The increasing use of artificial intelligence (AI) in the workplace is reshaping employers’ expectations and creating new demand in the job market for professionals who know how to use AI tools. For those curious about what an AI career path might look like, learning about the training and job options is a key step.
Data shows a sevenfold increase in demand for workers with AI fluency—proficiency in using and managing AI tools—over a span of two years, according to a McKinsey & Co. report about skills in the age of AI. The demand for AI skills is outpacing that of all other competencies mentioned in U.S. job postings, according to the report.
Jobs in computers and technology are among the most impacted by AI, according to the U.S. Bureau of Labor Statistics (BLS). Examples include:
- Software development: In this field, AI can help with development, testing, and coding software, as well as in improving data quality, developing AI-based business solutions, and maintaining AI systems.
- Data infrastructure: Since AI relies heavily on data, database administrators and architects are needed to set up and maintain the complex data infrastructures that power AI systems.
Jobs in these two fields are expected to see significant growth in the coming years, according to BLS projections. For example, employment of software developers is projected to grow 15% from 2024 to 2034, which is much faster growth than the average projected for all occupations. Employment of database administrators and architects is expected to grow 4% during the same period.
Why Pursue an AI Career Path?
Beyond the job growth projections of key AI-influenced roles, what are some other factors that can help individuals decide if an AI career path is worth pursuing? Benefits include the following:
Innovation-Driven Work Opportunities
There are many types of AI tools, which means there are many types of AI-connected job opportunities. Individuals who work with generative AI tools are familiar with ChatGPT and Claude, but these represent only a part of the AI tool spectrum.
For example, Google DeepMind’s AlphaFold has been used to accelerate biological discoveries by mapping millions of 3D protein structures, revealing how molecules interact within living systems. On the consumer side, companies like Walmart and Starbucks are using AI to streamline certain operations, from optimizing their supply chains to automating their inventory counting.
Growing, Evolving Job Market
Another key reason someone might want to pursue an AI career path is that the number of uses for AI tools is expanding at a remarkable pace. A Microsoft report on global AI adoption found that generative AI tools were used by 16.3% of people worldwide (about 1 in 6) in the latter half of 2025, up from 15.1% earlier in the year, illustrating the rapid adoption of a still-emerging technology.
High Earning Potential
AI is helping to drive measurable financial gains for organizations while increasing the wages of skilled professionals. PwC’s 2025 global AI jobs barometer shows that AI skills make employees significantly more valuable:
- Workers with AI skills had a 56% wage premium over those without them in the same role, up from 25% the previous year.
- Companies leveraging AI are expected to see three times higher revenue growth per worker in the coming years, even in industries like mining and agriculture that are not typically associated with AI.
5 Artificial Intelligence Career Paths
AI technologies and tools are being used in inventive ways across virtually every industry, creating new roles within existing fields. Potential AI career paths include roles such as the following:
1. Health Informatics Specialist
Health informatics specialists, sometimes called clinical informatics specialists, use data-driven technologies to tackle challenges in healthcare.
What Do Health Informatics Specialists Do?
Professionals who use AI in health informatics empower physicians and other healthcare providers by enabling them to access patients’ information within seconds—rather than having to flip through stacks of paper charts—allowing them to diagnose and treat patients more efficiently.
Health informatics specialists might perform a variety of tasks throughout the day, but their core responsibilities include the following:
- Setting up and maintaining electronic health records (EHRs)
- Training staff to use health information systems
- Applying data analysis methods to find insights that can be used to help improve patient care
Health Informatics Specialist Employment Outlook and Salary
According to BLS projections, health information technologists and medical registrars, including health informatics specialists, are expected to see 15% job growth from 2024 to 2034, much faster growth than the national average projected for all occupations. Health information technologists had a median annual salary of $67,310 in 2024.
How to Become a Health Informatics Specialist
Health informatics specialists require a blend of technical expertise and healthcare knowledge. However, individuals in these roles come from a range of professional backgrounds, including nursing, medicine, pharmacology, public health, and computer science.
Most employers look for candidates who hold at least a bachelor’s degree in a related field such as information technology, data analysis, or computer science. From there, individuals can enroll in a graduate or certificate program with foundational courses in health informatics and AI, healthcare law, privacy and ethics, and applications of AI in healthcare.
To further boost their credentials, individuals can pursue a professional certification from an organization such as the American Health Information Management Association (AHIMA) or the American Medical Informatics Association (AMIA).
2. Business Intelligence Analyst/Business Analyst
When a sales manager is staring at a spreadsheet trying to figure out why revenue dropped last quarter, a business intelligence analyst can help them more easily identify the underlying causes. Business intelligence analysts, also known as business analysts, transform raw data into clear, actionable insights that help businesses understand what’s working and what needs to change.
What Do Business Intelligence Analysts/Business Analysts Do?
Decision-makers rely on business analysts’ skills to analyze large volumes of data and uncover insights that guide business strategy. Their work allows business leaders to quickly spot trends via dashboards, visualizations, and reports and make confident, data-driven decisions.
Business analysts’ specific responsibilities vary by employer, but their responsibilities often include the following:
- Gathering data from stakeholders
- Identifying trends and patterns in company data
- Building reports and interactive dashboards
- Recommending strategic changes based on their findings
Business Intelligence Analyst/Business Analyst Employment Outlook and Salary
All management analysts, including business analysts, are expected to see 9% job growth from 2024 to 2034, according to the BLS. The BLS reports management analysts had a median annual salary of $101,190 in 2024.
How to Become a Business Intelligence Analyst/Business Analyst
Business intelligence analysts understand both data and business strategy. They typically hold a bachelor’s degree in a field such as computer science, data science, statistics, business administration, or economics. For those looking to gain hands-on experience early on, completing an internship can be a great way to build essential skills.
Individuals looking to advance can pursue a master’s degree with coursework covering topics such as AI applications in business, time series analysis, optimization for business decisions, marketing analytics, and business analytics.
Prospective business analysts can also pursue a professional certification such as Microsoft’s certified solutions expert in business intelligence, the certified business intelligence professional (CBIP) certification, or another business intelligence certification.
3. AI Architect
When a hospital’s scheduling systems, diagnostic tools, and patient records seamlessly share intelligence within its computer network, there is a high likelihood that an AI architect helped create the systems behind it. These professionals design the frameworks that connect an organization’s AI tools, ensuring that all its systems work together efficiently and align with the organization’s broader goals.
What Do AI Architects Do?
AI architects often have responsibilities that are similar to those of AI analysts. Their work requires them to have deep technical knowledge paired with strong communication and leadership skills. Organizations need AI architects to integrate their systems and maximize the value of their AI investments in ways that are strategic, scalable, and impactful.
AI architects perform tasks such as the following:
- Designing frameworks that connect an organization’s AI tools
- Selecting AI frameworks and technologies for business needs
- Coordinating with engineering teams to implement AI solutions
- Staying current with emerging AI technologies and best practices
AI Architect Employment Outlook and Salary
The AI architect role is relatively new, so long-term growth projections are limited. However, an AI jobs report from Autodesk found that demand for AI solutions architects has increased 109.3% year over year since 2023. According to Robert Half’s 2026 salary guide, AI architects with moderate experience have a median annual salary of around $175,000.
How to Become an AI Architect
Key competencies needed by AI architects include strategic planning, system design, machine learning infrastructure, generative AI integration, systems governance, compliance, and AI tool selection skills. On the technical side, proficiency in machine learning algorithms and frameworks, data science, programming languages like Python and Java, cloud computing, and big data technologies is essential.
There isn’t a single path to take to become an AI architect. However, a strong educational foundation in mathematics, statistics, algorithms, and data systems can help individuals build their relevant skills. From there, they can pursue a graduate degree or certificate program with coursework covering topics such as fundamentals of artificial intelligence, AI ethics and society, and AI applications in business.
4. Computer and Information Research Scientist
A computer and information research scientist might spend months developing a new technique that enables an AI system to detect early signs of lung disease in scans that were previously deemed normal. Breakthroughs like these don’t happen by accident. They require rigorous testing and careful validation, which are central to this role.
What Do Computer and Information Research Scientists Do?
Computer and information research scientists explore fundamental computing problems and develop and test theories. They often collaborate with engineers and scientists from other disciplines.
Though their responsibilities can vary, these professionals might be responsible for the following tasks:
- Developing and testing new computing theories or algorithms
- Collaborating with cross-disciplinary teams on research initiatives
- Applying machine learning and data science techniques to solve complex problems
- Validating their results through rigorous experimentation
- Publishing their findings
Computer and Information Research Scientist Employment Outlook and Salary
The demand for computer and information research scientists is strong. The BLS projects 20% employment growth for computer and information research scientists from 2024 to 2034, making this one of the fastest-growing technology or AI career path occupations. As of 2024, the median annual salary for computer and information research scientists is $140,910, placing the role among the higher-paying roles in technology.
How to Become a Computer and Information Research Scientist
Computer and information research scientists typically are required to hold at least a master’s degree in computer science or a related field such as computer engineering, though, in some cases, a bachelor’s degree may be sufficient. Some employers, particularly those in academia or advanced research settings, prefer candidates with a PhD.
A strong foundation in computer modeling, experimental design, databases, and programming is important for success in this field. For those just starting out, entry-level roles can provide individuals with valuable hands-on experience and help them build proficiency in algorithms, information systems, and data structures, all of which are essential for advancing into more senior research positions.
5. Data Scientist
Data scientists turn messy, unstructured information into meaningful insights that drive decision-making. They start by gathering data from a variety of sources—for example, surveys, databases, and web-scraping tools—and then clean that raw data so software programs can properly analyze it.
What Do Data Scientists Do?
Data scientists develop algorithms and models that power machine learning, using these tools to classify data, uncover patterns in the data, and make predictions based on what they learn. Ensuring the accuracy of the models is an ongoing part of the process, especially as new data becomes available. Data scientists use visualization software to present their results as charts, maps, and other graphics that make complex data easier to understand.
Typical data scientist responsibilities include:
- Gathering and cleaning raw data from multiple sources
- Building and testing algorithms and machine learning models
- Classifying data and generating predictions
- Creating visualizations that communicate their findings to stakeholders
Data Scientist Employment Outlook and Salary
The data scientist role is a fast-growing occupation, with projected employment growth of 34% from 2024 to 2034, according to BLS data. This far outpaces the average job growth projected for all occupations. The BLS reports that data scientists had a median annual salary of $112,590 in 2024. Robert Half’s 2026 workplace trends report further highlights the demand for these professionals, citing a 4.1% year-over-year increase in the national average data scientist salary.
How to Become a Data Scientist
Data scientists need to have a strong foundation in statistics, machine learning, and programming. Most data scientists hold at least a bachelor’s degree in data science, computer science, statistics, mathematics, or a related field, though some employers prefer candidates with a graduate degree.
Core skills for aspiring data scientists to develop include programming, machine learning, data wrangling, visualization, and communication skills. Gaining practical experience through internships, personal projects, or data competitions can help individuals demonstrate these skills in action. As with most tech-driven roles, staying current with new tools, frameworks, and industry developments is important for data scientists’ long-term career growth.
AI Career Path Resources
As AI use continues to evolve and expand across industries, staying informed is essential. Here are a few resources that can help individuals who are interested in pursuing an AI career path learn more:
- Centers of Excellence, “AI Guide for Government”: A practical guide to help government leaders learn about AI concepts, identify use cases, and build responsible AI capabilities within federal agencies
- EWeek, “Exploring Artificial Intelligence Career Paths: Opportunities in 2025”: An overview of emerging AI roles, required skills, and career opportunities across technical, research, and governance areas in the growing AI job market
- Fast Company, “How AI Can Accelerate Career Progression”: Explains how professionals can use AI tools and skills to increase their productivity, build new capabilities, and advance more quickly in their careers
- Intuit, “AI Skills to Boost Your Tech Career”: Highlights the key technical and practical AI skills—such as machine learning, data analysis, and prompt design skills—that can strengthen a technology career
- The Muse, “Is AI a Good Career Path? Pros and Cons to Help You Decide”: Examines the benefits and challenges of pursuing an AI career, helping readers evaluate whether the field aligns with their skills and interests
- Pluralsight, “AI Career Paths: 2026 Job Guide”: A career guide outlining major AI job tracks, the skills needed for each role, and the salary potential associated with AI careers
- TechTarget, “4 AI Career Path Trajectories for IT Professionals”: Describes several ways information technology (IT) professionals can transition into AI roles, including into AI architect, data scientist, and business intelligence developer positions
- Wolters Kluwer, “The Intelligence Era: Accounting’s Shift to AI and Insights”: Explores how AI is transforming accounting by automating routine work and shifting professionals’ responsibilities toward data analysis and strategic insight generation
Find Your AI Career Path
Given how new this technology is, every individual’s AI career path looks different.
Some professionals transition from a less technical role to a more technical one within their current industry. For example, someone working in manufacturing can stay in the industry while developing the skills needed to move into an AI-focused role. Others are already working in a related area such as data analytics and choose to strengthen their business and leadership skills to step into an AI leadership position. For individuals not yet in the workforce, targeted training can help them open the door to this rapidly growing field.
While there isn’t a single best degree to pursue to enter or advance in a career in AI, enrolling in a master’s program or a graduate certificate program might help individuals take a significant step in the right direction.