Dublin, March 14, 2025 (GLOBE NEWSWIRE) — The “Artificial Intelligence Engineering – Global Strategic Business Report” report has been added to ResearchAndMarkets.com’s offering.
The global market for Artificial Intelligence Engineering was valued at US$15.7 Billion in 2024 and is projected to reach US$87.5 Billion by 2030, growing at a CAGR of 33.1% from 2024 to 2030. This comprehensive report provides an in-depth analysis of market trends, drivers, and forecasts, helping you make informed business decisions.
Artificial Intelligence (AI) engineering is revolutionizing technology development by providing a structured approach to building and deploying AI systems at scale. Traditional AI implementations often struggle with issues such as scalability, reliability, and integration. AI engineering addresses these challenges by combining software engineering principles with AI-specific techniques, ensuring the creation of robust, scalable, and efficient systems. This approach facilitates the seamless integration of AI into existing business processes and technology ecosystems.
AI engineering focuses on automating the lifecycle of AI systems, from data preparation and model development to deployment and monitoring. Tools like MLOps (Machine Learning Operations) and AIOps (Artificial Intelligence Operations) streamline workflows, enabling teams to manage complex AI projects with greater efficiency. Furthermore, AI engineering practices prioritize explainability and transparency, ensuring that AI models are not only effective but also interpretable and aligned with ethical standards. These innovations are positioning AI engineering as the backbone of advanced technology development.
What’s Driving the Growth of the AI Engineering Market?
The growth in the Artificial Intelligence Engineering market is driven by several transformative factors, reflecting its increasing importance in modern technology ecosystems. The rapid adoption of AI technologies, combined with the growing need for scalable and reliable AI systems, is fueling demand for AI engineering practices. Organizations are investing heavily in AI engineering to ensure their AI initiatives are resilient, efficient, and aligned with business objectives.
Consumer expectations for intelligent and adaptive technologies are pushing companies to adopt AI engineering as a means of delivering innovative solutions at scale. Additionally, the rise of edge computing and IoT devices is generating unprecedented volumes of data, requiring sophisticated AI engineering frameworks to process and analyze it effectively.
Regulatory pressures for transparency, data privacy, and ethical AI practices are further encouraging the adoption of AI engineering, as organizations strive to meet compliance standards while maintaining high performance. These factors, along with advancements in automation and AI lifecycle management tools, are driving the exponential growth of the market, establishing AI engineering as a critical component of digital transformation strategies worldwide.
What Drives the Adoption of AI Engineering Across Industries?
The growing demand for scalable and reliable AI solutions is a significant driver of AI engineering adoption across industries. Businesses are increasingly recognizing the need for a systematic approach to implementing AI systems that can handle large-scale data and deliver consistent results. AI engineering addresses this demand by providing frameworks and methodologies that ensure the stability and scalability of AI-powered solutions. This is particularly valuable in industries like finance, healthcare, and manufacturing, where system reliability and performance are critical.
Additionally, the rapid advancement of AI technologies, such as natural language processing, computer vision, and generative AI, is driving the need for specialized engineering practices. These technologies require rigorous workflows for development, testing, and deployment, which AI engineering provides. The increasing emphasis on data privacy, security, and compliance is also fueling demand for AI engineering, as organizations seek to build AI systems that adhere to regulatory requirements while maintaining high performance. These factors are encouraging widespread adoption of AI engineering as a foundational practice for modern enterprises.
Can AI Engineering Enable Smarter Business Operations?
AI engineering is enabling smarter business operations by optimizing processes, enhancing decision-making, and driving innovation. By implementing AI systems that are designed for scalability and reliability, organizations can leverage real-time data insights to make informed decisions quickly and effectively. AI engineering practices ensure that these systems remain adaptable, enabling businesses to respond to changing market conditions and consumer demands with agility.
In addition to improving operational efficiency, AI engineering is fostering innovation across industries. By integrating advanced AI capabilities into products and services, companies can differentiate themselves in competitive markets. For example, AI-engineered solutions in retail enhance supply chain operations and personalize customer experiences, while in healthcare, they optimize diagnostic workflows and improve patient care. The ability to deploy AI systems seamlessly and maintain them efficiently ensures that organizations can unlock the full potential of AI, driving smarter operations and sustained growth.
Report Features:
- Comprehensive Market Data: Independent analysis of annual sales and market forecasts in US$ Million from 2024 to 2030.
- In-Depth Regional Analysis: Detailed insights into key markets, including the U.S., China, Japan, Canada, Europe, Asia-Pacific, Latin America, Middle East, and Africa.
- Company Profiles: Coverage of players such as Amazon Web Services, Inc., HTEC Group Inc., IBM Corporation, Intel Corporation, NVIDIA Corporation and more.
- Complimentary Updates: Receive free report updates for one year to keep you informed of the latest market developments.
Key Insights:
- Market Growth: Understand the significant growth trajectory of the AI Engineering Hardware segment, which is expected to reach US$24.1 Billion by 2030 with a CAGR of a 29.3%. The AI Engineering Software segment is also set to grow at 32.8% CAGR over the analysis period.
- Regional Analysis: Gain insights into the U.S. market, valued at $4.1 Billion in 2024, and China, forecasted to grow at an impressive 31.6% CAGR to reach $13.3 Billion by 2030. Discover growth trends in other key regions, including Japan, Canada, Germany, and the Asia-Pacific.
Segments
- Component (Hardware Component, Software Component, Services Component)
- Technology (Machine Learning Technology, Deep Learning Technology, Natural Language Processing (NLP) Technology, Computer Vision Technology)
- End-Use (IT & Telecom End-Use, BFSI End-Use, Retail End-Use, Manufacturing End-Use, Healthcare End-Use, Other End-Uses)
Key Attributes:
| Report Attribute | Details |
| No. of Pages | 162 |
| Forecast Period | 2024 – 2030 |
| Estimated Market Value (USD) in 2024 | $15.7 Billion |
| Forecasted Market Value (USD) by 2030 | $87.5 Billion |
| Compound Annual Growth Rate | 33.1% |
| Regions Covered | Global |
Key Topics Covered:
MARKET OVERVIEW
- Influencer Market Insights
- World Market Trajectories
- Economic Frontiers: Trends, Trials & Transformations
- Artificial Intelligence Engineering – Global Key Competitors Percentage Market Share in 2025 (E)
- Competitive Market Presence – Strong/Active/Niche/Trivial for Players Worldwide in 2025 (E)
MARKET TRENDS & DRIVERS
- Demand for AI-Driven Software Development Accelerates Adoption of Engineering Practices
- Focus on MLOps Strengthens Business Case for Continuous AI Model Optimization
- Rising Adoption of Cloud-Native AI Engineering Sets the Stage for Market Expansion
- Edge AI Engineering Drives Adoption in Latency-Sensitive Applications
- AI Engineering Bodes Well for Market Growth Amid Increased Need for AI Governance
- Growing Complexity in AI Workflows Highlights the Case for AI Engineering Automation
- AI Engineering Solutions Amplify Productivity in Multi-Cloud AI Deployments
- AI Engineering Expands Opportunities for Real-Time Analytics and Decision Making
- Integration of AI and DevOps (AIOps) Sets the Stage for Market Growth
- AI Engineering for Automated Testing Bodes Well for Improving Model Accuracy
- Emerging Need for Explainable AI Strengthens Market for Transparent AI Engineering
FOCUS ON SELECT PLAYERS:Some of the 22 companies featured in this Artificial Intelligence Engineering market report include:
- Amazon Web Services, Inc.
- HTEC Group Inc.
- IBM Corporation
- Intel Corporation
- NVIDIA Corporation
- Oracle Corporation
- Orient Software Development Corp.
- QuEST Global Services Pte. Ltd.
- Siemens AG
- Tenup Software Services
For more information about this report visit https://www.researchandmarkets.com/r/d6ju97
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- Artificial Intelligence Engineering Market
