An AI development company is a firm that designs, builds, integrates and operates artificial-intelligence systems for other organisations, from data preparation and model training to the deployment of generative and agentic applications inside business processes. Large IT services firms now describe much of their work in these terms: Accenture's annual report groups generative, agentic and physical AI under the heading "advanced AI" and describes a US$3.0 billion three-year investment to build those capabilities.
This list covers twelve publicly traded companies that sell AI development and implementation services, ordered by total revenue in their latest fiscal year as filed with the US Securities and Exchange Commission. Because the figures come from audited annual reports, they are comparable and verifiable; they measure each company's overall scale, not AI revenue alone.
Contents
- Types of AI development company
- Methodology
- The list
- Comparison table
- Limitations of a revenue ranking
- Frequently asked questions
- See also
Types of AI development company
Firms that build AI for clients fall into several groups. Global consultancies and IT service providers, such as Accenture, IBM, Cognizant and Infosys, combine strategy, systems integration and managed services, and increasingly package AI platforms of their own, such as Infosys Topaz. Engineering-led firms such as EPAM, Globant and Grid Dynamics focus on software and platform engineering, now organised around AI-native delivery models. Process and analytics specialists such as Genpact and EXL apply AI to operations in industries like insurance and banking. A further group serves model builders or governments directly: Innodata prepares training and evaluation data for frontier model developers, and Booz Allen Hamilton and BigBear.ai build AI systems for defence and national-security agencies.
Methodology
Companies were included if they sell AI design, development, integration or data services to other organisations, describe AI as a core part of their offering in their latest annual report, are listed on a US exchange and report revenue in US dollars to the SEC. Firms that report in other currencies (for example Wipro in Indian rupees or Endava in pounds sterling) and privately held firms that do not publish audited accounts were excluded so that every figure is directly comparable.
Entries are ordered strictly by total revenue for each company's most recent fiscal year with an annual report on file in November 2026, as stated in its Form 10-K or Form 20-F. Fiscal years end on different dates, noted for each entry. Revenue covers each company's entire business, including non-AI services and, for IBM, software and infrastructure; it is a measure of scale and delivery capacity, not of AI revenue or quality.
The list
1
A
Largest listed professional services firm, with AI and Data as a core engine
Best for: Global enterprise AI programmes spanning strategy to operations
Accenture plc, incorporated in Ireland with principal executive offices in Dublin, reported revenue of US$74.2 billion for the fiscal year ended 31 August 2026 and employed about 814,000 people. Its 2026 annual report names AI and Data as one of three internal "Reinvention Engines", responsible for building AI skills, incubating frontier AI partnerships and developing AI platforms that clients use to scale their AI investments. The company states that a US$3.0 billion, three-year AI investment positioned it to capture client spending on AI, and that it expects to invest at least US$1.0 billion over five years in AI safety. Revenue comes mainly from Forbes Global 2000 companies and government agencies.
- Revenue (FY2026, to 31 Aug 2026)
- US$74.2bn
- Employees
- About 814,000 (Aug 2026)
- Principal offices
- Dublin, Ireland
- Listing
- NYSE: ACN
Strengths
- Very large delivery capacity across 52 countries
- Dedicated AI safety advisory and investment programme
Limitations
- Scale and pricing are geared to large enterprises and governments
- Revenue figure covers all consulting and outsourcing, not AI alone
2
Hybrid cloud and AI vendor with a consulting arm that implements AI
Best for: Organisations wanting AI software and implementation from one supplier
International Business Machines, headquartered in Armonk, New York, reported total revenue of US$67.5 billion for 2025. Unlike the other companies in this list, IBM sells AI software and infrastructure as well as services: its annual report describes hybrid cloud and AI platforms that let clients carry out AI transformations across their applications and data, and a Consulting segment that combines strategy, experience design, technology and operations expertise to deliver transformation programmes. IBM states that it competes with hundreds of companies worldwide as it pursues its hybrid cloud and AI strategy. The total revenue figure includes software and infrastructure sales, so it overstates the size of the services business relative to pure-play consultancies.
- Revenue (FY2025)
- US$67.5bn (all segments)
- Headquarters
- Armonk, New York, US
- Listing
- NYSE: IBM
Strengths
- Owns its AI platforms as well as providing implementation services
- Long record in regulated industries
Limitations
- Consulting recommendations may favour IBM's own software
- Revenue includes non-services segments, limiting like-for-like comparison
3
IT services firm positioning itself as an "AI builder"
Best for: Large enterprises in healthcare, financial services and retail
Cognizant Technology Solutions, headquartered in Teaneck, New Jersey, reported 2025 revenue of US$21.1 billion and ended the year with about 351,600 employees, up from 336,800 a year earlier. Its 2025 annual report describes the company as an "AI builder" that combines industry knowledge with knowledge of clients' organisations to build industry-specific platforms and to embed context into systems, AI models and custom solutions. It helps clients implement and operate AI with integration, governance, security and monitoring controls, using intellectual property developed in its AI Lab. Cognizant also builds and runs global capability centres for clients.
- Revenue (FY2025)
- US$21.1bn
- Employees
- About 351,600 (Dec 2025)
- Headquarters
- Teaneck, New Jersey, US
- Listing
- Nasdaq: CTSH
Strengths
- Combines AI implementation with governance and monitoring services
- Offers to build and operate client capability centres
Limitations
- Annual report itself flags disruption risk from AI-native competitors
- Large-account focus
4
Bengaluru-based IT services firm with the Infosys Topaz AI suite
Best for: Large-scale AI-enabled modernisation with offshore delivery
Infosys Limited, with principal executive offices in Bengaluru, India, reported revenue of US$20.2 billion for the fiscal year ended 31 March 2026, up from US$19.3 billion a year earlier. It had 328,594 employees at that date, of whom 310,887 worked in service delivery. Its AI offering is built around Infosys Topaz, which the company describes as its generative and agentic AI suite, and an "AI first" value framework intended to help enterprises deploy AI at scale. The 20-F cites market estimates of a US$300–400 billion AI services opportunity by 2030.
- Revenue (FY2026, to 31 Mar 2026)
- US$20.2bn
- Employees
- 328,594 (Mar 2026)
- Principal offices
- Bengaluru, India
- Listing
- NYSE: INFY (ADS)
Strengths
- Packaged AI suite (Topaz) alongside services
- Large delivery workforce with offshore cost base
Limitations
- Revenue growth of about 4.6% in fiscal 2026 was modest
- Market-size claims in its filing rely on third-party estimates
5
US government contractor describing itself as the largest federal AI provider
Best for: US federal, defence and intelligence AI programmes
Booz Allen Hamilton, headquartered in McLean, Virginia, reported revenue of US$11.2 billion for the fiscal year ended 31 March 2026, down from US$12.0 billion the previous year, and employed about 31,500 people. Its annual report describes it as the federal government's largest AI provider, with about 400 active AI projects, building secure AI systems including agentic AI, physical AI and AI for radio access networks for mission-critical environments. Most of its work is for US defence, intelligence and civilian agencies. The company plans to move its headquarters to Reston, Virginia, in autumn 2027.
- Revenue (FY2026, to 31 Mar 2026)
- US$11.2bn
- Employees
- About 31,500 (Mar 2026)
- Headquarters
- McLean, Virginia, US
- Listing
- NYSE: BAH
Strengths
- Cleared workforce and experience with classified environments
- Large active AI project portfolio in government
Limitations
- Revenue fell in fiscal 2026
- Concentrated on US government clients
6
Software engineering firm focused on AI-native transformation
Best for: Complex custom software and AI engineering
EPAM Systems, headquartered in Newtown, Pennsylvania, traces its origins to a predecessor founded in 1993. It reported 2025 revenue of US$5.46 billion and had about 62,850 employees at year end, of whom about 56,600 were delivery professionals. The annual report states that its strategy is increasingly focused on end-to-end "AI-native" transformations and describes the ability to move clients from AI experimentation to production as a differentiator. EPAM expanded in Latin America and Spain through the acquisition of NEORIS, a consultancy with about 4,800 professionals, and continued to grow its delivery base in India.
- Revenue (FY2025)
- US$5.46bn
- Employees
- About 62,850 (Dec 2025)
- Headquarters
- Newtown, Pennsylvania, US
- Listing
- NYSE: EPAM
Strengths
- Engineering-heavy workforce suited to building custom systems
- Nearshore delivery in Latin America after the NEORIS acquisition
Limitations
- Significant delivery presence in Ukraine carries operational risk
- Less strategy-consulting depth than the largest firms
7
Process-intelligence firm describing itself as agentic and advanced technology
Best for: Applying AI agents to finance, accounting and back-office operations
Genpact reported 2025 revenue of US$5.08 billion and had more than 146,500 employees working in over 35 countries. Its annual report describes it as "an agentic and advanced technology solutions company" built on industry knowledge and process intelligence. Genpact argues that its experience running clients' business processes, such as finance and accounting, gives it the operational detail needed to deliver AI and agentic solutions for the "last mile" of execution, where general-purpose AI tools often stall.
- Revenue (FY2025)
- US$5.08bn
- Employees
- More than 146,500 (Dec 2025)
- Listing
- NYSE: G
Strengths
- Deep process data from operating clients' back offices
- Combines AI deployment with managed operations
Limitations
- Less suited to green-field product engineering
- AI positioning is recent relative to its outsourcing heritage
8
Latin American-founded digital engineering firm selling AI Pods by subscription
Best for: Digital product and AI engineering on subscription terms
Globant S.A., incorporated in Luxembourg, was founded in 2003 by Martín Migoya, Guibert Englebienne, Martín Umaran and Néstor Nocetti. It reported 2025 revenue of US$2.45 billion and had 28,773 employees in 31 countries at year end. In 2025 it introduced AI Pods powered by its Globant Enterprise AI platform, giving clients access to agentic AI capabilities, and a subscription-based pricing model for AI-powered engineering, product definition, design and testing services. It also opened a Middle East regional headquarters in Riyadh.
- Revenue (FY2025)
- US$2.45bn
- Employees
- 28,773 (Dec 2025)
- Founded
- 2003
- Listing
- NYSE: GLOB
Strengths
- Subscription pricing for AI-delivered services rather than time and materials
- Own enterprise AI platform
Limitations
- Revenue growth was under 2% in 2025
- Smaller scale than the global integrators
9
Data and AI services firm for insurance, healthcare and banking
Best for: Insurers and healthcare payers applying AI to data-heavy operations
ExlService Holdings (EXL), founded in 1999 and headquartered in New York, reported 2025 revenue of US$2.09 billion and has more than 65,000 employees. The company describes its aim as being an indispensable partner for data- and AI-led transformation, and in early 2025 restructured its reporting so that data and AI-led services form one of its two main service lines alongside digital operations. Its clients are concentrated in insurance, healthcare and life sciences, banking and capital markets, and retail.
- Revenue (FY2025)
- US$2.09bn
- Employees
- More than 65,000
- Founded
- 1999
- Headquarters
- New York, US
- Listing
- Nasdaq: EXLS
Strengths
- Strong vertical focus in insurance and healthcare
- Reports data and AI services as a distinct line
Limitations
- Narrower industry coverage than generalist integrators
- Less product-engineering capacity
10
Silicon Valley engineering firm built around its GAIN AI-native model
Best for: Retail and technology companies needing platform-scale AI engineering
Grid Dynamics, founded in 2006 and headquartered in San Ramon, California, reported 2025 revenue of US$412 million and had 4,961 personnel across the Americas, Europe and India. Its annual report presents the Grid Dynamics AI-Native (GAIN) engagement model as its strategic foundation, a framework that changes team composition and engineering workflows for software delivery with AI. The company argues that agentic AI systems need distributed, fault-tolerant engineering to run reliably at scale, which it presents as its core skill. Its engineers held more than 1,600 cloud hyperscaler certifications at year end.
- Revenue (FY2025)
- US$412m
- Personnel
- 4,961 (Dec 2025)
- Founded
- 2006
- Headquarters
- San Ramon, California, US
- Listing
- Nasdaq: GDYN
Strengths
- Engineering-centred delivery model designed around AI
- Revenue grew about 17% in 2025
Limitations
- Small relative to global integrators
- Limited consulting and change-management offering
11
Training, evaluation and safety data for frontier AI model builders
Best for: Model developers needing training and evaluation data
Innodata, founded in 1988 and headquartered in Ridgefield Park, New Jersey, reported 2025 revenue of US$251.7 million, up from US$170.5 million in 2024, and employed 10,107 people at year end. Rather than building business applications, it supplies AI lifecycle data services: training and post-training data, alignment and preference optimisation, and capability and safety evaluation. Its 10-K states that its customers include leading AI labs and five of the so-called "Magnificent Seven" technology companies, and that a substantial share of revenue comes from the largest technology companies.
- Revenue (FY2025)
- US$251.7m
- Employees
- 10,107 (Dec 2025)
- Founded
- 1988
- Headquarters
- Ridgefield Park, New Jersey, US
- Listing
- Nasdaq: INOD
Strengths
- Specialised in data for foundation-model training and evaluation
- Revenue grew about 48% in 2025
Limitations
- Revenue concentrated in a few very large technology customers
- Not a general application-development provider
12
AI decision-intelligence provider for defence, intelligence and border security
Best for: Government agencies needing cleared generative AI tooling
BigBear.ai Holdings, with principal executive offices in McLean, Virginia, reported 2025 revenue of US$127.7 million, down from US$158.2 million in 2024, and had 579 employees, most of them in the United States holding security clearances. It develops AI systems for national security, travel and trade, including identity verification and biometrics. On 31 December 2025 it completed the acquisition of Ask Sage, a generative AI platform for defence and intelligence customers that the company describes as the first of its kind to receive FedRAMP authorisation.
- Revenue (FY2025)
- US$127.7m
- Employees
- 579 (Dec 2025)
- Principal offices
- McLean, Virginia, US
- Listing
- NYSE: BBAI
Strengths
- Cleared workforce and FedRAMP-authorised generative AI platform
- Focused offering for defence and border use cases
Limitations
- Revenue declined about 19% in 2025
- Small company with narrow customer base
Limitations of a revenue ranking
Frequently asked questions
What does an AI development company do?
An AI development company designs, builds and deploys AI systems for clients. Work ranges from preparing and labelling training data, through selecting or fine-tuning models, to integrating generative and agentic AI into business software and operating it securely. Large firms such as Accenture and Cognizant combine this with consulting and managed services, while specialists like Innodata focus on data for model training and evaluation.
Which is the largest AI services company?
Among companies that report to the SEC in US dollars, Accenture had the largest revenue, US$74.2 billion for the fiscal year ended 31 August 2026, with about 814,000 employees. IBM reported US$67.5 billion for 2025, but that figure includes software and infrastructure as well as consulting. Neither company discloses a standardised AI-only revenue figure in its annual report.
Who builds AI for the US government?
Booz Allen Hamilton describes itself in its annual report as the federal government's largest AI provider, with about 400 active AI projects. Smaller providers include BigBear.ai, which in December 2025 acquired Ask Sage, a generative AI platform for defence and intelligence users that holds FedRAMP authorisation. Large integrators such as Accenture and IBM also serve government agencies.
How should a company choose an AI development partner?
Buyers typically compare relevant industry experience, the engineering and data skills of the proposed team, security and governance practices, pricing model and the partner's financial stability. Some firms now offer outcome- or subscription-based pricing, such as Globant's subscription model for its AI Pods, while most still bill by time and materials or fixed-price projects.
Are Indian IT companies good at AI development?
Indian-headquartered firms are among the largest AI service providers. Infosys reported US$20.2 billion in revenue for fiscal 2026 and markets its Infosys Topaz generative and agentic AI suite, and Cognizant, though headquartered in New Jersey, has a large Indian workforce. Their scale and offshore delivery suit large modernisation programmes; buyers usually assess specific team experience as for any provider.
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