What Is an AI Practitioner?

An artificial intelligence (AI) practitioner guides the implementation and use of AI in their organization. Artificial intelligence is rapidly changing the modern workforce, with some experts projecting it will transform 23 percent of all current occupations by 2027 [1]. The impact on the labor market has become so pronounced that the US Bureau of Labor Statistics now incorporates expected AI-driven shifts into employment and outlook projections [2]. 

AI innovations affect nearly every sector, from personalized sales recommendations to autonomous cars in the automotive industry. As a result, the demand for professionals who can implement and manage AI systems has skyrocketed, leading to the emergence of several new specialized professions, such as AI practitioners. 

To determine whether this role fits your interests, discover what an AI practitioner is, what their everyday responsibilities are, and what qualifications you may need for this role.

What is an AI practitioner?

As an AI practitioner, you apply AI techniques to solve real-world problems and oversee your organization's responsible use of AI. Depending on your industry, you may work with different AI and machine learning algorithms, such as natural language processing (NLP), computer vision, generative AI, and cloud computing techniques.

Your role will differ depending on the type of AI that most benefits your organization. If you work in sales, marketing, or product management, you could focus on learning and applying generative AI concepts, implementing security protocols, and building AI-driven infrastructure that your team can use to enhance customer engagement. In health care, you may employ NLP algorithms to analyze physician notes or build models that identify high-risk patients.

As an AI practitioner, another essential part of your job is AI ethics, meaning you’re responsible for ensuring your organization’s use of AI doesn’t cause harm. This involves carefully examining your company’s use of AI, staying up-to-date on current AI practices in your field, communicating your insights to your team, and shouldering the responsibility of ensuring ethical practice without formal regulations.

Why is an AI practitioner important?

AI technologies are becoming increasingly accessible to organizations, making it essential for companies to have professionals who understand these tools' theoretical and practical aspects. AI practitioners bring exciting skills to current business projects, helping teams automate tasks, improve efficiency, and gain a competitive edge in their market. 

However, beyond technical implementation, AI practitioners play a significant role in understanding the limitations and risks associated with AI. By understanding sources of error and biases in models, AI practitioners help identify flawed outcomes and recognize the margin of error of findings. For example, police forces have begun using AI-powered facial recognition systems to identify suspects. Without having trained staff to oversee the use of this technology, it’s possible for errors in the algorithm to lead to the misidentification of innocent people as suspects—something that has already happened with the use of these tools [3]. 

Without trained professionals bringing a deeper understanding of AI, professionals may avoid using AI and miss valuable advancements, or rely too heavily on AI tools without verifying outputs. AI practitioners help ensure AI tools enhance their organization's workflow while minimizing the potential drawbacks of implementing new systems. 

AI practitioner vs. AI developer

AI developers focus on the design and deployment of AI technologies. In contrast, AI practitioners focus on how to employ AI technologies to solve specific problems in their industry, use the technologies responsibly, and appropriately interpret outcomes. 

AI developers typically have strong software development knowledge that they can use to integrate AI models and algorithms into existing and novel systems. AI practitioners understand these concepts and may even work in development roles, but they also focus on determining the right types of technologies to use, how they integrate with their specific organization, and the limitations to be aware of. 

AI practitioner duties and responsibilities

The role of an “AI practitioner” is relatively new, and it’s likely to take different forms depending on how integral AI is to your organization and what type of AI oversight is needed. 

Everyday AI practitioner duties and responsibilities may include:

• Understanding and using foundational ML, AI, and cloud concepts in your area

• Selecting and fine-tuning the appropriate models for your industry use case

• Communicating AI insights and findings appropriately to teams

• Interpreting the results of model outputs

• Maintaining and monitoring deployed AI models

• Staying updated on emerging AI technologies

• Ensuring ethical and responsible use of all AI technologies in your organization

AI practitioner skills

This role requires both technical and human skills to be successful. In a technical sense, you need skills related to your industry and applications. This may include technical skills in computer science, AI, and machine learning areas, such as:

• Generative AI

• Computer vision

• Natural language processing (NLP) 

• Cloud computing

Because you’re working to oversee and implement AI technologies effectively, human skills related to communication and critical thinking are also extremely important. You need to be able to think critically about your AI models' design, where limitations may be, and how to implement your findings ethically. Many people in your organization may not understand AI and related limitations, so it’s your job to communicate and educate your team about insights.

Job outlook and salary for an AI practitioner 

The AI job market is expanding quickly, influencing the growth of many AI-related professions. According to the US Bureau of Labor Statistics, employment in computer and information research science, which includes AI roles, is projected to grow 26 percent between 2023 and 2033 [5]. The median annual wage for professionals in this field is $140,910 as of May 2024, though employees with specialized skills in AI may earn more [4]. 

AI practitioner education and training

Entering an AI practitioner role can help you gain a bachelor’s degree in computer science, mathematics, or a related field. This can help you build the foundation to use AI concepts and introduce you to different applications and career options. Sometimes, you might benefit from a master’s degree specializing in AI, machine learning, or data science. 

That said, you don’t necessarily need a degree for this role. Several Professional Certificates have become popular, offering another pathway to building relevant skills. You can easily find Professional Certificates, such as the CertNexus Certified Artificial Intelligence Practitioner Professional Certificate, on learning platforms like Coursera. Another popular choice is the AWS Certified AI Practitioner Certification. If you don’t know where to start with this one, consider the Exam Prep AIF-C01: AWS Certified AI Practitioner on Coursera to help you build the skills you need for this exam.

AI practitioner career path

Because the AI practitioner role varies, the career path is primarily determined by your area of expertise and background. Specific certifications like the AWS Certified AI Practitioner Certification have more defined career paths. This certification is intended for those in business analyst, IT support, marketing, project management, or sales roles who want to integrate AI into their organization. As you advance beyond these roles, your next steps are to earn qualifications as a machine learning engineer, data scientist, or AI architect. 

In other industries, such as government roles, your pathway might be slightly different. According to the IT Modernization Centers of Excellence department, AI practitioners tend to have a strong computer science or mathematics background, making roles such as junior data engineer and junior data scientist popular starting places [5]. As you progress, you may enter more advanced roles, such as a data architect or data scientist, which typically require extensive technical experience. If you’re in academia, you may enter a research scientist role. You can also enter more managerial roles, such as a technical project manager, or more specific AI roles, such as an “AI champion,” which ensures responsible use of AI technologies. 

Learn about AI with Coursera

An AI practitioner not only helps implement AI concepts into existing business operations but also oversees the responsible use and interpretation of AI systems. To build a foundation in AI, you can take exciting courses and Specializations on Coursera. The AI for Business Specialization by the University of Pennsylvania is a great place to start. In this Specialization, you can explore the fundamentals of using big data, artificial intelligence, and machine learning, and the various areas in which you can deploy them to support your business. Plus, you’ll have the opportunity to explore the ethics and risks of AI, governance frameworks to apply AI fairly, and insights into how AI and big data are revolutionizing businesses.