March 4, 2024

Artificial Intelligence Engineering Market Size, Share, Report by 2033

The global artificial intelligence engineering market size was valued at USD 9.2 billion in 2023 and is expected to touch around USD 229.61 billion by 2033, rising at a CAGR of 38% from 2024 to 2033.

Key Takeaways

  • North America held the largest share of the market in 2023.
  • Asia Pacific is forecasted to be the fastest-growing regional market.
  • By solution, the services segment held the largest market share of the artificial intelligence engineering market.
  • By solution, the software segment is expected to witness significant growth over the forecast period.
  • By technology, the machine learning segment dominated the market in 2023.
  • By technology, the deep learning segment is expected to witness significant growth over the forecast period.
  • By deployment mode, the cloud segment is expected to dominate the market over the forecasted period.
  • By deployment, the on-premise segment is expected to witness significant growth during the forecast period.
  • By vertical, the IT & telecom segment held the largest share of the market in 2023.
  • By vertical, the automotive and transportation segment is expected to witness significant growth during the forecast period.

Artificial intelligence engineering Market Size 2024 To 2033

The Artificial Intelligence (AI) Engineering market is experiencing rapid growth driven by advancements in technology, increasing demand for AI-powered solutions across various industries, and the growing focus on automation and efficiency. AI engineering encompasses the development, deployment, and management of AI systems, including machine learning algorithms, natural language processing, computer vision, and robotics. As businesses seek to leverage AI to gain a competitive edge, the AI engineering market is poised for significant expansion in the coming years.

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Growth Factors:

Several key factors are driving the growth of the AI engineering market. Firstly, the exponential increase in data generation has created vast opportunities for AI applications. Organizations are harnessing AI to analyze large datasets and derive valuable insights for better decision-making. Moreover, the proliferation of cloud computing and edge computing technologies has made AI more accessible and scalable, enabling businesses to deploy AI solutions with greater flexibility and efficiency.

Additionally, the rise of deep learning algorithms and neural networks has significantly enhanced the capabilities of AI systems, allowing for more complex tasks to be automated and optimized. This has led to widespread adoption of AI across industries such as healthcare, finance, retail, manufacturing, and transportation, driving the demand for AI engineering services and solutions.

Furthermore, the emergence of AI-driven technologies like autonomous vehicles, virtual assistants, predictive maintenance systems, and personalized recommendation engines is fueling the growth of the AI engineering market. These technologies are transforming business processes, improving operational efficiency, and delivering enhanced user experiences, driving further investment in AI engineering capabilities.

Artificial Intelligence Engineering Market Scope

Report CoverageDetails
Growth Rate from 2024 to 2033CAGR of 38%
Global Market Size in 2023USD 9.2 Billion
Global Market Size by 2033USD 229.61 Billion
Largest MarketNorth America
Base Year2023
Forecast Period2024 to 2033
Segments CoveredBy Solution, By Technology, By Deployment Mode, and By Vertical
Regions CoveredNorth America, Europe, Asia-Pacific, Latin America, and Middle East & Africa

Artificial Intelligence Engineering Market Dynamics

Drivers:

Several factors are driving the expansion of the AI engineering market. Firstly, increasing investment in research and development by technology companies, government agencies, and academic institutions is driving innovation in AI engineering techniques and algorithms. This investment is leading to the development of more advanced AI solutions capable of addressing complex business challenges.

Moreover, the growing adoption of AI across industries is creating a demand for skilled AI engineers and data scientists. Organizations are investing in talent development and training programs to build internal AI capabilities or partnering with AI engineering firms to access specialized expertise.

Additionally, regulatory support and initiatives aimed at promoting AI innovation and adoption are driving market growth. Governments around the world are introducing policies and funding programs to support AI research, development, and deployment, creating a favorable environment for AI engineering firms to thrive.

Restraints:

Despite the significant growth prospects, the AI engineering market faces several challenges and restraints. One of the primary concerns is the ethical implications of AI technologies, including issues related to data privacy, bias, and accountability. Addressing these ethical concerns requires careful consideration and responsible deployment of AI systems, which may slow down adoption in some industries.

Moreover, the complexity and technical expertise required to develop and deploy AI solutions can act as a barrier to entry for smaller companies and startups. Access to skilled AI engineers, computational resources, and data infrastructure can be costly, limiting the market potential for some organizations.

Additionally, concerns about job displacement and workforce disruption due to automation driven by AI technologies are prevalent. While AI has the potential to enhance productivity and create new job opportunities, it also poses challenges related to job displacement and the need for reskilling and upskilling the workforce to adapt to the changing labor market dynamics.

Opportunities:

Despite the challenges, the AI engineering market presents significant opportunities for growth and innovation. Firstly, the increasing adoption of AI in emerging markets presents untapped opportunities for AI engineering firms to expand their global footprint and cater to diverse industry needs.

Moreover, the convergence of AI with other transformative technologies such as IoT (Internet of Things), blockchain, and 5G connectivity is opening up new avenues for AI-driven innovation. These synergies enable the development of integrated solutions that offer enhanced capabilities and value propositions across industries.

Furthermore, the rise of AI-as-a-Service (AIaaS) models and platforms is democratizing access to AI technologies, allowing organizations of all sizes to leverage AI capabilities without significant upfront investment. This shift towards cloud-based AI solutions is driving market democratization and expanding the addressable market for AI engineering firms.

Additionally, the ongoing development of specialized AI applications and industry-specific solutions is creating niche opportunities for AI engineering firms to differentiate themselves and provide tailored offerings to specific market segments. From healthcare diagnostics to autonomous vehicles and predictive maintenance, AI is reshaping industries and creating new opportunities for innovation and growth.

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Recent Developments

  • In June 2023, Accenture bolstered its engineering capabilities by acquiring Nextira, an AWS Premier Partner. Nextira’s expertise in delivering cloud solutions and predictive analytics, powered by AWS, complements Accenture Cloud First’s offerings, enabling clients to access a broader range of cloud tools and capabilities.
  • In April 2023, Deloitte introduced a new practice focused on Generative AI and Foundation Models to help clients harness AI for increased productivity and innovation. Leveraging top-quality services and industry expertise, Deloitte aims to assist enterprise leaders in developing effective strategies and applications powered by Generative AI.
  • In March 2023, Amazon and IIT Bombay launched the Amazon IIT-Bombay AI-ML Initiative. This initiative, hosted by the IIT Bombay Department of Computer Science and Engineering, aims to advance research and scholarship in AI and ML, with a focus on speech, language, and multimodal AI domains. Through financial support and community events, the initiative seeks to drive innovation in these fields.

Artificial Intelligence Engineering Market Companies

  • Google LLC (United States)
  • IBM Corporation (United States)
  • Amazon Web Services, Inc. (United States)
  • Cisco Systems Inc. (United States)
  • Nvidia Corporation (United States)
  • Microsoft Corporation (United States)
  • Siemens AG (Germany)
  • Oracle Corporation (United States)
  • SAP SE (Germany)
  • Alibaba Cloud (China)

Segments Covered in the Report

By Solution

  • Hardware
  • Software
  • Services

By Technology

  • Deep Learning
  • Machine Learning
  • Natural Language Processing
  • Computer Vision

By Deployment Mode

  • Cloud
  • On-Premises

By Vertical

  • Healthcare
  • Automotive and Transportation
  • Agriculture
  • Information Technology (IT) & telecom
  • Business Management
  • Other End-Users

By Geography

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East and Africa

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