As artificial intelligence (AI) continues to disrupt—and, in some cases, bolster—the job market by creating new demand, the number of AI jobs has steadily increased in recent years. Recent Aura data shows that AI-related jobs accounted for over 12.5% of all software hiring.
| AI Job Market Trends: Data-Driven Insights You Can Use | |
| Percentage of software jobs focused on artificial intelligence | 12.5% |
| Percentage of total technology jobs focused on artificial intelligence | 5.4% |
| Percentage of AI jobs offering remote work environment | 12% |
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AI's potential impact on the job market was initially viewed as somewhat dire. For example, an early study by OpenAI on the labor market impact of large language models (LLMs) predicted that "around 80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of LLMs" and that approximately "19% of workers may see at least 50% of their tasks impacted."
However, a recent study from MIT CSAIL challenges the assumption that AI will rapidly automate significant portions of the workforce. The researchers found that only "about 23 percent of wages paid for tasks involving vision are economically viable for AI automation," highlighting that widespread automation may be slower than anticipated. This suggests a more measured pace of AI adoption, driven by economic and technical feasibility rather than pure technological capability.
AI technologies such as machine learning and data science are dramatically shaping businesses by creating new job roles, transforming careers, and revolutionizing industries ranging from software engineering to biological sciences, homeland security, and beyond. At Aura, we explore these job trends using our workforce analytics platform. Let's dive into the key trends in AI and AI-related jobs.
This AI-driven innovation surge opens up numerous career opportunities across various sectors.
Graph of AI Jobs by Aura Workforce Data
Recent research from Deloitte underscores the potential for generative AI to positively reshape labor demand. As a "brilliant" innovation, it stands out from incremental technologies by delivering significant productivity gains. Generative AI, classified as a general-purpose technology, transforms industries from legal services to financial modeling.
Its widespread adoption could result in substantial cost savings and a robust productivity effect. This growth is expected to drive demand for high-wage roles such as AI researchers, algorithm developers, and cybersecurity experts. These advancements are particularly promising in industries where AI augments human capabilities rather than replaces them.
However, the impact of generative AI also depends on labor scarcity and institutional policies. The transition is likely smoother in regions with strong worker protections. This approach minimizes displacement effects and encourages AI to complement human labor rather than automate it entirely.
These dynamics suggest that generative AI will continue to fuel job creation in specialized fields and reshape the broader labor market. The outcomes will vary across geographies and sectors, highlighting the need for a nuanced approach to its adoption.
The AI industry has experienced rapid growth in recent years, with a 74% increase annually in AI and machine learning positions within the last four years. This surge is driven by the escalating demand for AI skills across various sectors, including healthcare, education, marketing, retail, eCommerce, and financial services.
Nvidia’s CEO, Jensen Huang, summed up the potential of the AI industry in the company’s recent Q3 2024 earnings call: "Generative AI is the largest TAM [total addressable market] expansion of software and hardware that we’ve seen in several decades." This underscores the immense opportunity and ongoing momentum within the AI market as it transforms business operations and drives innovations.
And it's not just the large leaders like Nvidia; the number of artificial intelligence companies in the United States has doubled since 2017, reaching nearly 14,000 AI startups as of 2022.
According to the Bureau of Labor Statistics, the job outlook for AI roles is exceptionally promising, with a projected 15% increase annually in computer and information research jobs from 2019 to 2029.
Our recent AI job market trend report from Aura shows that California, New York, Texas, Washington, and Massachusetts lead the nation in the number of AI job postings.
This growth is in numbers and in adopting AI technologies across business operations. A recent report found that 40% of businesses use AI for at least one work function.
AI seems to have a wide-ranging impact. The OpenAI suggested that "LLMs have the potential to significantly affect a diverse range of occupations within the U.S. economy," from routine tasks to higher-wage jobs. The analysis found that higher-wage occupations tend to exhibit higher exposure to AI, as tasks requiring programming and writing skills are particularly vulnerable to disruption.
This trend is expected to continue as AI tools enhance worker productivity and improve the quality of their output. The AI industry is progressing upward, reshaping how businesses operate and simultaneously creating many opportunities for skilled AI-development professionals.
AI-related job openings have witnessed exponential growth over the last decade. According to labor statistics, many industries face a severe talent shortage, with AI-specific roles remaining unfilled for longer due to the high demand for specialized skills. Big tech companies are focused on scooping up this talent, ferociously competing for top engineers.
OpenAI’s research indicates that "LLMs [are] ... accelerating the need for skilled professionals in machine learning, AI engineering, and data science.
However, while AI-related job openings are increasing, research suggests that "AI adoption is driven by establishments that have a task structure suitable for AI use," but this has also "been associated with significant declines in establishment hiring." This points to a dual reality: AI's potential for task automation may outpace its capacity to create complementary human jobs, at least in the short term.
However, at least now, talent acquisition has become a critical focus for companies looking to stay competitive. The U.S. Bureau of Labor Statistics considers AI jobs the fastest-growing career opportunities, especially in software engineering, machine learning, and data science.
AI Job Trend Graph from Aura Workforce Analytics
Aura data indicates that, though technology hiring sank recently due to macro issues, the percentage of AI-related jobs continues to grow. For example, in August 2024, Aura found that 5.4% of tech jobs were AI-related. This relative strength indicates its growing importance.
Hiring managers are particularly focused on filling roles in AI development. AI tools and systems revolutionize data-driven decision-making processes across financial services, healthcare, transportation, and defense sectors.
As MIT researchers note, AI and automation is also opening up new roles in managing, maintaining, and improving AI systems. This could lead to the emergence of specialized careers focused on AI infrastructure and support. For instance, as certain jobs are automated, there will be a growing demand for roles where human skills remain indispensable, such as oversight and AI optimization.
The demand spans multiple industries, and AI is increasingly becoming an integral part of government and private companies, creating demand for talent.
Machine Learning Engineers: Responsible for designing algorithms that allow machines to learn from data, machine learning engineers are crucial in developing AI systems that can improve efficiency and automate complex tasks. Job descriptions often highlight the need for programming and data analysis expertise. These positions are particularly prevalent in California, where tech giants heavily concentrate their investments in AI infrastructure.
Data Scientists: Data science professionals are key to AI development. They analyze large datasets, perform data analysis, and develop models that enhance AI system performance. The need for data scientists has grown significantly in high-demand and data-intensive sectors like healthcare and defense, especially in industry tech clusters like Virginia. This concentrated surge in demand has opened up numerous employment opportunities for skilled data scientists.
AI Engineers: Besides building and maintaining AI systems, AI engineers play an essential role in developing new AI technologies. From creating virtual assistants to advanced cybersecurity tools, these professionals are at the forefront of innovation, driving growth across industries.
Program Managers: As more companies develop AI systems, program management has become critical for coordinating complex projects. AI program managers oversee multiple teams, ensuring the development aligns with company goals. Many AI program managers are now working on government projects with departments like Homeland Security (DHS), especially in roles concerning national safety and cybersecurity.
Analyst: AI analysts interpret data generated by AI systems, providing insights that drive decision-making, optimize operations, and improve AI models across various industries.
Annotation Specialist: Annotators label and organize data AI systems use for machine learning and training. Their work is foundational in building AI models for computer vision and language processing applications.
Artist: AI artists leverage AI tools like Midjourney and Photoshop to create visual content, merging creativity with technology. This role is particularly significant in fields like generative art and design.
Causal Inference Researcher: Causal inference experts in AI study how different variables interact, helping to determine cause-and-effect relationships within data, a vital component in decision-making models.
Chatbot Developer: These specialists create and refine AI chatbots used in customer service, marketing, and support, ensuring conversational AI tools operate smoothly and effectively handle user queries.
Computer Vision Specialists: These professionals work on AI systems that enable computers to interpret and understand visual information, such as images and videos. This is essential in areas like autonomous driving and surveillance.
Consultant: AI consultants advise businesses on integrating AI technologies into their workflows to improve efficiency, reduce costs, and stay competitive. They provide strategic guidance on AI implementation.
Content Writer: AI content writers develop text for AI-related content training or work with AI-driven tools to generate articles, technical documentation, and marketing materials, supporting AI outreach and education.
Conversational AI Developer: These professionals build AI systems designed for human interaction, such as virtual assistants and chatbots, optimizing them for natural, fluid conversations.
Cybersecurity Specialist: AI is increasingly important in cybersecurity, where experts use machine learning algorithms to detect and prevent security threats, enhancing the safety of systems and networks.
Data Scientist: Data scientists analyze and interpret complex datasets, often using machine learning models to generate insights that inform business decisions and improve AI systems.
Deep Learning Expert: Deep learning specialists develop complex neural networks that mimic the functioning of the human brain to improve AI applications in areas like image recognition, language processing, and autonomous systems.
Developer: AI developers are responsible for coding and developing AI algorithms and models. They build the underlying software that powers AI applications across industries, from virtual assistants to predictive analytics tools.
Engineer: Engineers design, build, and maintain artificial intelligence and machine learning systems. They are essential to advancements in automation, predictive analytics, and intelligent applications.
Entry Level Roles: Entry-level positions in AI, such as internships in data science, machine learning, or software engineering, offer newcomers the opportunity to build a career in AI by learning and contributing to small-scale AI projects under senior professionals.
Ethics Specialist: AI ethics professionals focus on the responsible and fair use of AI systems, tackling issues such as algorithmic bias, privacy, and the societal impacts of automation. They help guide companies in deploying ethical AI practices.
Finance Professional: AI is transforming finance, and professionals in this field apply AI to automate processes like risk assessment, financial modeling, fraud detection, streamlining operations, and improving decision-making.
Governance Specialist: AI governance professionals ensure that AI technologies are implemented in compliance with industry standards, regulations, and best practices, maintaining oversight of data security and ethical considerations.
Healthcare Specialist: Healthcare AI professionals work on developing systems that assist in diagnostics, patient care, and medical research, utilizing AI to improve health outcomes and operational efficiency in hospitals and clinics.
Internship Opportunities: AI interns contribute to projects by working with senior teams on the research, development, and testing of AI tools and applications, gaining valuable hands-on experience in the field.
Legal Specialist: AI legal professionals navigate the regulatory, ethical, and legal frameworks associated with AI technologies. They ensure that AI applications comply with data privacy, intellectual property, and safety laws.
Machine Learning Engineer: These engineers play a critical role in AI. They build algorithms that allow machines to learn from data. They apply machine learning techniques to automate tasks, create predictive models, and drive AI-based innovations.
Marketing Specialist: In AI, marketing professionals use data-driven insights to craft campaigns targeting businesses that can benefit from AI solutions or use AI tools to optimize content and customer outreach.
MLOps Engineer: MLOps professionals focus on the deployment and operationalization of machine learning models, ensuring their scalability, reliability, and efficiency in production environments.
NLP Specialist: Natural Language Processing experts work on enabling AI systems to understand, interpret, and respond to human language, contributing to advancements in chatbots, translation tools, and voice assistants.
Product Manager: AI product managers oversee the development and lifecycle of AI products, from ideation to implementation. They align technical teams and business strategies to deliver AI-driven solutions that meet market needs.
Project Manager: AI project managers coordinate between development teams and stakeholders to ensure AI projects meet goals, deadlines, and budgets. They manage the resources and tasks necessary to complete AI deployments.
Prompt Engineer: In AI job roles, prompt engineers work closely with generative AI systems, fine-tuning prompts to optimize outputs in models like GPT and other natural language processing systems. This role is crucial for advancing conversational AI technologies.
Researcher: AI researchers are at the cutting edge of developing new algorithms, models, and applications for AI. Their work pushes the boundaries of what AI can achieve in areas like deep learning, neural networks, and natural language processing.
Sales: Sales professionals in AI work to sell AI solutions and technologies to businesses across industries. Their role includes educating clients on the value of AI and aligning products with business objectives.
Strategy Consultant: AI strategy consultants advise businesses on aligning AI initiatives with broader corporate strategies, focusing on long-term growth, innovation, and competitiveness.
Tester: AI testers evaluate AI systems to ensure they function as expected, identifying bugs and performance issues. They play a critical role in the quality assurance of AI applications before deployment.
Training Specialist: This term is used two ways – as AI training professionals responsible for educating and upskilling teams on how to implement and leverage AI tools effectively, and as AI data training specialists, who input content and data into AI systems to help build intelligence.
These job roles offer diverse career paths in the AI industry, catering to various interests and expertise.
Entry-level AI jobs provide valuable experience and build foundational knowledge in AI. Common entry-level positions include:
Research Assistant: In this role, you’ll assist with AI and machine learning research projects, communicate with team members, and apply basic computer programming skills. It’s a great way to get hands-on experience in cutting-edge AI research.
Junior Data Analyst: As a junior data analyst, you’ll translate numbers and data into words and graphic visualizations, helping businesses and organizations make informed decisions. This role requires strong data analysis skills and effective communication of complex data insights.
Junior Software Engineer: This position involves developing software and systems for businesses and organizations. You’ll write simple code, debug existing software, and assist other team members, providing a solid foundation in software engineering and AI development.
These entry-level roles typically require a bachelor’s degree in a related field, such as computer science, statistics, or mathematics. Basic programming skills, data analysis capabilities, and knowledge of machine learning algorithms are also essential.
To break into AI roles, consider completing Python, Machine Learning, or Data Science certification programs. Practical experience, even through personal projects or AI hackathons, can also be a game-changer.
Mid-level AI jobs demand more experience and advanced skills compared to entry-level positions. Some common mid-level roles include:
Data Scientist: Data scientists use data to impact businesses and organizations significantly. They understand specific problems or challenges, use data modeling and visualization, and conduct exploratory analysis. This role requires a deep understanding of data science and machine learning techniques.
Software Developer: As a software developer, you’ll write code, create software designs, fix bugs, and collect user data. This role is crucial for developing robust AI applications and systems.
Program Manager: Program managers oversee the development and implementation of AI projects. They manage teams, ensure projects are completed on time and within budget, and align AI initiatives with business goals.
These mid-level positions require a bachelor’s degree in a related field and advanced programming, data analysis, and machine learning skills. They also demand a higher level of responsibility and the ability to drive significant business outcomes through AI.
Leadership roles in AI require substantial experience and advanced skills. These positions are critical for guiding AI development and implementation within organizations. Common leadership roles include:
Chief Artificial Intelligence Officer: This role involves leading AI development and implementation across an organization, overseeing AI strategy, driving innovation, and ensuring responsible and ethical use of AI technologies.
Director of Data Science: Directors of data science oversee the development and implementation of data science projects, manage teams, and ensure projects are completed on time and within budget. They play a pivotal role in driving data-driven decision-making.
AI Engineer: AI engineers design and develop AI systems, including machine learning algorithms and natural language processing systems. They are at the forefront of AI innovation, creating technologies that transform industries.
These leadership roles require a bachelor’s or master's degree in a related field, advanced programming skills, data analysis expertise, and in-depth knowledge of machine learning algorithms. Additionally, strong leadership and management skills and the ability to communicate complex technical concepts to non-technical stakeholders are essential.
By understanding the various career opportunities in AI, from entry-level to leadership roles, professionals can better navigate their career paths and capitalize on the growing demand for AI skills.
The AI job market is not restricted to technology; it offers numerous job opportunities across various sectors. In fact, AI’s penetration into industries like agriculture, accounting, transportation, and even biological sciences highlights its growing importance.
For instance, biological sciences leverage AI for data analysis in genomics, drug development, and disease control research. Similarly, agriculture uses AI to optimize crop yields, improve food security, and develop more efficient farming practices. Employment trends indicate a rising demand for AI skills in these diverse fields.
The role of AI in government and defense cannot be understated. The Department of Defense (DoD) and Homeland Security (DHS) are heavily investing in AI to enhance cybersecurity, streamline logistics, and improve surveillance. Integrating AI into defense has created numerous job opportunities for AI engineers, machine learning experts, and data scientists.
In sectors like defense and cybersecurity, the U.S. government has increasingly turned to AI to address national security concerns and specific job functions. Programs like DHS’s AI initiatives have led to AI-driven solutions for public safety, intelligence gathering, and infrastructure protection. Congress continues to advocate for more AI jobs in the public sector to bolster national safety. This shift is significantly shaping the employment landscape in these critical areas.
The path to an AI career often starts with a specialized education that significantly enhances job prospects. Students pursuing artificial intelligence, data science, and software engineering degrees are positioning themselves for lucrative careers in the growing AI market.
Many companies and governments fund AI research in universities, creating training programs to nurture the next generation of AI talent. Career development in AI is further supported by continuous learning and professional growth opportunities.
For those looking for entry-level positions, internships and junior roles in AI research, data analysis, and program management are becoming more common. Many companies are launching AI training programs to support talent development and address the high demand for professionals who can code, analyze data, and understand AI systems. This focus on education is vital as the AI field requires a deep understanding of coding languages like Python, Java, and R.
Graph - Data on Remote Jobs by Aura
Since the pandemic, there has been a rise in remote AI jobs and remote positions. Aura found that 6.4% of all new jobs had a remote component most recently, and nearly 12% of all AI-related positions now offer remote flexibility. The remote work environment has become a crucial factor in attracting top talent, and is often used as key perk to attract development talent. However, this shift is not just a perk but a necessity as companies broaden their talent pools beyond geographical constraints.
The future of AI jobs is incredibly promising for career advancement. As AI technologies advance, the need for specialized talent will continue to grow. According to market forecasts, the global AI market is projected to grow from $515.31 billion in 2023 to over $2 trillion by 2030, signaling continued investment and expansion in the field. Positions like AI research scientists, algorithm developers, and cybersecurity experts will remain in high demand, with companies searching for individuals who have mastered AI tools and systems. Job growth in this field is expected to be substantial.
Moreover, the development of AI is expected to create entirely new jobs and transform existing roles. AI-driven tools will automate many repetitive tasks in sectors like accounting, transportation, and manufacturing, freeing human workers to focus on more strategic, creative roles. For instance, AI applications in economics and businesses will help analyze complex market trends, making decision-making more efficient.
However, the situation is more tenuous for general and non-AI-specific job growth. Despite optimism surrounding AI’s ability to boost job creation through productivity improvements, recent MIT and the National Bureau for Economic Research research reveals that "AI will [not] increase hiring because of its large productivity effects." This highlights the challenges in realizing widespread job growth from AI technologies in the near term despite the surge in AI-related roles.
The AI job market is rapidly evolving, with demand for AI engineers, data scientists, and machine learning experts continuing to surge across multiple sectors, improving employment prospects. As AI becomes more integrated into private and public sectors, it will offer unparalleled career opportunities for those with the right skills, education, and experience. AI technologies are shaping today's job market and defining the future of work worldwide. Understanding job market trends is crucial for staying ahead in this dynamic field.
Stay informed on the latest AI trends and leverage Aura’s workforce data to make data-driven decisions about your AI hiring strategy, optimize your organization, or determine new investment opportunities. Book a demo today to discover how Aura can help you navigate the ever-changing AI job market.