In recent years, artificial intelligence has exploded in popularity, transforming industries and paving the way for exciting new job opportunities. In 2023, the global AI market was worth $197 billion, and this figure is expected to grow by 36.6% each year from 2024 to 2030. Even more striking: AI job listings are growing 3.5 times faster than the average rate for all job posts. From data analysis and business intelligence to manufacturing and healthcare, AI is reshaping the workforce. Keep reading to explore some of the fastest-growing AI positions and learn how you can take the first step toward a rewarding career in AI. 

What to Know About the AI Job Market 

Because the applications for AI are vast, companies across numerous industries are hiring AI professionals. The technology sector leads the way, with companies leveraging AI for advancements in software development, cybersecurity, cloud computing, data analysis, and many other domains. In healthcare, AI is used to improve diagnostics, imagining analysis, and drug discovery. In finance, it enhances fraud detection and portfolio management. Retail businesses use AI for everything from demand forecasting to personalized shopping recommendations. AI has also transformed the logistics and manufacturing sectors, with the technology being used to automate routine tasks, optimize inventory processes, detect manufacturing defects, and more. If you’re interested in AI careers, there are countless avenues to explore.

Essentials Skills for an AI Career  

Excelling in an AI role requires a mix of technical abilities and soft skills, including: 

• Computer programming. Whether the role involves building algorithms, maintaining AI models, or working with natural language processing (NLP), strong coding skills are essential in an AI position. 
• Machine learning. A firm grasp of machine learning concepts allows AI professionals to design systems that predict outcomes and solve problems with remarkable precision. 
• Data analysis. Since vast data sets power AI programs, you’ll need experience in statistical analysis, data visualization, and data processing.
• Deep learning. Deep learning uses artificial neural networks to process data, facilitating recent AI advances such as image and speech recognition. Knowledge of deep learning concepts like convolutional neural networks and long short-term memory can unlock opportunities for more advanced roles in AI. 
• Natural language processing. NLP allows computers to understand and generate human language. By learning the technology that makes NLP possible, AI professionals can expand career opportunities and qualify for more advanced positions.  
• Mathematics. An in-depth knowledge of mathematical and statistical concepts empowers AI professionals to analyze data and draw accurate conclusions. 
• Communication. AI professionals rely on strong communication skills to collaborate with colleagues, document processes, and explain complex concepts to nontechnical audiences.
• Critical thinking. Logic and reason guide AI professionals as they evaluate data, assess algorithm performance, and make sound decisions about AI implementation. 
• Teamwork. While working to solve problems and overcome challenges, AI professionals collaborate with software engineers, data scientists, business leaders, domain experts, and a range of other stakeholders. 

Top Jobs in AI to Consider

AI is a fast-growing field brimming with opportunities to explore, innovate, and shape the very future of technology. Many new jobs in AI have only come into existence in the last few years, demonstrating just how quickly AI is reshaping industries. These jobs span a diverse range of sectors, each playing a crucial role in advancing and applying AI technologies. Some key positions to consider include: 

AI Engineer  

AI engineers are the experts who design, develop, and implement artificial intelligence systems. A typical day in the life of an AI engineer often involves collecting, cleaning, and processing data, creating algorithms, and testing AI solutions for accuracy and performance. The role requires a solid foundation in programming languages such as Python, C++, and Java, as well as expertise in machine learning (ML) frameworks like TensorFlow and PyTorch. Salaries for AI engineers typically range from $161,000 to $267,000, and the median annual salary is $205,000. The demand for these professionals continues to grow rapidly as organizations across industries seek to incorporate AI technologies into their operations. 

Machine Learning Engineer 

While engineers work on entire AI frameworks, machine learning engineers focus on building, testing, refining, and deploying ML systems. These systems evaluate past data to identify patterns and predict future outcomes, enabling computers to operate autonomously. ML engineers develop data sets, train ML models using the data, optimize performance metrics, and collaborate with stakeholders. These professionals often work closely with robotics engineers to integrate ML into autonomous machines such as warehouse robots. The average annual salary for machine learning engineers is $163,390. As companies continue to implement machine learning and automation into business processes, the demand for ML engineers grows, making the job outlook for this field especially favorable. 

Data Scientist 

Studies show that the world now produces a staggering 403 million terabytes of data daily. For companies, this data is an invaluable source of information. Data scientists translate vast, complex data sets into actionable insights that help companies make informed decisions. Their days are spent collecting raw data, fixing problems such as duplicate or missing inputs, identifying trends, running tests, and analyzing results. The data science field increasingly relies on AI tools to automate tasks, ensure consistency and accuracy, and optimize processes. Data scientists’ work supports various AI initiatives, including generative AI, NLP, and data augmentation tools. The median annual salary for data scientists is $108,020, and the U.S. Bureau of Labor Statistics (BLS) projects that the demand for data scientists will grow by 36% from 2023 to 2033.    

AI Product Manager 

Companies that build chatbots, predictive analytics tools, smart assistants, and other AI products often hire AI product managers to oversee the product lifecycle. Like in other product management roles, a significant part of the job involves collaborating with stakeholders to align product development and deployment with business goals and users’ expectations. AI product managers are also tasked with describing complex AI functionalities and features to nontechnical audiences, making strong communication skills essential. The average annual salary for AI product managers is $159,405, and the job outlook is positive.

AI Ethics Specialists 

The ethical considerations surrounding artificial intelligence are extensive and complex. Concerns about AI bias, discrimination, privacy, and accuracy have been significant topics of discussion since the technology’s inception. AI ethics specialists develop policies and guidelines for AI projects, ensuring that systems comply with data privacy rules, consumer protection laws, and other standards. This involves auditing AI systems to identify potential risks, collaborating with stakeholders to address ethical concerns, conducting AI research, and advocating for ethical AI practices. The average annual salary for AI ethics specialists is $107,806 a year. As more companies implement AI, the role of AI ethics specialists will become increasingly important. 

Data Analyst 

Like data scientists, data analysts collect, evaluate, and visualize data. However, data analysts focus more on gathering insights from historical data rather than predicting future outcomes. Data analysts leverage programming languages like SQL, MATLAB, and Python, as well as data visualization programs such as Power BI and Tableau, to gather essential insights. The median annual salary for data analysts is $111,037 a year. With data becoming an increasingly valuable asset, the demand for data analysts is expected to rise significantly. The World Economic Forum’s 2025 Future of Jobs Report ranks “big data specialists” as the fastest-growing job sector. 

Computer Vision Engineer 

Computer vision engineers build the tools and systems that allow computers to interpret visual information. Their work has been integral to numerous groundbreaking technologies, including self-driving cars, augmented reality, facial recognition, and AI-enhanced video editing programs. Computer vision engineers often collaborate with research scientists and robotics engineers to develop robots that can “see” and understand the world around them. According to the BLS, the salary for computer and information research scientists, including computer vision engineers, was $145,080 as of May 2023. The employment of computer and information research scientists is projected to grow by 26% from 2023 to 2033. 

Business Intelligence Developer 

Big data is essential for modern companies, empowering them to understand the past, optimize the present, and predict the future. Business intelligence developers create and maintain tools that enable businesses to gather insights from data. They design custom dashboards, reporting systems, and data models using platforms like Power BI, Tableau, SQL, and Talend. The role is highly collaborative, with business intelligence developers working closely with stakeholders to craft tailored solutions that meet companies’ specific needs. Business intelligence developers need a mix of technical proficiency and business savvy. According to the BLS, business intelligence developers earned a median annual salary of $132,270 in May 2023. The employment of business intelligence developers is projected to grow by 17% from 2023 to 2033. 

Deep Learning Engineer 

Deep learning is a subtype of machine learning that uses artificial neural networks to simulate human brain processes. It is a crucial element in many advanced technologies, including voice assistants like Alexa, image recognition systems, and generative AI tools. Deep learning engineers design neural networks, train AI models, and help companies integrate deep learning into existing technological frameworks. The average salary for deep learning engineers is $156,998 a year, and annual salaries typically range from $105,083 to $234,560. The machine learning and AI field is expected to grow by 40% and generate an additional 1 million jobs from 2023 to 2027. 

AI Architect 

In the same way that a traditional architect creates blueprints for a physical structure, an AI architect designs the foundational framework for an artificial intelligence system. This involves aligning AI objectives with broader organizational goals, selecting AI tools and programs, overseeing the development team, ensuring regulatory compliance, and integrating AI components with existing IT infrastructure. The average salary for artificial intelligence architects is $128,756 a year. With AI-facilitated technologies booming, the job outlook for AI architects is expected to be highly favorable.  

How to Build a Career in AI 

If you’re interested in joining the exciting field of AI, you’re not alone. Data shows that over 2.9 million people searched the web for “open AI jobs” in January 2024 alone. The number of people looking for AI-related positions has skyrocketed in recent years. While AI opportunities are growing rapidly, there is also fierce competition in the field. To stand out from the competition, you’ll need a mix of education, experience, technical abilities, and soft skills.  

Earn a Relevant Degree 

Since AI is a specialized field that calls for extensive technical proficiency, most AI roles require at least a bachelor’s degree. Earning a degree in computer science, data analytics, information technology, or a related domain is a great way to build foundational skills and qualify for entry-level AI positions. To qualify for specialized or senior-level roles, you’ll likely need a master’s degree. The type of master’s degree you pursue depends on your career aspirations. For example, if you hope to land a role as an AI architect specializing in cybersecurity solutions, you may want to earn a master’s degree in cybersecurity and information assurance. If you want to become a deep learning engineer, you may want to pursue a master’s in computer science. 

Build AI Skills 

Successful AI professionals aren’t only tech-savvy. They’re also highly skilled at AI career essentials like critical thinking, problem-solving, communication, collaboration, and teamwork. One way to enhance both hard and soft skills is to attend an AI or coding boot camp. These “camps” are short-term intensive programs that provide students with hands-on learning experiences. Another option for skill enhancement is to earn professional certificates in relevant areas. Some popular certificates for AI professionals include: 

• IBM Applied AI Professional Certificate
• Microsoft Certified: Azure Data Fundamentals
• Google Cloud Professional ML Engineer
• CompTIA Data+
• CompTIA Security+
• AWS Certified Cloud Practitioner
• AWS Certified Solutions Architect

Build a Strong Portfolio

One of the most important pieces of AI career advice is to build a portfolio to showcase your skills. Whether you want to be a robotics engineer, AI architect, data scientist, or another AI professional, a portfolio allows potential employers to see examples of your work and get a sense of who you are. A portfolio also helps you stand out in online employment platforms like Indeed and ZipRecruiter. The exact elements included in your portfolio will depend on your specific career aspirations, but most portfolios include the following sections:

• Introduction. The introduction or “about me” section should give a general overview of your background, skill set, experience, and career objectives. 
• Projects. You’ll want to include examples of your best AI-related work. For those just starting their career, this may include AI or data-related projects you completed in college. 
• Education. In this section, you’ll list the relevant degrees and certifications that you’ve earned. 
• Practical experience. A strong portfolio emphasizes how your past experience has prepared you for a career in AI.  
• Contact information. Make sure that prospective clients and employers know how to get in touch with you. 

Prepare for AI Job Interviews

Any job interview can be stressful, but interviewing for a high-level AI position can be especially intimidating. Give yourself the best chances of success by preparing for the interview beforehand. Make sure your résumé and portfolio are updated and free of errors. Practice describing your education, experience, and most impressive projects. It’s also important to research the company you’re interviewing for. This will allow you to explain exactly how your experience and expertise can benefit the company. 

Start Your AI Career at WGU 

Across industries, companies are investing in AI technologies to streamline processes, improve efficiency, and gain an edge in the increasingly competitive market. If you’re ready to take the first step toward a career in AI, WGU can help. WGU offers industry-aligned, accredited degree programs in computer science, data analytics, software engineering, cloud computing, and other in-demand IT fields. Our online, competency-based learning model allows you to complete your degree on your terms. Whether you’re a working professional, parent, or fresh out of high school, WGU empowers you to earn a degree without sacrificing personal or professional obligations. Begin your educational journey by applying today.