U.S. Enterprises Embed AI Across Application Services

The report gives buyers provider evaluations alongside findings on how enterprises are checking AI-assisted software before release.

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Organizations adopt governed engineering models, predictive support and continuous validation to improve software delivery, ISG Provider Lens^® report says

STAMFORD, Conn.--(BUSINESS WIRE)-- U.S. enterprises are embedding AI throughout application lifecycles while tightening security, traceability and accountability, according to a new research report published today by Information Services Group (ISG) (Nasdaq: III), a global AI-centered technology research and advisory firm.

The 2026 ISG Provider Lens^® AI-Driven ADM Services report for the U.S. finds that AI is reshaping software engineering. It now spans development, testing and operations under coordinated controls. Buyers require measurable gains in productivity, service quality and release confidence together with human oversight and production safeguards.

“AI is shifting U.S. application services from delivery capacity to trusted software intelligence,” said Shafqat Azim, partner, ISG. “Buyers will judge progress by whether each AI-assisted change can be explained, reviewed and linked to business results.”

Application modernization remains a major priority in U.S. organizations as aging software and fragmented architectures impose high maintenance demands. Enterprises are using AI for application discovery, code understanding, reverse engineering and detailed cloud migration planning. They are simultaneously enhancing application support and testing with the help of AI to prevent disruptions within complex environments supporting daily operations. This integrated approach protects regulated workflows, customer-facing channels and critical business processes during multiyear transformation programs.

Strict requirements for operational resilience remain a high priority, increasing demand for observability, AI for IT operations (AIOps), IT service management integration and site reliability engineering across application portfolios. Enterprises use intelligent ticket handling, assisted remediation and continuous optimization to improve application stability, responsiveness and business continuity. For U.S. buyers managing critical systems and services, providers' ability to connect daily support with planned transformation has become an important sourcing consideration.

Quality engineering is evolving from a downstream test factory to a strategic risk-control function as enterprises adapt to cloud-native architectures and AI-generated code. To accelerate application delivery, organizations seek generative AI-based test design, defect prediction, test-data generation and continuous validation throughout development and application operations. Quality control requirements extend to AI itself, with organizations implementing AI model validation, bias testing, explainability, hallucination controls and security checks for intelligent applications before release, ISG says.

“Providers must unite AI, quality and continuity,” said Maharshi Pandya, ISG senior lead analyst and lead author of the report. “Enterprises seek partners that can monitor risks, prove applications are ready for production and measure benefits throughout the software lifecycle with transparent evidence.”

The report also explores other trends in U.S. ADM, including the growing use of platform engineering and agent-assisted development.

For more insights into the ADM challenges faced by enterprises in the U.S., along with ISG’s advice for addressing them, see the ISG Provider Lens Focal Points briefing here.

The report evaluates 59 providers across six quadrants: Application Development Outsourcing, Application Development Projects, Application Managed Services — GSIs, Application Managed Services — SIs, Application Quality Assurance and Continuous Testing Specialists.

The report names Accenture, Capgemini, Coforge, Cognizant, Deloitte, HCLTech, Hexaware, IBM, Infosys, TCS, UST and Wipro as Leaders in three quadrants each. It names Apexon, Hitachi Digital Services, HTC Global Services, Infinite Computer Solutions and Tech Mahindra as Leaders in two quadrants each. Atos, Birlasoft, Brillio, Innova Solutions, NTT DATA, Persistent Systems and Sutherland are named as Leaders in one quadrant each.

In addition, DXC Technology is recognized as a Rising Star — a company with a “promising portfolio” and “high future potential” by ISG’s definition — in two quadrants. Innova Solutions, LTM, Qualitest, Sutherland, TestingXperts and Unisys are recognized as Rising Stars in one quadrant each.

In the area of customer experience, Altimetrik is named the global ISG CX Star Performer for 2026 among AI driven ADM Services providers. Altimetrik earned the highest customer satisfaction scores in ISG's Voice of the Customer survey, part of the ISG Star of Excellence™ program, the premier quality recognition for the technology and business services industry.

Customized versions of the report are available from Capgemini, HTC and Hexaware.

The 2026 ISG Provider Lens AI-Driven ADM Services report for the U.S. is available to subscribers or for one-time purchase on this webpage.

About ISG

ISG (Nasdaq: III) is a global AI-centered technology research and advisory firm. A trusted partner to more than 900 clients, including 75 of the world’s top 100 enterprises, ISG is a long-time leader in technology and business services that is now at the forefront of leveraging AI to help organizations achieve operational excellence and faster growth. The firm, founded in 2006, is known for its proprietary market data and research, in-depth knowledge and governance of provider ecosystems, and the expertise of its 1,500 professionals worldwide working together to help clients maximize the value of their technology investments.

View source version on businesswire.com: https://www.businesswire.com/news/home/20260924763418/en/

Press Contacts:
Laura Hupprich, ISG
+1 203-517-3132
laura.hupprich@isg-one.com

Erik Arvidson, Matter Communications for ISG
+1 978-518-4542
isg@matternow.com

Source: Information Services Group, Inc.

Key Terms

aiops technical

AIOps (Artificial Intelligence for IT Operations) uses machine learning and data analysis to monitor, detect, and resolve problems in an organization’s technology systems automatically. It matters to investors because it can cut downtime and operating costs, speed up fixes, and make digital products more reliable—similar to an autopilot that notices and corrects issues before they disrupt service, which can protect revenue and reduce operational risk.

site reliability engineering technical

Site reliability engineering is a discipline that designs, tests and runs systems so a company’s websites and online services stay up, fast and secure—think of it as building maintenance for digital products, preventing and fixing outages before customers notice. Investors care because reliable systems protect revenue, customer trust and regulatory compliance, reduce the chance of costly interruptions, and make operational costs and risk more predictable.

cloud-native architectures technical

Cloud-native architectures are software designs built to run in cloud computing environments, breaking applications into small independent pieces that can be updated and scaled on demand. For investors, they matter because companies using these designs can deliver new features faster, absorb traffic spikes without large upfront hardware spending, and reduce downtime—similar to renting flexible office space instead of owning a fixed building, which can improve growth speed and cost predictability.

ai model validation technical

ai model validation is the formal process of testing and documenting that an artificial intelligence model performs as intended, is reliable, and does not produce biased, unsafe, or misleading outputs for its intended use. It typically includes checking accuracy, robustness, data quality, and governance controls, and matters to investors because it affects the trustworthiness, regulatory compliance, and operational risk of firms that use AI—much like a safety inspection matters for a bridge.