EXLS Q3 2025: Data and AI-Led Revenue Jumps to 56%, Reshaping Growth Trajectory
EXLS’s Q3 marked a structural inflection as data and AI-led solutions now comprise over half of revenue, up sharply from prior quarters, with the company capturing expanding client budgets for AI transformation. The shift is visible across every major vertical, with healthcare and insurance fueling outperformance and the international segment beginning to accelerate. EXLS raised full-year guidance, signaling confidence that its AI-centric strategy will sustain double-digit growth into 2026.
Summary
- AI-Led Revenue Surpasses Legacy Mix: Data and AI-led business now forms the majority of revenue, signaling a permanent pivot in the business model.
- Healthcare and Insurance Outperform: These segments accelerate on AI adoption, driving both growth and client stickiness.
- Guidance Raised on Pipeline Strength: Management sees durable demand and high renewal rates sustaining double-digit growth into next year.
Performance Analysis
EXLS delivered a 12% year-over-year revenue increase in Q3, with adjusted EPS up 11%, as the company’s core data and AI-led offerings accelerated to 18% growth and now account for 56% of total revenue. This marks a pivotal transition, with AI solutions overtaking traditional digital operations in the revenue mix for the first time. Segment-level results reinforce the strategic pivot: insurance (one-third of revenue) grew 9%, healthcare and life sciences (one-quarter of revenue) surged 22%, and banking/capital markets rose 12%. International markets, at 18% of revenue, grew 8%, highlighting geographic diversification efforts.
Operating margin declined 50 basis points year-over-year to 19.4%, reflecting increased investment in sales and AI solution development. SG&A rose as a percent of revenue, up 120 basis points, as EXLS expands front-end capabilities to address larger, more complex client opportunities. The balance sheet remains robust, with net cash and strong operating cash flow supporting ongoing buybacks and reinvestment. Full-year guidance was raised for both revenue and EPS, with management projecting continued double-digit growth into 2026, underpinned by high renewal rates and a growing pipeline of AI-centric projects.
- AI-Led Revenue Mix Shift: Data and AI-led revenue now dominates, reflecting client migration from traditional digital ops to embedded AI solutions.
- Healthcare Segment Momentum: Healthcare and life sciences outpaced all other segments, capitalizing on industry data complexity and AI adoption.
- Margin Investment Cycle: Margin compression driven by proactive investments in sales force and AI capabilities, positioning for long-term scale.
EXLS’s results show clear momentum in both core and emerging verticals, with the AI-led transformation now visible in both revenue mix and client relationships. The company’s ability to maintain revenue stability even as productivity rises signals a robust, expanding opportunity set.
Executive Commentary
"This is the third consecutive quarter we have accelerated our data and AI-led revenue growth, underscoring both the rising demand for AI-driven solutions and demonstrating our leadership in embedding AI directly into client workflows."
Rohit Kapoor, Chairman and Chief Executive Officer
"Our adjusted operating margin for the quarter was 19.4%, down 50 basis points year-over-year, driven by investments in front-end sales and new solutions. Our resilient business model and strong sales pipeline gives us confidence in our ability to maintain double-digit growth momentum in 2026."
Maurizio Nicolelli, Chief Financial Officer
Strategic Positioning
1. Data and AI-Led Transformation
EXLS’s core strategy is to embed AI and data solutions directly into client workflows, moving beyond traditional outsourcing to become a transformation partner. The launch of EXL data.ai, a GenAI suite for data modernization, directly addresses the primary barrier to AI adoption: fragmented and unstructured enterprise data. With 65+ AI agents, the platform automates data readiness, slashing implementation time and integrating with major cloud and data platforms. This positions EXLS as a critical enabler for clients seeking to operationalize AI at scale.
2. Vertical Integration and Client Expansion
Healthcare and insurance verticals are now EXLS’s largest and fastest-growing businesses, driven by domain expertise and the ability to deliver measurable ROI on AI investments. In healthcare, EXLS’s payment integrity and document-processing solutions are foundational, with rapid expansion into finance, pricing, and supply chain use cases. Insurance clients are increasingly shifting workflows to AI-powered models, with EXLS capturing share through renewal and expansion. The company’s approach is to start with a single use case, then scale across the client’s enterprise, deepening relationships and increasing wallet share.
3. Go-to-Market Evolution and Partner Ecosystem
EXLS has overhauled its go-to-market strategy, training account teams to engage with broader buying centers (CIOs, CDOs, business heads) and emphasizing innovation over cost savings. The company now co-sells with leading technology partners—Microsoft, AWS, Databricks, Snowflake, Palantir—expanding deal size and strategic relevance. This ecosystem approach is complemented by partnerships with private equity, accelerating AI adoption in portfolio companies.
4. International Growth Markets
While still a smaller share of revenue, international markets are seeing renewed investment in local talent, partnerships, and solution transfer from U.S. clients. EXLS is seeding these geographies with proven AI and data solutions, aiming to accelerate penetration and diversify geographic risk.
5. Margin Management and Productivity
AI adoption is structurally increasing revenue per employee, with headcount growth lagging revenue expansion. While productivity gains could be deflationary, EXLS is offsetting this by capturing new business from clients as workflows are automated, and by expanding into higher-value agentic AI and data governance services. Management expects this dynamic to support both top-line and margin growth over time.
Key Considerations
EXLS’s quarter reflects a business in the midst of a durable transformation, with AI-centric solutions now the core growth engine and client relationships deepening as a result. Investors should monitor both the pace of AI adoption and the company’s ability to sustain expansion in new segments and geographies.
Key Considerations:
- AI Revenue Sustainability: High client renewal rates and expansion into new workflows suggest the AI-led mix shift is structural, not cyclical.
- Margin Headwinds and Investment: Near-term margin pressure is a function of front-loaded investment in sales and capability, with management targeting gradual improvement as scale builds.
- Healthcare and Insurance Leverage: These segments offer significant untapped opportunity, with EXLS’s domain expertise and data capabilities driving competitive differentiation.
- International Upside: Renewed focus on local talent and partnerships positions EXLS to accelerate growth outside the U.S., diversifying the revenue base.
- Go-to-Market Complexity: Larger, more strategic deals require sophisticated sales execution and partner management, raising operational complexity and risk.
Risks
Key risks include the pace of enterprise AI adoption, which could slow if clients face integration or ROI challenges, and margin pressure from continued investment in talent and go-to-market capabilities. Competitive intensity in both data platform and AI services remains high, and EXLS must maintain differentiation as larger players enter the space. International expansion carries execution risk as the company builds local presence and adapts offerings to new markets.
Forward Outlook
For Q4 and the full year, EXLS guided to:
- 2025 revenue of $2.07B to $2.08B, up 13% YoY
- Adjusted EPS of $1.88 to $1.92, up 14-16% YoY
Management cited strong pipeline visibility, high renewal rates, and expanding client budgets for AI transformation as drivers. Margin is expected to stabilize, with incremental improvement targeted in 2026 as investments normalize and scale benefits accrue.
- Sales pipeline strength underpins confidence in sustained double-digit growth
- Capital allocation will balance reinvestment, share buybacks, and potential M&A
Takeaways
EXLS’s Q3 results confirm a durable pivot from legacy outsourcing to AI-enabled transformation, with structural changes in revenue mix and client engagement. The company’s ability to offset productivity-driven deflation with new, higher-value business is a key differentiator.
- AI-Led Growth Engine: The data and AI business is now the biggest growth driver, with robust client demand and high success rates on deployments.
- Margin and Productivity Leverage: Investments in talent and solutions are near-term headwinds but position EXLS for higher revenue per employee and operating leverage as the AI mix grows.
- Watch International and Healthcare: These segments are in early innings, with significant headroom for expansion and competitive advantage rooted in domain expertise.
Conclusion
EXLS’s Q3 marks a strategic inflection point, with data and AI-led solutions now anchoring both growth and client relationships. The company’s proactive investments and evolving go-to-market model position it for continued outperformance, provided execution remains disciplined as complexity rises.
Industry Read-Through
EXLS’s results highlight an accelerating enterprise shift from traditional outsourcing to AI-driven transformation, with clients prioritizing business model innovation and data modernization. The company’s traction in regulated, data-rich verticals (insurance, healthcare, banking) signals broad industry appetite for embedded AI solutions that deliver measurable outcomes. Competitors in IT services, BPO, and consulting will face rising pressure to build or partner for AI and data capabilities, while pure-play data platform vendors may see increased demand for integration and workflow automation. The international expansion narrative suggests global enterprises are ready to adopt AI at scale, but local execution and domain expertise will be critical differentiators.