Number Of AI Engineers Size, Share, Opportunities, And Trends By Age (25 – 40 Years, 40 - 50 Years, 50– 60 Years, >60 Years), By Gender (Male, Female), By Field (Natural Language Processing (NLP), Computer Vision, Machine Learning Applications, Robotics, Others), And By Region - Forecasts From 2023 To 2028

  • Published : Aug 2023
  • Report Code : KSI061615862
  • Pages : 140

AI engineers shoulder the responsibility of crafting, programming, and training sophisticated algorithmic networks that constitute Artificial Intelligence, enabling these systems to mimic human brain functions. Depending on their specialized areas, AI engineers can be classified into various fields, such as Natural Language Processing (NLP), Computer Vision, Machine Learning Applications, and Robotics. The escalating adoption of Artificial Intelligence across various sectors, investments in AI research and development, and robust government initiatives and investments in the field have provided a major scope for AI engineers.

Growing adoption of Artificial Intelligence.

The increasing adoption of AI is expanding the scope of AI engineers due to the rising demand for skilled professionals who can design, develop, and implement AI technologies across various industries. Businesses and organizations harness the potential of AI to enhance efficiency, automation, and decision-making which is increasing the need for AI engineers. This growing demand and diverse application areas are positioning AI engineers at the forefront of shaping the future of technology and driving advancements across numerous sectors. For instance, according to the IBM global AI adoption report, in 2022, the global adoption rate of AI experienced steady growth, reaching 35%, which indicates a 4% rise compared to the previous year.

Increasing investments in AI research and development.

The surge in investment in AI research and development is significantly driving the demand for AI engineers. The increased funding is creating more opportunities for skilled professionals in the AI field, as businesses and organizations seek to capitalize on AI's potential to enhance efficiency, innovation, and competitiveness. This growing demand due to R&D and expanding range of applications is empowering AI engineers to play a pivotal role in shaping the future of technology. For instance, in 2022, the Russian Direct Investment Fund (RDIF) secured a substantial investment of $2 billion from international investors. This funding aims to support Russian companies in their research and development endeavors within the field of Artificial Intelligence.

Government initiatives and investments.

Increased funding for AI research and development, along with supportive policies and incentives, have created a favorable environment for AI-driven projects and startups. These efforts have not only attracted more individuals to pursue careers in AI engineering but also provided opportunities for specialized education and training programs, cultivating a skilled workforce to meet the growing demand in the AI industry. As a result, the convergence of government support and investments has significantly contributed to the number of AI engineers. For instance, In February 2023, during the announcement of India's Union Budget, the finance minister declared the establishment of three centers of excellence for Artificial Intelligence (AI) within the country's leading educational institutions.

The United States is witnessing a rise in the number of AI engineers

U.S. government investments and initiatives in AI, together with the rising employment opportunities in the AI field, are instrumental in driving the number of AI engineers in the country. For instance, according to the U.S. Bureau of Labour Statistics, the United States is projected to witness an increase in data scientist employment, with an additional 40,500 positions anticipated between 2021 and 2031. Additionally, In May 2023, a collaborative effort by the U.S. National Science Foundation (NSF), numerous federal agencies, and higher education institutions led to the announcement of a $140 million investment for the establishment of seven new National Artificial Intelligence Research Institutes,

Financial constraints

The journey to becoming an AI engineer can be financially burdensome, and the substantial costs associated with specialized courses and degrees can act as a significant deterrent for many aspiring students. High tuition fees, coupled with the need for additional resources like software and hardware for practical training, can create barriers to entry, particularly for those with limited financial means. This financial constraint may restrain the number of AI engineers, as some potential students might opt for more affordable career paths or fields of study, despite their interest and passion for AI.

Key Developments

  • July 2023: Wipro Limited, a prominent technology services and consulting firm, unveiled Wipro ai360, an all-encompassing, AI-centric innovation ecosystem. This initiative capitalizes on Wipro's decade-long investments in Artificial Intelligence, aiming to infuse AI into all internal and client-offered platforms, tools, and solutions. To bolster the launch of Wipro ai360, the company has pledged a significant investment of $1 billion over the next three years to advance AI capabilities, reflecting its commitment to driving innovation and value through AI technology.
  • June 2023: Accenture declared a substantial $3 billion investment over three years toward bolstering its Data & AI practice. This strategic investment is designed to assist clients from various industries in rapidly and responsibly utilizing AI to unlock greater growth, efficiency, and resilience. By investing heavily in its AI capabilities, Accenture underscores its commitment to helping clients maximize the potential of AI in transforming their business operations.
  • May 2022: The Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), recognized as the world's first graduate-level, research-focused Artificial Intelligence (AI) university, unveiled plans for a strategic collaboration with IBM. Top executives from both institutions have formalized this partnership through a Memorandum of Understanding, with a shared vision of propelling fundamental AI research forward. The collaboration aims to expedite scientific breakthroughs with the potential to harness AI's power to address some of the most pressing challenges facing humanity, underlining the commitment of both institutions to the responsible and innovative use of AI.
  • February 2021:, a machine learning firm headquartered in California, unveiled a new design center in Bengaluru, India. This strategic move is anticipated to catalyze job creation in the local community, thereby stimulating regional economic growth. The AI lab is poised to be instrumental in the company's mission to broaden the utilization of critical AI-based edge applications. These applications span several fields, including robotics, medical technology, and autonomous vehicles, demonstrating's commitment to driving AI adoption in diverse sectors.


  • By Age
    • 25 – 40 Years
    • 40 - 50 Years
    • 50– 60 Years
    • >60 Years
  • By Gender
    • Male
    • Female
  • By Field
    • Natural Language Processing (NLP)
    • Computer Vision
    • Machine Learning Applications
    • Robotics
    • Others
  • By Region
    • Americas
      • USA
      • Others
    • Europe, Middle East, and Africa
      • Germany
      • UK
      • Others
    • Asia Pacific
      • China
      • Japan
      • Others


1.1. The Changing Job Landscape: How AI is Shaping Opportunities

1.2. Academic Ability Of Colleges And Universities

1.2.1. AI Curriculum Setting 

1.2.2. Strong Interconnection between Academia and Industry

1.3. R&D Department of AI Giants


2.1. Research Design

2.2. Research Data

2.3. Validation


3.1. Key Findings


4.1. Market Drivers

4.1.1. Increase in AI Research Centers

4.1.2. High Demand from Top Companies

4.1.3. Rise in AI Start-Ups

4.2. Market Challenges

4.2.1. Supply Shortfall: Meeting Market Demand Challenges

4.3. AI Universities in Key Countries

4.4. Government Initiatives

4.5. R&D Investments

4.6. Forecast and Recommendations


5.1. Introduction

5.2. 25 - 40 Years

5.3. 40 - 50 Years

5.4. 50 - 60 Years

5.5. >60 Years


6.1. Introduction

6.2. Male

6.3. Female


7.1. Introduction

7.2. Natural Language Processing (NLP)

7.3. Computer Vision

7.4. Machine Learning Applications

7.5. Robotics

7.6. Others


8.1. Introduction

8.2. Americas

8.2.1. USA

8.2.2. Others

8.3. Europe, Middle East and Africa

8.3.1. Germany 

8.3.2. UK

8.3.3. Others

8.4. Asia Pacific

8.4.1. China

8.4.2. Japan

8.4.3. Others


9.1. List of Major AI Companies 

9.2. List of Major Universities and Schools

9.3. Key Developments and Investments

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