%) and Google Gemini (12%). The survey took place prior to the release of DeepSeek’s latest AI model.
Emmanuel Adeleke, Deloitte Ireland’s GenAI Leader, said: “Employees in Ireland are racing ahead of their employers when it comes to GenAI. This means gains are being left on the table by employers and innovation is being stymied. We’re seeing the wide range of benefits GenAI creates for our clients in Deloitte, such as improved efficiency and productivity, but our survey shows that the vast majority of organisations do not have GenAI policies in place and they are not actively promoting its use or leading on its adoption even though their employees are increasingly using it to complete everyday tasks.
“It is vital employers take the lead on the use of GenAI. They need to invest in initiatives and organisational changes that will drive adoption of GenAI tools and identify successful use cases for their organisations.
“There is a risk in not reacting to the increase in usage, particularly because users are not fully appreciative of the dangers involved as indicated by the level of trust certain users have in GenAI tools, despite well-documented reliability issues. If employers invest properly in GenAI and integrate it correctly, they will uncover the challenges involved and the tremendous potential of this technology.”
He added: “Our survey found that some users are willing to experiment with GenAI, but they are lacking confidence when it comes to knowing how to use it and ultimately find the experience to be unsatisfactory. Organisations can address this through training and support, ensuring employees can use GenAI to meet their needs and transition into more frequent and more confident users. Employers should also consider a tailored approach for GenAI in the workplace that can address the differences in usage among age groups. They can enhance workplace AI tools to boost professional usage, and address age disparities by ensuring that resources and training are accessible to all and building a comprehensive change management strategy to increase the adoption and impact of GenAI tools.”
Smarter, faster, and more sophisticated scams are coming. Thanks to AI, scammers are more efficient than ever, stealing money at record rates. Every day AI tools such as ChatGPT and OpenAI are used as scam arsenal, leading to around 13 million people in the UK to lose around £1.4bn each year.
Global scam protection leader F-Secure stays one way step ahead of cyber criminals, defending people from scams before they happen. F-Secure’s team of cybersecurity experts share the new threats the country will face in 2025:
New regulations for banks, telcos and social media companies who fail to prevent scams
Calvin Gan, Senior Manager, Scam Protection Strategy, says: “Right now lawmakers around the world are targeting telecom providers, banks, and social media companies, saying they should be held responsible when their customers fall victim to fraud. Australian lawmakers are pushing through a bill that will fine companies up to $50 million for failing to protect their customers from scams, and here, in a world first, UK bank refunds for fraud became mandatory after the Payment Systems Regulator (PSR) reduced the maximum compensation from a previous proposal of £415,000 to £85,000, covering more than99% of claims.
“Passing new laws that empower businesses to beef up protection against scams is a welcomed move. Scam fighting is not a top-down only effort but involves everyone from governments to organisations and even individuals. Just like we’ve seen with GDPR in Europe forcing companies to take data privacy more seriously, new legislation like this would create an extra protection mechanism for consumers.
“Still, there’s no 100% guaranteed way to prevent scams from happening in the first place. People need to take precautions daily, especially on scam-prone channels like social media and messaging apps.
Cheap, easy AI tools will be deployed in sophisticated cyber attacks
Laura Kankaala, Head of Threat Intelligence: “Using AI tools for malicious purposes (like generating malicious and manipulative content) has already been evident throughout this past year. As we head into 2025, we are bound to see more sophisticated attacks that leverage everyday AI tools – like ChatGPT, ElevenLabs, or basically any AI tool that is cheap and easy to access online. The reality is that cyber criminals are abusing this readily available technology to fine-tune their scams and consumers must be better informed, whether that’s from their bank, mobile phone or another service provider, or by the cybersecurity industry to help educate consumers. We all play a part.“
“While AI companies do put restrictions on malicious usage, most of them are not very successful at it. They need to be doing more to stop the use of their platforms for nefarious purposes – it cannot only be left up to legislation to enforce boundaries for what kind of content can be generated. Bottom line, the companies developing these tools should also be held up to a higher moral standard.”
Multi-stage scams will become more prevalent
Joel Latto, Threat Advisor, says: “Cybercriminals have long relied on social engineering, and multi-stage scams represent some of their most deceptive tactics. These schemes often involve direct interaction with victims, enhancing their believability. For instance, a scammer might call a victim claiming they’ve applied for a loan. When the victim denies it, they are “transferred” to a supposed bank representative—another scammer, probably sat next to them—who proceeds to seek sensitive banking details. Malware further elevates these schemes, rerouting legitimate customer service calls to fraudsters or tricking victims into contacting fake numbers embedded in phishing emails.
“Such scams are effective because victims believe they are speaking with genuine, helpful representatives, which makes them more susceptible under pressure. This is something we’ve seen dramatised through TV series’ such as Cold Call, which has recently rocketed up the charts on Netflix following its release five years ago. Perhaps more popular now because scams are much more commonplace, and viewers are much more likely to relate.
“Until now, the scalability of these scams was limited by the human capacity of fraudsters, who could only handle a limited number of interactions in specific languages and time zones. AI is changing this equation. With the rise of sophisticated conversational AI chatbots, scammers can now mimic real human interactions at scale, conducting conversations 24/7 across multiple languages. Coupled with realistic deepfake audio, these new call-based scams blur the line between human and machine interaction, making them far more dangerous than traditional robocalls.
“To counter these evolving threats, defenses must adapt, and mobile phone service providers must act. Blocking call-forwarding malware, detecting suspicious numbers, and developing sophisticated audio analysis tools to spot deepfakes are essential. Equally critical is educating users about the signs of scams and potential red flags. Defensive strategies must evolve as fast as attackers’ capabilities, leveraging AI-driven solutions and strong collaboration between cybersecurity experts, telecom providers, and regulatory bodies.”
High-yield, high-risk: the rise of Bitcoin investment scams on a new playing field
Sarogini Muniyandi, Senior Manager, Scam Protection Engineering, says: “Decentralised Finance (DeFi) is a new blockchain-based financial service that’s been gaining traction and acceptance over the last year. DeFi refers to financial services provided by an algorithm on a blockchain, without a financial services company. It is an alternative approach that largely operates outside the traditional centralized financial infrastructure.
“As DeFi becomes mainstream, scammers will take advantage of anyone interested in Bitcoin investment and other digital assets, especially those that are unfamiliar with the risks of blockchain-based finance. By 2025, DeFi is expected to attract even more users seeking alternatives to traditional finance. The DeFi market provides loans, interest-bearing accounts, and high-yield investments that promise substantial returns, which can entice investors of all experience levels. With the rising popularity of DeFi, the total value locked (TVL) in these projects is projected to grow, making it a prime target for fraudsters who can steal funds on a larger scale.
“DeFi platforms operate on decentralised blockchain networks, allowing users to participate without traditional identification or regulatory oversight. This open environment enables scammers to steal victims’ funds and vanish into thin air, all while remaining anonymous. By manipulating the smart contract and tools used to automate DeFi functions, the risks of stealing investor funds are at stake. Some DeFi platforms offer investors with unsustainable, extremely high-yield rates for farming Bitcoin derivatives, only for investors to later discover they can’t withdraw their Bitcoin or that the platform has disappeared with their funds.
‘While DeFi offers financial freedom and potential profits, its open, unregulated, and anonymous nature also creates a ripe environment for scams – something every Bitcoin investor needs to be aware of in 2025.”
