AI jobs for non-programmers
Plenty of AI-related roles do not require a technical background. Uncover career possibilities in AI with our list of non-technical roles.
By: Jacob Given, Edited by: Rebecca Munday, Reviewed by: Jeff Le
Published: August 1, 2025
Artificial intelligence is one of the biggest technological achievements in recent memory. Several technological breakthroughs in data science make AI tools like ChatGPT, Claude, and Gemini possible.
That said, you don't need to become an expert in data science to contribute to the AI field or leverage AI for your day-to-day work. Check out our guide to learn more about AI jobs for non-programmers.
Why you should build AI skills as a non-programmer
Employers in today's market often prefer candidates with AI-related skills. While AI is not without significant pitfalls, the technology can also lead to increased automation and productivity.
Though AI poses a significant threat of disruption to today's job market, it also opens up new professional niches. While many people believe that you need extensive training in computer science or programming to work in the field of artificial intelligence, the truth is that many AI-related roles do not require a technical background.
Top non-technical AI jobs
While some of the top jobs in AI require a background in one or more technical disciplines, many roles remain accessible to non-technical candidates who want to explore or improve their efficiency with AI. "At its core, a fundamental curiosity to utilize AI tools in daily work and life is critical," says Jeff Le, managing principal at 100 Mile Strategies.
The following list covers a few roles with minimal technical barriers to entry.
AI product manager
Product managers bring vision and purpose to a product development team. They enumerate product features that align with user requirements and provide their teams with an overarching strategy.
AI product managers guide teams in developing AI-powered products. These professionals stay current on emerging trends in AI technology and consumer markets.
Skills needed:
- Organization: AI product managers must understand how to coordinate teams to accomplish development goals.
- User research: AI product managers need to conduct user research in order to gather requirements.
- UI/UX design: An understanding of user interface (UI) and user experience (UX) design can help product managers choose the right features for their project.
How to start working with AI
- Read widely: Stay informed on the latest trends in AI. Pay attention to both successes and failures in the field.
- Use a wide variety of tools: Gain practical experience with AI tools to understand the potential impact of and use cases for different features.
- Maintain a critical stance toward AI: Ensure you understand the technology's limitations so you can deliver a satisfying experience to the end user.
AI project manager
Project managers define goals and coordinate teams to accomplish them. They eliminate obstacles for their teammates, maintain communication with stakeholders, and ensure the timely delivery of results.
AI project managers work with teams to develop AI-powered solutions for their clients.
Skills needed:
- Planning and estimation: Project managers must estimate the time to completion for various tasks and create a project plan to achieve their deliverables within that time frame.
- Project management software: Many companies use project management software like Asana, Monday, or Atlassian to coordinate teams.
- Communication skills: Project managers must effectively coordinate with team members and other stakeholders to ensure productivity and efficiency.
How to start working with AI
- Read widely: AI and its applications are rapidly changing, which affects the time it takes for project teams to produce deliverables. Staying up to date on AI developments can help project managers adjust timelines and project plans accordingly.
- Research a variety of AI tools: Project managers who work on AI products should remain familiar with their popular features and use cases.
- AI-powered project management software: Project managers can bring AI into their workflows by using AI-powered software in their day-to-day tasks.
- Choose AI-related projects: If possible, choose AI-related projects to gain experience and build a portfolio.
AI ethicists
Ethicists consider moral and legal principles and their practical implications. They also counsel organizations on regulatory and ethical compliance.
AI ethicists focus on the moral principles surrounding the development, deployment, and usage of AI systems.
Skills needed:
- Critical thinking: Ethicists need to apply critical thought to make judgements about difficult situations and dilemmas.
- Research: Ethicists must gather relevant facts from reliable sources. Many ethicists have graduate-level training in research.
- Communication: When delivering their findings to stakeholders, ethicists must communicate clearly and efficiently.
How to start working with AI
- Read widely: Get familiar with major ethical issues in AI. Take a course in AI ethics or conduct independent research.
- Publish: Consider publishing articles on ethical questions surrounding AI to demonstrate your knowledge.
- Apply to AI-oriented roles: Seek out ethics positions at AI-oriented tech companies.
AI content writer
AI content writers leverage artificial intelligence to produce written work. They adhere to editorial requirements, conduct research, and use composition best practices.
In addition to typical writing skills, content writers who leverage AI need to understand how to prompt and correct an AI model to mitigate errors.
Skills needed:
- Composition: AI content writers should understand the principles of written composition, including grammar and style.
- Editing: AI content writers need to be able to edit for content and tone to ensure the content is accurate and the tone of the piece doesn't "sound" like AI.
- Research: Content writers must understand how to find, interpret, and cite reliable sources and find and include different perspectives in their content
- Teamwork: When completing a writing assignment, content writers must communicate with their editors and follow internal style guidelines.
How to start working with AI
- Learn prompt engineering: Utilizing prompting techniques like retrieval-augmented generation to produce high-quality output.
- Learn to evaluate AI output: AI can produce confident errors (known as "hallucinations"). Learn how to spot them.
- Learn when not to use AI: Practice with a variety of models to learn their limitations. In some cases, correcting low-quality output can take more time than writing from scratch.
AI marketer
Marketers promote products and services through advertising, search engine optimization, and other means. They leverage demographic data to develop promotional strategies.
AI marketers use artificial intelligence to assist with interpreting research and planning marketing campaigns.
Skills needed:
- Demographic research: Marketers need to understand demographics in order to reach potential customers efficiently.
- Data analysis: Marketing research often involves a lot of numbers and statistics. Marketers need to understand how to sift through data and interpret it.
- Search engine optimization: Many people use search engines like Google on a daily basis. Marketers can use search engine optimization to promote a product or service.
How to start working with AI
- Experiment with AI in your workflow: AI can assist with a variety of tasks, but the ideal use case depends on your specific workflow. Experiment to determine the best use of AI for you.
- Get a second opinion on data: AI can offer insights into data sets that might otherwise escape notice. Use AI to evaluate your interpretations.
- Honestly evaluate AI output: While AI can assist you in many cases, it can also produce erroneous outputs. Maintain a critical eye.
AI trainer
AI trainers provide feedback to help train AI systems. By annotating, verifying, or correcting outputs, trainers provide feedback that helps the AI model become more accurate.
AI trainers do not necessarily need coding expertise, but they should be curious and well-rounded in their interests. Occasionally, AI development teams request trainers with subject-matter experts in a particular field.
Skills needed:
- Openness to instruction: AI trainers must follow protocols and training standards.
- Wide expertise: Models require training on a wide variety of subjects. AI trainers benefit from a broad understanding of various fields and various AI models.
- Versatility: Trainers provide feedback on a variety of output modes, including text, image, audio, and video.
How to start working with AI
- Learn data analytics: Complete a course or certificate, or perform independent research about best practices for data annotation, cleaning, and analysis.
- Maintain attention to detail: AI can produce confident-sounding mistakes. Maintain a critical eye as you become familiar with AI's limitations.
- Apply for AI trainer positions: Many AI-training roles are part-time or contract positions, allowing you to work a flexible schedule.
AI legal counsel
As a new field, artificial intelligence presents as many legal challenges as it does technical ones. Tech companies and AI teams in highly regulated fields require legal counsel to ensure regulatory compliance.
Skills needed:
- Education: To qualify for legal counsel roles, you typically need to acquire a law degree and pass the bar exam.
- Specialization: Areas like privacy and intellectual property may prove helpful specializations for AI-related legal counsel.
- Adaptability: Legal counsel must stay current as AI advances and the legal landscape shifts.
How to start working with AI
- Familiarize yourself with AI: Understand common use-cases, risks, and potential abuses of AI.
- Research AI lawsuits: As a legal counsel, your clients will expect you to understand the current legal landscape surrounding AI.
- Search for a legal counsel role: Check for AI legal counsel openings in government, private businesses, and law firms.
AI researcher
The government, research labs, and think tanks need talented researchers in disciplines like economics, psychology, and social science to understand and evaluate AI's impact.
If you have training in a research field, an interest in artificial intelligence, and familiarity with multiple types of LLMs, you may qualify for an AI researcher role even if you don't possess technical skills.
Skills needed:
- Information literacy: AI researchers need to understand how to acquire, evaluate, and synthesize information from reputable sources.
- Research: Depending on their particular specialties, AI researchers may conduct qualitative research, such as case studies, focus groups, and interviews.
- Writing: Researchers must present their findings to stakeholders in clear, concise language.
How to start working with AI
- Read widely: Familiarize yourself with current trends in AI research.
- Publish: Seek publication in academic or popular venues. Keep a portfolio of your publications or maintain a website.
- Search for a research role: Apply for AI researcher roles with governments, universities, or private research labs.
AI prompt engineer
Without adequate direction, models can return vague, inaccurate, or imprecise responses. Prompt engineers create, test, and refine prompts that return high-quality outputs from an AI model.
Despite the technical-sounding title, prompt engineers don't typically need to know code. They employ various techniques using plain language to improve a model's performance at any given task.
Skills needed:
- Logic: Prompt engineering often requires careful, step-by-step logic.
- Writing: You don't need to be a wordsmith, but you must be able to write clearly and precisely. "Strong, specific, and creative prompts can unleash faster and deeper insights that can inform deliverables needing extensive depth and analysis," Le said.
- Curiosity: Successful prompt engineers often engage in iterative testing, which requires curiosity and a willingness to experiment.
How to start working with AI
- Learn prompting methods: Become familiar with a variety of prompting methods, such as retrieval-augmented generation, chain of thought, and chain prompting.
- Experiment with a variety of models: Prompt engineers should understand the strengths and limitations of different models and which prompting methods work best for each.
- Build a prompt library: When you develop an effective prompt, document it. Build a collection of prompts for reference.
AI UX/UI designer
User experience (UX) and user interface (UI) designers create intuitive layouts for software. They use design software to create wireframe references for development teams. UX/UI designers can leverage AI tools in various ways, including automating repetitive tasks, simulating user feedback, and troubleshooting software.
Skills needed:
- Understanding of design principles: Taking a course or earning a certification in UX/UI design can help you understand best practices.
- Software expertise: UX/UI designers use specialized software like Figma and Adobe XD to create prototypes.
- Problem solving: UX/UI designers must come up with creative solutions to meet user requirements and address feedback from testing.
How to start working with AI
- Software troubleshooting: AI can assist you if you know the basics of a UX/UI design program but need to troubleshoot a specific problem.
- Brainstorming: Sometimes, you need help getting the creative juices flowing. Use AI as a brainstorming partner to get your project off the ground.
- Critique: While it should never replace robust testing, AI can help you spot problems during the design process.
How to get started in AI as a non-technical professional
Even without a technical background, professionals in a variety of roles can use AI. Businesses leverage AI in many ways, requiring even those in non-technical roles to use the tech. Individuals who want to leverage AI should understand the strengths and limitations of the technology and experiment to find appropriate use cases that enhance efficiency.
Additionally, non-technical workers who want to take on AI-related roles can contribute to the field without learning to code.
Here are a few steps non-technical professionals can take to pivot into the AI field:
- Identify ways AI tools can help you in your work.
- Experiment with AI tools in your day-to-day work and learn the strengths of each.
- Take a course or earn a certificate in AI.
- Stay up to date on AI news.
- Search for roles in AI that match your non-technical expertise.
- Experiment with prompts to capture specific outcomes and results.