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Learn about the generative AI model DALL-E, how it works, and what you can use it for.
![[Featured image] A professional showing their coworker concept art generated on DALL-E.](https://d3njjcbhbojbot.cloudfront.net/api/utilities/v1/imageproxy/https://images.ctfassets.net/wp1lcwdav1p1/B7NtqznsJUOHvIqsZsLK2/1e7f28a93d0569884f4928d3b086617b/gettyimages-1023305676.webp?w=1500&h=680&q=60&fit=fill&f=faces&fm=jpg&fl=progressive&auto=format%2Ccompress&dpr=1&w=1000)
DALL-E is an AI model capable of generating images based on the descriptions it receives.
First released in 2021, the latest iteration of DALL-E is DALL-E 3.
You can use DALL-E for a wide variety of use cases, such as developing marketing visuals, brainstorming ideas, creating visual educational aids, and making custom printed art.
DALL-E is primarily used for generating images based on prompts that allow it to make connections between text and images similar to human thought processes. Read on to discover the uses of DALL-E, who uses it, the pros and cons of this technology, and how you can start using it.
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DALL-E is an artificial intelligence model that can generate images when you feed it textual descriptions. To accomplish this, it translates billions of text bits from the internet into an abstraction of stored information, which it then uses as a reference tool for describing things and generating those images. First introduced in 2021, DALL-E has seen continuous updates as it has become increasingly popular. DALL-E learns a “latent space representation of images,” allowing it to generate high-quality and varied images [1].
Inspired by the human brain, DALL-E attempts to mimic the creative process that human artists experience while creating their own work. DALL-E’s use of connections between subjects allows it to make associations, which it can then use to generate artwork, and this process reflects the one your brain employs to produce your thought patterns. Trained on an extensive data set of image-to-text pairs, DALL-E can run your text input through a text encoder and generate an image based on the information received from its image decoder.
DALL-E has a wide variety of uses, including the following:
Brainstorming ideas
Custom printed art
Creating 3D art
Creating 3D renders
Marketing visuals
Designing logos and brand materials
Creating educational visual aids
You can use DALL-E to generate concept art and design elements based on the text you input, speeding up the design process. You can also use DALL-E to spruce up your business's or restaurant's interior design by generating art pieces, printing them out, and decorating with them. As a 3D artist, you might use DALL-E to mock up 3D renders before proceeding with 3D modeling, saving you brainstorming time.
Read more: How to Use ChatGPT to Generate Images: A Step-by-Step Guide
You can use DALL-E to generate relevant images for ad campaigns. You might consider providing the AI model with your target audiences and a detailed product description to further curate DALL-E's content. You can also use DALL-E to place your advertising product in a traditionally challenging-to-achieve background, such as a mountain or coral reef. DALL-E generates visibly interesting brand imagery with a uniform style.
As an instructor, you can use DALL-E to generate images representing difficult-to-understand subjects for your learners. For learners who absorb material visually, DALL-E can create visual aids, like representations of different organizational structures, for educational use to complement your teaching style. The material generated can allow teachers, instructors, trainers, and professors to teach more successfully, empowering learners to commit the material to memory more effectively.
Various careers and individuals utilize DALL-E, including creative minds looking to have fun, sellers creating prints of the AI artwork, and businesses for productivity benefits. Given that AI systems and their uses are still growing, more careers related to DALL-E will be available to you in the future. As a machine learning engineer, an AI engineer, or a computer vision engineer, you may also use generative AI like DALL-E. If you’re interested in one of these positions, the US Bureau of Labor Statistics states that you can expect to see this sector of the economy grow 22 percent from 2025 to 2035, which is much faster than average [2]. You can read below in more detail what machine learning, artificial intelligence, and computer vision engineers do.
Median annual total salary in the US (Glassdoor): $166,000 [3]
As a machine learning (ML) engineer, you create and solve issues related to technology-based applications, programs, and devices. An ML engineer combines programming and data science principles to form a multidisciplinary role with specialization in conventional software development. Since machine learning is one of the various practices used to create artificial intelligence and AI tools, you, as an ML engineer, would design, test, and assemble AI systems grounded in machine learning principles.
Median annual total salary in the US (Glassdoor): $156,000 [4]
AI engineering involves the development of tools, systems, and processes to facilitate the use of artificial intelligence in the real world. As an AI engineer, you program with Java, C++, or Python, work with data, apply machine learning algorithms and libraries, and research and design deep learning applications. AI engineers use the programs they write and the data they collect to create AI tools like DALL-E.
Median annual total salary in the US (Glassdoor): $169,000 [5]
If you become a computer vision engineer, you will instruct computers to process, understand, and recognize images. This technology is already being utilized in many applications, such as facial recognition, image enhancement, content moderation, and image search. You will need a strong working knowledge of computer programming languages like Python and Java in this position. Your everyday duties might include developing and testing algorithms, presenting novel solutions to real-world problems, or managing computer vision projects of various sizes.
All salary information represents the median total pay from Glassdoor as of October 2026. These figures include base salary and additional pay, which may represent profit-sharing, commissions, bonuses, or other compensation.
Due to the open-source nature of generative AI like DALL-E, you can find both pros and cons with its usage.
High quality: The content you generate with DALL-E is of very good quality and correctly corresponds to textual inputs, providing the creative industry with a crucial new tool.
Versatility: With DALL-E, you can generate incredibly unique and specific visuals, from realistic to fantastical, making it very versatile.
Real-time applications: With the evolution of generative AI technology and the ever-changing AI itself, real-time applications of AI like DALL-E are likely to become more common, maybe when you are editing video or creating content.
Trouble generating text: Even the newest DALL-E model, DALL-E 3, struggles to properly generate text within its images. If you wish to avoid this issue, describe your image in greater detail, leaving out any mention of text.
Job displacement: The use of DALL-E can contribute to the displacement of creativity-based jobs, as you may have the AI model perform a task that would previously require hiring an artist or graphic designer.
Ethical concerns: Unfortunately, generative AI tools like DALL-E come with ethical concerns, including deepfakes, bias, and the automation of jobs, which can negatively affect people’s ability to earn money.
You can begin using DALL-E to see how it responds to your text inputs. Visit the OpenAI website and either log in or make an account with OpenAI, then begin describing the image you would like to create and click “generate.” DALL-E will then create four different images based on your text input.
You can use prompt engineering to design text input prompts for DALL-E to attain your desired product. You can think about details like clarity, specificity, and context when creating practical and effective prompts. This will provide the AI with enough information to generate a relevant response. Consider using specific methods, like the rhetorical approach, which has you describe your primary claim and then your rhetorical situation, such as the audience, context, and style/delivery.
DALL-E offers a free plan that provides a certain number of features per month, a normal processing speed, and one image per request per day. If you would like to create more images with DALL-E, you can sign up for the Starter plan, which costs $15 per month and allows for 1,000 credits per month, fast processing, and three images and one video per request, as well as a commercial license [6]. You can also opt for a Plus plan for $30 per month and get 2,000 credits, four images, and two videos per request, or choose the Pro plan, which is $50 per month for 4,000 credits monthly, ultra-fast processing, six images, and three videos per request [6].
To stay current on trends and job opportunities in your field, join Career Chat, our LinkedIn newsletter. You can also explore these other free resources to learn more about AI and its uses:
Watch on YouTube: 3 Cool Applications of GenAI | Generative AI 101
Read our Career Chat issue: 3 GenAI Prompting Methods Worth Trying
Learn the terminology: Artificial Intelligence Glossary: Learn AI Vocabulary
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University of Michigan. “GenAI In-Depth: The Science and Capabilities of GenAI, https://genai.umich.edu/in-depth/science-and-capabilities.” Accessed October 19, 2026.
US Bureau of Labor Statistics. “Computer and Information Research Scientists, https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm#tab-1.” Accessed October 19, 2026.
Glassdoor. “How Much Does a Machine Learning Engineer Make?, https://www.glassdoor.com/Salaries/machine-learning-engineer-salary-SRCH_KO0,25.htm.” Accessed October 19, 2026.
Glassdoor. “How Much Does an Artificial Intelligence Engineer Make?, https://www.glassdoor.com/Salaries/artificial-intelligence-engineer-salary-SRCH_KO0,32.htm.” Accessed October 19, 2026.
Glassdoor. “How Much Does a Computer Vision Engineer Make?, https://www.glassdoor.com/Salaries/computer-vision-engineer-salary-SRCH_KO0,24.htm.” Accessed October 19, 2026.
DALL-E AI. “Choose Plan, https://www.dall-efree.com/pricing/.” Accessed October 19, 2026.
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