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AI vs Designers in 2026 — A Conversation with Margot Ellery

Printablemenulab — Mon, 01 Jun 2026 15:26:57 +0000

In Conversation · Design Tools

“The designer didn’t disappear. The designer got asked to be six people.”

Margot Ellery on what twelve years inside UK magazine publishing taught her about how AI has actually changed the design profession — the freelancers being squeezed out, the small restaurants making their own logos, and why the tools that “democratised design” are now charging serious money to keep using.

Margot Ellery, Editor, Printable Menu Lab. Photograph: house archive.

§ 01 · What actually happened

“AI didn’t replace the graphic designer. It replaced about thirty percent of what a designer used to bill for.”

Margot, there is a familiar story circulating among designers right now — that AI has replaced them overnight, that the profession is dying, that twenty-five years of experience now counts for nothing. How accurate is that picture?

Partially accurate. The dramatic version of the story circulates because it feels true to anyone who has been freelancing in the last eighteen months. The honest version is more complicated. What AI has done is replace the lower-value end of design work — the quick logo, the social tile, the simple menu update, the email banner, the trade-show poster mockup — with something the client can produce in twenty minutes for the price of a cup of coffee. That work used to pay a freelancer five hundred to fifteen hundred pounds a month if you stacked enough small clients. It doesn’t any more. That is the part of the story that is true.

And the part that is more complicated?

The higher-value end of design work has actually become more, not less, valuable. Brand identity that needs to be coherent across thirty touchpoints, editorial systems that have to hold together across years, print production for fine printing on unusual stocks, packaging that needs to survive being scanned at a till and photographed for Instagram — that work is the same work as it was five years ago, and it pays well. What has happened is that the middle has hollowed out. The bottom is now AI plus the client themselves. The top is still designers. There is no middle.

For a designer who has spent their career in that middle, what does this actually look like in 2026?

It looks like one of three things. They either retrained towards the top — got serious about brand strategy, art direction, complex production — or they retrained sideways into roles where design is one skill among several, like marketing manager or content lead. Or they left the profession. I know a fair number of people who took all three paths. The ones who took the third path are the ones writing the catastrophe pieces on LinkedIn. The other two are doing fine, or at least no worse than they were doing in 2021.

§ 02 · The expanding job description

“The job advert used to say ‘graphic designer.’ Now it asks for nine people.”

There’s a recurring complaint I see online — that small companies expect a graphic designer to also be a UI/UX designer, a video editor, an animator, a front-end developer, a copywriter, and a social media manager. Is this real or just venting?

It is entirely real. I have seen job postings in the last six months asking for proficiency in Adobe Creative Suite, Figma, After Effects, Premiere Pro, Canva, HTML and CSS, a working knowledge of WordPress, basic copywriting skills, social media management experience, and the ability to operate a TikTok strategy. The salary band is sometimes thirty thousand pounds. That is one person being asked to do the work that used to be done by five specialists, for the wage of a junior copywriter. It is not a sustainable expectation, but it is the expectation that employers have set.

Where did this come from?

Three things compounded. First, the tools genuinely got better. Figma made UI design accessible to print designers; Premiere Pro became smooth enough to be picked up alongside other Adobe products; Canva absorbed enough animation features that motion graphics felt less like a specialism. So employers reasoned that one well-rounded person should be able to handle it all. Second, budgets were tight, especially for small businesses and creative agencies through 2022 and 2023. Hiring five specialists was no longer feasible for most teams. So they hired one generalist and asked them to do the work of five. And third — the part nobody talks about openly — designers themselves contributed to the dynamic by accepting it. The market punished the ones who said no. The ones who said yes kept their jobs. And so the new normal got set.

And now AI sits on top of all of that.

Now AI sits on top of all of that. Which has two effects, both of them complicated. The first is that AI absorbs some of the work the generalist designer was already drowning in — quick social tiles, video subtitles, image upscaling, background removal, simple animation, draft copy. That should be good news for the designer. The second effect is that employers see this and assume the designer can therefore do even more, because they now have AI helping them. So the job description expands again. The designer who used to do five jobs is now doing seven, with AI doing the work of perhaps two of those seven invisibly in the background. The total workload, measured in things the designer is held accountable for, has gone up.

Figure 1 · What “graphic designer” has come to mean

The skill stack of one designer, over thirty years.

§ 03 · The logo and the menu

“The freelance logo at three hundred pounds is the work most directly replaced. And it’s the work that used to fund freelance careers.”

For the readers of this publication specifically — small business owners who design their own menus, certificates, invitations — what does the AI shift actually look like in practice?

It looks like the small café owner I’ve mentioned before, who designed her own menus on Canva on a Sunday afternoon. She had access to AI-generated background images for the headers, AI-generated icons for the menu categories, and AI-generated colour-palette suggestions that matched her interior. None of that existed in usable form in 2020. All of it existed by 2024. By 2026, it’s built into Canva natively. She made a menu that would have cost her four hundred to seven hundred pounds at a small design studio five years ago, for the cost of her Canva Pro subscription. The work was good. The freelance designer who used to do that work for her, however, has lost that client and another twenty like her.

And logos specifically?

Logos are the most directly affected. A small business that needed a logo in 2020 had three paths. Pay a designer eight hundred to three thousand pounds for a proper identity. Use a marketplace like 99designs and crowdsource it for three hundred. Or use a logo-builder tool and produce something acceptable for fifty. In 2026, the fourth path has effectively eaten the second and third paths and is starting to eat the bottom of the first. AI generates a logo concept in thirty seconds. Tools like LogoAI, Looka, Brandmark, and increasingly Canva’s own brand kit feature, will iterate on it until the small business owner has something they’re satisfied with. The total cost is the monthly subscription. The freelance market for small-business logos has, frankly, collapsed in the last eighteen months.

Are the AI logos any good?

This is the question that designers and clients answer differently. Designers will tell you, accurately, that AI logos lack typographic discipline, that the symbol marks are generic, that the colour systems don’t scale across applications, and that an AI logo will look dated within eighteen months. All of that is true. Clients will tell you, also accurately, that their AI logo looks fine on the menu, on the business card, on the Instagram bio, and on the awning. And that they spent twenty pounds on it rather than eighteen hundred. The market is making its preference clear, and the market is not in the designer’s favour.

Table I — What a small business pays now versus what they used to pay
Design deliverable	Freelance (2020)	AI route (2026)	Quality gap
Small restaurant menu	£400–£800	£15/month subscription	Small for casual use
Logo for a single-location café	£800–£2,500	£20–£60 one-off	Medium — scales poorly
Wedding invitation suite	£500–£1,500	£12–£30 template + AI imagery	Negligible if customised well
Small-business brand kit	£1,500–£5,000	£30–£200 one-off	Large — AI lacks coherence across applications
Print certificate, party flyer	£100–£400	Template + AI image, under £10	None for one-off use
Editorial layout (magazine)	£3,000+	Not yet replaceable	Substantial — AI fails on multi-page systems
Packaging design	£2,000+	Not yet replaceable for retail	Substantial — print production constraints

Figures reflect UK small-business design market rates. “Quality gap” reflects average outputs; high-skill use of AI tools can narrow the gap, while low-skill use widens it.

“

The tools that “democratised” design have started charging serious money. The freelance designers who survived the first wave are now spending a meaningful share of their margin on the AI subscriptions they had been told would liberate them.

Margot Ellery

§ 04 · The cost backside

“A designer running ten client projects on GPT-image-2 at retail rates is now spending three hundred pounds a month on what used to be free Photoshop time.”

There’s a part of this story that isn’t often told — the cost of the AI tools themselves. Walk us through what that looks like for a working freelance designer in 2026.

It’s a real and growing expense, and it gets very little attention compared to the “AI is free” narrative. A freelance designer running ten to fifteen small client projects per month, generating perhaps fifty images per project across drafts and final outputs, is now spending somewhere between one hundred and four hundred pounds a month on AI image generation alone — before the cost of Midjourney, of Canva Pro, of Adobe Creative Cloud, of any video tool, or of any subscription stack. The cost is variable. It depends on which model they’re using, how often they iterate, and whether they generate at high resolution. But it adds up faster than people expect.

What are the main models people are running?

Midjourney for general illustration and stylised imagery; DALL-E and its successor models for things that need to be more literal; Stable Diffusion for designers who want local control; and increasingly OpenAI’s GPT-image-2 for designers working inside ChatGPT or via the API, especially for product mockups and lifestyle imagery. The pricing varies considerably. GPT-image-2 at the retail API rate is, for example, ten cents per high-quality image. That sounds nothing. Multiplied by five hundred generations a month, it’s fifty pounds in raw inference. Multiplied by an agency-scale workflow with three thousand generations a month, it’s three hundred pounds. That money used to be entirely in the designer’s margin.

And there’s a response to this happening on the procurement side?

There is, and it’s the part of the conversation that working designers actually talk about — not whether AI will replace them, but how to keep their margin intact now that AI consumes a meaningful chunk of it. Most freelance designers I know are spending a bit of time figuring out how to buy cheap gpt-image-2 credits and Midjourney credits in bulk, rather than paying the retail subscription rate. The marketplaces that have emerged in the last twelve months aggregate enterprise-bought credits and resell them to small users at margins of fifteen to forty percent below list price. For a working designer that’s the difference between making a 20 percent margin on a client project and a 28 percent margin. Multiplied across a year of project work, it’s the difference between a frustrating year and a viable one.

Is this becoming standard practice?

Among the designers paying attention, yes. Among the designers still on the fence about whether to engage with AI at all, no. The first group is treating their AI costs the way agencies have always treated their software stack — as a recurring expense that needs to be procured intelligently. The second group is still paying retail rates because they haven’t had a serious conversation with themselves about what the tools actually cost. The gap between those two groups, measured in annual margin, is now somewhere between five and ten thousand pounds. It’s the difference between feeling like you’re running a business and feeling like you’re working for the tool providers.

§ 05 · Who wins, who loses

“The interesting thing is not that AI killed graphic design. It’s that AI redistributed who gets to do it.”

If we zoom out from the individual freelance experience and look at the profession as a whole, who has gained from this shift?

Three groups, broadly. First, small business owners and the self-employed who previously couldn’t afford a designer at all. Their access to acceptable design has expanded dramatically. The local hairdresser who couldn’t justify a four-hundred-pound logo can now have one for nothing. The community theatre that used to print posters from a Word template now produces something genuinely attractive. The neighbourhood coffee shop, the wedding photographer’s own marketing, the small accountancy practice — all of them now look better than they did in 2018, and at no incremental cost. That’s a real welfare gain, even if it comes at the cost of someone else’s livelihood.

Second group?

Senior designers who specialised hard. Brand strategists, art directors at established agencies, designers running their own studios with reputation and clientele built over fifteen or twenty years. These people are doing well. Their work is now harder to commodify, more clearly differentiated from the AI alternative, and more valuable than ever to clients who care about brand-level outcomes rather than asset-level outputs. The number of these designers is small relative to the profession, but their hourly rates are up, their backlog is full, and their work is more interesting than it was five years ago.

And the third?

The designers who pivoted into adjacent roles. Marketing managers, content leads, product managers at small software companies, in-house creative directors. These are roles where design is one of several core skills, and they reward generalists with strong visual judgement. Many of the displaced freelancers landed here, and most of them are reporting that they’re happier than they were as freelancers — more stable income, less feast-or-famine billing, more interesting cross-functional work. It’s a real path that doesn’t get enough credit in the “designers are dying” narrative.

Who has lost?

The middle. Specifically: mid-career freelance generalists working in the small-business segment. Ages roughly thirty-five to fifty-five, ten to twenty years of experience, billing the bulk of their work at three to fifteen hundred pounds per project. Their work has been most directly replaced. Their costs have gone up because of the AI subscriptions. They are too senior to compete with junior generalists on price and not specialised enough to compete with senior designers on craft. That group is genuinely struggling. The story of design in 2026 is mostly about what’s happening to that group, and the broader narrative gets it mostly wrong by attributing the cause to AI alone rather than to a market structure that was already shifting against them.

§ 06 · What to do with all this

“Stop fighting the tools. Start procuring them properly.”

If a small business owner is reading this and trying to design their own menu or invitation, what should they take away?

That you have access to better tools than any small business has ever had, and that the tools are improving faster than you can read about them. Use them. The cafe owner with the menu was right. The wedding planner customising her own template was right. The school deputy head designing certificates on a sixty-pound budget is right. You don’t need to feel guilty about not hiring a designer for work that AI can handle adequately. You do need to be honest about when the work has outgrown the tools — brand identity that has to last a decade, packaging that has to survive at retail, anything print-production complex — and at that point hire a designer worth their fee.

And to working designers?

Two things. Procurement and positioning. On procurement: stop paying retail for your AI credits. If you are running a freelance practice and not buying through a marketplace, you are leaving fifteen to forty percent of your AI margin on the table for no reason. On positioning: identify what part of your work AI is actually replacing, and stop selling that part. Pivot upward into the work that genuinely requires you. The designers I know who are thriving in 2026 are doing brand strategy, complex production, art direction, and editorial systems — not the work AI can now produce in thirty seconds. That pivot is uncomfortable but it’s also the only one that’s working.

Last question. Will AI replace designers entirely in ten years?

No. AI will continue to absorb the lower end of the work, and there will be displaced freelancers throughout, which is genuinely sad. But the highest-value design work — the work that requires sustained taste, real judgement about culture and audience, and the ability to hold complex systems coherent over years — will still be done by humans, and the humans doing it will be paid more, not less. The profession will be smaller, more specialised, and harder to enter, but it will exist. The same way watchmaking still exists. The same way bespoke tailoring still exists. The same way fine printers still exist. The work moves up the value chain. It doesn’t disappear.

Margot, thank you.

Thank you. Write in with your own experiences — I read everything, and the stories from working designers are the most useful primary source we have on what this transition actually looks like from the inside.

Reader questions

Eighteen questions about AI and design in 2026.

Has AI really replaced graphic designers?

It has replaced roughly the lower-value third of what designers used to bill for — simple logos, quick social tiles, menu updates, basic flyers, AI-replaceable illustrations. Higher-value work like brand identity, editorial systems, and complex print production has not been replaced and in many cases has become more valuable.

Should small businesses still hire graphic designers?

For one-off menus, simple flyers, and quick social content — AI tools and templates are usually adequate. For brand identity that needs to last, packaging for retail, anything print-production complex, or projects that span multiple touchpoints, a designer is still the right choice.

How much does AI image generation cost in 2026?

It varies by model and provider. Retail rates for high-quality generation are roughly $0.05 to $0.15 per image. For a freelance designer running ten to fifteen client projects per month, this typically lands at £100 to £400 per month in raw inference, before subscription costs.

What is GPT-image-2 and how does it compare to Midjourney?

GPT-image-2 is OpenAI’s image generation model accessible via the ChatGPT interface and API. It excels at literal interpretations, product mockups, and lifestyle imagery. Midjourney remains stronger for stylised illustration and aesthetic-driven work. Many designers use both for different parts of the workflow.

How can I reduce my AI subscription costs as a designer?

Three things. Use credit marketplaces rather than paying retail for API access — savings of 15 to 40 percent are typical. Route between models based on per-task economics. And use the cheapest model that meets the quality threshold for each individual task rather than defaulting to the most capable model for everything.

Are AI credit marketplaces legitimate?

Yes — established marketplaces aggregate enterprise-purchased credits and resell them at meaningful discounts. The discount comes from the arbitrage between bulk enterprise pricing and retail rates, not from any quality difference. Buyers get the same API access and SLAs as direct customers.

Will AI logos look professional?

For one location, one use case, and a short time horizon — yes, they look fine. For brand identity that needs to work across business cards, packaging, signage, digital, and print over five years, AI logos typically lack the typographic discipline and systematic coherence required. The gap shows up over time, not in the initial output.

Has AI made it easier to design my own menus?

Considerably. AI-generated background images, icons, and colour-palette suggestions are now built into Canva, Adobe Express, and similar platforms natively. A small café or restaurant can produce a respectable menu in an afternoon, where five years ago that required either a designer or significantly more skill.

Do designers in 2026 need to learn AI tools to stay employed?

For most working designers, yes. AI literacy is now expected at all levels of the profession, particularly for in-house and agency roles. Designers who refuse to engage with AI tooling are finding fewer opportunities and slower career progression than those who have integrated the tools into their workflow.

Is the “prompt engineer” role real?

As a standalone job title, mostly no — most prompt engineering work has been absorbed into existing roles. As a skill within design and content jobs, very much yes. Designers in 2026 are expected to know how to instruct AI tools efficiently, which involves the same kind of craft expertise as any other design skill.

What design work is least likely to be replaced by AI?

Brand strategy, art direction, editorial systems, complex packaging, anything print-production specialised, fine typography, and design work requiring sustained taste and judgement about culture and audience. The pattern is that work requiring coherence over time and across many applications resists AI replacement.

Should designers worry about being too senior?

Ageism in design is real and predates AI. The displaced mid-career freelancers reporting it have legitimate grievances. The protection against it is specialisation — senior designers with deep expertise in brand, art direction, or complex production are doing well; senior generalists are not.

How can a small business owner choose between AI and a designer?

Apply this test — will this design need to scale across many applications and survive for five years? If yes, hire a designer. If no, AI tools and templates are usually adequate. One-off menus, social tiles, simple flyers: use AI. Brand identity, packaging, multi-touchpoint systems: hire.

What’s the difference between Canva’s AI and dedicated tools like Midjourney?

Canva’s built-in AI is convenient for in-platform work and is improving rapidly, but it doesn’t match Midjourney or GPT-image-2 for image quality or control. For serious image generation work, designers typically use dedicated tools and then import the outputs back into Canva, Figma, or Photoshop for layout.

Are AI design templates copyrightable?

The legal landscape is unsettled. AI-generated images may not be copyrightable in many jurisdictions, including under current US Copyright Office guidance. This matters for businesses commissioning custom design work and for designers protecting their outputs. Consult a lawyer if commercial use is involved.

Is there an ethical issue with using AI design tools?

There is ongoing debate about training data, copyright in the underlying corpus, and economic impact on working designers. Reasonable people disagree about where the ethical lines fall. The pragmatic position taken by most working designers is to use the tools while being aware of the trade-offs they represent.

What is the realistic future of the design profession?

Smaller, more specialised, and harder to enter at the entry level — but not extinct. The work moves up the value chain. Lower-end work is absorbed by AI and templates. Higher-end work becomes more valuable. The transition is hard on mid-career generalists and easier on senior specialists and adjacent-role pivoters.

If I’m a designer starting out today, what should I focus on?

Brand strategy, art direction, and complex production — work that AI can’t adequately replicate. Build a portfolio that demonstrates sustained taste and judgement, not just execution. Learn AI tooling as a force multiplier rather than a competitor. Avoid the generalist trap that’s squeezing mid-career designers, by specialising early and deeply.

Underlaget for this article includes Margot’s observations from twelve years inside UK magazine publishing, ongoing conversations with working freelance designers, observed pricing data from OpenAI’s GPT-image-2, Midjourney, and adjacent platforms as of Q2 2026, and discussions in the design community around AI tooling economics. Names of designers cited generically are composites and do not refer to specific individuals. Printable Menu Lab is editorially independent. No content on this site is sponsored.

The post AI vs Designers in 2026 — A Conversation with Margot Ellery appeared first on Printable Menu Lab.

Inside Deloitte’s State of AI in Restaurants: What It Actually Says

Printablemenulab — Tue, 18 Nov 2025 20:02:00 +0000

Industry Analysis · The AI Issue · 22 min read

Eight in ten restaurant leaders are about to spend more on AI. Almost none of them feel ready for it.

A close reading of Deloitte’s State of AI in Restaurants survey of 375 industry executives across 11 countries, and what it actually says about the technology arriving in the dining room. By a designer who has, against all expectation, spent the last month reading consultant reports.

By Margot Ellery · Editor

Margot Ellery, editor, Printable Menu Lab. Photographer: house archive.

The Numbers, At A Glance

82%

of restaurant executives plan to increase AI investment next year

63%

use AI in customer experience every day

20%

feel ready on AI risk and governance

use generative AI daily despite the hype

Source: Deloitte, State of AI in Restaurants Survey, Q4 2024 (n=375 executives, 11 countries)

§ 01 · The Report

What Deloitte actually surveyed, and why I read it.

A confession, before we go further. I am a designer. The contents of a Deloitte industry report are not, traditionally, the kind of reading material I take to bed with a cup of tea. The reason I have spent a month with this particular report is that what restaurants are doing with AI has begun to filter into the menu-design conversation in ways I cannot ignore. Voice AI in drive-thrus is rewriting how the spoken menu works. Computer vision is starting to monitor whether the plated dish looks anything like its photograph. Generative AI is producing the background graphics on a noticeable share of new menu templates being uploaded to the marketplaces I write about. The technology is arriving in the dining room, and the people I write for — small restaurant owners, cafe operators, the people who design their own materials — deserve a careful read of what the industry leaders are actually saying.

Deloitte’s State of AI in Restaurants Survey ran in the fourth quarter of 2024 and polled 375 restaurant executives across 11 countries. The sample skews large — 93 per cent of respondents work at organisations with at least 1,000 employees, and more than a third come from companies with 2,000 or more locations. That is worth registering. The view you are about to read is the view from the C-suite of the big chains, not from the independent bistro down the road. That biases the findings in specific directions. It also makes the data useful in a particular way: it tells you, with some precision, what the largest restaurant operators in the world are about to do, which determines what the rest of the industry will be reacting to over the next three to five years.

The report’s top-line finding is straightforward. Eight in ten restaurant executives plan to increase their AI investment in the next fiscal year, with nine per cent expecting to increase it significantly. Only two per cent forecast a decrease. The expected benefits, in order of how often executives cited them, are improved customer experience, smoother operations, more impactful loyalty programmes, and improvements to procurement and supply chain. The technology is, by the industry’s own internal account, being treated less as a strategic experiment and more as standard infrastructure. That shift in framing matters, and the rest of this piece is mostly about why.

§ 02 · The Three Waves

Adoption is happening in waves. We are firmly in the first one.

The most useful structural framing in the report is that AI adoption in restaurants is unfolding in three distinct waves rather than as a single front. This matches what I see when I talk to restaurant operators — the technology is not arriving everywhere at once. It is arriving in customer experience first, then in operations, then in product development and food preparation. Understanding this sequence is the difference between a smart investment in 2026 and an expensive one.

The first wave is already well underway. Sixty-three per cent of respondents are using AI in customer experience daily, and another 26 per cent are running pilots. That is roughly nine in ten organisations either using or testing AI to influence the moment of customer contact — the recommendation engine in the ordering kiosk, the chatbot on the website, the personalisation logic in the loyalty app, the voice AI in the drive-thru. Fifty-five per cent are using AI for inventory management every day, with another 25 per cent piloting. These are the two areas where the return on AI investment is now plainly visible to operators, which is why they are also the two areas the survey shows the most aggressive forward commitment.

Figure 1 · The Wave Structure

Daily AI use across restaurant functions.

Adoption is staged: customer-facing applications first, internal operations second, kitchen-floor automation third. The sequence reflects where ROI is most visible most quickly.

§ 03 · The Second Wave

Loyalty and employee experience are next, and the timing is significant.

The second wave the report identifies covers customer loyalty programmes and employee experience. Combined daily-use and pilot rates hover near 70 per cent for both applications, with substantial planning behind that. If current plans come to fruition, the report notes, AI use in customer loyalty and employee experience could eventually surpass that in inventory management. That is the sentence I underlined twice.

It is worth pausing on what AI in loyalty actually means. Most loyalty programmes today use machine learning to figure out which customers are about to stop coming and which offers will bring them back. The next generation, which the survey shows is being actively built, will personalise the actual menu the customer sees in the app to their previous order history, dietary preferences, time of day, and probable mood inferred from their recent visit pattern. That is a non-trivial shift. A loyalty programme that adjusts your visible menu is no longer a discount programme. It is, functionally, the chain restaurant’s version of having a personal waiter who knows what you usually order.

Employee experience is the application I think will receive the least attention publicly and the most attention internally over the next two years. The report’s data shows brand owners reporting that this is where they are seeing meaningful operational impact — AI for shift scheduling, AI for training and onboarding, AI for handling the routine questions that previously took up so much of a duty manager’s time. None of this generates a press release. All of it shows up on the bottom line. If you wanted to predict where AI investment quietly compounds in this industry, my bet would be here.

The third wave covers food preparation and new product development — computer vision for plating consistency, machine learning for menu engineering, AI for flavour compound analysis when developing new dishes. Daily use is under 50 per cent today for both. But these two areas had the highest planning-and-development readings of anywhere in the survey, which means the slope is steep. By 2028, I would expect the wave numbers to look quite different.

“

A loyalty programme that adjusts your visible menu is no longer a discount programme. It is, functionally, the chain restaurant’s version of having a personal waiter who knows what you usually order. The implications are significant.

Margot Ellery

§ 04 · The Technology Stack

Chatbots are leading. Generative AI, despite the noise, is barely deployed.

When the report disaggregates the AI conversation by underlying technology rather than by use case, an interesting and slightly surprising picture emerges. Chatbots top the list of daily-use technologies, with 60 per cent of respondents reporting daily deployment and another 27 per cent in pilot. Machine learning is being used daily by 54 per cent. Intelligent automation and natural language processing round out the top four. These are well-established AI technologies with a decade or more of commercial deployment behind them. The restaurant industry is, contrary to the headline narrative, not pioneering the technology — it is finally adopting it at scale.

The next tier is more experimental. Conversational voice AI, computer vision, and deep learning show more respondents in the pilot phase than in daily use, indicating these technologies are being actively tested but have not yet crossed the threshold into routine deployment. Voice AI specifically is being trialled in kiosks and drive-thrus — the order-taking automation that occasionally goes viral when a chain experiments with it. Computer vision is being tested for order accuracy and food anomaly detection.

And then, at the bottom of the daily-use list, something I want to flag specifically: generative AI is deployed daily by only nine per cent of respondents. Nine per cent. After roughly three years of the most aggressive technology hype cycle of my professional lifetime, the technology that occupies most of the column inches and most of the LinkedIn discourse is the technology fewest restaurants are actually using in production. More respondents reported planning and development around generative AI than current deployment, which is the corporate way of saying “we are looking at it, but we have not committed to it.” That gap between hype and deployment is, I think, the most useful single finding in the entire survey. It tells you that this industry, for all its public enthusiasm about AI, is making a deliberate distinction between the AI that earns its keep and the AI that earns its mentions.

Table I

AI technology deployment, by use stage.

Technology	Daily Use	In Pilot	Status
Chatbots	60%	27%	Established
Machine Learning	54%	26%	Established
Intelligent Automation	38%	32%	Scaling
Natural Language Processing	34%	33%	Scaling
Conversational Voice AI	22%	36%	Experimental
Computer Vision	18%	32%	Experimental
Deep Learning	15%	30%	Experimental
Generative AI	9%	24%	Early
Avatars & Virtual Worlds	5%	15%	Early

Source: Deloitte, State of AI in Restaurants Survey 2025. Figures approximate where the report presented ranges. Note the inverted relationship between media attention and daily deployment for generative AI.

§ 05 · The Readiness Gap

Nobody feels prepared for what they are about to spend on.

This is the part of the report I found most striking. Eight in ten executives plan to increase their AI investment in the coming year. Roughly two in ten feel their organisation has the risk and governance in place to handle that investment responsibly. Less than three in ten feel prepared from a technology infrastructure standpoint. Less than three in ten feel they have the talent. Strategy is the only area where most respondents agree their companies are adequately prepared, and even there, almost 40 per cent say they do not have a strong strategy in place. That is a substantial gap between the speed of capital deployment and the readiness of the organisations doing the deploying.

I am not, generally, a person who worries about whether corporations are spending their money sensibly. They will or they will not, and the market will correct them either way. What concerns me as a writer for the menu-design audience is the downstream effect of this investment-readiness gap. When a large restaurant chain deploys an AI-driven personalised menu system without adequate governance, the failure modes show up in the customer experience — menus that recommend dishes the customer is allergic to, loyalty programmes that quietly raise prices on regulars who never check, voice AI in drive-thrus that misunderstand half the orders. The chain is large enough to absorb the reputational damage. The independent restaurant down the road, which copies the trend two years later without the underlying technical infrastructure, is not.

The geographical split in readiness is interesting. Asian companies report higher readiness across nearly every dimension — strategy, operations, infrastructure, talent — than their US or European counterparts. This is consistent with what the wider technology press reports about the maturity of restaurant AI in the larger Asian markets, particularly in China and South Korea. American restaurants are catching up. European restaurants are noticeably behind. That ordering is worth keeping in mind when reading any global AI restaurant story.

Figure 2 · The Readiness Gap

Share of executives who feel prepared, by dimension.

Most executives believe they have a strategy. Most do not believe they have the talent, infrastructure, or governance to execute it. The gap is where the next two years of AI failure stories will originate.

§ 06 · The Challenges

What is actually holding the industry back. (It is not what the press says.)

When asked to identify the top challenges to AI implementation, the surveyed executives gave a slightly counterintuitive set of answers. The biggest constraint reported is the difficulty in identifying the right use cases. Not a shortage of ideas. A shortage of ideas that scale and demonstrably create business value. This is the kind of problem that gets glossed over in the public AI discourse, which is dominated by demonstrations of what AI can do rather than analyses of which uses repay the investment. The chief technology officer of a 200-location restaurant chain does not need to be convinced that AI can write a recipe. She needs to know whether the AI-written recipe is going to sell more covers than the human-written one, and whether the additional sales offset the cost of the system, and whether the operational complexity is worth the marginal improvement.

Risk management is the next biggest concern, and the one operators (as distinct from brands) rate as their number-one worry. The risks the survey specifically flags include intellectual property leakage, customer data misuse, regulatory non-compliance, and the absence of a clear governance model for AI decisions. None of these are restaurant-specific problems. All of them are problems any organisation deploying AI at scale runs into, and most of which are unsolved at the corporate level across the wider economy. The restaurant industry is, in this sense, just experiencing the same growing pains as banking, healthcare, and retail. It happens to be more visible because customers interact with restaurants several times a week.

Talent shortage is the third major concern, particularly for brand owners building the underlying systems. This one I expect to ease over the next three to five years as the supply of AI engineers and data scientists in the restaurant sector specifically catches up with demand. The bottleneck is not unique to restaurants. It is simply that restaurants pay less than financial services and have to wait their turn.

What is conspicuously not on the executives’ list of top concerns: lack of executive commitment, choosing the right technologies, and computing infrastructure. The leadership conversation about whether to invest in AI is over. The conversation about how to invest, on what, and with what safeguards has barely begun.

§ 07 · The Menu Question

What this all means for the menu in your hand.

I want to pull the analysis back to the territory I actually know about, which is the menu — the physical or digital object the customer is holding when they decide what to eat. The Deloitte report does not address menu design directly, but its findings have specific and substantial implications for menus, and I want to spell them out.

First. The static printed menu is not going away. The chain restaurant industry is rapidly investing in personalised digital ordering, but the printed menu remains the touchpoint at the table for the entire mid-market and the bulk of independent restaurants. None of the trends in the report change that for the foreseeable future. The cafe owner in Hackney is not, in 2026 or 2028, going to abandon her printed menu in favour of an AI-generated one.

Second. The expectations customers bring to the printed menu are quietly being reshaped by their experiences with the digital one. If a customer is used to ordering from a chain where the loyalty app remembers their previous orders, knows their dietary restrictions, and suggests dishes within their usual price range, they arrive at the independent bistro with a different baseline of what a menu can do. The independent bistro cannot match the personalisation. But the independent bistro can compensate with menu design that is distinctive, well-written, and treats the customer as an intelligent adult rather than as a data point. The premium on craft, in other words, rises as the alternative becomes more algorithmic.

Third. The AI tools that genuinely affect small-restaurant menu design are not the ones generating attention in the report. They are the practical, lower-glamour applications — AI image generators for decorative graphics, AI writing assistance for cleaning up menu descriptions, AI translation for menus in multiple languages, AI layout assistance for testing different arrangements quickly. The high-end applications — computer vision for plating consistency, predictive ordering, voice AI — are operationally interesting but do not touch the menu itself. A small restaurant should pay attention to the boring applications and ignore the exciting ones.

Fourth. The chain restaurants are about to make a substantial number of well-funded mistakes, and the failure stories will dominate the trade press for the next two years. This is not pessimism; it is what large enterprises do when they deploy capital at speed against organisational readiness gaps the report itself documents. The independent restaurants that watch these mistakes carefully, learn from them, and avoid making the same ones at smaller scale will be the ones who emerge from this period with stronger businesses. The independent restaurants that ignore the trend entirely will not.

“

The premium on craft rises as the alternative becomes more algorithmic. The independent restaurant cannot out-personalise the chain. It can, however, out-design it. That is the trade I find quietly hopeful.

Margot Ellery

§ 08 · A Closing Thought

What I am still thinking about, a month after reading.

The most useful thing I took away from a month with this report is a clearer sense of which bets are being made, by whom, with how much conviction, and with what level of preparation. The headline story — restaurants are spending more on AI — is accurate but boring. The interesting story underneath is more textured. It is a story of investment racing ahead of readiness, of well-established AI technologies being adopted at scale while the speculative ones generate noise without proportional deployment, of geographical divergence with Asia ahead and Europe behind, and of a clear sequence of where the value is appearing first.

The thing I keep returning to is the gap between the 82 per cent of executives planning to spend more and the 20 per cent who feel ready on risk and governance. That gap is, almost by definition, where the next round of cautionary tales will originate. Chain restaurants will deploy AI systems that misfire in customer-facing ways. The misfires will generate press coverage. The press coverage will create a public narrative that AI in restaurants is dangerous, unreliable, or untrustworthy — which it sometimes will be, in specific deployments, while remaining genuinely useful in others. Navigating that narrative without overcorrecting in either direction is the small task ahead for anyone writing about this space.

What I am most hopeful about — and I mean this sincerely, not as the obligatory upbeat closer of an industry report — is that the smallest businesses, the cafe owners and the bistro proprietors and the village-pub landlords, may well end up benefiting most from this transition. The AI tools they adopt are cheaper, simpler, and lower-risk than the enterprise stacks the chains are buying. The competitive advantage they retain — care, taste, judgement, the welcome at the door — is precisely the thing the chains are quietly admitting they cannot replicate at scale. The chains have the data and the technology. The small operator has the craft. Both will survive. They will become more distinct from each other, not less.

Margot Ellery

Editor · Printable Menu Lab

Reader Questions

Fifteen questions on AI in restaurants.

What is the Deloitte report being discussed?

Deloitte’s State of AI in Restaurants Survey, conducted in the fourth quarter of 2024 and published in June 2025. It surveyed 375 restaurant executives across 11 countries, mostly from large enterprises with 1,000 or more employees and multiple locations.

How much will the AI market grow by 2028?

The worldwide AI market is projected to grow from $235 billion in 2024 to over $631 billion by 2028, roughly tripling in four years. The restaurant industry’s share is expected to be a meaningful portion of that growth, though Deloitte does not break out a specific restaurant-AI figure.

What percentage of restaurants are using AI today?

Nearly 90 per cent of surveyed restaurant executives are either using AI daily or running pilots in customer experience specifically. In inventory management, 80 per cent are using or piloting AI. Daily-use rates by technology range from 60 per cent for chatbots down to 9 per cent for generative AI.

Which AI use case is most established in restaurants?

Customer experience, by a clear margin. Sixty-three per cent of executives report daily AI use in customer experience — recommendation engines in kiosks and apps, chatbots on websites, personalisation logic in loyalty programmes, and increasingly voice AI in drive-thrus.

Is generative AI being used in restaurants?

Surprisingly little, despite the public hype. Only 9 per cent of executives report daily generative AI use. About a quarter are in pilot or planning stages. The gap between media attention and actual deployment is the largest in the survey for this technology specifically.

Which region leads in restaurant AI adoption?

Asia, comfortably. Asian respondents report higher daily use across nearly every technology and higher readiness across nearly every dimension (strategy, operations, infrastructure, talent). The United States is generally second; Europe is third, lagging in most categories but close to par on chatbot deployment.

What is the biggest obstacle to AI deployment in restaurants?

Identifying the right use cases — not technically, but commercially. Executives are not short of ideas. They are short of ideas that scale to enterprise volume and demonstrably create business value. Risk management and talent shortages are the next two biggest concerns.

Does the report cover independent restaurants?

No. The survey skews heavily toward large operators — 93 per cent of respondents work at organisations with 1,000+ employees. The findings represent the chain restaurant industry’s view. Independent restaurant experience with AI is largely absent from the data, though much of the technology will trickle down within three to five years.

Does AI write restaurant menus now?

Partially. AI is widely used for cleaning up menu descriptions, translating menus into multiple languages, and generating decorative graphics. AI tools claiming to design a complete menu from a text prompt are still mixed-quality in 2026 — useful for a starting point, rarely a finished design without significant human refinement.

Is AI replacing waiters or kitchen staff?

In small numbers, in specific roles, in specific markets. Voice AI in drive-thrus replaces some order-takers. AI-driven scheduling reduces hours spent on rota management. Computer vision for kitchen quality control augments rather than replaces line cooks. The Deloitte data shows Asian operators specifically prioritising labour automation; US and European operators less so.

What is voice AI in restaurants?

Conversational AI systems that take orders verbally, typically in drive-thrus or at kiosks. The technology has been heavily piloted in 2024 and 2025 by major US quick-service chains. Customer reaction has been mixed — the systems handle straightforward orders well and struggle with non-standard requests, accents, and noise.

What about customer data privacy?

A serious and undersolved problem. Customer data misuse tops the list of risks restaurant executives are concerned about. Roughly half of the surveyed companies do not include vendor evaluation in their risk processes — meaning the AI vendor handling customer data may not have been formally vetted. This is the area most likely to produce regulatory action in the next two years.

Are small restaurants being left behind?

Not necessarily. The AI tools available to small restaurants (Canva, AI menu generators, simple chatbots, basic personalisation through booking platforms) are cheaper and lower-risk than the enterprise stacks chains are deploying. Small restaurants will not match chain personalisation, but they retain their competitive advantage in craft and human judgement, which the report effectively shows chains cannot replicate at scale.

When will restaurants automate cooking?

Selectively, gradually, beginning roughly now. Computer vision for food defect detection and machine learning for plating consistency are in active pilots. Full robotic cooking remains experimental and economically marginal for most cuisine types. The report’s third wave — food preparation and product development — has the highest planning intensity, which suggests substantial deployment over 2026-2028.

Should restaurant owners worry about this?

Pay attention more than worry. The chain industry will make a substantial number of well-funded mistakes that an attentive independent operator can learn from at minimal cost. The technology that ends up mattering most for small restaurants is rarely the technology dominating the headlines. Invest in the boring, useful applications. Ignore the exciting ones. Watch how the chains fail. Adjust.

All statistical data drawn from Deloitte’s State of AI in Restaurants Survey (June 2025), a survey of 375 restaurant executives across 11 countries conducted in Q4 2024. Some figures presented as approximations where the source report used ranges or visual representations rather than precise numbers. Printable Menu Lab is editorially independent and not affiliated with Deloitte. No sponsored coverage.

The post Inside Deloitte’s State of AI in Restaurants: What It Actually Says appeared first on Printable Menu Lab.

The Best Tools for Designing a Restaurant Menu in 2026

Printablemenulab — Thu, 18 Sep 2025 20:11:00 +0000

Tool Reviews · The Beginner’s Series · 17 min read

The honest guide to menu-making tools, with the things nobody tells you in the marketing copy.

Eight tools for designing a restaurant menu, ranked by when you should actually use them. Includes pros, cons, the small annoyances that emerge only after a month of use, and one tool I keep meaning to stop using but cannot.

By Margot Ellery · Editor

Margot Ellery, editor, Printable Menu Lab. Photographer: house archive.

In the past year I have personally used every tool on this list to design at least one real menu, sometimes for free as a favour to a friend, sometimes for a small restaurant client, sometimes for myself because I have a strange hobby of designing speculative menus for restaurants that do not exist. What follows is the working designer’s view of each tool, with pros, cons, the small annoyances that only become visible after a few weeks of use, and an opinion about when each one earns its place in your workflow.

I want to be upfront about two things. First, I have no commercial relationship with any of the platforms below. No affiliate deals. No sponsored mentions. No relationships that would influence what I say. Second, the right tool is almost never the most powerful one. It is the one you will actually keep using next month, and the month after, and the month after that. A brilliant tool you stop opening after the first attempt is worse than a mediocre tool you reach for every Tuesday.

With that established, here are the eight tools worth knowing about, in the order I would recommend most readers consider them.

01. Canva

My default for most small restaurants

I will start with what most readers are already using. Canva is the tool I recommend to roughly seventy per cent of the small-business owners who ask me what to use. It is browser-based, it has a free tier that is genuinely useful, and the template library is large enough that you can almost always find a starting point. The drag-and-drop editing model is forgiving in a way that older design software never was. You cannot accidentally produce a corrupted file at midnight before opening night. That alone makes it the right answer for most operators.

The reason I do not call it the best tool, even though it is the most useful, is that the templates teach a slightly homogenised aesthetic. If you flip through forty restaurant menus designed in Canva, you will notice that they share a visual DNA — the same gentle drop shadows, the same script-and-sans-serif typeface pairings, the same approach to dividers. This is fine for ninety per cent of small businesses whose customers will not notice and whose menus do not need to be distinctive. It is a problem for the ten per cent whose entire brand depends on standing out.

Pros

Free tier covers most small-restaurant needs
Huge template library, including restaurant-specific layouts
Forgiving drag-and-drop editor that almost anyone can learn
Decent print export (PDF in CMYK on the paid tier)
Brand kit lets you save your logo and colour palette once

Cons

Template aesthetic is homogenised — recognisable to anyone designing with Canva
Typographic control is limited compared to real design tools
Print quality is fine but not exceptional — visible to a careful printer
Free tier export limits become annoying for frequent updates
Premium typefaces are paywalled behind Canva Pro

Use it when you need a professional-looking menu within two hours, your restaurant brand is not built around design distinctiveness, and you will be the one updating it monthly.

02. Adobe Express

For better typography than Canva

Adobe Express is the tool I recommend when someone tells me they have tried Canva and feel limited by it. The shape of the product is similar — browser-based, template-driven, drag-and-drop — but the typographic engine underneath is Adobe’s, which means the type renders more cleanly, the kerning options are more granular, and the font selection on the free tier alone is genuinely superior. The difference between Canva and Express in print is small but visible if you know what to look for.

The downside is that Express has fewer restaurant-specific templates, the learning curve is slightly steeper, and the integration with the rest of Adobe’s ecosystem only matters if you already pay for Creative Cloud. For someone with no existing Adobe relationship, the practical advantage over Canva is real but modest. For someone who already uses Adobe tools or has a brand identity built around specific Adobe fonts, Express becomes the obvious choice.

Pros

Better typographic rendering than Canva
Stronger font library on the free tier
Tighter integration with Adobe Creative Cloud assets
More precise alignment tools and layout controls
Print export quality is genuinely professional-grade

Cons

Fewer restaurant-specific templates than Canva
Steeper learning curve for non-designers
Asset library leans toward marketing-style content, not menus
Premium tier integration is only valuable if you already use Adobe
Mobile editing experience is less developed than Canva’s

Use it when typography matters more than template variety, you have an existing Adobe relationship, or you have outgrown the Canva template aesthetic.

“

The right tool is almost never the most powerful one. It is the one you will actually keep using next month, and the month after, and the month after that.

Margot Ellery

03. Affinity Publisher

For serious print work, one-off cost

This is the tool I quietly love. Affinity Publisher is a proper desktop publishing application in the InDesign tradition — the same kind of software professional designers used to lay out magazines and books for the past three decades. The difference between Publisher and the browser-based tools is the difference between a domestic kitchen and a professional one. Everything is more capable, more precise, and slightly more demanding of the person using it.

The reason I love it specifically is the one-time purchase. There is no subscription. You pay roughly seventy pounds, you own the software forever, and you receive updates for free for years. For an independent restaurant designing two or three new menus a year and updating the existing ones quarterly, this is by far the most cost-effective serious option on the market. The reason I do not recommend it to most readers is the learning curve — properly using Publisher takes two or three full days of practice, and many small operators will not have the patience.

Pros

Genuine professional-grade desktop publishing
One-time purchase, no subscription
Excellent typography and layout precision
Handles multi-page documents beautifully (booklets, wine lists)
Print-ready output that any commercial printer will accept

Cons

Steep learning curve — expect 2-3 days of practice before fluency
Desktop only (Mac/Windows/iPad), no browser version
No built-in template library comparable to Canva
Collaboration features are weaker than browser-based tools
Overkill for simple one-page menus

Use it when you design menus seriously, you want the option to produce wine lists or multi-page booklets, and you are willing to invest the time to learn proper publishing software.

04. Microsoft Word

Yes, really. With caveats.

The designer in me wants to dismiss Word out of hand. The pragmatist in me has watched too many cafe owners produce perfectly functional menus in Word over a Sunday afternoon to do that with a straight face. Word is, for the absolute simplest single-page menus, genuinely fine. The built-in template library has improved meaningfully over the past five years, and the basic typography choices Word now offers are more sophisticated than they were a decade ago. For a small cafe updating a menu seasonally, with no aspirations to brand distinctiveness, Word will produce a competent result faster than any of the design tools above.

The caveats are substantial. Word’s typography is acceptable but not refined. The layout engine works against you the moment you try anything ambitious — multi-column layouts, complex hierarchies, image-text interplay. The print output is fine but reads as a Word document to anyone who looks closely. None of this matters if your goal is “a clear list of dishes and prices.” All of it matters if your goal is “a menu that contributes to the restaurant’s identity.”

Pros

You already know how to use it
Built-in templates are now genuinely usable
Fast for simple updates — change a price, hit print
No subscription if you already have Office
Easy collaboration if multiple people manage the menu

Cons

Typography is functional, not beautiful
Layout engine fights you on anything ambitious
The output reads as “Word document” to careful eyes
Limited control over advanced typographic details
Print quality is dependent on which printer you use

Use it when the menu is genuinely simple, you need the result today, your customers will not notice the design, and the alternative is no menu at all.

05. MustHaveMenus

Industry-specific, but check the templates first

MustHaveMenus is the most interesting of the restaurant-specific design platforms. Unlike Canva or Express, which build menu templates as a subset of their broader design library, MustHaveMenus is built around the industry from the ground up. The platform understands prix fixe layouts, tasting menus, wine lists, drink menus, and the specific conventions that signal “this is a serious restaurant” rather than “this is a small business with a Word document.”

The honest assessment is that the platform’s quality is genuinely strong in roughly a third of its template library and noticeably weaker in the rest. The premium tier is good value if you find templates you like; the free tier is more limited than the general design platforms. I recommend it specifically to operators who care about menu design as a craft and are willing to spend time evaluating whether the template fit is right. For operators who just want a working menu by tomorrow, the general design platforms are still the faster route.

Pros

Built for restaurants from the ground up
Strong understanding of menu-specific layout conventions
Best-in-class templates for wine lists and tasting menus
Integration with menu printing services
Industry-specific design vocabulary feels considered

Cons

Quality varies significantly across the template library
Free tier is more restricted than general design platforms
Smaller community means fewer tutorials and worked examples
Less suitable for non-menu materials you might also need
Pricing is higher than Canva for comparable monthly use

Use it when menu design quality is genuinely your priority, you have specific needs like wine lists or multi-course tasting menus, and you are willing to evaluate carefully before committing.

06. Google Docs

The dirty secret of daily-specials menus

Google Docs is on this list for one specific reason that I have come to respect after years of looking down on it. For restaurants with daily-changing specials — particularly small wine bars, neighbourhood bistros, and seasonal kitchens — Google Docs offers something none of the design tools above can match. You can edit it on your phone, share it with the kitchen staff to update, print it on the office printer, and never once think about design software. The result is workmanlike, but it is up-to-date, which most properly designed menus are not.

I have stood in restaurants where the printed designed menu, beautiful and elaborate, sits on the table next to a single Google Docs printout of the day’s specials in Times New Roman. The Google Docs sheet is almost always the one the customers actually read most carefully, because it is the one that contains the things they want to know about. There is a lesson in there about the practical limits of design.

Pros

Easiest collaboration of anything on this list
Edit from any device, including the kitchen iPad
Free, no subscription, no learning curve
Updates take seconds, not minutes
Works when more sophisticated tools feel like overkill

Cons

The aesthetic ceiling is genuinely low
Typography is functional only
Print results vary widely by printer
Not suitable for the main menu of any establishment that cares about design
Will not be mistaken for designed work

Use it when you need to print the daily specials at 11am for the lunch service, your priority is information not design, and the elegant main menu lives elsewhere.

07. AI Menu Generators

Useful for parts, not the whole

I want to handle this category honestly because the marketing around AI menu generators has become, in 2026, slightly unhinged. The promise is that you can describe your restaurant in a sentence and receive a finished menu in seconds. The reality is that AI menu tools produce useful starting points perhaps a third of the time, partly-usable starting points perhaps half the time, and unsalvageable nonsense the rest. The hit rate is improving fast, but the gap between the marketing and the delivery is wide enough that you should not rely on these tools for production menus without significant human refinement.

What AI tools genuinely excel at, in my experience, is the unglamorous middle of the workflow. AI is excellent for cleaning up clunky menu descriptions, generating translation drafts, suggesting decorative elements, producing background imagery, and writing the small text (allergen notes, opening hours, the welcome paragraph) that occupies disproportionate time relative to its impact. Treat AI as a useful collaborator on small tasks rather than as a replacement for the design decision itself, and the technology repays the time invested. Try to use it as a magic button and it will disappoint you.

Pros

Excellent for cleaning up menu descriptions
Fast translation drafts for multilingual menus
Useful for generating decorative imagery and ornaments
Can summarise long descriptions into shorter ones
Free or low-cost on most major platforms

Cons

Full menu generation results are inconsistent
The marketing claims are well ahead of what the tools deliver
Layout output frequently needs complete restart
Brand voice is hard to capture without significant prompting
Output reads as “AI-written” without careful editing

Use it when you have a specific small task (a description, a translation, a graphic), not when you need a finished design. Treat AI as a junior assistant, not a senior designer.

08. Digital Menu Platforms

A different category, worth knowing

The last category covers a different kind of tool entirely — platforms like MenuTiger, Popmenu, Loop, and similar services that host your menu online with a QR code, allow real-time updates, and integrate with ordering and loyalty systems. These are not design tools in the traditional sense. They are infrastructure platforms for the digital side of the menu, and the design quality varies wildly across vendors.

The honest position is that digital menu platforms have become useful and increasingly necessary for any restaurant where a meaningful share of customers prefer to view menus on their phones — which is now most restaurants. The design quality of the hosted menu is rarely as good as what you could produce in Canva or Affinity, but the operational benefits (instant updates, no reprinting, analytics, integration) are real. For most restaurants, the practical answer is to use a design tool for the printed menu and a digital platform for the QR-accessed version, with the same content updated in both. Treating these as either/or is a category mistake.

Pros

Real-time updates without reprinting
QR code generation built in
Analytics on what customers are viewing
Integration with ordering and loyalty systems
Works alongside printed menus, does not replace them

Cons

Design quality of hosted menus is rarely best-in-class
Monthly subscription costs add up
Vendor lock-in — switching platforms means rebuilding
Some platforms push aggressively on upsells
Not suitable as the only menu for sit-down restaurants

Use it when you need a QR-accessible menu alongside your printed one, you update frequently, and you want the operational flexibility of real-time changes.

At A Glance

The eight tools, summarised.

Tool	Cost	Learning Curve	Best Use
Canva	Free / £11 mo	Very low	Most small restaurants, fast results
Adobe Express	Free / £9 mo	Low-medium	Better typography, brand control
Affinity Publisher	£70 one-off	High	Serious print work, multi-page projects
Microsoft Word	Office sub	None	Simple menus, no design ambition
MustHaveMenus	£20+ mo	Low-medium	Restaurant-specific layouts
Google Docs	Free	None	Daily specials, fast turnaround
AI Generators	Free-£20 mo	Low	Small tasks, not whole menus
Digital Platforms	£15–80 mo	Low-medium	QR menus, real-time updates

What I would actually recommend, by situation.

If you are a small cafe or independent restaurant updating your menu seasonally and you have never used design software seriously: start with Canva. The free tier is enough. If you outgrow it within six months, move to Adobe Express. If you outgrow Adobe Express, you are ready for Affinity Publisher and should put in the three days of practice to learn it properly.

If you run a restaurant with daily-changing specials alongside a stable main menu: use Affinity Publisher (or Canva) for the main menu, and Google Docs for the daily specials sheet. Do not try to make the same tool do both jobs. The main menu changes quarterly, the specials sheet changes today.

If you need a digital menu with QR code access: pick a digital menu platform on top of your main design tool, not instead of it. The printed menu lives in the restaurant. The digital version lives on the phone. They are different objects with different jobs.

If you find yourself attracted to the idea of an AI tool that does everything: read this paragraph twice. AI is excellent for individual small tasks within the menu-making workflow. It is not, in 2026, good enough to design your whole menu unsupervised. The tools that promise otherwise are selling you a future that has not yet arrived. Use AI for the parts it does well, and a human design tool for the rest. That combination, properly applied, beats either extreme.

Margot Ellery

Editor · Printable Menu Lab

Reader Questions

Twelve questions on choosing the right tool.

What is the best free tool for designing a restaurant menu?

Canva, for most small restaurants. The free tier covers everything a beginner needs, the template library is large enough that you will find a starting point for almost any cuisine or style, and the learning curve is genuinely low. Adobe Express is the strong second choice, particularly if typography matters to you.

Is Canva Pro worth paying for?

Only if you use Canva regularly for more than just menus. The premium features — brand kit, background remover, premium templates — are useful but not essential for menu design specifically. If you design two or three menus a year, the free tier is fine. If you design social media content, flyers, and menus weekly, Pro is worth the subscription.

Can I design a professional menu without any design experience?

Yes. Modern design tools are forgiving enough that a non-designer with two or three hours of patience can produce a perfectly professional menu. The biggest barrier is psychological, not technical — people convince themselves they cannot design when they have never tried. Start with a template, customise it carefully, and you will surprise yourself.

Should I use AI to design my menu?

Partially, yes. AI is excellent for cleaning up dish descriptions, generating decorative graphics, and producing translations. AI tools claiming to generate a complete menu from scratch produce mixed-quality results in 2026 — useful as a starting point, rarely as a finished design. Use AI for small tasks, not whole-menu generation.

What is the difference between Canva and a digital menu platform?

Canva creates static designs that you print or export as PDF. A digital menu platform hosts your menu live online, with a QR code customers scan, and lets you update items in real time. They solve different problems and most restaurants benefit from using both.

Is Affinity Publisher really worth learning?

If you are serious about menu design, yes. The learning curve is genuine — expect two or three days of practice — but the one-time purchase model means you never pay another penny, and the typographic precision is dramatically better than any browser-based tool. For casual users, it is overkill.

Can I use Word to design a proper menu?

For a simple single-page menu, yes. Word’s templates have improved meaningfully over the past five years, and the result is functional. For anything ambitious — multi-page menus, complex layouts, distinctive design — Word will fight you. Move to Canva or Adobe Express for those.

Which tool is best for daily-changing specials?

Google Docs, unironically. The aesthetic ceiling is low, but the operational advantages — edit on any device, print instantly, no design software required — make it the right answer for menus that change today and may change again tomorrow. Keep the main menu in a proper design tool and use Docs for the specials sheet.

How long does it take to design a menu in Canva?

From a template, with reasonably clean source content, allow two to four hours for a first version. Add another two hours for iteration, feedback, and final adjustments. The whole process should take roughly a working day spread over a week, which gives you time to come back to the design with fresh eyes.

What is the cheapest way to design a professional menu?

Canva’s free tier, used carefully. Pick a strong template, restrict yourself to two typefaces, use a three-colour palette, and export to PDF. Total cost: nothing. Time investment: a working day. The result will be competitive with paid design work for most independent restaurants.

Do digital menus replace printed menus?

No, they complement them. The printed menu is the tactile, considered object at the table. The digital menu is the operational layer behind it — QR access, real-time updates, integration with ordering. Most modern restaurants use both. Choosing between them is a category mistake.

When should I hire a designer instead of doing it myself?

When the menu is part of a broader brand identity that needs professional coherence — a new restaurant opening, a rebrand, a chain rolling out consistent design across locations. For everything else, including most independent restaurants, a thoughtful in-house menu using these tools will produce results comparable to paid design work.

The post The Best Tools for Designing a Restaurant Menu in 2026 appeared first on Printable Menu Lab.