Artificial intelligence (AI) is technology that teaches computers to think and learn like humans. Instead of following rigid programming, AI systems analyze data, spot patterns, and make decisions. These systems get smarter over time, learning from each interaction to improve their performance.
More than a passing tech trend, ecommerce business owners treat AI as a practical tool that transforms how they run their businesses. A 2025 Shopify survey of store owners found 75% of established business owners already use AI.
Whether you want to make money with AI or are interested in learning more about generative AI tools, this guide shares what you need to know about artificial intelligence and how it can grow your business.
What is AI, exactly?
Artificial intelligence (AI) teaches machines to think and solve problems like humans do. It combines computer science fields like machine learning (ML), natural language processing (NLP), computer vision, and robotics to create systems that can analyze information, make predictions, and learn from experience.
Advanced AI systems work like simplified versions of the human brain, using artificial neural networks to process information. These systems can teach themselves new skills without human guidance—similar to how you might learn to recognize your favorite coffee shop’s logo after seeing it a few times.
How AI works: the building blocks
AI encompasses several techniques that work together to create intelligent systems. Here are the main approaches that power most AI applications:
Machine learning: computers that learn from data
Machine learning (ML) teaches computers to identify patterns in large amounts of historical data and make predictions without being explicitly programmed for each scenario. Instead of writing code that says “if this, then that,” you feed the system examples and let it figure out the rules.
The AI system learns through three main approaches:
- Supervised learning: Learning from examples with known answers.
- Unsupervised learning: Finding complex patterns in data without guidance.
- Reinforced learning: Where AI agents learn through trial and error.
When you shop online and see “Customers who bought this also bought,” for example, that’s machine learning analyzing thousands of purchase patterns to predict what you might want next.
Machine learning also powers AI business tools like Shopify Sidekick. The AI assistant can:
- Redesign your website
- Write copy, including product descriptions and marketing emails
- Edit product images
- Custom-code new apps
- Offer personalized tech support
Deep learning and neural networks
Deep learning mimics how the human brain processes information. These systems use artificial neural networks (ANNs) with multiple layers. Think of them as interconnected decision-making nodes that work together to solve complex problems.
Different types of deep neural networks excel at different tasks:
- Convolutional neural networks (CNNs) process patterns in visuals for image recognition.
- Recurrent neural networks (RNNs) handle sequential data like language translation and speech recognition.
Natural language processing (NLP)
Natural language processing (NLP) teaches computers to understand and generate human language. This technology handles tasks like analyzing text sentiment, recognizing important information, and translating between languages.
NLP combines statistical methods, rule-based approaches, and machine learning algorithms to process text and speech. This foundation allows large language models (LLM)—the technology behind chatbots and virtual assistants—to communicate naturally with humans.
For example, say you were to ask Shopify Sidekick, “What’s my bestselling product in California over the last 30 days?” The AI assistant would use NLP to understand what you mean and retrieve the relevant Shopify Analytics report.
Computer vision
Computer vision allows AI tools to understand what something is. It uses a convolutional neural network (CNN) to identify what an image or video contains, then powers AI features like visual search.
Take Google Lens, which uses computer vision when users upload an image to the visual search platform. It can understand what the image contains, then match it with similar products from an ecommerce brand’s website. The platform powers more than 20 billion of these queries every month.
Types of AI: from narrow to general
AI systems fall into three main types of AI based on what they can do:
Narrow AI (ANI): the only AI that exists today
Narrow AI (ANI) is a type of AI model that’s trained to do one thing. Think of it as a single-minded tool that’s very good at what it’s designed for but is unable to apply its knowledge to entirely new situations.
Ecommerce examples of narrow artificial intelligence applications include:
- Website analytics tools. These AI tools audit your websites and analyze site usage and customer behavior.
- AI product recommendations. Suggests items based on what shoppers view or add to their carts.
- Smart on-site search. Reorders search results on your website if a query (e.g., “black sneakers”) isn’t getting clicks.
- AI customer segmentation. Groups buyers by behavior (like lifetime value or churn risk), which powers personalized ads and SMS campaigns that target each customer segment.
- Automated emails and texts. Triggers messages based on past purchases.
General AI (AGI) and superintelligence: what’s next
Artificial general intelligence (AGI) is still theoretical, but it’s expected to match (or even surpass) human reasoning across all domains. Computer scientists envision AI machines that can learn, reason, solve problems, and adapt to new situations just like a human can.
AI experts have different expectations on when this type of superintelligence will happen. Anthropic’s CEO Dario Amodei estimates it could be as soon as 2027.
In the future, AGI might be capable of:
- Creating original works. An AGI system could process human language to write a news article, compose a musical piece, create visual art, or even design a building.
- Understanding and responding to complex questions. Intelligent machines running on AGI could analyze vast amounts of information to answer questions in a comprehensive and informative way, even if the answers require reasoning or making judgments.
- Solving complex problems. AGI neural networks could analyze data on matters of global importance—such as water scarcity—and they could work with humans to develop effective solutions or propose solutions without human intelligence.
In the context of ecommerce, AGI might be able to handle everything from strategy to execution as a single system, without switching between different tools.
Reactive machines, limited memory, and beyond
Reactive AI systems respond to immediate situations using preset rules. They have limited memory and don’t learn from past experiences or remember previous interactions. They simply follow their programming.
Examples of reactive AI include basic product recommendation engines that suggest items based only on what’s currently in your customer’s cart without considering their purchase history.
A brief history of AI
To understand AI, it helps to look back at the history, including the initial foundations and how it became democratized:
- 1950s: The Turing Test. Mathematician Alan Turing introduced the Turing Test. It measured whether a human could distinguish between human and machine-generated responses. Computer scientist John McCarthy coined the phrase “artificial intelligence” in the 1956 Dartmouth Conference.
- 1966: The first AI chatbot. Computer scientist Joseph Weizenbaum launched ELIZA. A research paper published by Joseph said: “Some subjects have been very hard to convince that ELIZA (with its present script) is not human.”
- 1996: Deep Blue. IBM launched the chess supercomputer program Deep Blue. It became the first computer system to defeat world chess champion Garry Kasparov one year later.
- 2001: Google starts using machine learning. It used statistical machine learning to suggest better spellings and detect spam.
- 2011: Apple launches Siri. Siri used NLP to understand voice commands and Apple integrated the AI assistant into iPhones beginning in October 2011.
- 2022: ChatGPT launches. OpenAI made AI accessible to all with ChatGPT. Anyone with an internet connection could chat with the AI tool, which used NLP and LLMs to give answers. It had one million users in the first five days.
AI examples in everyday life
Pew Research found 79% of AI experts think people in the US interact with AI several times a day. The technology is found in several industries, from ecommerce to healthcare:
AI in shopping and ecommerce
Platforms like ChatGPT, Google Gemini, and Microsoft Copilot have become crutches for shoppers who need personalized help.
NielsenIQ’s 2026 data found 42% of customers have used at least one AI tool to shop in the past month. Of them:
- 17% have asked AI for product recommendations
- 10% have used a voice assistant to buy or reorder products
- 5% have used AI agents to place orders on their behalf
“I think that’s going to be a paradigm shift over the next couple of years,” says Paul Tran, founder of Manscaped, in a Shopify Masters interview. “Shoppers’ exploration of new products will be disrupted by AI.”
AI in communication and productivity
AI can make decisions much faster than the human brain can. It can propagate at almost the speed of light.
This speed influences productivity: Anthropic’s 2025 data shows AI can reduce task completion time by 80%. It estimates that people use AI in minutes for tasks that would take humans roughly 1.4 hours to complete.
Chatbots are an example of how this productivity influences communication. Better availability, speed, and more accurate information are the top reasons customers opt for AI over human support.
The same productivity gains are true for human customer support agents: Salesforce’s 2025 report found reps using AI spend 20% less time on routine cases. It frees up an estimated four hours every week.
AI in transportation and healthcare
Artificial intelligence uses patterns to predict what might happen next. This technology powers Waymo’s self-driving cars.
Waymo uses machine learning to make split-second decisions based on the car’s surroundings. The brand’s 2026 safety report found their autonomous vehicles are involved in 92% fewer crashes that cause fatal or serious injuries to human drivers in the same conditions.
The health care industry is also impacted by AI, with everyday people using AI models for this purpose.
One person said ChatGPT saved their life after the AI model suggested they get medical attention for a possible bleeding risk. An Australian man also custom-built a cancer vaccine for his dog by having AI understand the tumor’s DNA.
What AI means for your business
A 2025 Shopify survey of store owners found efficiency on repetitive tasks (55%) and help with brainstorming and creativity (55%) are the top two reported benefits of AI.
“Think small, iterate fast, then scale,” advises Alex Pilon, Shopify staff developer and AI advocate. “When you’re working with big data, testing your prompts on specific cases or running AI-based processes on small batches makes it easier to spot-check and battle-test your process.”
Here’s what that looks like in practice with AI use cases for ecommerce:
Writing product descriptions and content
Syndigo’s 2025 report found 44% of customers have abandoned a purchase because there wasn’t enough product information available. But content can be difficult to manually scale across a large product catalog.
“We have hundreds of products, and I can tell you, if you’re a new store owner, or especially if you’ve been in the industry for a while, if you add a whole suite of new products and you have to add product descriptions: the first couple’s cool,” says Mikey Moran, CEO of Private Label, in a Shopify Masters interview. “You’re all hyped up and excited. Then you’ll notice the creative process in your brain and the words all start becoming the same.”
Generative AI can step in and write new website copy—including product descriptions—based on a prompt. Here’s what that AI prompt might look like in Sidekick:
“Write me a product description for my hand-poured candle. The scent is vanilla and it comes in a reusable jar. Keep the tone of voice fun and playful.”
Sidekick is an AI assistant that knows your store data. It’s handled millions of conversations and usage is up fourfold year over year.
“It becomes very difficult to stay creative for a long period of time,” Mikey says—but that’s where Shopify Sidekick helps. “It just blew my mind how fast I could create amazing product descriptions.”
Customer service and chatbot automation
AI-powered chatbots handle routine customer questions 24/7, from order status updates to return policies to product information. For complex issues, AI chatbots can gather information and route customers to the right human team member.
AI chatbot systems can engage customers across multiple channels—your website, SMS, social media—providing instant responses. It caters to the 88% of customers who expect faster response times than a year ago, per Zendesk’s 2026 CX report.
Take Sean Frank, CEO of Ridge, who now has AI handle 60% of all customer support tickets. The brand’s Net Promoter Score (NPS) jumped up two points after implementation.
“The real benefit is that my human customer service team can now focus on the complicated cases that require more judgment and empathy,” says Sean. “The AI handles the volume while humans handle the nuance.”
Inventory, pricing, and operations
AI helps you predict demand by analyzing sales trends, seasonal patterns, and market conditions. Gartner estimates that 70% of large organizations will use AI technology to predict future demand by 2030.
Retailers can use AI to help with inventory management tasks like:
- Automating reordering
- Adjusting prices based on demand
- Optimizing inventory carrying costs
Sean says Ridge previously had three people responsible for inventory planning and buying. “Now I have one inventory director handling everything,” he says. “We feed our sales data, trends, launch calendar, and forecasts into an AI model that does the complex analysis. That one person reviews it, applies judgment, and makes the calls.”
Selling inside AI conversations: ChatGPT storefronts
Shoppers’ willingness to shop through AI platforms presents huge opportunities for brands with agentic commerce.
Shopify’s 2026 data found more than half of AI-referred sessions start on product pages, compared to 20% for organic search. Those shoppers convert at almost 50% higher rates and spend 14% more when they do.
If you’re on Shopify, you can sell directly inside ChatGPT conversations. The integration pulls data from your Shopify store into relevant ChatGPT conversations—no links or redirects—to reach customers where they’re already using AI to shop.
AI myths vs. reality
There are some misconceptions around AI, particularly relating to the job market and its complexity. Here are three common myths and whether they’re true:
“AI will replace my job”
Over half of workers think AI will eventually be able to perform at least some parts of their job as well as them, per SurveyMonkey’s 2026 report. A quarter think AI will be able to replace at least 25% of their responsibilities.
Despite those concerns, BCG estimates AI will reshape between 50% to 55% of jobs in the US, which is more than it’ll replace. And PwC’s Global AI Jobs Barometer found wages are growing in virtually every AI-exposed occupation.
Mikey shares how he handles AI job security concerns from his team: “I say, ‘No, it’s not going to replace you—it’s going to make you twice as valuable because of all the stuff that you’re going to be able to get done in a day, so then I can probably pay you more once it starts working.’”
“AI is too complex for small businesses”
Shopify’s 2025 Store Owner Survey found that of store owners who don’t already use AI, 29% don’t know where to start. If that’s you, turn to the AI models already built into the tools you’re using.
Shopify Sidekick is built into every Shopify plan. You can use the AI assistant for daily tasks, strategic planning, product descriptions, and store management. It offers round-the-clock instant help with Shopify tasks, bulk operations, product description generation, and personalized advice.
For example, you could ask Sidekick:
- What traffic source drives the most customers to my website?
- Make me a 10%-off sitewide discount code, and draft an email I can use to send the code to my top 50 customers.
- Set up a Shopify Flow automation to notify me by email when any product drops below 10 units.
“There’s a total misconception that you need 50 different tools,” says Catherine Goetze, founder and CEO of Physical Phones. “We use one or two on a regular basis, and we just know how to use them really, really well.”
“AI is always accurate”
AI is only as good as the data it’s trained on. If that initial data is biased or inaccurate, or the AI model pulls from unreliable external data sources (like the internet), the tool can give:
- False information which is factually incorrect.
- Fabrications, which happen when the model makes a false assumption based on initial training data.
HAI’s 2026 data found AI models hallucinate between 22% and 94% of the time. Always check anything it gives you and include a human in the loop to limit risk.
“If I was starting with AI for the first time, I would say interact with it as a ‘thought partner’—just ask it some questions about something, about anything you’re doing,” says Alex. “Take things with a grain of salt as you build your intuition for how it works and what its capabilities are.”
What is AI FAQ
What exactly is AI in simple terms?
Artificial intelligence (AI) is a type of technology that lets computers simulate the human brain. It’s trained to spot patterns in large datasets, then use what it’s learned to predict what might happen next.
What is an example of AI?
Personalized recommendations are an example of AI in ecommerce. The technology can spot patterns in a shopper’s behavior to predict what they might like. It surfaces connected products as “You may also like” recommendations.
What is the difference between AI and machine learning?
AI is a broad type of technology that simulates human thinking, while machine learning is the technology that lets AI algorithms learn without rule-based programming.
Who invented artificial intelligence?
No single person created AI, but the phrase dates back to 1956, when computer scientist John McCarthy first introduced the term at the Dartmouth Conference.
Is AI safe to use for my business?
AI is safe for businesses, provided you have guardrails in place. AC Hampton, founder of Supreme Ecom, says: “AI can’t feel emotion. And the one thing you do with marketing is push out emotion. Pain points, desires, real feelings—you can’t make that up. That’s where I don’t let AI touch.”
