https://nocodelab.ai/assets/how-businesses-use-ai-DvcpPDjx.js

1import{j as e,P as g,I as f,J as b,L as d,at as w,Q as y}from"./index-AVLkCZeP.js";import{L as j}from"./lead-in-0DkVjwqy.js";import{C as v}from"./copy-page-button-B1HSZ4cw.js";const m="/downloads/NoCodeLab-AI-Usage-Benchmark.pdf",u="How UK, Ireland and Italy use AI at work.pdf",x="PDF, 11 pages, 487 KB";function s({children:t}){return e.jsx("section",{className:"container-wide mt-6",children:e.jsx("div",{className:"rounded-block px-6 py-12 sm:px-12 sm:py-16",children:t})})}function a({index:t,blurb:n,children:o}){return e.jsxs("div",{className:"mb-10",children:[e.jsx("div",{className:"h-px w-full bg-foreground/15 mb-6","aria-hidden":"true"}),e.jsxs("div",{className:"flex items-baseline gap-3 flex-wrap",children:[e.jsx("span",{className:"font-mono text-[22px] sm:text-[26px] leading-none opacity-80",style:{color:"var(--terracotta)"},"aria-hidden":"true",children:t}),o]}),n?e.jsx("p",{className:"mt-3 text-[15px] text-foreground/70 max-w-[720px]",children:n}):null]})}function i({columns:t,rows:n,caption:o}){return e.jsxs("div",{className:"max-w-[820px]",children:[e.jsx("div",{className:"overflow-x-auto rounded-[16px] border border-foreground

1/10",children:e.jsxs("table",{className:"w-full min-w-[440px] border-collapse text-[15px]",children:[e.jsx("thead",{children:e.jsx("tr",{className:"bg-foreground/[0.04]",children:t.map((r,l)=>e.jsx("th",{scope:"col",className:`px-4 py-3 text-[11px] font-mono font-bold uppercase tracking-[0.14em] text-foreground/60 ${l===0?"text-left":"text-right"}`,children:r},r))})}),e.jsx("tbody",{children:n.map(r=>e.jsx("tr",{className:"border-t border-foreground/10",children:r.map((l,p)=>e.jsx("td",{className:`px-4 py-3 leading-[1.6] ${p===0?"text-left text-foreground/85":"text-right font-mono tabular-nums text-foreground/75"}`,children:l},p))},r[0]))})]})}),o?e.jsx("p",{className:"mt-3 text-[13px] leading-[1.6] text-foreground/60",children:o}):null]})}function c({value:t,label:n}){return e.jsxs("div",{className:"md:border-l md:border-white/25 md:pl-6 md:first:border-l-0 md:first:pl-0",children:[e.jsx("div",{className:"font-sans text-[52px] leading-none tracking-tight md:text-[64px] font-bold text-white",children:t}),e.jsx("div",{className:"mt-4 text-[11px] uppercase tracking-[0.2em] text-white/80",children:n})]})}function h({tag:t,heading:n,children:o}){return e.jsxs("div",{children:[e.jsx("span",{className:"text-[10px] font-mono font-bold uppercase tracking-[0.22em] block mb-3",style:{color:"var(--terracotta)"},children:t}),e.jsx("h3",{className:"font-sans font-bold text-[19px] tracking-tight mb-3",children:n}),e.jsx("div",{className:"space-y-3 text-[15px] leading-[1.7] text-foreground/75",children:o})]})}function A(){return e.jsxs("div",{className:"pt-6 pb-10 px-3",children:[e.jsx("section",{className:"container-wide",children:e.jsxs("div",{className:"rounded-block px-6 pt-14 pb-12 sm:px-12 sm:pt-20 sm:pb-14",children:[e.jsx(j,{eyebrow:e.jsx(g,{children:"AI Usage Benchmark"}),meta:"11 min read · July 2026",title:"How the UK, Ireland and Italy actually use AI at work",subtitle:"We have a Ferrari. We use it to drive to the shops.",lead:"Two of the largest AI companies published what their users do all day. We read both, ran the comparison for our three markets, and checked every figure against the published datasets rather than the coverage of them. The single most common work task a UK professional gives AI is writing a business email."}),e.jsx(f,{authors:b("Sara Simeone and Deborah Cleary"),meta:"NoCodeLab, UK · Ireland · Italy"}),e.jsxs("div",{className:"mt-8 flex flex-wrap items-center gap-3",children:[e.jsx("a",{href:m,download:u,className:"btn-primary",children:"Download the full report"}),e.jsx(v,{})]}),e.jsxs("p",{className:"mt-3 text-[13px] text-foreground/55",children:[x,". Free, no email required."]})]})}),e.jsxs("div",{"data-copy-root":!0,children:[e.jsx("section",{className:"container-wide mt-6",children:e.jsxs("div",{className:"rounded-block px-6 py-10 md:px-14 md:py-14",style:{backgroundColor:"var(--petrol)"},children:[e.jsx("p",{className:"text-[11px] uppercase tracking-[0.2em] text-white/70 mb-8",children:"Anthropic Economic Index, May 2026 · Google ATLAS v1.0 · ONS, June 2026"}),e.jsxs("div",{className:"grid grid-cols-1 gap-10 md:grid-cols-3 md:gap-6",children:[e.jsx(c,{value:"2.39%",label:"Of UK conversations are writing an email"}),e.jsx(c,{value:"68/21",label:"Percent of occupations, percent of their tasks"}),e.jsx(c,{value:"28%",label:"Of UK micro businesses use any AI"})]})]})}),e.jsx("section",{className:"container-wide mt-6",children:e.jsxs("div",{className:"rounded-block px-6 py-12 sm:px-12 sm:py-16",children:[e.jsx("p",{className:"label-eyebrow mb-8",children:"Why these three countries"}),e.jsxs("div",{className:"grid grid-cols-1 gap-x-14 gap-y-6 md:grid-cols-2",children:[e.jsxs("div",{className:"space-y-5",children:[e.jsx("p",{className:"text-[17px] leading-[1.65] text-foreground/85",children:"Between us we are Ital

1ian and Irish, and we are both based in the UK. Three markets, one company, and a long-running argument about whether people in each of them actually use AI the same way."}),e.jsx("p",{className:"text-[15px] leading-[1.7] text-foreground/75",children:"We train and build in all three, so the answer is not academic for us. It decides what a workshop in Dublin opens with, what a Milan engagement leads on, and which examples land in a London boardroom."})]}),e.jsxs("div",{className:"space-y-5",children:[e.jsx("p",{className:"text-[15px] leading-[1.7] text-foreground/75",children:"When Anthropic published its Economic Index, we went looking for the answer. Then Google released ATLAS, built on nearly 15 million Gemini interactions. Two of the largest AI companies had each published what their users really do all day. We could not find the two read side by side against the countries we work in, so we did it ourselves."}),e.jsx("p",{className:"text-[17px] leading-[1.65] font-bold text-foreground",children:"What we found stopped us."})]})]})]})}),e.jsxs(s,{children:[e.jsx(a,{index:"01",blurb:"Anthropic publishes its request data as a tree. At the finest level it reports, the largest single work task in the UK is business correspondence, at 2.39% of all UK Claude conversations. Nothing else that counts as a discrete work task comes close.",children:e.jsx("h2",{className:"font-sans font-bold text-[24px] sm:text-[30px] tracking-tight leading-tight",children:"What people actually use AI for at work"})}),e.jsx("p",{className:"text-[15px] leading-[1.7] text-foreground/75 max-w-[820px] mb-8",children:"Content creation and copywriting is the biggest category of any kind, at 21.5% in the UK and 22.7% worldwide. The tasks a business would actually pay for sit far below."}),e.jsx(i,{columns:["Work task (UK)","Share"],rows:[["Business correspondence (emails)","2.39%"],["Post copywriting","1.62%"],["Marketing copy","1.37%"],["Scheduled reporting","1.21%"],["Presentation authoring","1.08%"],["Recruitment and HR operations","0.57%"],["Knowledge base authoring","0.55%"],["Business reports","0.47%"],["Financial modelling","0.35%"],["Invoicing","0.24%"]],caption:"Every row is a leaf-level task, the most granular unit Anthropic publishes. Broader cluster

1s sit above these and are labelled as clusters wherever we use them. Source: Anthropic Economic Index, May 2026."}),e.jsxs("div",{className:"mt-12 max-w-[820px]",children:[e.jsx("h3",{className:"font-sans font-bold text-[19px] tracking-tight mb-4",children:"Two numbers people will get wrong"}),e.jsxs("div",{className:"grid grid-cols-1 md:grid-cols-2 gap-x-12 gap-y-8",children:[e.jsxs("div",{children:[e.jsx("p",{className:"font-sans font-bold text-[30px] leading-none tracking-tight mb-3",style:{color:"var(--terracotta)"},children:"3.66%"}),e.jsx("p",{className:"text-[15px] leading-[1.7] text-foreground/75",children:"Starting a business looks like it beats email. It does not compete on the same footing: it is a cluster one level up the tree, holding competitive research, product comparison, market sizing and entrepreneurship guidance together."})]}),e.jsxs("div",{children:[e.jsx("p",{className:"font-sans font-bold text-[30px] leading-none tracking-tight mb-3",style:{color:"var(--terracotta)"},children:"5.57%"}),e.jsx("p",{className:"text-[15px] leading-[1.7] text-foreground/75",children:"Searching electronic sources for information is the UK's top entry in a separate classification, the US occupational task catalogue. Both lenses are legitimate. A number from one cannot be ranked against a number from the other."})]})]}),e.jsx("p",{className:"mt-8 text-[15px] leading-[1.7] text-foreground/75",children:"What survives both readings is the same picture. We have built the most capable reasoning tools in commercial history, and the most common thing we ask them to do is look something up and write it up nicely."})]})]}),e.jsxs(s,{children:[e.jsx(a,{index:"02",blurb:"Google's data answers the same question from a completely different angle, and lands in the same place.",children:e.jsx("h2",{className:"font-sans font-bold text-[24px] sm:text-[30px] tracking-tight leading-tight",children:"How much of the average job AI actually touches"})}),e.jsxs("div",{className:"max-w-[820px] space-y-4 text-[15px] leading-[1.7] text-foreground/75",children:[e.jsx("p",{children:"AI has reached 68% of all occupations, which is two in three rather than all of them. But in the median occupation where it is used at all, it touches just 21% of the tasks. Only 3% of occupations show AI use across more than three quarters of their work: software QA testers, HR specialists and document management specialists. Read those three carefully, because their task catalogues absorb requests from adjacent work, which lifts them up the depth ranking."}),e.jsx("p",{className:"font-bold text-foreground",children:"Broad, and shallow. Two thirds of occupations touched, a fifth of the tasks inside them."}),e.jsx("p",{children:"Anthropic's classifier also estimates how long each task would take a person working alone, and those estimates run well ahead of the time the conversations themselves take. We have deliberately not put a ratio on that, and you should be sceptical of anyone who does. It is a model-generated estimate rather than a measurement, it is bucketed by order of magnitude, and a finished conversation is not the same thing as a finished job. Fewer than one in ten conversations involving complex cognitive work is even an attempt to complete the task end to end. The direction is real. The multiple is not something either dataset can support."})]})]}),e.jsxs(s,{children:[e.jsx(a,{index:"03",blurb:"Anthropic's usage index divides a country's share of Claude usage by its share of working-age population, so 1.0 means usage exactly proportional to population. All three markets run well ahead of parity. None of them lead.",children:e.jsx("h2",{className:"font-sans font-bold text-[24px] sm:text-[30px] tracking-tight leading-tight",children:"Italy buys automation, the UK buys process, Ireland buys positioning"})}),e.jsx("div",{className:"mb-12",children:e.jsx(i,{columns:["Market","Usage index","Rank"],rows:[["United Kingdom","3.35","16 of 121"],["Ireland","3.23","18 of 121"],["Italy","1.70","39 of 121"],["Population parity","1.00","the neutral line"]],caption:"Source: Anthropic Economic Index, May 2026."})}),e.jsxs("div",{className:"grid grid-cols-1 md:grid-cols-3 gap-x-10 gap-y-10",children:[e.jsxs(h,{tag:"UK",heading:"Advice and administration",children:[e.jsx("p",{children:"Adv

1ice and recommendations make up 13.6% of everything Claude produces for UK users against 10.7% globally, the single largest deviation in the UK's output profile. It leads the three markets on business process and operations at 4.8%, and has the highest share of study-related use at 17.5%. It is also the most hands-on: 55.2% of UK conversations are collaborative rather than hand-offs, against 51.4% worldwide."}),e.jsx("p",{children:"Two caveats, and we would rather say them than have someone else find them. Ireland produces more advice than the UK does, at 15.5%. And the UK's work share, 39.0%, sits below the global 43.4%."})]}),e.jsxs(h,{tag:"IE",heading:"Careers and self",children:[e.jsx("p",{children:"Nearly 48% of Irish conversations are personal rather than work or study, the highest of the three, and its work share is the lowest at 36.3%. Health questions run higher than either neighbour, at 1.88% against the UK's 1.48% and Italy's 1.46%."}),e.jsx("p",{children:"Its standout is careers. CV writing accounts for 1.57% of all Irish conversations against the UK's 0.93% and Italy's 0.43%. Grouped, the careers work comes to roughly 5.4% of everything Irish users do, against 3.9% in the UK and 1.9% in Italy."})]}),e.jsxs(h,{tag:"IT",heading:"Building and processing",children:[e.jsx("p",{children:"Italy ranks lowest of the three on the usage index, but the mix is the most technical and the most work-oriented: 42.9% of Italian conversations are work, against 39.0% in the UK and 36.3% in Ireland."}),e.jsx("p",{children:"Software development is 11.5% of Italian conversations, matching the global average, while the UK sits at 8.2%. Document processing runs 5.3% against the UK's 3.1%. Translation is four times the UK rate. Presentation authoring is the highest of the three at 1.67%."})]})]})]}),e.jsxs(s,{children:[e.jsx(a,{index:"04",blurb:"The same measures across the three markets. Compare a row across the markets rather than one row against another.",children:e.jsx("h2",{className:"font-sans font-bold text-[24px] sm:text-[30px] tracking-tight leading-tight",children:"Where the three markets diverge"})}),e.jsx(i,{columns:["Measure","UK","Ireland","Italy"],rows:[["Advice and recommendations","13.6%","15.5%","10.4%"],["Careers cluster","3.9%","5.4%","1.9%"],["CV writing","0.93%","1.57%","0.43%"],["Software development","8.2%","7.6%","11.5%"]],caption:"Global averages: advice 10.7%, software development 11.5%. The careers cluster is our own grouping, not a category the dataset defines. CV writing is a single leaf-level task. Source: Anthropic Economic Index, May 2026."}),e.jsxs("div",{className:"mt-12",children:[e.jsx("h3",{className:"font-sans font-bold text-[19px] tracking-tight mb-2",children:"The work and personal split"}),e.jsx("p",{className:"text-[15px] leading-[1.7] text-foreground/75 max-w-[820px] mb-6",children:"Italy is the only one of the three close to the global work share. Ireland is the furthest from it."}),e.jsx(i,{columns:["Market","Work","Personal","Coursework"],rows:[["Italy","42.9%","40.9%","16.2%"],["United Kingdom","39.0%","43.5%","17.5%"],["Ireland","36.3%","47.9%","15.8%"],["Global average","43.4%","40.2%","16.5%"]],caption:"Share of all classified conversations. Source: Anthropic Economic Index, May 2026."})]})]}),e.jsxs(s,{children:[e.jsx(a,{index:"05",blurb:"A trap worth flagging, because it will be quoted widely and it is misleading.",children:e.jsx("h2",{className:"font-sans font-bold text-[24px] sm:text-[30px] tracking-tight leading-tight",children:"Why the 13% against 43% work statistic is wrong"})}),e.jsxs("div",{className:"max-w-[820px] space-y-4 text-[15px] leading-[1.7] text-foreground/75",children:[e.jsx("p",{children:"Google's data says 13% of Gemini conversations are work-related. Anthropic's says 43.4%. That is a 3.3x gap, and it looks like a profound finding about how differently people use the two tools."}),e.jsx("p",{children:"It is not. ATLAS covers the Gemini App, Google AI Mode and the Gemini API, but the 13% work share is computed on the consumer surfaces, which reach a search audience of over a billion monthly users. Google itself names that audience composition as a possible complete explanation for the difference. Anthropic's figure covers a paid assistant that people open deliberately."}),e.jsx("p",{className:"font-bold text-foreground",children:"Quote either number on its own and you have described a product's audience, not a workforce."})]})]}),e.jsxs(s,{children:[e.jsx(a,{index:"06",blurb:"Neither AI study reports anything by company size. The UK's Office for National Statistics does, and the picture is stark.",children:e.jsx("h2",{className:"font-sans font-bold text-[24px] sm:text-[30px] tracking-tight leading-tight",children:"AI adoption among UK SMEs"})}),e.jsx(i,{columns:["Business size","Using at least one AI technology"],rows:[["0 to 9 staff (micro)","28%"],["10 or more staff","35%"],["250 or more staff","49

1%"]],caption:"Firms using at least one AI technology on the ONS definition, which counts named technologies rather than any tool with an AI feature in it. Private surveys using the looser definition report UK adoption above 50%. Source: ONS, Artificial intelligence in UK businesses, 2023 to 2026."}),e.jsxs("div",{className:"mt-8 max-w-[820px] space-y-4 text-[15px] leading-[1.7] text-foreground/75",children:[e.jsx("p",{children:"Among firms that have adopted, around three fifths use AI to improve business operations. And adoption stays shallow: the average adopter runs 1.6 AI technologies, barely up from 1.4 in late 2023."}),e.jsx("p",{children:"So the honest summary is not that small businesses use AI badly. Most do not use it at all. Among those who do, the work is orientation and communication rather than operations."}),e.jsx("p",{children:"There is one bright spot, and it is a large one. Starting a business, the cluster covering competitive research, product comparison, market sizing and entrepreneurship guidance, accounts for 3.66% of UK conversations, 3.83% in Ireland and 3.16% in Italy. In all three markets that cluster outranks every named business-operations cluster. People bring AI the decision. They just do not yet bring it the work that follows."})]})]}),e.jsxs(s,{children:[e.jsx(a,{index:"07",children:e.jsx("h2",{className:"font-sans font-bold text-[24px] sm:text-[30px] tracking-tight leading-tight",children:"The gap is the opportunity"})}),e.jsxs("div",{className:"max-w-[820px] space-y-4 text-[15px] leading-[1.7] text-foreground/75",children:[e.jsx("p",{children:"None of this is a criticism of anyone. It is where the technology sits a few years into public use, and the same pattern appeared in two independent datasets built by two competing labs."}),e.jsxs("p",{children:["But the distance between what these tools can do and what we currently ask of them is the entire commercial opportunity of the next few years. It closes fastest for people who"," ",e.jsx(d,{to:"/the-lab",className:"underline decoration-foreground/30 hover:decoration-foreground",children:"learn to drive it properly"}),", and it closes first inside organisations that treat this as a skill to be taught rather than a licence to be bought."]}),e.jsx("p",{children:"We are a training business, so of course we would say that. The numbers are public. Check them."})]})]}),e.jsxs(s,{children:[e.jsx(a,{index:"08",children:e.jsx("h2",{className:"font-sans font-bold text-[24px] sm:text-[30px] tracking-tight leading-tight",children:"Questions we get asked about this data"})}),e.jsx("div",{className:"max-w-[820px] space-y-8",children:w.map(t=>e.jsxs("div",{children:[e.jsx("h3",{className:"font-sans font-bold text-[17px] tracking-tight mb-2",children:t.q}),e.jsx("p",{className:"text-[15px] leading-[1.7] text-foreground/75",children:t.a})]},t.q))})]}),e.jsxs(s,{children:[e.jsx(a,{index:"09",blurb:"Three primary sources, and the cross-comparison done ourselves. No figure here is second-hand reporting.",children:e.jsx("h2",{className:"font-sans font-bold text-[24px] sm:text-[30px] tracking-tight leading-tight",children:"Methodology and sources"})}),e.jsxs("div",{className:"max-w-[820px] space-y-5 text-[15px] leading-[1.7] text-foreground/75",children:[e.jsxs("p",{children:[e.jsx("span",{className:"font-bold text-foreground",children:"Claude usage figures"})," come from the"," ",e.jsx("a",{href:"https://www.anthropic.com/economic-index",className:"underline decoration-foreground/30 hover:decoration-foreground",target:"_blank",rel:"noopener noreferrer",children:"Anthropic Economic Index"}),", May 2026 period, covering 121 countries with published detail down to region and subtopic level."]}),e.jsxs("p",{children:[e.jsx("span",{className:"font-bold text-foreground",children:"Gemini usage figures"})," come from Google's AI & Economy ATLAS v1.0, published 23 July 2026, covering 14,653,926 de-identified interactions across the Gemini App, Google AI Mode and the Gemini API. The 13% work share we quote is computed on the consumer surfaces, not on the API."]}),e.jsxs("p",{children:[e.jsx("span",{className:"font-bold text-foreground",children:"UK business adoption figures"})," come from the Office for National Statistics release"," ",e.jsx("a",{href:"https://www.ons.gov.uk/businessindustryandtrade/business/businessservices/articles/artificialintelligenceinukbusinesses/2023to2026",className:"underline decoration-foreground

1/30 hover:decoration-foreground",target:"_blank",rel:"noopener noreferrer",children:"Artificial intelligence in UK businesses, 2023 to 2026"}),"."]}),e.jsxs("p",{children:[e.jsx("span",{className:"font-bold text-foreground",children:"How we read the Anthropic tree."})," ","Request data is published as a hierarchy. Individual tasks such as business correspondence sit at the leaf level; groupings such as starting a business or translation sit above them. We label clusters as clusters, and we never rank a cluster against a leaf. Where we group tasks ourselves, as with the careers figures, that grouping is ours and not a category the dataset defines. Anthropic separately maps the same conversations onto the US occupational task catalogue, which is a different classification and cannot be compared line by line with the request tree."]}),e.jsxs("p",{children:[e.jsx("span",{className:"font-bold text-foreground",children:"Limitations we think you should know about."})," ","Both AI studies describe observed usage of their own product, not AI adoption across the market. Both are single-month snapshots with no trend series, so nothing here shows growth or decline. Neither identifies users, employers or company size, which is why the SME figures come from the ONS instead. Shares are of all classified conversations, so a topic at 2% of everything is a considerably larger share of the working subset. Not published means an entry fell below the privacy threshold and never means a measured zero. Both studies map conversations onto US occupational taxonomies, and Google notes this makes it difficult to judge whether an occupation is over-represented outside the United States."]}),e.jsx("p",{className:"text-foreground/60",children:"Every figure was re-verified against the published datasets at source on 29 July 2026. If you spot an error in our reading of these datasets, tell us and we will correct it publicly."})]})]})]}),e.jsx("section",{className:"container-wide mt-6",children:e.jsxs("div",{className:"rounded-block px-6 py-10 md:px-14 md:py-14",style:{backgroundColor:"var(--petrol)"},children:[e.jsx("p",{className:"text-[11px] uppercase tracking-[0.2em] text-white/70 mb-4",children:"The full benchmark"}),e.jsxs("div",{className:"flex flex-col gap-8 md:flex-row md:items-end md:justify-between",children:[e.jsxs("div",{className:"max-w-[540px]",children:[e.jsx("h2",{className:"font-sans font-bold text-[26px] sm:text-[32px] tracking-tight leading-tight text-white",children:"Every chart, every source, every contested number"}),e.jsx("p",{className:"mt-4 text-[15px] leading-[1.7] text-white/80",children:"The designed edition of this analysis, including the three-market comparison charts, the world usage map and the page listing every figure we think you should read with caution. Built for circulating to a team rather than reading on a phone."})]}),e.jsxs("div",{className:"shrink-0",children:[e.jsx("a",{href:m,download:u,className:"inline-flex items-center rounded-full bg-white px-7 py-3.5 text-[15px] font-bold tracking-tight text-black transition-opacity hover:opacity-90",children:"Download the report"}),e.jsx("p",{className:"mt-3 text-[12.5px] text-white/60",children:x})]})]})]})}),e.jsx("section",{className:"container-wide mt-6",children:e.jsxs("div",{className:"rounded-block px-6 py-10 sm:px-12 sm:py-12",children:[e.jsx("p",{className:"label-eyebrow mb-6",children:"Keep going"}),e.jsxs("div",{className:"flex flex-col sm:flex-row gap-4",children:[e.jsxs(d,{to:"/tools/roi-calculator",className:"group flex-1 p-6 rounded-[20px] border border-foreground

1/10 bg-background hover:border-foreground/40 transition-colors",children:[e.jsx("span",{className:"text-[10px] font-mono font-bold uppercase tracking-widest text-foreground/60 block mb-3",children:"Free tool"}),e.jsx("span",{className:"font-sans font-bold text-[18px] tracking-tight block mb-1",children:"The ROAI Calculator"}),e.jsx("span",{className:"text-[14px] text-foreground/70",children:"Put a number on the gap inside your own business, not the market's."})]}),e.jsxs(d,{to:"/ai-agents",className:"group flex-1 p-6 rounded-[20px] border border-foreground/10 bg-background hover:border-foreground/40 transition-colors",children:[e.jsx("span",{className:"text-[10px] font-mono font-bold uppercase tracking-widest text-foreground/60 block mb-3",children:"The full guide"}),e.jsx("span",{className:"font-sans font-bold text-[18px] tracking-tight block mb-1",children:"AI Agents"}),e.jsx("span",{className:"text-[14px] text-foreground/70",children:"What sits beyond writing an email, and how the five we run with clients work."})]})]})]})}),e.jsx(y,{})]})}export{A as component};