The essential small business guide to generative AI (2023)

Generative AI (Artificial Intelligence) isn’t new, but the recent explosion of AI chatbots, AI image-generation tools and AI-driven applications leaves many small business owners in new and unfamiliar territory. What is generative AI? And how should or could entrepreneurs use generative AI for a small business?

While people are continuing to experiment with what AI is capable of versus what grabs the headlines, there are already some simple ways in which generative AI can help small business owners. Our guide aims to help small business owners learn more about generative AI and how it can help save small businesses time and money.

  • What is generative AI?
  • 5 ways to use AI for small business.
    1. Generate creative and unique business names.
    2. Automate content creation.
    3. Enhance customer service.
    4. Support for social media management.
    5. Optimize content for SEO.

What is generative AI?

Generative AI refers to a type of artificial intelligence that is capable of creating new content autonomously by learning from existing data. This can include generating text, images, music, or even design concepts by leveraging advanced machine-learning algorithms, such as deep learning and neural networks.

OpenAI’s ChatGPT and DALL-E are dominating the news, but new chatbot and AI art generation tools are being rolled out on a near-daily basis. From Google’s Bard to Meta’s BlenderBot, large tech companies are rolling out increasingly sophisticated generative AI tools.

It’s easy to start feeling overwhelmed, but it’s important to have develop a high-level understanding of generative AI and what it can do (along with what it can’t do).

Leveraging AI technology is crucial for small businesses to stay competitive in today’s rapidly-evolving global market. AI can help small business owners improve their efficiency and productivity by writing copy for websites or blogs, automating tasks, streamlining decision-making using data, and improving the overall customer experience.

Interested in learning more about how to use generative AI for small businesses? Let’s take a closer look at some examples that you can apply to your business.

Related: AI prompts for small business owners

A quick word of caution

This guide is meant as a general overview of how generative AI can help small business owners save time, and often money when running their businesses. We strongly recommend closely reviewing the output of the AI tool that you intend to use, as AI can return incorrect, false or outdated information or may include content containing third parties’ intellectual property.

Additionally, be aware that generative AI tools may save information that a user enters, so avoid entering any commercially sensitive or proprietary information in your prompts (the questions or tasks you ask an AI tool to help with).

5 ways to use generative AI for small business

From getting started with business ideas to optimizing your website content, here are 5 examples of how generative AI can help.

(Video) Generative AI Is About To Reset Everything, And, Yes It Will Change Your Life | Forbes

1. Generate creative and unique business names

The biggest barrier to getting started is sometimes a blank screen. Generative AI is great for helping to get your creative juices flowing. So if you’re stuck with writers block, or if thinking of a catchy business name isn’t your strong suit, consider using AI to kick-start the process.

AI can generate a large number of potential business names in a short amount of time, giving entrepreneurs a list of unique and creative names that they might not have come up with otherwise.

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And, if you’re not completely happy with the recommendations, you can iteratively improve the generated names simply by refreshing your prompt and telling the AI chatbot what you’d prefer to see, ensuring the final name selection is well-suited for your business.

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2. Automate content creation

Artificial Intelligence has the potential to revolutionize the way small business owners generate content for their business, By simplifying the content creation process and enhancing the effectiveness of published materials, such as website content, newsletters or blogs, AI can save entrepreneurs both time and money.

Using advanced natural language processing algorithms and deep learning techniques, AI-powered content-generation tools are able to analyze existing content within a specific industry or niche. Using that information, AI tools can then generate relevant and engaging content. In addition, you can tailor the output to match the overall vibe of your business.

Does your small business tend to be more light-hearted and fun? Add adjectives to help the AI tool generate content that fits your brand voice.

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Additionally, AI can automate the process of content scheduling and distribution across various channels, allowing small business owners to reach their audience with consistent and timely communication.

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(Video) How AI Could Empower Any Business | Andrew Ng | TED

By streamlining the content creation process and reducing the time and effort required, AI enables small business owners to focus on other critical aspects of their business, ultimately helping to drive growth and success in the competitive marketplace.

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3. Enhance customer service

Another area where AI can be a powerful tool for small business owners is to enhance customer communication. With AI, business owners can quickly craft personalized responses, such as thank-you emails to customers after they make a purchase or sign-up for a service, creating a sense of appreciation and helping to foster customer loyalty.

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AI can also streamline the writing process for creating follow-up messages, such as reminders for upcoming appointments or subscription renewals, making it easier to maintain a strong connection with clients.

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Customers aren’t always happy with the service they’ve received. Another task that AI can help with is responding to customer inquiries and complaints by analyzing the content of messages and generating customizable responses that address the specific issue at hand.

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Customer service interactions can quickly eat into a small business owner’s day. However, AI-powered chatbots and virtual assistants can handle multiple customer interactions simultaneously for you, significantly reducing the response time and allowing customer service representatives to focus on more complex tasks. This results in a more cost-effective customer service operation.

By providing fast and personalized responses to customers, AI-powered tools can enhance the overall customer experience, leading to higher satisfaction rates and a stronger brand reputation, all while freeing up time for business owners.

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(Video) Generative AI in the Enterprise, with EY Chief Technology Officer (CXOtalk #779)

4. Support for social media management

Social media is a necessary part of owning a small business, but managing multiple platforms and attempting to brainstorm creative new content can feel daunting. AI can help out here as well.

Here are a handful of tasks that AI is able to help with:

  • Brainstorm creative captions for image-based posts
  • Create editorial calendars based on local holidays or celebrations
  • Generate conversation starters for a social media audience
  • Write simple video scripts
  • List creative content ideas
  • Craft ad copy to grab people’s attention

While this list isn’t exhaustive, AI-based tools are a great way to get the creative process rolling, especially on days when your creativity feels like it’s in a rut.

AI is also helpful with identifying key moments and relevant events for a target audience. Events would include local celebrations such as festivals and parades, as well as industry-specific holidays. This can provide businesses with an opportunity to create content that connects with their audience on a more personal level.

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Another AI advantage is the ability to help small business owners maintain a consistent posting schedule, which ensures that businesses remain regularly active and visible on social media platforms. Consistent activity on social media platforms keeps the audience engaged and establishes the business as reliable and authoritative.

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The benefits that AI brings to the table for a small business owner ultimately contribute to increased brand visibility and a stronger connection with the target audience, making AI an invaluable tool for businesses looking to thrive in today’s digital age.

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5. Optimize content for SEO

For small businesses looking to drive traffic to their business, SEO is still king. And while SEO is definitely a skill, AI is able to give SEO novices the boost they need to get found online.

Keyword research is important for SEO, and AI is able to help business owners identify relevant and high-performing keywords in their industry.

(Video) How We Prevent the AI’s from Killing us with Paul Christiano

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In addition to helping business owners brainstorm keywords, AI can help create copy for a website. AI is able to generate SEO-friendly content that incorporates target keywords seamlessly while still providing value to the reader. This helps improve the website’s search engine ranking and increases the likelihood of attracting and retaining visitors.

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AI is also able to generate optimized meta tags and descriptions for web pages, ensuring that they accurately reflect the content and include relevant keywords. These elements play a significant role in how search engines index and rank web pages, which influences their visibility in search results.

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Another factor for SEO is website update frequency, and AI is able to assist here by suggesting content for blog posts or articles on a business website.

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And, if you need help coming up with a first draft for your blog post, AI can help with generating keyword-rich text, ensuring that the content is optimized for search engine ranking, which increases the visibility of a small business online. You can then just make tweaks so it’s authentic to your business.

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Summing it all up

Hopefully, we’ve given some helpful insights into how this new and evolving technology can help small business owners make the most of this new technology, and hopefully save save time and money. Just remember, it is crucial to check and review the output of AI tools and always avoid using sensitive information, leveraging generative AI to streamline tasks and improve the customer experience can give small businesses a competitive edge.

(Video) The REAL potential of generative AI


What is an example of generative AI? ›

Generative AI systems create things, such as pictures, audio, writing samples and anything that can be built with computer-controlled systems, such as 3D printers. Discriminative systems identify things such as people in pictures, words in speech or handwriting and what's real versus what's fake.

What is the difference between generative AI and general AI? ›

Artificial general intelligence is not limited to any specific task or domain, carrying on tasks without specific programming. On the other hand, generative AI focuses on generating new content within a niche based on existing patterns and data.

What are the challenges with generative AI? ›

Here are seven generative AI challenges business leaders should take into account.
  • Handling technical complexity. ...
  • Tackling legacy systems. ...
  • Avoiding technical debt. ...
  • Reshaping some of the workforce. ...
  • Monitoring for potential misuse and AI hallucinations.
2 days ago

What is the benefit of generative AI? ›

Generative AI could help businesses step up their personalization game. Machine learning algorithms can analyze a user's purchasing history and online behavior to improve product recommendations or generate custom content.

What is generative AI summary? ›

Generative AI is a set of algorithms, capable of generating seemingly new, realistic content—such as text, images, or audio—from the training data.

Which company is using generative AI? ›

Inworld AI, founded in 2021, is a company that uses generative AI and text-to-character prompts to help gaming and media companies make NPC characters more realistic.

What are the negative effects of generative AI? ›

Ethical Concerns with Generative AI

Generative AI raises ethical concerns, particularly when it involves deepfakes and synthetic media where the technology can learn from or be used to create fake or misleading content. We can only surmise the potential impact on privacy, security, and trust.

What is generative AI How is it being used today? ›

Generative AI is a form of artificial intelligence in which algorithms automatically produce content in the form of text, images, audio and video. These systems have been trained on massive amounts of data, and work by predicting the next word or pixel to produce a creation. And it's not just Big Tech.

What is the disadvantage of generative models? ›

Generative AI models can be difficult to explain. It's hard to understand why the model made a particular prediction or how it arrived at a certain conclusion. This can be a major issue for businesses that need to explain their decisions to stakeholders.

What type of value can be generated with generative AI? ›

The ultimate goal of Generative AI is to generate significant productivity and economic value.

What is generative AI and how much power does it have? ›

Generative AI is a type of artificial intelligence that focuses on creating new content based on the patterns and structures it learns from existing data. It is thus often used for creative tasks whereas other AI types are often used for goals such as classification or decision-making.

What is the purpose of generative learning? ›

Generative Learning Theory (GLT) suggests that learning occurs when learners are both physically and cognitively active in organizing and integrating new information into their existing knowledge structures.

What is generative AI for dummies? ›

Generative AI produces new content, chat responses, designs, synthetic data or deep fakes. Traditional AI has focused on detecting patterns, making decisions, honing analytics, classifying data and detecting fraud. Generative AI, as noted above, often uses neural network techniques such as transformers, GANs and VAEs.

How are people using generative AI? ›

Generative AI models and applications can, for example, be used for: Text generation. Text generation, as a field, with AI tools has been in development since the 1970s—but more recently, AI researchers have been able to train generative adversarial networks (GANs) to produce text that models human-like speech.

Is Grammarly generative AI? ›

Grammarly Business works across more than 500,000 applications and websites to enhance and accelerate workflows. With GrammarlyGO, the Grammarly experience now comes with the power of generative AI—across the digital spaces you write in most.

What are three 3 main categories of AI algorithms? ›

There are three major categories of AI algorithms: supervised learning, unsupervised learning, and reinforcement learning. The key differences between these algorithms are in how they're trained, and how they function.

What are the 3 types of AI *? ›

The 3 types of AI are artificial superintelligence, general or strong AI, narrow or weak AI.

What are the three types of AI models? ›

What are the 3 types of AI?
  • Artificial narrow intelligence (ANI), which has a narrow range of abilities;
  • Artificial general intelligence (AGI), which is on par with human capabilities; or.
  • Artificial superintelligence (ASI), which is more capable than a human.
Oct 24, 2017

What is the most highly valued generative AI? ›

OpenAI alone is valued at an estimated $29 billion, while Jasper AI and four others have also achieved unicorn status, with each having a valuation of $1 billion or more. The development of generative AI has been made possible by dramatic advances in semiconductor technology.

What is the best generative AI? ›

1. Chatsonic. It is a revolutionary generative AI tool built to beat all the limitations of Open AI, turning out to be the best alternative to ChatGPT. It integrates with Google Search to create content with the latest information.

Which AI company is under Elon Musk? ›

The billionaire owner of Tesla and Twitter is named as a director in a business-incorporation document filed in March for a new company called Corp.

Which AI is sponsored by Elon Musk? ›

Elon Musk is reportedly planning to launch an artificial intelligence company to compete with OpenAI, the creator of ChatGPT, as Silicon Valley battles for dominance in the rapidly developing technology.

How big is the generative AI market? ›

The global generative AI market size was estimated at USD 10.79 billion in 2022 and is projected to hit around USD 118.06 billion by 2032, growing at a CAGR of 27.02% during the forecast period 2023 to 2032. U.S. generative AI market was valued at USD 2.7 billion in 2022.

What are the three limitations of AI today? ›

AI's three biggest limitations are (1) AI can only be as smart or effective as the quality of data you provide it, (2) algorithmic bias and (3) its “black box” nature.

What are 3 negative impacts of AI on society? ›

These negative effects include unemployment, bias, terrorism, and risks to privacy, which the paper will discuss in detail.

Why has generative AI become so popular? ›

Generative AI allows people to create personalized content in seconds, ushering in a new paradigm for business. However, in our view, the technologies on which it is built — large language models (for text) and diffusion models (for images) — enable broader use cases beyond the 'generative' ones we see now.

Why is generative AI popular? ›

In conclusion, generative AI is a powerful tool that has the potential to revolutionize several industries. With its ability to create new content based on existing data, generative AI has the potential to change the way we create and consume content in the future.

What is the new generative AI technology? ›

Like other forms of artificial intelligence, generative AI learns how to take actions from past data. It creates brand new content - a text, an image, even computer code - based on that training, instead of simply categorizing or identifying data like other AI.

What is the opposite of generative models? ›

"Generative" describes a class of statistical models that contrasts with discriminative models. Informally: Generative models can generate new data instances. Discriminative models discriminate between different kinds of data instances.

Is generative model deep learning? ›

Generative Adversarial Networks, or GANs, are a deep-learning-based generative model. More generally, GANs are a model architecture for training a generative model, and it is most common to use deep learning models in this architecture.

Is generative AI supervised or unsupervised learning? ›

There are two main types of generative AI—unsupervised learning and supervised learning. Unsupervised learning involves training a model without any labels or instructions, while supervised learning requires labeled data sets with specific instructions for the model's output.

What algorithms are used in generative design? ›

By defining parameters and rules, the generative approach is able to provide optimized solution for both structural stability and aesthetics. Possible design algorithms include cellular automata, shape grammar, genetic algorithm, space syntax, and most recently, artificial neural network.

What is the difference between conversational and generative AI? ›

Generative AI is capable of generating new data by recognizing patterns in existing data. In the context of conversational AI, it involves utilizing machine learning algorithms to produce natural language responses to user queries or requests.

What is the opposite of generative AI? ›

New content might include images, text, or videos. The generative nature of Chatgpt is created through algorithms that pull from existing data. In contrast, analytical AI takes mass amounts of data and produces observations or analyses of the information collected.

What is the most powerful AI program? ›

List of Artificial Intelligence Tools
  • Scikit Learn.
  • TensorFlow.
  • PyTorch.
  • CNTK.
  • Caffe.
  • Apache MXNet.
  • Keras.
  • OpenNN.

What is the strongest AI ever? ›

Top 5 World's Most Advanced AI Systems | 2023
  • GPT-3 (OpenAI) The first in our list is GPT-3 short for Generative Pre-trained Transformer 3 is the third series of generative language models developed by OpenAI. ...
  • AlphaGo (Google DeepMind) ...
  • Watson (IBM) ...
  • Sophia (Hanson Robotics) ...
  • Tesla Autopilot (Tesla Inc)

What are the 4 key concepts of generative learning? ›

In an article in, Christopher Pappas explains that Generative Learning Theory comprises four key concepts: recall, integration, organization, and elaboration. Teachers and creators of teaching materials can involve one, two, or more of those concepts.

What is an example of a generative activity? ›

Examples include generating concept or mind maps based on a text, summarizing the events of a movie in the form of a timeline or producing an own video on the learning content.

What are the eight strategies to encourage generative learning? ›

In this article, we present eight learning strategies intended to promote generative learning: summarizing, mapping, drawing, imagining, self-testing, self-explaining, teaching, and enacting.

What is an example of a generative AI model? ›

ChatGPT, DALL-E 2, and Bing AI are just some of the popular examples of generative AI tools.

What is the advantage of generative approach? ›

In a generative model, each class is learned individually and only considers the data whose labels correspond to it. The model does not focus upon inter-model discrimination and avoids considering the data as whole. Thus the learning is simplified and the algorithms proceeds faster.

What are some of the common challenges generative AI is facing? ›

Generative AI models can sometimes generate hallucinations or unrealistic outputs because they are designed to learn patterns and generate outputs that resemble the training data they were trained on. This means that if the training data is noisy or contains mistakes, the generative model may learn to reproduce them.

Do real writers use Grammarly? ›

Grammarly is a top spelling, grammar and plagiarism checker. It'll help you find and fix errors fast, and it works everywhere. It's trusted by millions of writers for a reason.

Who actually uses Grammarly? ›

Professionals use Grammarly to provide expert help and instant feedback on the accuracy, impact, and credibility of their English writing in a variety of fields, such as law, healthcare, academia, marketing, engineering, and journalism.

Who writes algorithms for AI? ›

Algorithm engineers—also called algorithm developers—are responsible for the design and integration of algorithms. Well-designed algorithms offer real-time solutions when installed into a software or computer environment.

What is an example of generative system? ›

One of the better-known examples is Conway's Game of Life, a cellular automaton. Other examples include Boids and Wikipedia. More examples can be found in generative music, generative art, and, more recently, in video games such as Spore.

What is generative method example? ›

A generative model includes the distribution of the data itself, and tells you how likely a given example is. For example, models that predict the next word in a sequence are typically generative models (usually much simpler than GANs) because they can assign a probability to a sequence of words.

What is generative AI applications? ›

At a high level, generative AI refers to a category of AI models and tools designed to create new content, such as text, images, videos, music, or code. Generative AI uses a variety of techniques—including neural networks and deep learning algorithms—to identify patterns and generate new outcomes based on them.

What is an example of generative algorithm? ›

Some popular generative algorithms are: Naive Bayes Classifier. Generative Adversarial Networks. Gaussian Mixture Model.

What are generative questions examples? ›

25 Powerful and Generative Questions
  • What question, if answered, could make the most difference to the future of (your specific situation)
  • What's important to you about it and why do you care?
  • What draws you/us to this inquiry?
  • What's our intention here? ...
  • What opportunities can you see in this ?
Mar 3, 2011

What are real life examples of generative design? ›

There are several examples of generative design and additive manufacturing being used to enhance the performance of a part. For instance, automotive manufacturer General Motors redesigned a seat belt bracket using Autodesk's generative design solution and metal 3D printing.

What are the 4 key concept of generative learning? ›

In an article in, Christopher Pappas explains that Generative Learning Theory comprises four key concepts: recall, integration, organization, and elaboration. Teachers and creators of teaching materials can involve one, two, or more of those concepts.

How does generative AI work? ›

Generative AI models use neural networks to identify the patterns and structures within existing data to generate new and original content. One of the breakthroughs with generative AI models is the ability to leverage different learning approaches, including unsupervised or semi-supervised learning for training.

What are some applications of generative models? ›

Deep generative models have numerous applications: Data generation: images, texts, audio, molecules, graphs, material structures, text-to-speech, lyric-to-singing, text-to-image, trajectories in imitation learning (GAIL), etc. Measuring the plausibility of data: Anomaly detection.

How do I create a generative AI? ›

Several key steps must be performed to build a successful generative AI solution, including defining the problem, collecting and preprocessing data, selecting appropriate algorithms and models, training and fine-tuning the models, and deploying the solution in a real-world context.

What are the most popular generative AI models? ›

The leading generative AI tools include DeepMind's Alpha Code (GoogleLab), ChatGPT, GPT-3.5, DALL-E, MidJourney, Jasper, and Stable Diffusion.

What are generative techniques? ›

Common generative research methods include: ethnography, contextual interviews, focus groups, and data mining. Our customers often: 1. Ask people to record their everyday activities, behaviors, and thoughts.

What are common ways to be generative? ›

Generativity is expressed in many forms: parenting, mentoring, community service, ecological conservation, and political activism are just a few examples. The common thread is that generative acts allow us to leave a positive legacy that benefits society in a lasting way.

What languages are used in generative programming? ›

Many artists these days also use JavaScript and the JavaScript library, p5. js to create their generative art sketches. There is also OpenFrameworks (c++, relevant if you would like to create shaders.) Pretty much any programming language can be used to create generative art though including Python, R, etc.


1. Generative AI for Beginners
2. Understanding Generative AI, Its Impacts and Limitations
(Analytics Insight)
3. What are Generative AI models?
(IBM Technology)
4. Top AI Tools for Small Business You Wish You Knew Before (2023)
(Phil Pallen)
5. How Generative AI Could Replace Artists in Creative Industries | Tech News Briefing | WSJ
(Wall Street Journal)
6. Beginner's guide to Generative AI
(The Visual Appeal)


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