AI Practitioner vs. Cloud Practitioner: What’s the Difference?

AI practitioners and cloud practitioners often overlap, with each group actively using, designing, building, or implementing either artificial intelligence (AI) and machine learning solutions or cloud-based solutions. For AI practitioners, job roles might include positions like AI engineer or AI research scientist. For cloud practitioners, it might consist of careers like cloud implementation engineers or cloud administrators. It’s also notable that many AI practitioners access AI and ML solutions through the cloud, making them both AI and cloud practitioners. 

In these professions, you can help companies assess their needs for either AI and ML or cloud solutions, then design or build those solutions, and help your organization migrate from their existing infrastructure to the new technology. Both roles can also refer to line of business professionals, or professionals who work with AI and ML solutions but don’t directly build and deploy them. 

AI and cloud computing will both likely play an increasing role in business operations over the coming years, as more professionals embrace these technologies in their day-to-day tasks. Compare AI practitioner vs. cloud practitioner professions, including the demand for professionals with skills in both areas to implement, build, and optimize new technology solutions, to begin charting your potential career and learning pathways. 

What is the difference between a cloud practitioner and an AI practitioner?

A cloud practitioner uses cloud-based services, either as a tool to help them complete their job tasks more efficiently or in a role focused on assisting companies in building, implementing, and migrating to cloud-based solutions. An AI practitioner’s role is similar, but instead of using cloud services, these professionals focus on AI and ML to automate and optimize their job tasks or they may actively work on designing, training, and implementing AI and ML models. 

AWS AI Practitioner vs. AWS Cloud Practitioner certifications

AWS AI Practitioner and AWS Cloud Practitioner refer to two foundational certifications from Amazon Web Services. AWS offers these credentials to help professionals validate their skills using AWS cloud-based solutions, including AI and ML solutions. You can explore each option to help you learn skills in both AI and cloud computing, which may allow you to stand out from other candidates or start your education for a career in building and implementing solutions. 

What is an AI practitioner?

An AI practitioner is a broad term referring to any professional who uses AI solutions in their line of work. While this can include many AI-focused roles like AI engineers or AI product managers, it can also refer to professionals working in positions like sales, marketing, business operations, program management, or other areas that benefit from AI technology. You can consider AI practitioners in two main groups: professionals who work to make AI better and professionals who use AI to make their work better. 

AI practitioner roles working to build, develop, or design AI

Professionals who work to make AI better include AI researchers, AI engineers, AI policy directors, AI ethicists, and more. These career roles are considered AI practitioners because the primary practice of their professional lives is working with artificial intelligence. AI technology is still developing as an industry, and companies and organizations are still in the process of formalizing these roles. This means that you may find overlap in the daily responsibilities or job descriptions of different AI practitioner roles with various job titles. 

AI practitioner roles working with AI solutions for automation and efficiency 

Program managers, customer support representatives, marketing professionals, and sales associates are among the professionals who use AI to improve their work. These careers increasingly implement solutions that use AI and machine learning to help them work more efficiently, better manage data, and automate tasks. 

A 2023 Amazon study found that 92 percent of employers plan to implement AI solutions and 93 percent anticipate using generative AI in their business processes and workflows by 2028. As a result, 73 percent of employers reported they are actively looking for candidates with AI skills in roles like IT, sales, and human resources. Yet of that group, 75 percent report struggling to find candidates with proven experience using AI solutions. Considering that employers also reported a willingness to pay candidates with AI skills 35 to 47 percent more than counterparts without AI skills, it may be lucrative to develop your AI skills in many different positions [1]. 

How much do AWS AI practitioners make?

The amount you can earn as an AWS AI practitioner or in other positions using AI skills will depend heavily on your exact role working with AI. For example, you may earn an AI practitioner certification to help you start a career as an AI engineer, earning an average salary of $103,754 [2], or you might earn a certification to help you advance your career as a marketing manager, earning an average salary of $81,331 [3]. Other examples of AI practitioner careers (and their average salaries) include: 

• AI researcher: $96,271

• Machine learning engineer: $119,494

• AI policy director: $194,029

• AI ethicist: $92,201

• Customer support representative: $44,102

• Sales representative: $67,918

• HR manager: $81,609

• BI analyst: $93,917

*All salary data comes from Glassdoor as of May 2025 and does not include additional pay such as bonuses, commissions, or profit sharing.

What is a cloud practitioner?

Similar to AI practitioners, cloud practitioners are loosely defined as professionals who use cloud-based services in their work. Many roles focus on creating, building, or implementing cloud services, including roles like cloud implementation engineers, cloud architects, or cloud administrators. However, as companies increasingly implement cloud solutions outside of their IT department to lower costs, increase innovation, and create Agile processes, more and more professionals are conducting their work inside cloud-based programs and infrastructure. These cloud computing line of business roles include sales professionals, HR representatives, and project managers.

Cloud practitioners working to implement and build cloud solutions

The massive rate of cloud adoption requires that professionals help companies design, build, and implement cloud solutions. Companies must also consider the additional IT factors that cloud computing introduces, such as cloud security. Job titles for cloud practitioners working on these areas of cloud technology include cloud implementation engineers, IT infrastructure services analysts, implementation consultants, cloud architects, and solutions engineers. 

Globally, cloud computing is worth $752.44 billion as a total market [4]. That figure will grow by 20.4 percent from 2025 to 2030. This wave of adopting cloud-based services could help companies create $3 trillion in global value by 2030 by increasing capabilities while lowering costs and driving innovation [5]. Cloud-based AI solutions contribute to this estimate by allowing companies to access powerful AI solutions with the scalability and flexibility of cloud computing. Cloud services also offer companies the ability to access a higher level of computing power and infrastructure for big data analysis. The ongoing shift toward cloud-based services will likely mean that companies need skilled cloud practitioners to help manage, plan, and implement cloud adoption. 

Line of business cloud practitioners

The emphasis on cloud adoption across industries means that an increasing number of professionals will rely on cloud-based solutions to complete their work and access programs that make their workflow more efficient. These include professionals working in project management, human resources, sales, marketing, and more. For example, a team of professionals might use cloud-based collaboration tools like Slack, Asana, Monday.com, or Google Workspace. You can access generative AI through the cloud without having to develop your own AI models, enabling generative AI use cases in customer service, role-based personal assistants, marketing, and dozens of other capabilities. 

Cloud computing is an in-demand skill, and companies often have a difficult time finding candidates with the capability to create and implement cloud based solutions. Developing your cloud computing skills can help you stand apart from other applicants in roles like sales, marketing, or HR and help you position yourself positively against future trends in your industry. 

How much do AWS cloud practitioners make?

Just as with AI practitioners, the salary you can expect to earn as a cloud practitioner will depend on whether you have a technical role like cloud implementation engineer, or a line of business role like customer service representative or marketing manager. A few careers for cloud practitioners (and their average salaries) include: 

• Cloud implementation engineer: $97,356

• IT infrastructure analyst: $92,571

• Implementation consultant: $86,542

• Cloud architect: $145,886

• Solutions engineer: $105,936

• Systems administrator: $92,786

• Project manager: $83,800

• Data scientist: $113,803

*All salary data comes from Glassdoor as of May 2025 and does not include additional pay such as bonuses, commissions, or profit sharing.

AI practitioner vs. cloud practitioner

AI practitioners and cloud practitioners are professionals with different skills but can both refer to technical professionals building, designing, and implementing technical solutions, as well as professionals who benefit from technical solutions in their job roles. As an AI practitioner, you work to create and implement AI and machine learning solutions or use said solutions to automate and optimize your work. In the role of a cloud practitioner, meanwhile, you will build and deploy cloud-based solutions or benefit from the scalability and computing power of cloud-based solutions. Both AI/ML and cloud computing are skills that can help you differentiate yourself in your field and potentially earn more money. 

Learn AI and cloud skills on Coursera

Learning AI or cloud computing skills can help you qualify for a role as an AI practitioner or a cloud practitioner, either helping to design and build solutions using these technologies or implementing them into your workflow for automation, efficiency, and collaboration. If you want to learn more about working with AI, machine learning, or cloud computing, you can find resources on Coursera to help you begin. For example, consider the AWS Cloud Solutions Architect Professional Certificate to design architectural solutions for addressing common business challenges, create and operate a data lake in a secure and scalable way, ingest and organize data into the data lake, and optimize performance and costs. 

Or explore the AI For Business Specialization offered by the University of Pennsylvania to start learning skills like machine learning, data analysis, algorithms, human learning, leadership and management, business analysis, and more.