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Businesses overestimate real progress on AI

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EXL (NASDAQ: EXLS) released its 2026 U.S. Enterprise AI Study, highlighting a major gap between perceived and actual AI progress. While 76% of businesses believe they are ahead on AI, only 10% qualify as AI Leaders with company‑wide integration and measurable ROI.

AI Leaders report approximately 27% revenue growth, 26% cost reduction, and 22% margin improvement in areas where AI is implemented, driven by redesigned operating models and reimagined workflows. The study also finds data infrastructure is the top barrier to scaling AI, with 70% citing data challenges, including privacy, security, and siloed data.

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AI-generated analysis. How Rhea-AI works. Not financial advice.

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News Market Reaction – EXLS

-3.23%
33 alerts
-3.23% News Effect
-2.4% Trough in 2 hr 31 min
-$134M Valuation Impact
$4.01B Market Cap
0.7x Rel. Volume

On the day this news was published, EXLS declined 3.23%, reflecting a moderate negative market reaction. Argus tracked a trough of -2.4% from its starting point during tracking. Our momentum scanner triggered 33 alerts that day, indicating elevated trading interest and price volatility. This price movement removed approximately $134M from the company's valuation, bringing the market cap to $4.01B at that time.

Data tracked by StockTitan Argus on the day of publication.

What This Means

This announcement positions EXL as a data- and AI-focused advisor, using a survey of 322 senior lead...
Analysis

This announcement positions EXL as a data- and AI-focused advisor, using a survey of 322 senior leaders to highlight gaps between perceived and actual AI progress. The study underscores how only 10% of firms qualify as AI Leaders, achieving 27% revenue growth, 26% cost reduction and 22% margin improvement in AI-enabled areas. In context with prior AI platform and partnership news, investors may watch how EXL converts this research into concrete client engagements and revenue impact.

Key Figures

Firms feeling ahead on AI: 76% AI Leaders share: 10% Revenue growth (Leaders): 27% +5 more
8 metrics
Firms feeling ahead on AI 76% Companies believing they are ahead of competitors on AI
AI Leaders share 10% Companies meeting EXL’s criteria for AI Leaders
Revenue growth (Leaders) 27% Estimated revenue growth in AI-implemented areas
Cost reduction (Leaders) 26% Estimated cost reduction from AI use
Margin improvement (Leaders) 22% Estimated margin improvement from AI use
Survey respondents 322 C-suite and senior decision makers in 2026 U.S. Enterprise AI Study
Leaders redesigned models 44% AI Leaders that completely redesigned enterprise-wide operating models
Laggards redesigned models 23% AI Laggards that redesigned enterprise-wide operating models

Previous AI Reports

5 past events · Latest: Jun 12 (Positive)
Same Type Pattern 5 events
Date Event Sentiment 24h Move Catalyst
Jun 12 Databricks AI partnership Positive +0.8% Expanded Databricks collaboration and Gold Tier status to strengthen data foundations for AI.
Jun 04 NVIDIA AI integration Positive -0.2% Integration of NVIDIA transaction foundation model into EXLerate.ai for financial institutions.
Mar 16 EXLerate.ai platform advance Positive +3.2% Expanded NVIDIA collaboration to scale EXLerate.ai with GPUs and governance tools.
Mar 11 Agentic AI launch Positive -0.6% Launch of agentic AI solutions and new EXLerate.ai, EXLdecision.ai capabilities.
Feb 24 AI event announcement Positive +0.8% Announcement of AI in Action Americas virtual event featuring major technology partners.

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Pattern Detected

AI-related headlines have produced mixed reactions, with three positive and two negative next-day moves, indicating no consistent pattern yet.

Recent Company History

Over recent months, EXL has repeatedly highlighted AI capabilities, from enhancing its EXLerate.ai platform with NVIDIA tools to deepening its Databricks collaboration and hosting the AI in Action event. These AI-tagged announcements have seen next-day moves between about -0.55% and +3.18%. Today’s AI adoption study fits this pattern of positioning EXL as an enterprise AI enabler rather than introducing a discrete commercial deal or product launch.

Historical Comparison

+0.8% avg move · In the past 6 months, EXLS released 5 AI-tagged updates with an average next-day move of 0.81%. Toda...
AI
+0.8%
Average Historical Move AI

In the past 6 months, EXLS released 5 AI-tagged updates with an average next-day move of 0.81%. Today’s AI adoption study continues that steady, modest reaction profile for AI-related news.

AI-tagged news shows a progression from platform launches and agentic AI solutions to scaled partnerships with NVIDIA and Databricks, now complemented by thought-leadership research on enterprise AI adoption.

Regulatory & Risk Context

Short Interest: 9.63%
Short Interest
9.63% of shares outstanding
as of 2026-05-29 Days to cover: 6.05

Key Terms

ROI, operating model, data infrastructure, data privacy and security, +1 more
5 terms
ROI financial
"experiencing a notable return on investment (ROI) from their AI initiatives."
Return on investment (ROI) measures how much money an investor makes or loses relative to the amount they put in, expressed as a percentage. It helps compare the efficiency of different investments—like checking which of several gardens produced the most fruit for the seeds planted—so investors can decide which opportunities deliver the best payoff for the risk and capital they commit.
operating model technical
"The gap is not a technology problem. It is an operating model problem."
An operating model is the way a company organizes and manages its resources, processes, and activities to deliver its products or services. It acts like a blueprint that shows how different parts of the business work together to create value. For investors, understanding a company's operating model helps assess how efficiently it operates and how well it can adapt to change or grow over time.
data infrastructure technical
"Data infrastructure remains the single most cited barrier to scaling AI,"
The systems and tools a company uses to collect, store, move and analyze its digital information so that people and applications can use accurate data quickly. Investors care because strong data infrastructure lets a business make faster, more reliable decisions, scale operations without breaking, protect sensitive information, and extract value from data — all of which affect growth, costs and risk. Think of it as the roads, pipes and traffic signals that keep information flowing smoothly.
data privacy and security technical
"Data privacy and security (34%), siloed data across multiple sources (31%),"
Data privacy and security are the policies, tools and practices that keep sensitive information—such as customer records, financial details and proprietary business data—protected from unauthorized access, loss or misuse. For investors, strong privacy and security reduce the risk of costly breaches, regulatory fines and damage to reputation that can hit revenues and share price; weak controls are like leaving a company’s safe unlocked, exposing it to theft and expensive repairs.
model transparency technical
"and limited model transparency (31%) were the three most frequently named obstacles."
Model transparency is how clearly the steps and inputs behind a computer model’s predictions or decisions can be seen and understood, like being able to read a recipe rather than just tasting the final dish. Investors care because transparent models make it easier to judge risks, verify performance, spot errors or bias, and meet regulatory or audit expectations, which helps protect value and inform better investment choices.

AI-generated analysis. How Rhea-AI works. Not financial advice.

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EXL’s 2026 U.S. Enterprise AI Study finds significant gap between perceived progress on AI adoption and real-world performance improvement

  • 76% of companies believe they are ahead of their competitors on AI
  • Just 10% meet the criteria of an AI Leader
  • AI Leaders achieve 27% revenue growth, 26% cost reduction and 22% margin improvement by reimagining core workflows

NEW YORK, June 17, 2026 (GLOBE NEWSWIRE) -- Most companies believe they're outperforming their competitors on AI. New research from EXL [NASDAQ: EXLS], a global data and AI company, shows only one in 10 are making significant company-wide progress integrating AI across core business functions and experiencing a notable return on investment (ROI) from their AI initiatives. The gap is not a technology problem. It is an operating model problem.

The third annual EXL U.S. Enterprise AI Study is based on a survey of 322 C-suite and other senior decision makers across the banking and finance, insurance, retail, utilities, life sciences, and healthcare payer industries. Its findings reveal a significant disconnect between how organizations assess their AI progress and where they currently stand on real-world AI integration.

“Every company is now using AI in some capacity, but we’re really starting to see leaders distinguish themselves from the pack when it comes to large-scale enterprise integration,” said Anand “Andy” Logani, executive vice president and chief AI officer at EXL. “What separates the leaders is that they've stopped trying to fit AI into the way they already work, and started asking a more fundamental question: if AI were built in from the start, how would this workflow, this team, this decision look different? Moving from AI experimentation to AI execution requires more than technology investment; it requires operating model transformation.”

The following are some of the report’s key findings:

  • Most companies see themselves as ahead on AI, but the reality is more sobering, while 76% say they are ahead of competitors, our research show only 10% qualify as AI Leaders. Those leaders have moved beyond pilots and embedded AI into high-impact workflows, reimagining how work gets done to generate greater business value.
  • AI leaders generate quantifiable ROI: AI Leaders, despite representing just 10% of respondents, are generating substantially stronger returns. Leaders estimate that AI has reduced costs by 26%, boosted revenue by 27%, and improved margin by 22% within the specific areas it’s been implemented. Laggards trail in all three areas. Leaders also report greater stability in uncertain markets, better customer engagement, and more effective market expansion as direct results of AI use.
    • Operating model transformation is a key differentiator: Central to the Leaders' approach is a willingness to redesign enterprise-wide operating models rather than adapt existing ones. While many organizations have made incremental changes to accommodate AI, Leaders have taken a more fundamental step: rebuilding workflows, redefining roles, and restructuring decision processes with AI embedded at the core. All told, 44% of Leaders have completely redesigned their enterprise-wide operating models to accommodate AI use. That number falls to just 23% among Laggards.
    • Data-readiness remains a massive challenge: Data infrastructure remains the single most cited barrier to scaling AI, with seven in 10 respondents describing data as a challenge. Data privacy and security (34%), siloed data across multiple sources (31%), and limited model transparency (31%) were the three most frequently named obstacles. Among Laggards, 83% still contend with data siloed within business functions, compared to 44% of Leaders who have achieved enterprise-wide data accessibility.

To dive deeper into the findings, download the 2026 EXL U.S. Enterprise AI Study. For more information and to explore how EXL can deliver value for your AI initiatives, contact us

About EXL

EXL (NASDAQ: EXLS) is a global data and AI company that offers services and solutions to reinvent client business models, drive better outcomes and unlock growth with speed. EXL harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world's leading corporations in industries including insurance, healthcare, banking and capital markets, retail, communications and media, and energy and infrastructure, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have approximately 67,000 employees spanning six continents. For more information, visit www.exlservice.com.

Cautionary Statement Regarding Forward-Looking Statements

This press release contains forward-looking statements within the meaning of the United States Private Securities Litigation Reform Act of 1995. You should not place undue reliance on those statements because they are subject to numerous uncertainties and factors relating to EXL's operations and business environment, all of which are difficult to predict and many of which are beyond EXL’s control. Forward-looking statements include information concerning EXL’s possible or assumed future results of operations, including descriptions of its business strategy. These statements may include words such as “may,” “will,” “should,” “believe,” “expect,” “anticipate,” “intend,” “plan,” “estimate” or similar expressions. These statements are based on assumptions that we have made in light of management's experience in the industry as well as its perceptions of historical trends, current conditions, expected future developments and other factors it believes are appropriate under the circumstances. You should understand that these statements are not guarantees of performance or results. They involve known and unknown risks, uncertainties and assumptions. Although EXL believes that these forward-looking statements are based on reasonable assumptions, you should be aware that many factors could affect EXL’s actual financial results or results of operations and could cause actual results to differ materially from those in the forward-looking statements. These factors, which include our ability to maintain and grow client demand, our ability to hire and retain sufficiently trained employees, and our ability to accurately estimate and/or manage costs, rising interest rates, rising inflation and recessionary economic trends, are discussed in more detail in EXL’s filings with the Securities and Exchange Commission, including EXL’s Annual Report on Form 10-K. You should keep in mind that any forward-looking statement made herein, or elsewhere, speaks only as of the date on which it is made. New risks and uncertainties come up from time to time, and it is impossible to predict these events or how they may affect EXL. EXL has no obligation to update any forward-looking statements after the date hereof, except as required by federal securities laws.

Media Contact   
Keith Little    
media.relations@exlservice.com   


FAQ

What is the key finding of the 2026 EXL (NASDAQ: EXLS) U.S. Enterprise AI Study?

The study finds most companies overestimate AI progress, with only 10% qualifying as true AI Leaders. According to EXL, 76% of firms think they are ahead on AI, yet few achieve broad integration and strong, measurable returns from AI initiatives.

How do AI Leaders in the EXL 2026 Enterprise AI Study outperform other companies?

AI Leaders report stronger, quantifiable returns where AI is deployed, including 27% revenue growth, 26% cost reduction, and 22% margin improvement. According to EXL, these leaders embed AI in high-impact workflows and redesign operating models rather than making only incremental changes.

What percentage of companies qualify as AI Leaders in EXL’s 2026 U.S. Enterprise AI Study?

Only about 10% of surveyed companies qualify as AI Leaders in EXL’s 2026 study. According to EXL, these organizations move beyond pilots, embed AI across core workflows, and realize notable revenue, cost, and margin benefits in the areas where AI is implemented.

What operating model changes distinguish AI Leaders in EXL’s 2026 AI Study (EXLS)?

AI Leaders are more likely to redesign enterprise-wide operating models with AI at the core. According to EXL, 44% of Leaders have completely redesigned operating models for AI, compared with 23% of Laggards, including reworked workflows, roles, and decision processes.

What data challenges to AI adoption does the 2026 EXL U.S. Enterprise AI Study highlight?

The study identifies data infrastructure as the most cited barrier to scaling AI, with about 70% reporting data challenges. According to EXL, key obstacles include data privacy and security, siloed data across sources, and limited model transparency, especially among AI Laggards.

How do data silos differ between AI Leaders and Laggards in EXL’s 2026 AI Study?

AI Laggards face more severe data silos, with 83% reporting data trapped within business functions. According to EXL, only 44% of AI Leaders still struggle with this issue, reflecting broader enterprise-wide data accessibility among the leading organizations.