AI use in Ireland has crossed an unmistakable threshold: what looked like early experimentation in 2023–2024 is now behaving like routine behaviour for a growing slice of the population, and that shift has practical, commercial and policy consequences for technology vendors, marketers and everyday Windows users alike. Core’s new AI Connect 2026 research — a nationally representative survey of 2,000 adults in Ireland — finds 18% of adults use generative AI tools regularly, and places that uptake inside what the study calls the “Early Majority” phase of adoption.
The headline numbers in Core’s AI Connect 2026 study are simple but consequential: regular generative-AI use among adults in Ireland sits near one-in-five; ChatGPT is reported as the clear leader with 25% of adults using it at least weekly, closely followed by Meta AI (24%), while Google Gemini and Microsoft Copilot lag behind in the survey results. The study also finds adoption concentrated among 25–39-year-olds, particularly those with higher incomes, with surprisingly lower uptake among 18–24-year-olds and minimal engagement from the over-65s. Public trust in AI is context-dependent: confidence is highest for productivity and learning tasks but falls sharply for human-centred domains like health, wellbeing and companionship.
Those Core figures fit inside a broader, global picture in which ChatGPT remains a dominant presence in the AI-chat landscape. Independently collected analytics show ChatGPT driving the overwhelming majority of AI-chat referrals to websites — Statcounter reported ChatGPT accounted for roughly four-fifths of AI-chatbot referrals in mid‑2025 — a finding that underscores the platform’s outsized role in discovery and information flows even where niche national differences exist.
For Windows users, the Microsoft story remains strategically important even if Copilot’s consumer take-up trails in some polls. Microsoft is embedding Copilot and multimodal features into Windows and Office, and hardware partners are increasingly shipping devices with enhanced on‑device NPUs and Copilot+ signatures. That means:
Source: AdWorld.ie New Research from Core Suggests AI Has Gone Mainstream | AdWorld.ie
Background / Overview
The headline numbers in Core’s AI Connect 2026 study are simple but consequential: regular generative-AI use among adults in Ireland sits near one-in-five; ChatGPT is reported as the clear leader with 25% of adults using it at least weekly, closely followed by Meta AI (24%), while Google Gemini and Microsoft Copilot lag behind in the survey results. The study also finds adoption concentrated among 25–39-year-olds, particularly those with higher incomes, with surprisingly lower uptake among 18–24-year-olds and minimal engagement from the over-65s. Public trust in AI is context-dependent: confidence is highest for productivity and learning tasks but falls sharply for human-centred domains like health, wellbeing and companionship.Those Core figures fit inside a broader, global picture in which ChatGPT remains a dominant presence in the AI-chat landscape. Independently collected analytics show ChatGPT driving the overwhelming majority of AI-chat referrals to websites — Statcounter reported ChatGPT accounted for roughly four-fifths of AI-chatbot referrals in mid‑2025 — a finding that underscores the platform’s outsized role in discovery and information flows even where niche national differences exist.
What the Core data actually tells us
Adoption by the numbers — what’s robust, what’s provisional
- 18% regular use (generative AI): Core’s survey places regular generative-AI use at 18% of Irish adults. That’s the study’s central claim and the one most likely to be used as shorthand for “AI has gone mainstream” in journalistic headlines. The figure is plausible given global usage trends and platform scale, but it should be read as a snapshot from a single commissioned study rather than a definitive national census of AI behaviour.
- Platform ranking: ChatGPT leads (25% weekly), Meta AI (24% weekly), Gemini and Copilot trailing. These relative positions mirror broader referral and usage metrics that show ChatGPT as the global market leader for AI chat interactions, even if local market nuance can shift small differences. Statcounter and other analytics outlets continue to show ChatGPT’s referral and active-user dominance, lending external credibility to the ranking Core reports.
- Demographics: Adoption concentrated in 25–39 cohort and higher incomes. That profile is consistent with what independent research in other markets has shown: early mainstreaming tends to be led by digitally active professionals who see immediate workplace and productivity value. The unexpectedly lower uptake among 18–24s is worth noting — it challenges assumptions that Gen Z are automatically the heaviest adopters of new conversational tools.
Where the data is limited — and why that matters
Core’s study offers useful behavioural snapshots, but a few methodological caveats are essential before we translate numbers into policy or procurement decisions:- The publicly reported coverage (2,000 adults) implies a reasonable sample size for national estimates, but the headline figures in secondary reporting do not show confidence intervals, weighting strategies or the exact question wording used to define “regular use.” That matters, because small differences in phrasing (e.g., “use weekly” vs “use regularly for work”) can yield materially different percentages.
- Platform definitions matter. “Meta AI” can mean different things to different survey respondents (a social-app feature, a standalone chatbot, or a brand-level shorthand), and the way respondents self-identify which tool they use can skew platform rankings.
- Cross-sectional surveys capture intent and self-report behaviour, which is valuable — but usage telemetry (clicks, API calls, referral volumes) tells a complementary story and sometimes a different one. Core’s survey should be read alongside behavioural analytics (Statcounter, internal platform telemetry) to get the full picture.
Why “mainstream” — unpacking the phrase
Saying AI has “gone mainstream” is shorthand that can mean several different things. In practice, the Core results point to three distinct but related phenomena:- Behavioural normalization: People are no longer only experimenting with cool demos. A sizeable minority use AI tools repeatedly for everyday productivity and discovery tasks: learning, drafting text, brainstorming, quick calculations, recipes, travel planning and similar chores. The survey explicitly highlights productivity and learning as high‑trust contexts.
- Platform consolidation in discovery: Even as many tools proliferate, one platform — ChatGPT — continues to capture a large slice of attention and referral traffic. That concentration matters for marketing, SEO/AEO strategies, and the distribution economics of content. Statcounter’s referral data is an important independent datapoint here.
- Workforce integration: “Mainstream” can also mean enterprise buy‑in. Where employees adopt tools on their own (shadow AI), organizations either accept that reality or respond with governance, procurement and training. Anecdotal and enterprise reporting through 2025–2026 shows rapid movement on that front: universities and large employers rolling out official copilots, and vendors integrating agents and copilots into productivity suites. For Windows users and IT teams, that transition is particularly relevant because of the rising importance of Copilot and on‑device AI features.
Use cases and trust: where AI is welcome — and where it’s not
Core’s trust findings are revealing in their bluntness: 62% of respondents are confident in AI for learning, creativity or career guidance tasks, but confidence falls when tasks require emotional judgement or human empathy such as healthcare support, wellbeing or companionship. In short, Irish consumers appear willing to employ AI as a cognitive assistant — not as an emotional substitute.High-trust categories (growth opportunities)
- Administrative life tasks: navigation, weather, travel planning, scheduling and simple automation are seen as natural fits for AI.
- Discovery behaviours: recipe inspiration, quick research, idea generation — places where speed and breadth trump deep provenance.
- Productivity and learning: drafting documents, summarising material, language practice and career coaching are all categories where users report measurable confidence.
Low-trust categories (resistance persists)
- Health and wellbeing advice beyond informational support (users want human affirmation and ethical safeguards).
- Emotional companionship or relationship mediation — respondents explicitly recoiled at the idea of substituting human empathy with a machine.
- Deep legal, medical or moral decisions where accountability and provenance matter.
Platform landscape: why ChatGPT leads, and why Copilot matters for Windows users
Core’s Ireland snapshot shows ChatGPT first and Copilot trailing. That pattern mirrors global referral and usage dashboards: ChatGPT dominates AI-chat referrals to websites and remains the default for many discovery tasks. Statcounter’s mid‑2025 referral data put ChatGPT at roughly 80% of AI-chat referral share globally, a structural advantage that continues to matter.For Windows users, the Microsoft story remains strategically important even if Copilot’s consumer take-up trails in some polls. Microsoft is embedding Copilot and multimodal features into Windows and Office, and hardware partners are increasingly shipping devices with enhanced on‑device NPUs and Copilot+ signatures. That means:
- Enterprises and Windows power users may adopt Copilot not because it’s currently the top consumer referral platform, but because Copilot is tightly integrated into productivity workflows, enterprise identity and management controls.
- Hardware that accelerates on‑device AI (improved NPUs and platform optimisations) will materially shift the experience for local Copilot features — and that will influence uptake in professional settings where latency, privacy and offline capability matter. Uploaded analyses and vendor coverage of 2026 laptop platforms underscore this transition toward on‑device AI acceleration in Windows laptops.
Practical implications for WindowsForum readers — individuals, IT pros and businesses
For everyday Windows users
- Treat generative AI as an advanced productivity tool: use it to draft, summarise, plan and discover, but always verify outputs when stakes are high.
- Be mindful of privacy settings: free tier chat tools and mobile integrations differ in data collection and retention policies. If you use AI for work, separate personal and enterprise accounts when possible.
For IT administrators and in-house teams
- Audit shadow AI usage: workers will bring their own agents. Run quick surveys or telemetry checks to identify which tools staff are using unofficially.
- Define clear guardrails: draw operational distinctions between “assistive” (drafting, summarisation) and “decision‑grade” (compliance, legal, medical) uses.
- Prioritise education: short courses in prompt engineering, model evaluation and provenance checks will deliver outsized returns.
- Evaluate Copilot and enterprise copilots not only on accuracy but on identity, audit trails, and data-residency guarantees.
For marketers and publishers
- Prepare for generative-engine optimisation (GEO/AEO): if ChatGPT and other assistants remain major discovery surfaces, content creators must adapt to how models summarise, cite and synthesise web material. Statcounter’s referral metrics are a strong signal for this shift.
Risks, harms and regulatory questions
Core’s study highlights user reluctance to accept AI in emotionally charged roles. That consumer scepticism intersects with three broader risk categories that demand attention:- Hallucination and provenance risk: Generative models can fabricate plausible but false assertions. For information tasks and anything with legal or health consequences, hallucination risk is nontrivial and requires both technical guardrails and human review.
- Privacy and data governance: Many consumer AI tools collect interaction logs; when employees or customers discuss proprietary or sensitive matters inside a chatbot, data residency and confidentiality become top concerns. Enterprise copilots with on‑prem or managed-cloud options reduce exposure, but governance still matters.
- Economic and labour impact: The rapid mainstreaming of assistive AI shifts the tasks humans perform while creating demand for new supervisory and evaluation skills. Policy makers will need to balance upskilling programs with protections for workers whose roles are most exposed to automation.
Strategic recommendations for vendors, integrators and content creators
- Build with explicit boundaries: products that advertise AI assistance should be precise about what the assistant can and cannot do.
- Invest in verification tools: integrated citations, provenance traces and confidence scores are differentiators that build user trust — and reduce liability.
- Design for human‑centred workflows: position AI as an assistant, not a decision‑maker. Create easy handoffs from AI to human experts for high‑stakes tasks.
- Optimise for discovery in an AI era: creators should test how their content is summarised by popular assistants and consider structured data formats that make accurate citations more likely.
Cross-checking the claims: what independent data shows
I cross‑referenced Core’s reported platform rankings and adoption claims with two independent streams:- Behavioural referral metrics: Statcounter’s AI-chatbot referral tracking shows ChatGPT capturing the majority share of AI-chat referrals — a consistent external datapoint that supports Core’s finding of ChatGPT leadership in Ireland. That same data set shows current gaps for Google Gemini’s referral share compared to ChatGPT.
- Market user statistics and trend reports: industry dashboards and synthesis pieces from data providers (tracked in independent analyses) show ChatGPT’s user base and referral reach remain far greater than alternatives in many markets — a reality that helps explain why ChatGPT appears at the top in Core’s Irish survey. These aggregate data sources corroborate a pattern: platform concentration at discovery and uneven but growing adoption for productivity uses.
Strengths and notable contributions of Core’s report
- Timeliness and representativeness: A 2,000‑adult sample gives reasonable statistical power for national estimates and, crucially, a timely snapshot at a moment of fast change.
- Behavioral nuance: The survey separates use contexts and trust levels, which is more informative than simple “do you use AI?” questions.
- Actionable cues: Its emphasis on everyday utility tasks (navigation, travel, weather, recipes) helps vendors focus resources on practical features that will likely drive the next wave of user adoption.
Weaknesses, risks and things to watch
- Method transparency: The headline reporting does not publish full methodology or questionnaire wording; independent replication would strengthen confidence in the precise percentages.
- Platform confusion risk: Brand-level answers (e.g., “Meta AI”) can hide provider-split variance. Surveys should clarify the exact apps and integrations respondents mean.
- Fast obsolescence: The AI landscape changes quickly — platform updates, pricing changes, and new feature releases can shift user behaviour in months. Surveys that don’t capture ongoing telemetry risk lagging behind real usage patterns.
A short note on hardware, Windows and the future of on-device AI
The mainstreaming of AI is not only about who talks to which chatbot: it is increasingly about where inference happens. The Windows ecosystem is on a clear trajectory toward tighter Copilot integration and more capable on‑device AI, driven by silicon improvements and partner hardware roadmaps. Recent platform analysis has called out new laptop platforms and NPUs designed to push Copilot+ features into mainstream Windows machines — a trend that will matter for enterprise deployment choices and for privacy‑sensitive use cases that prefer local inference. For IT teams planning Copilot rollouts, hardware capability will become a procurement and policy consideration.Conclusion — what this means now and next
Core’s AI Connect 2026 is a useful, pragmatic wake‑up call: AI is not just a research topic anymore; for a meaningful minority in Ireland it has become a routine cognitive tool. That mainstreaming is selective — high trust for productivity and discovery, low trust for emotional and life‑critical domains — and it’s uneven across age and income groups. For Windows users, IT pros and content creators, the takeaways are clear:- Treat AI as an integrated productivity layer, not a magical replacement for human judgement.
- Prepare governance, identity and training controls before large-scale enterprise adoption.
- Optimise content and discovery strategies for the new generative-discovery era where ChatGPT and its peers shape what users see first.
- Expect platform leadership to matter for distribution; expect Copilot’s enterprise integration and on‑device AI acceleration to change the Windows productivity story in the coming quarters.
Source: AdWorld.ie New Research from Core Suggests AI Has Gone Mainstream | AdWorld.ie
