By Xian (Chad) Qian | 10/30/2026
The field of artificial intelligence (AI) is expanding rapidly. Artificial intelligence tools have permeated almost every industry, such as information technology, healthcare, retail, energy, higher education, and finance.
In healthcare, for instance, AI helps doctors analyze medical images. For example, AI can help identify patterns in medical images that may indicate certain diseases, assisting healthcare professionals in diagnosis.
In retail, AI can analyze customer behaviors and recommend related products to help businesses increase their sales. For example, Walmart® and Amazon® always recommend products based on customers’ shopping behavior with the aid of AI software.
In finance, AI can help with auditing. For example, AI can detect unusual transfer activities between bank accounts.
In addition, we regularly interact with artificial intelligence tools from home. For instance, we might converse with chatbots designed to make conducting business faster, better, and more cost-effective. Our homes have smart assistants that employ AI to provide us with answers to our queries, and we use large language models (LLMs) such as ChatGPT®, Perplexity®, and Claude® to look up information.
Now that more and more businesses are adopting artificial intelligence technology, there are AI industry careers that have come into existence. Artificial intelligence offers diverse career opportunities, and understanding these roles can help job seekers stand out in a competitive market.
Potential Artificial Intelligence Career Paths
There are several potential career paths for AI professionals. These roles include:
- Machine learning engineer
- AI engineer
- Data scientist
- AI product manager
These professions focus on designing, building, and applying AI technologies.
Machine Learning Engineer
A machine learning (ML) engineer develops machine learning models and scalable algorithms for predictive analytics. A machine learning engineer trains computers how to use an algorithm to solve a problem in the real world.
For example, imagine that a machine learning engineer creates an algorithm to build Microsoft® PowerPoint® presentations. The ML engineer then trains computers how to use this algorithm to build future PowerPoints.
How does this role benefit organizations? A machine learning engineer can automate tasks and make repetitive work faster.
For example, imagine that a department needs to submit a monthly sales report on the last day of each month. Such a report needs to follow standard rules for monthly sales data.
A machine learning engineer can create an algorithm to load the monthly sales data and generate that monthly sales report based on those standard rules. As a result, the sales department saves a lot of time and effort.
A machine learning engineer can also aid decision-making because AI tools are capable of finding patterns in large amounts of data more quickly than humans.
For instance, let’s say that a pet store owner wants to know the most popular and least popular products. A machine learning engineer can build an algorithm to process sales data and provide an answer for data-based decision making.
If you want to be a machine learning engineer, it’s necessary to have technical expertise in different areas, such as:
- Python® – Strong programming skills in Python are essential for AI model development.
- Statistics – Mathematics and statistics are necessary for developing and understanding AI algorithms and how AI technologies aim to simulate human intelligence.
- Data structure knowledge – An ML engineer must organize information efficiently and determine how data is saved.
- Model evaluation techniques – A machine learning engineer needs to understand if an AI model is working correctly by developing and testing the model.
- Data analysis skills – Data analysis is crucial for building accurate AI models.
AI Engineer
An AI engineer designs and builds AI applications. The work of AI engineers can benefit an organization in several ways.
For instance, AI engineers can build chatbots and other tools to provide faster and more convenient customer service. Chatbots also reduce operating costs for companies by reducing the need to hire human customer service representatives and purchase equipment for them.
Similarly, AI engineers can also help a company to create new products. For example, an AI engineer could build innovative AI applications, such as an AI assistant to help graphic designers in the creation of a new logo.
If you’re thinking about becoming an AI engineer, you’ll need to develop essential skills in different areas, such as:
- Software development – AI engineers use Python and other programming languages to create custom applications.
- Deep learning – AI engineers use neural networks to solve complex problems. For example, they can build facial recognition software for security logins.
- Cloud computing – Today, many IT resources are hosted on the cloud. AI engineers need to know how to build and deploy AI applications to cloud platforms like Amazon Web Services® (AWS®) or Microsoft Azure®.
Data Scientist
Data scientists analyze complex datasets and extract insights for business decisions. This work often overlaps with business intelligence through dashboards and reporting that support decision-making. For example, a data scientist can analyze customer purchasing behavior and recommend products that customers are likely to buy.
The work of a data scientist can create real business value for different organizations. For instance, a data scientist can help businesses to find business trends and discover their best-selling products.
Data scientists can recommend new business strategies based on historical sales data for improved decision-making. Also, data scientists can predict future outcomes by using AI systems and their abilities to forecast total sales for the next month, so that they can deliver real business value.
If you want to become a data scientist, you should have these skills:
- Computer languages such as Python, R, and Structured Query Language (SQL) – Python can be used for data analysis and AI modeling, and R can be used for predictive models and text processing. SQL is a popular database programming language for creating relational databases, as well as accessing and managing those databases.
- Statistics – Data scientists should be familiar with statistics in order to collect data, analyze it, and communicate the data’s significance to decision makers.
- Data visualization – Data scientists can build charts and graphs to display data on a sales dashboard.
- Extract, transform, and load (ETL) tools – ETL tools are used to integrate data from multiple sources into one location.
- Machine learning – Data scientists need to understand machine learning techniques and how they can be used to train algorithms for decision making.
AI Product Manager
An AI product manager oversees the lifecycle of AI-powered products and acts as a bridge between business strategy and technical execution. For example, a software company might use an AI product manager to oversee the planning and development of an AI product.
The work of an AI product manager involves connecting business and technology. AI product managers use their knowledge and excellent communication skills to help technical teams align with business stakeholders on real-world projects.
AI product managers amy also serve as project managers, keeping AI application projects organized and working with cross-functional teams. They can also improve product success by ensuring that AI applications are delivered on time and on budget.
If you aspire to become an AI product manager, you’ll need to have both technical skills and business skills in areas such as:
- Business and product management
- Risk management
- Software engineering
- AI
- Leadership
- Communication skills
Artificial Intelligence Certifications
AI certifications demonstrate your competency, knowledge, and skill sets. Here are some of the most popular AI certifications:
- Microsoft Certified Azure AI Engineer Associate – This certification demonstrates that you can build AI solutions using Microsoft Azure.
- AWS Certified AI Practitioner – This certification demonstrates that you can build AI solutions using AWS.
- Google Professional Machine Learning Engineer – This certification focuses on machine learning.
- International Business Machines (IBM®) AI Engineering Certificate – This general AI certificate shows your knowledge of foundation AI and machine learning skills.
Additional education and/or specific work experience may be required to be eligible to take industry certifications. It is important to check all requirements by contacting the organization which administers the certifications.
The Future of The AI Job Market
Today, many industries are looking for candidates who have a strong background in AI. If you want to embark on an AI career path, consider learning AI skills and gaining hands-on experience through AI projects.
Also, work on acquiring soft skills such as collaboration and communication, especially to non-technical stakeholders. Being able to explain complex AI features to non-technical stakeholders will be highly valuable.
The Bachelor of Science in Artificial Intelligence at APU
For adult students interested in studying artificial intelligence, American Public University part of American Public University System (“APU”) offers an online Bachelor of Science in Artificial Intelligence. This degree provides students with the opportunity to learn a wide range of topics, including prompt engineering, algorithms and data structures, data science, and the fundamentals of artificial intelligence. Other courses include artificial intelligence applications, machine learning, user experience design, and artificial intelligence impacts, risks, and ethics.
For more information about APU’s information technology degrees, visit our information technology degree program page.
While this bachelor’s degree program does not award any professional certifications, APU’s courses may be helpful in preparing to earn AI certifications.
Walmart® is a registered trademark of Walmart Apollo, LLC.
Amazon® is a registered trademark of Amazon Technologies, Inc.
ChatGPT® is a registered trademark of OpenAI OpCo, LLC.
Perplexity® is a registered trademark of Perplexity AI, Inc.
Claude® is a registered trademark of Anthropic, PBC.
Microsoft® and PowerPoint® are registered trademarks of Microsoft Corporation.
Python® is a registered trademark of Python Software Foundation.
Amazon Web Services® and AWS® are registered trademarks of Amazon Technologies, Inc.
Azure® is a registered trademark of Microsoft Corporation.
IBM® is a registered trademark of International Business Machines Corporation.