Artificial Intelligence As A Service Market Size and Share
Artificial Intelligence As A Service Market Analysis by Mordor Intelligence
The Artificial Intelligence As A Service Market size is estimated at USD 20.64 billion in 2025, and is expected to reach USD 98.82 billion by 2030, at a CAGR of 36.78% during the forecast period (2025-2030).
Rapid migration from pilot projects to production workloads fuels this rise as enterprises embed generative-AI APIs in customer-facing and back-office systems. Subscription pricing lowers entry costs for small firms, while custom AI accelerators cut inference expenses by up to 80%, widening margins for providers. Government stimulus packages, such as Japan’s USD 65 billion AI plan, add momentum, and hyperscale data-center build-outs keep compute capacity expanding despite near-term power constraints. Together, these forces push the Artificial Intelligence as a Service market toward broad, cross-industry penetration.
Key Report Takeaways
- By deployment model, public cloud held 78% revenue share in 2024; hybrid cloud is projected to expand at a 32.1% CAGR to 2030.
- By service type, machine-learning platform services commanded 42% of the Artificial Intelligence as a Service market share in 2024, while AI infrastructure services are advancing at a 44.5% CAGR through 2030.
- By organization size, large enterprises led with a 59% share in 2024, but the SME segment is on track for a 36.8% CAGR between 2025-2030.
- By end-user industry, BFSI accounted for 23% of the Artificial Intelligence as a Service market size in 2024, whereas healthcare and life-sciences are growing fastest at 28.4% CAGR to 2030.
- By geography, North America captured a 38% share in 2024; Asia-Pacific is accelerating at a 27.9% CAGR through 2030.
- Amazon Web Services, Microsoft, and Google collectively controlled about 65% of global revenue in 2024, underscoring the sector’s moderate concentration.
Global Artificial Intelligence As A Service Market Trends and Insights
Drivers Impact Analysis
Driver | (~) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
---|---|---|---|
Growing demand for predictive & prescriptive analytics | +8.20% | Global, concentration in North America & Europe | Medium term (2-4 years) |
Subscription-based AI tools lowering TCO for SMEs | +6.80% | Global, strongest in APAC & emerging markets | Short term (≤ 2 years) |
Custom AI accelerators slashing inference cost | +9.10% | North America & APAC core, spill-over to Europe | Medium term (2-4 years) |
Verticalised AIaaS bundles for regulated sectors | +4.70% | North America & EU, expanding to APAC hubs | Long term (≥ 4 years) |
Source: Mordor Intelligence
Growing Demand for Predictive & Prescriptive Analytics
Enterprises now prize foresight over hindsight. Manufacturers using AI-driven analytics posted 61% revenue premiums, while supply-chain optimization shaved 15% off logistics costs. [2]IBM Institute, “AI-Driven Supply Chain Optimization,” IBM, ibm.com Healthcare systems gained 451% ROI over five years by automating radiology workflows. Banks boosted fraud-detection accuracy and see USD 170 billion additional profits by 2028 through AI forecasting. Real-time data ingestion plus agentic AI systems sustain this momentum, positioning predictive analytics as a core growth engine for the Artificial Intelligence as a Service market.
Subscription-Based AI Tools Lowering TCO for SMEs
Low-commitment pricing dismantles historic entry barriers. Global SME adoption of generative-AI tools reached 18%. [1]OECD Analysts, “SME Adoption of Generative AI,” OECD, oecd.org In the United States, AI usage among firms with four workers rose from 4.6% to 5.8% in a single year. Retailers illustrate practical returns: Target deployed AI employee-assistance tools across 400 stores to raise productivity without large capital outlays. By turning AI from capex to opex, subscription platforms broaden the Artificial Intelligence as a Service market across micro-enterprise segments.
Custom AI Accelerators Slashing Inference Cost
Provider economics hinge on silicon. Google’s TPUs deliver inference at roughly 20% of the GPU cost base, equating to a 4-6x advantage. Amazon’s Trainium and Google’s new Ironwood inference chip, launched in 2025, intensify price competition. Analysts expect custom devices to lift their slice of the USD 334 billion accelerator space from 10% to 15% by 2030. These savings empower vendors to cut prices yet protect margins, accelerating adoption for inference-heavy tasks and propelling the Artificial Intelligence as a Service market.
Verticalised AIaaS Bundles for Regulated Sectors
Regulation breeds specialization. HIPAA-ready healthcare stacks require encrypted storage and Business Associate Agreements, pushing vendors to craft compliant bundles. Financial institutions face model-risk rules that favor turnkey, audit-capable solutions. Utilities see 82% of operators embedding AI for grid safety and cyber-threat detection. Domain-tuned offerings thus deepen penetration in compliance-intensive fields, anchoring long-run expansion of the Artificial Intelligence as a Service market.
Restraints Impact Analysis
Restraint | (~) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
---|---|---|---|
Escalating cloud-compute cost inflation | −4.3% | Global, acute in North America & Europe | Short term (≤ 2 years) |
Persistent MLOps talent shortage | −3.1% | Global, severe in APAC & emerging markets | Medium term (2-4 years) |
Source: Mordor Intelligence
Escalating Cloud-Compute Cost Inflation
AI workloads strain infrastructure economics. Data centers may draw 9% of the United States' electricity by 2030. AI energy needs are set to top Bitcoin mining in 2025, reaching 23 GW. Forty-seven percent of Fortune 2000 firms now develop generative AI on-premises to tame runaway bills. Rising power prices plus tight chip supply lower near-term affordability and clip growth in the Artificial Intelligence as a Service market.
Persistent MLOps Talent Shortage
Skills gaps delay deployment. Sixty-one percent of UAE employees feel under-trained for AI tools despite heavy regional spending. Only one-quarter of manufacturers report full C-suite backing for generative-AI programs. The G7 notes that micro-firms lack in-house expertise, calling for policy support. Short supply of data engineers, model validators, and governance specialists inflates project costs, tempering near-medium term expansion of the Artificial Intelligence as a Service market.
Segment Analysis
By Deployment Model: Hybrid Cloud Gains Momentum
Public-cloud delivery retained 78% share in 2024, ensuring the Artificial Intelligence as a Service market remains anchored to hyperscale infrastructure. Hybrid cloud, however, is the clear growth engine, registering a 32.1% CAGR for 2025-2030 as boards demand tighter cost control and regulators press for data residency safeguards. Many Fortune 2000 firms now train large models in the cloud yet run inference on-premises, balancing scale with sovereignty.
Hybrid uptake redirects procurement. Hospitals adopt cloud-burst architectures to keep personally identifiable health data within local servers while exploiting elastic compute for model training, meeting HIPAA rules without losing time-to-value. Manufacturers mirror this pattern, reserving edge nodes for latency-sensitive vision tasks while pushing bulk analytics to regional cloud zones. The twin priorities of compliance and budget certainty thus keep hybrid models central to the Artificial Intelligence as a Service market outlook.
Note: Segment shares of all individual segments available upon report purchase
By Service Type: Infrastructure Services Accelerate
Machine-learning platforms supplied 42% of 2024 revenue, but AI infrastructure services are growing faster at 44.5% CAGR. This shift places compute-optimized clusters and networking fabrics at the heart of the Artificial Intelligence as a Service market size expansion for backbone workloads. Custom chip adoption underpins the trend: Google’s TPUs and Amazon’s Trainium deliver multi-fold price-performance gains, prompting clients to favor providers offering such silicon.
Software layers evolve in lockstep. Managed distribution bundles now pair optimized kernels with orchestration tooling to ease multi-cloud scaling. Vendors embed self-healing functions, automated patching, and performance dashboards to shrink operational toil. Together, these enhancements tighten the nexus between raw infrastructure and developer productivity, reinforcing the revenue trajectory in this segment of the Artificial Intelligence as a Service market.
By Organization Size: SME Adoption Accelerates
Large enterprises controlled 59% of spending in 2024, yet SMEs post a 36.8% CAGR, signalling deep democratization. Subscription AI suites, pre-configured templates, and low-code builders cut learning curves and capex, allowing small teams to unlock use-cases such as demand forecasting or automated support. The US Census Bureau recorded rising AI uptake among sub-five-employee firms, an early proof point of scale beyond the Fortune rankings.
SME priorities differ. Leaders focus on cashflow efficiency, targeting quick-hit wins like invoice reconciliation or lead-scoring. Vendors respond with seat-based licensing, modular functionality, and canned governance policies. These traits align with smaller budgets and limited IT staff, widening the Artificial Intelligence as a Service market addressable pool without eroding service quality.
By End-User Industry: Healthcare Leads Growth
BFSI retained the revenue crown at 23% in 2024, underpinned by fraud detection and robo-advice rollouts. Healthcare and life-sciences, however, expand at 28.4% CAGR as diagnostic imaging, clinical documentation, and drug-discovery workloads migrate to managed AI stacks. Providence Health System cut physician messages by 30% by automating triage responses.
Retailers tap AI for dynamic merchandising and fulfillment routing, while telecom operators improve network fault prediction. Manufacturing saw 93% of firms start new AI projects with productivity gains approaching USD 1.1 trillion. Each use case feeds demand for vertical modules that simplify compliance and domain adaptation, further enlarging the Artificial Intelligence as a Service market.
Geography Analysis
North America held 38% of global revenue in 2024, buoyed by an installed base of hyperscale data centers and a deep startup ecosystem. Cloud majors pledged more than USD 250 billion in fresh capacity during 2025, yet grid constraints loom as US data-center power draw may hit 9% of national supply by 2030. FTC probes into cloud-AI pacts could also recalibrate competitive boundaries.
Asia-Pacific charts the fastest ascent with a 27.9% CAGR. Japan earmarked USD 65 billion for AI and chips, and SoftBank invested USD 960 million in a generative-AI backbone.[3]Nikkei Asia Reporters, “Japan’s USD 65 Billion AI Push,” Nikkei Asia, nikkei.com China’s Alibaba allocated 380 billion yuan to cloud model services, while ByteDance’s Volcano Engine processed nearly half of the country’s public model calls. Corporate surveys show 54% of APAC firms now target long-term AI payouts, signalling depth beyond pilot activity.
Europe grows steadily, balancing innovation with strict oversight under draft AI regulations. The Middle East and Africa ride sovereign-AI strategies: the UAE expects USD 46.33 billion in sector value by 2030 as Microsoft injects USD 1.5 billion into G42. Saudi Arabia’s USD 100 billion AI fund underscores regional ambition, and 75% of GCC enterprises deploy generative models, eclipsing global averages. Access to affordable energy and proactive policy frameworks position the region as a bridge market linking Europe, Africa, and South-Asia for Artificial Intelligence as a Service market rollouts.

Competitive Landscape
The Artificial Intelligence as a Service market shows moderate consolidation, with Amazon Web Services, Microsoft Azure, and Google Cloud holding 32%, 23%, and 10% shares, respectively. Competitive pressure intensifies as OpenAI splits workloads across multiple clouds, signing an unprecedented multiyear pact with Google Cloud. CMA clearance of Microsoft’s USD 13 billion OpenAI stake reduces regulatory uncertainty in the United Kingdom.
Emerging challengers capture white-space. CoreWeave secured a USD 11.9 billion, five-year contract to host OpenAI services and projects 700% revenue growth for 2024. Nebius Group, backed by billion-dollar funding, readies custom accelerators to rival incumbent silicon roadmaps. Partnerships also blur lines: Oracle and Microsoft now federate infrastructure to extend Azure AI capacity on OCI hardware.
Vertical specialization and edge deployment add new fronts. Startups focus on HIPAA-secure imaging or low-latency financial tick stream inference, delivering a differentiated experience unmatched by general platforms. Energy constraints and sovereignty mandates further splinter demand, encouraging regional clouds in the Middle East or EU to pitch tailored compliance guarantees. Such forces keep the Artificial Intelligence as a Service market dynamic despite big-tech scale advantages.
Artificial Intelligence As A Service Industry Leaders
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Microsoft Corporation
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Google LLC
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Amazon Web Services, Inc.
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IBM Corporation
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BigML Inc
- *Disclaimer: Major Players sorted in no particular order

Recent Industry Developments
- June 2025: OpenAI finalized a multiyear cloud agreement with Google Cloud to diversify compute beyond Microsoft
- May 2025: Microsoft added xAI’s Grok 3 models to Azure to broaden AI choices for enterprise clients.
- April 2025: Google unveiled its Ironwood TPU for inference clusters up to 9,216 chips.
- March 2025: CoreWeave sealed a USD 11.9 billion, five-year hosting deal with OpenAI as part of a broader financing round.
Global Artificial Intelligence As A Service Market Report Scope
Artificial Intelligence-as-a-Service (AIaaS) accounts for a third-party offering to outsource artificial intelligence. It allows companies or end-users to experiment with AI for various purposes by limiting initial investment and lowering risk.
The artificial intelligence-as-a-service (AIaaS) market is segmented by type of cloud (public, private, hybrid), by organization size (small and medium enterprises, large enterprises), by end-user industry (BFSI, retail, healthcare, IT and telecommunications, manufacturing, energy), and by geography (North America, Europe, Asia-Pacific, Latin America, the Middle East, and Africa). The market sizes and forecasts are provided in terms of value in USD for all the above segments.
By Deployment Model | Public Cloud | |||
Private Cloud | ||||
Hybrid Cloud | ||||
By Service Type | Machine-Learning Platform Services | |||
Cognitive Services (NLP, CV, Speech) | ||||
AI Infrastructure Services (GPU/TPU) | ||||
ManagedandProfessional AI Services | ||||
By Organisation Size | SmallandMedium Enterprises | |||
Large Enterprises | ||||
By End-user Industry | BFSI | |||
RetailandE-commerce | ||||
HealthcareandLife Sciences | ||||
ITandTelecom | ||||
Manufacturing | ||||
EnergyandUtilities | ||||
Others (Media, Agriculture, Public) | ||||
By Geography | North America | United States | ||
Canada | ||||
Mexico | ||||
South America | Brazil | |||
Argentina | ||||
Rest of South America | ||||
Europe | Germany | |||
United Kingdom | ||||
France | ||||
Italy | ||||
Spain | ||||
Russia | ||||
Rest of Europe | ||||
Asia-Pacific | China | |||
Japan | ||||
India | ||||
South Korea | ||||
AustraliaandNew Zealand | ||||
South-East Asia | ||||
Middle EastandAfrica | Middle East | GCC (Saudi Arabia, UAE, Qatar) | ||
Turkey | ||||
Rest of Middle East | ||||
Africa | South Africa | |||
Nigeria | ||||
Rest of Africa |
Public Cloud |
Private Cloud |
Hybrid Cloud |
Machine-Learning Platform Services |
Cognitive Services (NLP, CV, Speech) |
AI Infrastructure Services (GPU/TPU) |
ManagedandProfessional AI Services |
SmallandMedium Enterprises |
Large Enterprises |
BFSI |
RetailandE-commerce |
HealthcareandLife Sciences |
ITandTelecom |
Manufacturing |
EnergyandUtilities |
Others (Media, Agriculture, Public) |
North America | United States | ||
Canada | |||
Mexico | |||
South America | Brazil | ||
Argentina | |||
Rest of South America | |||
Europe | Germany | ||
United Kingdom | |||
France | |||
Italy | |||
Spain | |||
Russia | |||
Rest of Europe | |||
Asia-Pacific | China | ||
Japan | |||
India | |||
South Korea | |||
AustraliaandNew Zealand | |||
South-East Asia | |||
Middle EastandAfrica | Middle East | GCC (Saudi Arabia, UAE, Qatar) | |
Turkey | |||
Rest of Middle East | |||
Africa | South Africa | ||
Nigeria | |||
Rest of Africa |
Key Questions Answered in the Report
What is the current market size of the Artificial Intelligence as a Service market?
The Artificial Intelligence as a Service market size reached USD 20.64 billion in 2025 and is forecast to hit USD 98.82 billion by 2030, implying a 36.78% CAGR.
Which deployment model is growing fastest in this market?
Hybrid cloud is the fastest-growing deployment model, projected to post a 32.1% CAGR between 2025-2030 as firms balance cost, control, and compliance.
Why are custom AI accelerators important for service providers?
Custom chips such as Google’s TPUs lower inference costs by up to 80%, allowing providers to cut prices without compressing margins and thus stimulate wider adoption.
Which end-user industry is expected to grow most rapidly?
Healthcare and life-sciences leads with a 28.4% CAGR thanks to diagnostic automation, clinical documentation, and drug-discovery applications.
What are the main restraints that could slow market growth?
Rising cloud-compute costs and shortages of skilled MLOps personnel are the top two near-to-medium term constraints on sector expansion.
How are small and medium enterprises benefiting from AIaaS?
Subscription-based platforms and low-code tools reduce upfront costs and skills barriers, driving a 36.8% CAGR for SME spending on AI services through 2030.
Page last updated on: July 8, 2025