EXL's AI-Led Revenue Hits 61% While Its Legacy Operations Line Shrinks

EXL's data and AI-led revenue reached $362.6 million in the second quarter of 2026, 61% of the company's $594.8 million total and up 30% year over year, while its legacy digital operations line fell 1.5% to $232.2 million in absolute dollars (EXL, GlobeNewswire, July 28, 2026). That is not two lines growing at different speeds. It is one line taking revenue directly from the other.

The distinction matters for anyone who buys analytics support from EXL rather than building it in-house. A vendor whose AI-led category is simply growing faster than its legacy services business is selling an add-on. A vendor whose legacy services line is shrinking in dollar terms while the AI-led category absorbs the difference is selling a substitute, and substitution has different implications for what a carrier's own reserving and pricing teams need to retain internally. actuary.info tracked EXL's first quarter crossing 60% of $570.4 million in its May coverage of that milestone; the second-quarter print is the first time the two revenue categories moved in opposite dollar directions in the same release, not just at different rates.

The Substitution Signal, Read Line by Line

EXL does not report data and AI-led revenue as a GAAP segment. It is an internal classification the company discloses voluntarily, defined in its own filings as work delivered through "data management, analytics, AI services and solutions," including AI-embedded business operations such as payment integrity, set against digital operations, the "managed services that blend the company's deep domain expertise with industry-specific solutions" to run client business functions (EXL, Form 10-Q, filed with the SEC, August 2026). Engagements move between the two buckets as AI displaces the labor content of a given workflow, which is precisely the mechanism worth watching.

The four-quarter trend confirms the pattern is accelerating, not plateauing. Data and AI-led revenue grew 18% year over year in the third quarter of 2025, 21% in the fourth quarter, 28% in the first quarter of 2026, and 30.7% in the second quarter, a steady climb even as the digital operations comparison base got easier (EXL Q2 2026 investor presentation, via Investing.com, July 28, 2026). Total company revenue grew 15.6% over the same comparison, so the AI-led category is not simply capturing the whole company's growth; it is capturing growth from both new demand and the digital operations base itself. Management frames the shift as intentional: total operations revenue, the sum of both categories, still rose 10% year over year, which is the evidence EXL points to that carriers are expanding scope rather than just relabeling existing work.

Metric	Q2 2025	Q2 2026	Change
Total revenue	$514.5M	$594.8M	+15.6%
Data and AI-led revenue	~$277.4M	$362.6M	+30.7%
Digital operations revenue	~$235.7M	$232.2M	−1.5%
Insurance segment revenue	$172.2M	$197.8M	+14.9%

Source: EXL second-quarter 2026 earnings release (GlobeNewswire, July 28, 2026) and investor presentation (Investing.com, July 28, 2026). Q2 2025 data and AI-led and digital operations figures are derived from the disclosed year-over-year growth rates.

That still leaves an open question for a carrier evaluating the vendor relationship: is the digital operations decline evidence that the underlying labor-intensive work is disappearing, or evidence that EXL is simply moving the same work into a higher-margin reporting bucket without changing what its analysts and actuaries actually do day to day? EXL's own segment gross margin data offers a partial answer. Insurance segment gross margin was 34.6% in the second quarter, and the company's overall gross margin was 38.0%, up from prior periods as the AI-led mix grew (EXL, GlobeNewswire, July 28, 2026). Margin expansion alongside a shrinking digital operations line is consistent with genuine automation, not just reclassification, because a pure relabeling exercise would not move the blended margin.

What Buying the Substitute Does to In-House Actuarial Capacity

The insurance segment, EXL's largest, grew revenue 14.9% to $197.8 million in the quarter, comparable to the 12.6% growth to $193.9 million the segment posted in the first quarter (actuary.info, May 2026). That segment covers claims processing, underwriting support, subrogation, regulatory reporting, and customer operations, the functions that sit closest to a carrier's actuarial teams without actually being actuarial work product. As those engagements migrate from headcount-priced digital operations to AI-led delivery, the labor content a carrier used to buy by the FTE increasingly arrives as a packaged analytics output instead.

That shift changes what an in-house actuarial function needs to staff for. A reserving actuary who previously received claims triage data processed by a large offshore team now receives it processed by EXL's AI-augmented workflows, with fewer human touchpoints and a compressed cycle time. The work still needs actuarial review, but the review point moves earlier in the pipeline, from validating a large volume of manually processed transactions to validating the outputs and assumptions of a vendor's model. That is a narrower, more specialized skill set than the general reserving analyst headcount insurers have traditionally carried to absorb data-processing volume.

The staffing backdrop makes this substitution more attractive to carriers than it would have been a few years ago. Roughly 30% of insurers already outsource actuarial and risk functions, according to a July 2026 market analysis, in a global actuarial services market valued at $25.94 billion in 2026 and projected to reach $38.69 billion by 2035, a 4.8% compound annual growth rate (Business Research Insights, Actuarial Services Market report, July 2026). Actuarial, executive, and analytics positions have remained among the hardest categories to fill for five consecutive years of insurance labor-market surveys, and roughly half of current insurance personnel are expected to retire within 15 years. A vendor whose AI-led category can absorb work that used to require proportional headcount growth is offering carriers a way to grow analytical output without competing as hard for the same shrinking pool of credentialed reserving and pricing talent.

Carriers are not, however, outsourcing the actuarial opinion itself at anywhere near that 30% rate; core reserving, pricing, capital, and reinsurance functions remain the parts of the actuarial department insurers are least willing to hand to a vendor, even as they outsource more of the data preparation and analytics layer beneath those functions. EXL's own headcount data supports that boundary staying intact rather than eroding: the company added 986 employees sequentially to reach 68,413 in the second quarter, with attrition running at 24.7% (EXL Q2 2026 investor presentation, via Investing.com, July 28, 2026). A vendor genuinely automating away headcount at scale would show shrinking or flat employment while revenue accelerates; EXL is still growing its own headcount, just growing revenue faster than it, which is consistent with AI raising output per employee rather than eliminating the analytical layer altogether.

The Governance Boundary Vendor Analytics Cannot Cross

Whatever share of a carrier's data pipeline runs through EXL's AI-led workflows, the actuarial opinion attached to loss reserves or rate filings remains the responsibility of a credentialed actuary employed by, or under contract directly to, the carrier. That boundary does not move just because the inputs feeding the reserving process increasingly arrive pre-processed by a vendor's proprietary models. It does mean the appointed actuary's documentation burden shifts: instead of validating a large volume of manually keyed claims data, the actuary now needs to understand, at least at a high level, how a third-party AI system classified, triaged, or scored the underlying claims and policy data before it reached the reserving database.

This is not a new problem in kind, actuaries have always relied on vendor-supplied loss development factors, catastrophe models, and rating algorithms without personally rebuilding them. It is a new problem in scale, because the volume of vendor-touched data flowing into a single carrier's reserving and pricing process is now large enough, and growing fast enough, that a governance framework built for occasional vendor tools does not scale cleanly to a relationship where 61% of the vendor's own revenue is generated by AI-embedded delivery. The practical question for a carrier's actuarial leadership is not whether to trust EXL's outputs, but what documentation, audit rights, and model-change notification terms are written into the vendor contract, since those terms determine how much the actuary of record can actually say about the provenance of the data underlying a reserve estimate.

Payment Integrity and Data Management: The Adjacent Growth Lines

Two smaller lines inside the data and AI-led category illustrate where the substitution is happening fastest. Payment integrity, the healthcare-adjacent service line that reviews claims for improper payments before or after adjudication, is growing quickly enough that related contract-asset receivables on EXL's balance sheet rose from $24.8 million at the end of 2025 to $36.9 million at the end of the second quarter of 2026, a 49% increase in six months (EXL, Form 10-Q, filed with the SEC, August 2026). Healthcare and life sciences overall grew to $158.0 million in the quarter and $309.9 million for the first six months of 2026, up from $129.5 million and a comparable six-month base a year earlier.

Data management, the raw discipline of structuring and governing the information that feeds both AI-led analytics and traditional actuarial models, is described by EXL management as accelerating from a smaller base but becoming an increasingly prominent part of the business mix. For carriers, this line is arguably more actuarially consequential than the AI-led headline figure, because bad data governance upstream produces bad reserving and pricing inputs regardless of how sophisticated the AI layer processing that data becomes. A carrier that outsources data management to the same vendor that also runs its AI-led analytics is concentrating both the data quality function and the analytical function in one counterparty, which raises the stakes of the vendor's own internal controls in a way a carrier's own actuarial function has limited visibility into without contractual audit rights.

iMerit and the Push Into the AI Training Layer

EXL agreed to acquire iMerit, a company management described as "a recognized leader in AI model training, evaluation, and reinforcement learning," in a deal management called "a transformational pivot for EXL" (EXL Q2 2026 earnings call transcript, via Investing.com, July 28, 2026). The deal carries $170 million of upfront consideration plus up to $140 million in earnouts tied to milestones over two years, for a maximum value of $310 million, and was expected to close July 31, 2026 (EXL, Form 10-Q, filed with the SEC, August 2026). Full-year guidance already reflects the acquisition, with management expecting iMerit to contribute $28.0 million to $32.0 million of revenue for the remainder of 2026.

The rationale extends EXL's AI-led thesis upstream, into the layer that trains and evaluates the foundation models EXL's own products increasingly rely on, and adds relationships with foundation model companies alongside expanded capabilities in what management called regulated industries where "domain knowledge, context, and compliance are absolutely critical." For a carrier's build-versus-buy calculus, iMerit is the clearest evidence yet that replicating EXL's stack in-house means replicating not just an application layer but a training and evaluation layer few insurers have any internal capability to build, a dynamic this site has tracked across the broader insurtech AI funding landscape, where capital is concentrating in vendors that control proprietary data and training infrastructure rather than spreading across point-solution competitors.

Guidance, Margin Trajectory, and the Second-Half Question

EXL raised full-year 2026 revenue guidance to $2.39 billion to $2.415 billion, up from prior guidance, with organic constant-currency growth of 13% to 14% and adjusted diluted earnings per share of $2.25 to $2.29 (EXL, GlobeNewswire, July 28, 2026). CFO Maurizio Nicolelli attributed the raise to "strong second quarter performance, sustained growth momentum and healthy pipeline" giving the company confidence to lift organic guidance (EXL Q2 2026 earnings call transcript, via Investing.com, July 28, 2026). Adjusted diluted EPS grew 22.3% year over year to $0.59, and adjusted operating margin reached 19.7% in the quarter.

Management also cautioned that adjusted operating margin will run lower in the second half of 2026 than the first, as the company increases investment in sales capacity, data and AI capabilities, and solutions development, with full-year margins still expected to land comparable to 2025. That guidance detail is a useful check on the substitution story: if the AI-led category were purely a margin-accretive reclassification of existing work, the natural expectation would be margin expansion accelerating, not a management team pre-announcing a second-half dip to fund further AI investment. The dip signals EXL views the AI-led buildout as still capital-intensive, not a finished platform generating pure incremental margin, which matters for how durable carriers should expect the current pricing and capability trajectory to be.

Reading the Substitution Signal Forward

The second-quarter print gives carriers a sharper version of the build-versus-buy question than the first quarter's crossing of 60% did. It is no longer just that a vendor is growing an AI category faster than the rest of its business. It is that the category a carrier used to buy, priced by the transaction or the FTE, is contracting in absolute dollars while a differently priced, more proprietary, more vertically integrated category takes its place. Carriers that treat this as simply "EXL's AI push" are underpricing what has actually changed in the vendor relationship: the commercial terms, the data provenance chain feeding actuarial work product, and the skill set an in-house team needs to retain to meaningfully oversee what the vendor delivers. actuary.info's ongoing tracking of carrier and vendor AI patent activity suggests EXL is not alone in this pattern, but its willingness to disclose the mix shift quarter over quarter makes it the clearest public data point for how fast the substitution is actually moving.

Further Reading on actuary.info

• Verisk's loss-cost data pricing power and the actuarial build-versus-buy problem - A parallel vendor-dependence story on the pricing-data side of the same build-versus-buy question.
• EXL Q1 2026: AI Revenue Hits 60% and Reshapes the Insurance Vendor Model - The first-quarter milestone this piece extends, including the vendor ecosystem comparison against Verisk, Guidewire, and Sapiens.
• EXL's $310 Million iMerit Acquisition Moves Insurance AI Into the Training Layer - A deeper look at the deal terms and what the training-layer push means for carrier governance.
• Insurtech's H1 2026 AI Funding Concentrates Around Build-vs-Buy - How capital allocation across the wider insurtech AI market mirrors EXL's own vertical-integration strategy.
• Bevaya and the Build-vs-Buy Data Moat in Insurance-Native AI - A carrier-side comparison for what building a proprietary data advantage in-house actually requires.
• McKinsey's $50B-$70B Insurance GenAI Revenue Thesis - The market-sizing context for why vendor AI-led revenue is scaling as fast as EXL's numbers show.