Artificial Intelligence Engineering Market Size & Share 2023 to 2032
Market Size by Solution (Hardware [Graphics Processing Unit, Application Specific Integrated Circuit, Central Processing Unit, Field-Programmable Gate Array)], Software, Services), Technology, End Use, Deployment.
Report ID: GMI5383
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Published Date: October 2022
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Report Format: PDF
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Authors:
Preeti Wadhwani, Aishvarya Ambekar
Artificial Intelligence Engineering Market Size
AI Engineering Market size valued at USD 8 billion in 2022 and is anticipated to grow at around 35% CAGR from 2023 to 2032. The growing focus of market players on eliminating loopholes in AI technology will be a key driver for business expansion.
Support from governments of varied developing countries towards promoting AI technology to strengthen the IT infrastructure has also played a crucial role in supporting industry expansion. Heavy investment to improve public welfare areas, including predictive healthcare, adaptive education, and optimized crisis response, by investing in long-term research projects is propelling the artificial intelligence engineering market. For instance, in June 2022, the government of Canada granted approximately USD 370 million to the country's researchers for AI and computer science research projects.
The rising preference for cloud-based applications will generate lucrative growth opportunities for AI engineering solution provider. Artificial intelligence improves cloud computing in terms of productivity, data management, errors and cost, and security, which has encouraged organizations to adopt AI to automate such routine tasks and functions. As per a survey published in February 2022, 67% large enterprises expedited cloud adoption while 39% medium-sized companies and 38% small companies began their cloud journey.
Artificial Intelligence Engineering Market Analysis
The growing risk of cyberattacks is likely to hamper AI engineering market size. The surging adoption of AI in the government sector and end-user industries have boosted their susceptibility to cyberattacks that can have malicious end goals. This has empowered attackers to corrupt sophisticated and intelligent technology solutions and find loopholes in corporate IT networks. Nevertheless, many developed nations have implemented strict regulations for the integration of artificial intelligence, which is expected to help operators overcome this issue.
The FPGA hardware segment is estimated to expand at above 33.5% growth rate through 2032, on account of the flexibility of FPGAs that enables it to be programmed for various kinds of workloads, from signal processing to deep learning & big data analytics.
The hardware segment captured over 30% of the AI engineering market share in 2022 and is slated to attain tremendous growth in coming years. Consistent efforts by industry players to introduce innovative products may increase segmental revenues.
The machine learning segment held more than 48.5% of the industry revenue share in 2022. The mounting uptake of IoT and M2M-based devices has amplified the demand for machine learning technology. Moreover, IoT connected devices penetration is set to reach 29.4 billion by 2030.
The IT & telecom segment is poised to record nearly 34.5% growth between 2023 and 2032. AI is widely utilized in the telecom industry for predictive maintenance and fraud detection, which is boosting product penetration.
The on-cloud segment is predicted to exhibit 37% growth rate till 2032. The segment growth is attributed to developments in the cloud infrastructure of companies, along with enhanced AI capabilities.
Regionally, the Europe artificial intelligence engineering market is showcase 36.5% gains through 2032. Top automobile players, including Audi, Mercedes, Ford, and others, are investing heavily in autonomous mobility, thereby facilitating the extensive use of AI in the region.
Artificial Intelligence Engineering Market Share
Some of the major key players operating in the AI engineering market include
These companies are majorly focusing on advancing product operational skills and innovating reliable AI services.
Impact of COVID-19 Pandemic
During the COVID-19 pandemic, the industry witnessed a huge surge in demand as AI technology aided public and private companies in managing the crisis. Machine learning technology allowed enterprises to scale up and adjust to the new remote working environment while healthcare and government institutions adopted ML software to enable contactless screening of COVID-19 symptoms. For instance, in May 2020, Clevy.io, a French AI-based technology start-up, launched an AWS chatbot for customers to easily find official government communications regarding the coronavirus. These factors are foreseen to positively influence the demand for AI engineering solutions.
This artificial intelligence (AI) engineering market research report includes in-depth coverage of the industry with estimates & forecast in terms of revenue in USD million from 2018 to 2032 for the following segments:
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Market, By Solution
Market, By Technology
Market, By End-use
Market, By Deployment
The above information has been provided for the following regions and countries:
Research methodology, data sources & validation process
This report draws on a structured research process built around direct industry conversations, proprietary modelling, and rigorous cross-validation and not just desk research.
Our 6-step research process
1. Research design & analyst oversight
At GMI, our research methodology is built on a foundation of human expertise, rigorous validation, and complete transparency. Every insight, trend analysis, and forecast in our reports is developed by experienced analysts who understand the nuances of your market.
Our approach integrates extensive primary research through direct engagement with industry participants and experts, complemented by comprehensive secondary research from verified global sources. We apply quantified impact analysis to deliver dependable forecasts, while maintaining complete traceability from original data sources to final insights.
2. Primary research
Primary research forms the backbone of our methodology, contributing nearly 80% to overall insights. It involves direct engagement with industry participants to ensure accuracy and depth in analysis. Our structured interview program covers regional and global markets, with inputs from C-suite executives, directors, and subject matter experts. These interactions provide strategic, operational, and technical perspectives, enabling well-rounded insights and reliable market forecasts.
3. Data mining & market analysis
Data mining is a key part of our research process, contributing nearly 20% to the overall methodology. It involves analysing market structure, identifying industry trends, and assessing macroeconomic factors through revenue share analysis of major players. Relevant data is collected from both paid and unpaid sources to build a reliable database. This information is then integrated to support primary research and market sizing, with validation from key stakeholders such as distributors, manufacturers, and associations.
4. Market sizing
Our market sizing is built on a bottom-up approach, starting with company revenue data gathered directly through primary interviews, alongside production volume figures from manufacturers and installation or deployment statistics. These inputs are then pieced together across regional markets to arrive at a global estimate that stays grounded in actual industry activity.
5. Forecast model & key assumptions
Every forecast includes explicit documentation of:
✓ Key growth drivers and their assumed impact
✓ Restraining factors and mitigation scenarios
✓ Regulatory assumptions and policy change risk
✓ Technology adoption curve parameter
✓ Macroeconomic assumptions (GDP growth, inflation, currency)
✓ Competitive dynamics and market entry/exit expectations
6. Validation & quality assurance
The final stages involve human validation, where domain experts manually review filtered data to identify nuances and contextual errors that automated systems might miss. This expert review adds a critical layer of quality assurance, ensuring data aligns with research objectives and domain-specific standards.
Our triple-layer validation process ensures maximum data reliability:
✓ Statistical Validation
✓ Expert Validation
✓ Market Reality Check
Trust & credibility
Verified data sources
Trade publications
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Industry databases
Proprietary and third-party market databases
Regulatory filings
Government procurement records and policy documents
Academic research
University studies and specialist institution reports
Company reports
Annual reports, investor presentations, and filings
Expert interviews
C-suite, procurement leads, and technical specialists
GMI archive
13,000+ published studies across 30+ industry verticals
Trade data
Import/export volumes, HS codes, and customs records
Parameters studied & evaluated
Every data point in this report is validated through primary interviews, true bottom-up modelling, and rigorous cross-checks. Read about our research process →