‘Alexa, tell me a joke’: how talking to AI impacts young children’s development

Clara Macarena Ponce Romero, Universidade de Santiago de Compostela

Image: Vitaly Gariev - unsplash

Children are innately curious, and throughout any given day they come up with all manner of questions: Why don’t fish have hair? Why do flowers wilt so quickly? Their need to understand the world – and develop their language skills and ideas – makes them tireless conversationalists.

While their inquiries would usually be directed at parents or teachers, in modern homes even the youngest kids might now talk to a digital interface like Siri or Alexa. These AI systems are fast becoming part of many children’s everyday lives, as kids ask them to play music, help with their homework, answer questions, or just chat to them.

These kinds of interactions are no longer strange, but we need to ask what happens when they become completely routine. Do they change the way children learn to communicate? Do they change the words they use? And are they a threat to kids’ cognitive abilities?

Language learning

Learning to speak has never been a question of just learning words. Children acquire language through human relationships, and by building emotional ties to other people. They learn to take turns, how to interpret silence and context, and how to tell when someone is tired, annoyed or distracted. They also discover that conversations do not need to be perfect – there will always be interruptions, misunderstandings, and off-the-cuff explanations.

But AI does not think like a human. Think about your interactions with ChatGPT or Gemini. We rarely lose our patience while talking to these virtual assistants, partly because these interactions are, by their very nature, governed by a very different logic to human conversation. These tools are built for quick responses and infinite patience, and this changes the experience of communication.

AI and politeness

In many homes, something very curious is becoming increasingly common: some children (and even adults) are adapting their speech so that virtual assistants will understand them better. They speak in simple sentences, and give direct instructions: “play cartoons, open YouTube, tell me a joke”. This kind of speech – known as instrumental language – aims to get immediate results.

This shift does not necessarily mean children are becoming ruder or less empathetic, but it may influence their expectations of conversation in general. Human interactions are usually slow and ambiguous, and require patience, attention and negotiation. Chatbots, on the other hand, are designed to give quick, fluid responses, or even create a sense of virtual empathy with the user.

This all leads us to a question that may seem minor, but reveals a lot: should we teach children to say “please” and “thank you” to Alexa? Beyond the surface-level question of whether we should be polite to machines, this debate forces us to think about the communicative habits that children develop through daily interactions with technology that always obeys them. The wider question for families and educators alike is: what idea of “conversing” will children construct in this context?

Alongside these doubts, we should not lose sight of the opportunities that these systems present. Many children feel freer to ask questions when they do not fear judgement, and a chatbot will repeat an explanation as many times as is necessary, adjust the level of complexity, or support them as they learn new languages or concepts.

These tools provide a safe space for trial and error, free from the social pressures that often accompany human conversation. This is not just the case for children. Many of us now resort to AI to ask ordinary questions, from “Alexa, how do I recover my password?” to more embarrassing queries that we would rather not voice out loud.

Responding is not understanding

Current AI systems produce extremely convincing answers, but they do not understand the world the way a person does. They do not have experiences, emotions, or intentions – even if they talk like they do. Just like many adults, young children tend to attribute human qualities to the things they interact with. If something can converse, it is easy to presume that it also has understanding or knowledge.

However, a lot of the information in human conversation is unspoken. An adult can tell when a child’s question is the product of curiosity, fear, or a simple need for attention. This pragmatic dimension – consisting of gestures, tone, looks, feelings – is crucial for children’s development. It is difficult to replicate in a machine, which can only offer an answer without capturing any of this nuance.

Humans are not machines

When children grow up surrounded by a particular kind of linguistic exchange – one that consists of quick responses and having every single request obeyed – it ends up shaping habits, expectations and ways of interacting. This can lead children to always expect clear, quick, effortless answers, as though any conversation were something to be resolved on the spot.

The adults who live with young children therefore have a vital role to play. They are the ones who mediate daily use of these tools both at home and at school, who understand their limitations, and who are able to integrate these conversations into general learning.

A child asking Alexa to answer their questions or tell them a joke is not, in and of itself, detrimental to their language development. But we should guide these conversations so that they understand they are dealing with a machine that responds to them, not a person.

We need to show children what separates us from machines, how we should interact with them, and in what situations it is alright to use them. We should accompany them in these everyday interactions, commenting on them and helping them to understand AI’s limitations.

AI can be useful as a support, but under no circumstances should it take the place of replace conversation between people. Despite rapid developments in technology, human interaction remains at the heart of the way we exist in the world.

Clara Macarena Ponce Romero, Profesora del área de Didáctica de la Lengua y la Literatura, Universidade de Santiago de Compostela

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World

Research Finds People Better Understood Literal Than Figurative Cybersecurity Language

By Flinders University

Cyberattacks now cost the global economy trillions, yet most people still struggle to understand what actually happens when a breach occurs.

Image: freepik

Research by Associate Professor Sky Marsen, an applied linguist and Communications course director at Flinders University, and Professor Robert Biddle, a computer scientist based from Carleton University, Canada, suggests a surprising reason for this gap: the language used to explain cybersecurity may be part of the problem.

In an experimental study comparing “figurative” cybersecurity language (terms such as phishing, virus, or trojan) with more literal explanations, the authors found that people understood incidents significantly better when the language was clearer and less metaphorical.

This challenges a widespread assumption in science communication – that metaphors help non-experts grasp complex ideas. In cybersecurity, the opposite may be true.

“These terms weren’t designed for the public in the first place,” explains Associate Professor Marsen. “They emerged from inside hacker culture, and terms that may sound creative and playful within expert communities, are often opaque to outsiders. When they are used in public communication, they can obscure rather than clarify what’s happening.”

Given the rise of cybersecurity concerns, Associate Professor Marsen says it’s timely to understand how non-experts understand cybersecurity words and metaphors – especially the figurative language created by computer scientists to describe cybersecurity incidents.

A lack of accurate information makes cybersecurity an issue that is difficult to clearly explain to the public – and this can lead to major losses for individuals and serious reputational damage for organizations.

“Organisations routinely tell customers they’ve been hit by phishing or a malware attack, but if people don’t fully understand what that means, they may not know how to respond or protect themselves,” says Associate Professor Marsen. “Worse is that unclear communication can downplay the responsibility of organisations, or leave users vulnerable.”

Using a set of cyberattack stories composed with figurative words and a set composed with more literal versions, and an online survey, the study examines whether the use of metaphor and neologism clarifies or obfuscates the technical aspects of cybersecurity for non-experts.

The results showed participants in the literal set scored significantly better in comprehension. However, participants made important errors in both literal and figurative versions. This underlines the need for organizations to employ language strategically and provide more effective explanations of cybersecurity situations.

Associate Professor Marsen says a key takeaway from this research is that paying attention to language choices in professional communication is not just a stylistic choice but a public safety issue.

The research – “Grok hackspeak? Communicating cybersecurity with figurative language”, by Sky Marsen and Robert Biddle – has been published by the International Journal of Business Communication. https://journals.sagepub.com/doi/10.1177/23294884251329160.

This post was originally published on Flinders University News and republished here with permission.

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World

85% of kids are still using social media despite ban. But we need a new measure to judge its success

Samuel Cornell, The University of Queensland

Image: Sixteen Miles Out - unsplash

Six months on from Australia’s under-16s social media ban taking effect, the early verdict from headlines and children themselves has been blunt: it isn’t working.

A new study published today in the British Medical Journal appears to add even more weight to this judgement.

Led by University of Newcastle public health researcher Courtney Barnes, the study found very little evidence that kids had stopped accessing restricted social media platforms such as TikTok, X, Facebook and Instagram.

But the question “are children evading social media age checks?” might be the wrong one to ask when considering the long-term success of Australia’s world-first experiment.

Isolating the effect of the ban

The team behind the new study followed 408 adolescents aged 12–16, surveying them just before the law took effect in December 2025 and again three months later. They compared teenagers just under the age cutoff with those just over it to isolate the law’s effect.

They found more than 85% of under-16s were still using restricted platforms at follow-up, mostly through their own accounts.

Two thirds had encountered age verification, but the most common form was simply being asked to state their age. A minority used fake accounts or private browsing to access social media. But VPN use to evade the ban was rare.

When the researchers checked whether under-16s used social media any less than the just-over-16s who were free to keep their accounts, they found no meaningful gap at the age cutoff.

The researchers were transparent about the study’s limitations. The analysis was underpowered (which means the study may not have had enough participants to detect an effect if one existed). The sample sizes either side of the cutoff were also small.

Nevertheless, these results square with recent research from the eSafety Commissioner that showed roughly 7 in 10 children kept their accounts after the law came into effect.

So, case closed, right? The ban is a failure? Not quite.

An unrealistic pipe dream

It was an unrealistic pipe dream that the ban would stop all of today’s under-16s from using social media overnight. All online technology comes with inherent capacities to be exploited or its features circumvented.

Instead, the ban enables the government to put pressure on social media companies to comply with their directives – to restrain and contain them with greater power than existed before.

The ban should be considered over a longer timeframe. Its logic is more aligned with another form of public health law: the generational approach now being applied to tobacco control.

Britain’s Tobacco and Vapes Act, which received royal assent in April 2026, bars anyone born on or after January 1 2009 from ever being sold tobacco.

The aim is not to make today’s smokers quit but to raise a generation for whom smoking never becomes normal. Australia’s social media law makes a similar bet: that if access is delayed long enough, social media might lose its grip on childhood the way cigarettes slowly did.

That is the measure that matters, and it’s a far slower and less certain test than counting how many teens still have Instagram six months after the ban took effect.

A benighted idea for future generations

Granted, there’s a catch to this framing.

Tobacco use has been denormalised with a public health approach for decades, and its supply has been squeezed from multiple directions: higher prices, plain packaging, advertising bans.

It’s hard to put pressure on social media use in the same way. Effectively, social media is “free”, practically infinite, and engineered to maximise engagement.

Shifting a generation’s social media norms this way only works if the pressure on platforms is relentless and sustained for years, not abandoned the moment the first headlines call it a failure.

My research into social media use and risk-taking found the same difficulties: norms are sticky. Social media rewards risky content and changes what is deemed as normal or acceptable. Changing norms like these overnight is unlikely.

But viewed in the long term, or even generationally, we can see how social media use for children may become a benighted idea for future generations.

Effects not clear for a decade

Naturally, laws that “ban” things often have unintended or even detrimental consequences. When mandatory bicycle helmet laws were introduced in Australia in the early 1990s, one result was that some people simply cycled less.

The new study in the British Medical Journal reflects this, with small numbers of young people turning to fake accounts, private browsing or messaging apps. Some may drift to less visible corners of the internet that are harder to watch than the mainstream platforms.

We shouldn’t take this to mean the ban is a failure. It means we are judging it on a timeline that does not fit its design.

The researchers make the point themselves: the greatest opportunity may lie with children under eight who have not yet started using social media, rather than teenagers whose habits are already set, whose norms are to use social media.

By their estimate, the full effects may not be clear for a decade.

Australia has volunteered to be the world’s test case, with other countries now following. To do the social media age restrictions justice, we should test the right thing.

Samuel Cornell, Honorary Research Fellow in Public Health, The University of Queensland

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World

How AI Is Supporting the Next Generation of Small Businesses

By Jelyn Johnson

Artificial intelligence is not something that is used occasionally to help small businesses. It is now a part of how these businesses work every day. Research from Adobe shows that artificial intelligence is becoming a part of what makes small businesses run. It is no longer an extra tool that helps with a few things but it is now a key part of everything from marketing, to the way things are done in the office.

This is a deal: artificial intelligence is not just making things a little faster, it is actually changing the way work is done in small businesses. It is changing how all the different parts of a business work and operate with each other. AI is really changing what it means to be a business.

A New Formula to Help Business Growth

Small businesses software often has a specific application. There is one software application for sending emails, there is another one for accounting purposes, and another for designing. The role of AI in small businesses is breaking this trend. The majority of small businesses are embracing AI in their operations for more than one process compared to their previous use for individual processes.

The truly amazing thing about all of this is the fact that the use of software is gradually turning into the integration of software into operations. The AI technology is being applied to automate repetitive operations such as creation of content, media posting, customer communications, and handling administrative tasks.

AI software is not being used alone. Rather it is being added to the existing ways of doing things to make everything run more smoothly. AI technology is being used to complement tasks like content creation, social media creation, customer communication and administration to make these tasks easier for businesses.

This is a significant change in small business operations since small businesses are always looking for ways to save time or be more efficient.

Workflow Automation is Becoming the Primary Driver of Adoption

Perhaps one of the most evident pieces of evidence from research results is the fact that small businesses are not using AI as an experimental tool. The reason why AI adoption among small firms is happening is practical; it means that people want to save their time by making work more efficient.

There were tasks that used to take much time, such as creating social media posts, marketing copywriting, or anything else, which is done for the customers’ benefit. These kinds of tasks are now often partly or completely automated using the power of AI. Often, these processes are not done from scratch anymore, but instead, they are handled as a kind of first draft in collaboration with AI assistance.

This trend is really important because it changes the way people work at businesses. Artificial Intelligence is not taking the place of workers, it is just doing repetitive tasks.

Time Savings are Being Allocated to Higher-Value Work

We can see that when small businesses use Artificial Intelligence they do not get free time. Instead the owners of these businesses are using this newfound time to do things that will help their business continue to grow.

The time saved is being used for thinking about the future, talking to customers and making their business better. AI is helping business owners to focus on these things. This implies that AI technology is not only increasing efficiency and also changing the priority of time usage.

The reallocation serves a very important structural change in the operation of small businesses. As the repetitive work is reduced and time is saved, the constraint moves from being ‘available time’ to ‘quality of decision-making’. The business owner is no longer constrained by their ability to execute as much as they can be by the effective use of time.

• Also read: AI saves time – so why does it make us feel guilty?

AI is Quietly Standardizing Small Business Workflows

Another developing trend is the process standardization that occurs within small businesses as they begin to implement the use of AI at scale. With many companies implementing tools that are used to generate content, to communicate, and to manage marketing processes, there are certain patterns of behavior that start to develop.

For instance, the content production process is often becoming increasingly uniform in its pattern, with the development of an idea, automatic generation of the draft, and finally, manual refining of the draft.

Over time, this will lead to a smaller variation of actions taken by the small businesses when performing the tasks, especially marketing and communications tasks. At the same time, it raises the question of differentiation, as all outputs from the use of AI become similar.

How Gains in Productivity are Beginning to Show Their Impact

From our findings, AI positively contributes to business operations on top of streamlining day-to-day processes. Productivity increases lead to drastic improvements on business outputs.

There are observable improvements among small businesses as they deploy artificial intelligence. They are improving their core competencies, which in turn has a positive impact on customer engagement levels and the bottom line. This shows that AI has an impact beyond internal business operations for small businesses.

Customer engagement and revenue generation are other ways artificial intelligence has a positive impact on business performance.

The main process behind this effect seems to be compounded efficiency. The time savings in the execution process allow the company to do more work in terms of marketing, customer communication, etc., without additional costs.

In that way, AI acts not as a device but as a multiplier of business potential.

The Emerging “AI-first” Small Business Model

Together, these developments seem to signal the emergence of a new operational model, the small business that operates on the basis of AI-first. This does not imply that small businesses become fully automated operations.

Decision-making methods will still be a collaborative effort led by human thinking when it comes to strategy development, creative aspects, and relations with customers. Yet, the process of performing the tasks associated with decision-making is done through the assistance of AI algorithms.

Overall, this results in a combined operational model in which humans make decisions, and AI performs the majority of tasks.

Thus, AI becomes a tool that expands the capabilities of an existing business operation.

Take a look at these infographics for more insights on small businesses are leveraging AI today:

Some key insights:

• AI usage has climbed to 85% among surveyed small business owners, with 65% citing improved confidence in future growth.
• "Small business owners using image generation tools are 32% more likely to cite burnout reduction as their primary motivator".
• "47% of small business owners saw an increase in revenue since beginning to use Al tools, with an estimated revenue increase of 21%".
• "Small business owners are investing an average $218 on Al training this year to stay competitive, with about one in seven investing $1,000 or more".

The Next Phase of Technology

The more that small businesses use AI technology the harder it will be for other small businesses to keep up. When small businesses use AI technology they can do things without needing to hire more people.

For example AI technology helps with a lot of tasks. This means small businesses can be more productive and efficient with their time. The notion of what software and tools can do for businesses is also changing.

It's not just one thing, people are looking for systems that can automate a lot of things. It's the AI technology that makes all these systems work together. It makes things run smoothly, which in turn makes things happen faster.

If you look at the landscape you can see that AI technology is a part of how small businesses operate online. AI technology is transforming how small businesses do business on the Internet.

Thus, what we can conclude from this data is that the use of AI tech in small businesses is no longer a process of experimenting or making the process more efficient. It becomes an essential part of the change in how small businesses operate.

Reviewed by Irfan Ahmad.

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by Guest Contributor via Digital Information World

The Highest-Earning Creators of the Internet Content Machine

By Katharina Buchholz, Statista

Content creator MrBeast aka Jimmy Donaldson earns more than anyone else in the business. This is according to the newest edition of the Forbes Top Creators list published Tuesday. The 28-year-old who grew up in North Carolina made $300 million in gross earnings between March 2025 and March 2026, according to the source, far outpacing other influencers. Donaldson has had resounding success with his YouTube channel focused on over-the-top challenges (and the occasional grand gesture) and released the second season of his Amazon Prime series Beast Games in January. Earnings also come from a food side business, an analytics tool and toy and clothing licensing. Donaldson's company reportedly has taken on venture investments at a $5 billion valuation as well as purchased a personal finance app for teens.

The latest release of Forbes' list of the most successful influencers shows that YouTubers generally rank high among the best-paid content creators. One aspect of this is sponsored posts and ads earning more if they are in a video format. According to Forbes, Donaldson is in fact capitalizing on this aspect. However, many creators who have earned millions as social media personalities have done so by outside business deals. Rhett McLaughlin and Link Neal of channel Rhett & Link have branched out from YouTube sketch comedy and other entertainment content to streaming deals, live appearances, merch and book sales. Mark Edward Fischbach, known as Markiplier on YouTube, initially uploaded gaming videos, but now also earns cash with merch sales and a clothing line. After some podcast and TV deals, he self-released his first feature film earlier this year.

Also among the highest earners are two creators focusing on personal finance and business tips. Phoenix-native Codie Sanchez pivoted from a career in journalism and finance to teaching small business ownership through her multiple online channels, a podcast and a New York Times Best Seller. She has been a prominent voice in the passive income and vending machine/laundromat hype has has been circulating online. Serial startup founder Steven Bartlett meanwhile became famous for his podcast The Diary of a CEO, which streams on YouTube and audio platforms. The format, which features interviews with CEOs, entrepreneurs and celebrities, became one of the most listened-to podcasts in the world. Since then, Bartlett has continued founding and investing in companies, has authored two books and has become an angel investor on the British TV show Dragon's Den.

Second-ranked Dhar Mann shot to internet fame producing mini dramas that can be viewed on YouTube and social media platforms after trying his hand at other entrepreneurship ventures. Having started out with motivational content, his current video releases have been described as morality plays, featuring stories in which a character has to navigate between good and evil influences. Raised in Oakland, Calif., by Indian parents, Mann employs 200 studio crew who shot video in eight teams simultaneously and collaborates with around 2,000 actors per year.

This post was originally published on Statista and republished here with permission.

Reviewed by Irfan Ahmad.

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by External Contributor via Digital Information World

Spy agencies say AI can help combat AI cyber risks. But don’t forget the basics

Toby Murray, The University of Melbourne

Cybersecurity agencies of Australia, Canada, New Zealand, the United Kingdom and the United States issued a call to action on Monday for cyber defenders. The message was clear: artificial intelligence (AI) is a powerful weapon for cyber attackers; defenders must act urgently to improve their cyber defences.

Image: Trophim Laptev/Unsplash

There is much hype and uncertainty surrounding AI and cybersecurity right now. This latest statement comes little over a week since the US government caused frontier AI provider Anthropic to block access to Mythos and Fable, its most advanced AI technology, over fears they might be misused by foreign adversaries to attack US government systems.

In this torrid environment, it’s important for cyber defenders to look past the noise and prioritise what is truly important in protecting their systems.

A call to arms

The joint statement was issued by the heads of the national cybersecurity agencies of the Five Eyes. It warns that AI is dramatically shifting cyber risk and spells out how defenders must act to secure their organisations.

It notes how powerful AI is already helping adversaries carry out more sophisticated attacks more quickly.

One way this is happening is through automated vulnerability discovery and exploitation. No software is perfect. Adversaries leverage subtle design or implementation flaws in a system’s software to break into that system. They then take control of it and use it as a staging ground to launch further attacks.

This is why it’s so important for cyber defenders to keep up to date with deploying software patches. These are small modifications to system software that close off known vulnerabilities.

AI is enabling adversaries to find flaws orders of magnitude faster, as well as to work out how to exploit those flaws to carry out attacks.

For this reason, the Five Eyes statement warns that AI is dramatically shrinking the time between when a vulnerability is first discovered and when it is first exploited in an attack. Defenders can no longer afford to wait weeks before deploying software patches.

What can defenders do?

The Five Eyes report notes cyber fundamentals are crucial and encourages organisations to use AI to boost defences. But deploying AI without first investing in cybersecurity basics would be a mistake.

The cyber defenders who will be able to weather the AI storm will be those who already have mature practices. They know exactly what assets they need to protect, which systems in their organisation are exposed to attack, and what defences are in place to protect exposed systems. They also know to measure defence effectiveness and determine where defences are missing.

They also use evidence-based processes for tracking known vulnerabilities in their systems and prioritising which are most important to patch. These are backed up by reliable processes for rapidly testing and rolling out software patches, as well as for responding to cyber breaches and incidents.

When AI makes finding software vulnerabilities cheap, the next generation of software needs to be engineered to be secure by construction.

Working out the best methods to do this is what I have devoted my research career to.

Before reaching for AI, defenders should first invest in their fundamentals. Otherwise, they are effectively deploying a robot guard dog to defend an unlocked door.

The role for AI in cyber defence

This doesn’t mean AI can’t play an important role for cyber defence – just that it should augment rather than replace strong cyber fundamentals.

AI benefits attackers and defenders alike. An AI model that can help attackers find software vulnerabilities can also help defenders fix those same vulnerabilities.

AI that can automatically exploit software vulnerabilities is just as useful to defenders in helping them to confirm their software has been correctly patched. AI that can map and discover sensitive assets within a computer network is useful for both offensive and defensive purposes.

This is why it’s so important that defenders have access to AI capabilities, so they can be leveraged to harden and protect systems before that same AI is used to attack them.

Can regulation help?

Working out how to balance the competing benefits and risks of new cybersecurity technology is nothing new.

In the 1990s, society grappled with how to regulate the encryption that protects online communication from adversaries but also allows them to avoid law enforcement.

In the 2000s the rise of cyber exploit kits allowed defenders to better test their systems but also enabled any disaffected teenager with an internet connection to become a “script kiddie” hacker, leading to arms controls debates a decade later.

The 2010s gave us blockchain technologies such as Bitcoin and other cryptocurrencies, which were built on defensive cyber technologies but whose lasting legacy remains the rise of ransomware attacks and online illicit marketplaces.

The rise of AI presents a similar dilemma for regulators.

A blanket export ban on advanced AI models is likely to be counterproductive. Open-source AI models such as DeepSeek lag only months behind the most advanced models of OpenAI and Anthropic. Recent research suggests that much of that gap can be closed by pairing less powerful AI models with complementary technologies.

Defenders should therefore assume their adversaries already have access to AI on par with that used for cyber defence. Only by investing in strong foundations can they hope to escape the cat-and-mouse AI cyber arms race.

Toby Murray, Professor of Cybersecurity, School of Computing and Information Systems, The University of Melbourne

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Reviewed by Irfan Ahmad.

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• Top AI Logo Makers in 2026 [Ad]

by External Contributor via Digital Information World

Top AI Logo Makers in 2026 [Ad]

If you had to create a logo today, would you still start from scratch, hire a designer, or try one of the many AI logo tools available online?

The reality is, most people now turn to AI logo makers first. The challenge isn’t access anymore… It’s choosing the right tool from a growing list that all promise fast, professional results but deliver very different experiences.

In this article, we look at the top AI logo makers in 2026 and how they actually perform when used for real branding work.

Quick Verdict

After testing these platforms across various branding scenarios, Design.com emerged as the most complete option overall. It consistently produced strong logo concepts quickly while also offering deeper customization and broader branding tools compared to the rest.

That said, not every tool serves the same purpose. Some are better for quick experimentation, while others are designed for full brand ecosystems or website-first businesses.

We tested these tools based on:

• Speed of logo generation: how quickly usable logo concepts are created
• Design quality and originality: whether outputs feel generic or professionally crafted
• Customization flexibility: how much control users have over the final design
• Branding ecosystem: whether logos extend into other assets like websites or marketing materials
• Export usability: file formats, resolution, and real-world application readiness

Quick Comparison

Tool	Best For	Strength	Limitation
Design.com	Full branding systems	Deep AI + branding tools	No native app yet
BrandCrowd	Template-based logo creation	Fast workflow	Less technical integration
Canva	General design & collaboration	Easy and versatile	Less logo-specialized
Adobe Express	Simple logo creation	Clean interface	Fewer branding features
Shopify (Hatchful)	E-commerce branding	Simple store-focused logos	Limited design depth

1. Design.com – Best Overall AI Logo Maker for Full Branding

Design.com is built as a full branding platform rather than just a logo maker. When we tested it, the system didn’t just create logos, it generated full brand directions, including variations, layouts, and supporting design assets.

What stood out most was how the AI could be adjusted conversationally. Instead of manually editing every element, we could request changes like “make the logo more minimal,” “change to a warmer color palette,” or “try a more modern icon style,” and the system would update the design accordingly.

It feels less like using a template tool and more like iterating with a design assistant.

Key Features

• Conversational AI editing for real-time logo adjustments
• Large library of logo templates and design assets
• Automatic brand consistency across fonts and colors
• Built-in tools for business cards, websites, and marketing materials
• Multiple export formats, including print-ready files

Pros

• Strong AI-driven customization flow
• High-quality logo outputs
• Full branding ecosystem beyond logos
• Fast iteration process

Cons

• Web-based only

Pricing

Free Plan:

Design.com offers a genuinely free logo option with no watermarks, high-quality downloads, full editor access (including AI chat editing), and a solid selection of free logo templates.

Paid Plans:

• Starter: from $3/month (annual) or $9/month
• Value: from $4/month (annual) or $14/month
• Premium: from $5/month (annual) or $19/month

See it in action below:

Logo samples:

Logo customization:

Asking AI to do the changes:

2. BrandCrowd - Best for Template-Driven Logo Creation

BrandCrowd focuses heavily on speed and template variety. When we tested it, the workflow was straightforward: enter a business name, browse logo design concepts, and customize from there.

It works well for users who want something polished quickly without spending too much time refining details.

Key Features

• Large library of logo templates
• Fast keyword-based logo generation
• Simple customization editor
• Export options for digital and print use
• Additional branding assets, like business cards and social media designs

Pros

• Very fast workflow
• Large template selection
• Easy to use

Cons

• Less technical integration

Pricing

Free Plan:

BrandCrowd offers a selection of genuinely free logo templates with no watermarks, full editor access, and high-quality downloads in formats such as PNG, JPG, SVG, PDF, EPS, GIF, and MP4.

Paid Plans:

• Starter: from $3/month (annual) or $9/month (monthly)
• Value: from $4/month (annual) or $14/month (monthly)
• Premium: from $5/month (annual) or $19/month (monthly)

See it in action below:

Logo samples:

Logo Customization:

3. Canva – Best for All-in-One Design Work

Canva is less of a dedicated logo maker and more of a full design platform. In testing, we found that logo creation is only the starting point; most users will likely stay within Canva to build the rest of their design.

Its strength lies in collaboration and versatility.

Key Features

• Drag-and-drop logo editor
• Millions of design templates
• Real-time team collaboration
• Brand kit tools for consistency
• Easy export across formats

Pros

• Extremely easy to use
• Strong collaboration features
• Huge template ecosystem

Cons

• Not specialized in logo design
• Advanced branding requires a paid plan

Pricing

• Free Plan: Includes access to templates, basic design tools, and a large library of free assets for logo creation.
• Pro Plan: around $12.99/month – unlocks premium templates, Brand Kit, background remover, and advanced branding tools.
• Teams: Custom pricing for collaboration and business use.

See it in action below:

4. Adobe Express – Best for Clean, Simple Logo Design

Adobe Express offers a more lightweight logo creation experience compared to Adobe’s professional tools. During testing, it performed best when users wanted something clean, minimal, and fast.

It doesn’t overwhelm users with options, which can be a strength depending on the use case.

Key Features

• Simple logo templates
• Fast editing tools
• Cross-device support
• Basic branding elements
• Adobe ecosystem integration

Pros

• Clean interface
• Fast workflow
• Professional-looking outputs

Cons

• Limited customization depth
• Fewer branding tools compared to competitors

Adobe Express – Pricing

• Free Plan: Includes basic logo templates, editing tools, and standard design features.
• Premium Plan: around $9.99/month – unlocks premium templates, brand tools, and AI features.
• Business Plan: Custom pricing for teams and organizations.

See it in action below:

5. Shopify (Hatchful) – Best for E-commerce Logos

Shopify’s Hatchful tool is designed specifically for e-commerce users. When we tested it, the experience was very structured—users select an industry, visual style, and then receive curated logo options.

It’s simple, but intentionally limited to keep things fast.

Key Features

• Industry-based logo generation
• Pre-designed style categories
• Simple editing options
• E-commerce-focused branding outputs
• Free logo downloads

Pros

• Very easy to use
• Free access
• E-commerce-oriented designs

Cons

• Limited customization
• Not suitable for advanced branding
• Better suited for simple ecommerce logos than full brand identities
• Logo designs can feel less unique for niche industries

Pricing

Free Plan: A completely free logo maker with downloadable logo files included. No paid tiers required for logo creation, making it a simple option for quick ecommerce branding.

See it in action below:

Conclusion

Choosing an AI logo maker is no longer just about generating a logo. The best tools help you create a visual identity that can grow with your business, from social media graphics and business cards to websites and marketing materials.

If you're looking for an AI logo maker that can take you from your first logo concept to a fully branded business presence, Design.com is the best place to start!

by Sponsored Content via Digital Information World