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Ladies and gentlemen, welcome to the Cognizant Technology Solutions Second Quarter 2026 Earnings Conference Call. All lines have been placed on mute to prevent background noise. After the speakers' remarks, there will be a question-and-answer session. If you would like to ask a question at that time, please press star then one. A confirmation tone will indicate that your line is in the question queue. I would now like to turn the conference over to Mr. Tyler J. Scott, Senior Vice President, Investor Relations. Please go ahead.
Thank you, operator, and good morning, everyone. Welcome to Cognizant's Second Quarter 2026 Earnings Call. I am joined today by Ravi Kumar, Chief Executive Officer and Jatin Pravinchandra Dalal, our Chief Financial Officer. By now, you should have received a copy of the earnings release and investor supplement. If you have not, copies are available on our website, cognizant.com. Before we begin, I would like to remind you that some of the comments made on today's call and some of the responses to your questions may contain forward-looking statements. These statements are subject to the risks and uncertainties as described in the company's earnings release and other filings with the SEC. Additionally, during our call today, we will reference certain non-GAAP financial measures that we believe provide useful information for our investors. Reconciliations of non-GAAP financial measures where appropriate to the corresponding GAAP measures can be found in the company's earnings release and other filings with the SEC. With that, over to you, Ravi.
Thank you, Tyler. Good morning, everyone. Thank you for joining us. We delivered a solid second quarter with organic revenue growth at the high end of our expectations and year-over-year adjusted operating margin expansion. Nearly all our healthy sequential growth was driven by our organic business. We accelerated our evolution as an AI builder by building new capabilities, launching new platforms, and deploying Frontier talent as we begin to unlock entirely new business categories and client value pools. Looking at the quarter's highlights, revenue grew 4.1% year-over-year in constant currency led by strong performance in North America as large deals signed over the past year moved into full execution. Financial services grew nearly 12% year-over-year in constant currency, the second consecutive quarter of 10%-plus growth. Trailing 12-month bookings increased 5%. We signed seven large deals each with TCV of more than $100 million, including three new logos. As we expanded adjusted operating margins year-over-year for the sixth straight quarter demonstrating continued profitable revenue growth. From an AI indicators perspective, our revenue and adjusted operating income per associate increased 4.6% and 7.1%, respectively. Starting this quarter, we are excluding trainees who are not fully deployed for both the current and the comparable prior periods. Over 40% of our software development is now AI-assisted. We have over 8,000 AI engagements, and we view strength in financial services, which includes some of the world's most technically sophisticated companies, as a leading indicator for other industries. Our research reveals that financial services is well ahead with AI initiatives and advanced AI adoption. We are helping clients tackle significant technology debt by using AI to compress modernization timelines that are shifting towards outcome-based pricing. We also now see financial services clients leveraging AI for growth imperatives with new discretionary spend cycles. We completed our previously announced acquisition of Astreya, a global IT managed services provider with deep expertise in data center infrastructure, enterprise networks, digital workplace services, and AI-first managed operations. Momentum is already building. Astreya will continue its work with Google to deliver services across its corporate and engineering environment, including global ID ops, workplace collaboration infrastructure, and platform services. We delivered these results against the cautious demand environment while growing at the top of our peer group. While we expect that caution to persist in the near term, AI is driving fundamental change in our industry and we believe it creates significant long-term growth opportunities. The key question is why growing AI capability has not yet translated into more enterprise value. Our research shows two-thirds of the Global 2000 have not yet realized measurable AI productivity gains; one in four have paused AI deployments, and billions of dollars in potential value remain unrealized. The opportunity to address this gap is enormous. We estimate the $1 trillion system integration market can expand into a $5 trillion to $6 trillion enterprise operations market with $4.5 trillion of operational labor exposed to AI. Services firms are structurally positioned to capture this opportunity. As models proliferate and inference costs decline, models stop being the differentiator and value shifts to the applied layer, which is context, governance, and business processes. This layer addresses how each enterprise applies AI, what it learns from it, how effectively it retains, reuses, and compounds that learning, and how well it protects the proprietary intelligence that constitutes its alpha. That is why we launched the Cognizant AI Delivery Operating System, a continuously learning delivery system that combines human expertise, organizational knowledge, client context, and AI intelligence. It has three pillars: our engineering harness, which coaches engineers in real-time; our business operations harness, which feeds best practices into a shared organizational system; and our intelligence spine, which connects intelligence across physical and edge environments. All of this is supported by our context engineering capabilities, which is the ability to assemble an enterprise's work drafts, guardrails, and tribal knowledge. Working with Cisco, we are using context fabric to build a digital signature of the account management role, forming the foundation for an account manager's digital twin and broader identification solution. This AI solution with digital twin capabilities holds the potential to streamline daily operations and support on-time, in-full complete delivery, improving customer satisfaction. For a large North American bank, we piloted a solution for their fraud management and KYC operational workflows. Context was engineered through a custom solution that combines static knowledge from customer and operations interactions and documents with dynamic business context sourced through enterprise application APIs. The fraud dispute management multi-agent pilot solution has demonstrated the potential to reduce manual effort by more than 50% while the KYC process can significantly improve decision efficacy reducing the risk of fines and fees. Last quarter, I described how AI is reforging our industry's first principles and driving four significant shifts. First, becoming an AI builder rather than a traditional systems integrator: owning the full stack required to design bespoke AI systems. Second, rebuilding a talent model by shifting from a traditional pyramid towards interdisciplinary teams working at the intersection of domain operations and technology. Third, shifting our economics from labor to outcomes. Our mix of fixed-price and transaction-based work has grown for three consecutive years creating a more durable business. And fourth, moving from delivering projects to underwriting results. Let me share our progress across these four shifts starting with the first one, becoming an AI builder by strengthening our proprietary IP and ecosystem. This year, we launched a dedicated AI market unit, an elite team of business designers, industry strategists, and frontier engineers focused on converting our investments into realized value. We are already seeing early traction. For example, a large payer client chose us to help build an agentic development practice for its biggest division through pods of Frontier engineers and AI agents. We cut manual effort by 60% for a mid-sized payer while improving claims throughput, and we compressed AI development cycles from months to days for a leading European online fashion retailer advancing agentic workflows across supply chain, inventory, returns, and customer experience. On the partnership front, we established a dedicated Gemini Enterprise practice as a Google Cloud Diamond partner and we joined OpenAI's Daybreak Cyber Partner Program. We also expanded our partnership with Anthropic, becoming one of the small number of global premium partners in the Cloud Partner Network. An example of this partnership at work is Travelport, where we partnered with Anthropic on a strategic AI transformation aimed at modernizing Travelport's software development and embedding AI across Travelport's travel retailing and distribution platforms. And with A+E Global Media, we partnered with Snowflake to deploy custom intelligent agents that transform complex advertising operations and legal workflows. By automating document validation and enabling natural language queries, we helped accelerate decision-making and significantly improved time-intensive processes. For the second shift, we are rearchitecting our talent model into AI early-career talent led by more senior player coaches. We introduced two new certified roles: Frontier-certified engineers who audit workflows and build intelligent agents, and Frontier business operators who manage blended human-digital teams to deliver outcomes. We plan to scale this Cognizant Forward team to 5,000 Frontier-certified engineers and 10,000 Frontier business operators. We currently have 10,000 cloud-certified architects, the most of any organization globally, and we power one of the largest pools of Codex and Gemini Enterprise trained badges. Last quarter, we introduced Cognizant SkillSpring, an AI-native platform that embeds agent-driven tutoring directly into daily workflows and gives associates real-time visibility into their AI proficiency and token usage. It is gaining significant momentum with our associates as learning time has doubled and AI users tripled. We have also opened this platform to early prospective clients. Our third and fourth shifts move Cognizant from a labor-based model to an agentic and platform-enabled model and from delivering outcomes to underwriting results. This is why we established a new AI products and platform group earlier this year to unify Cognizant's proprietary offerings and scale innovation across the portfolio. Our platform strategy has two dimensions. First, our engineering platforms, which provide the foundation for everything we build, including accelerators, agent frameworks, and AI engineering tools that power our AI-native software development lifecycle and agents development lifecycle. They are increasingly powered by their own agent tech workforce. Together, they compress the software cycle, improve productivity, and accelerate business outcomes for clients. Second, and building on that foundation, our business platforms combine technology, data, AI, and deep industry to create differentiated client value. Purpose-built for the industries we serve, they embed industry-trained agents directly into critical workflows. TriZetto is the strongest proof point of our platform strategy. Our healthcare platform business generates more than $1.1 billion in annual revenue. And through the first half of 2026 grew faster than the overall company while delivering substantially higher margins. What began as a software product has evolved into a broad healthcare platform. TriZetto demonstrates how platforms can drive deep client relationships, create recurring revenue streams, and deliver growth and profitability that exceeds traditional services. It is a blueprint for how we intend to scale platform-led growth across other industries. In healthcare claims, we built a pioneering auto-adjudication solution that uses large language models to digitize adjudication knowledge and rules, enabling agentic AI to analyze claims, apply complex business rules, and reach decisions with human validation wherever it is needed. It positions us to take a share in this large high-volume category. Other platform-led modernization wins include a global claims and risk administration leader leveraging neuro AI, FlowSource, and our 3Cloud-enhanced Microsoft expertise; we signed a five-year agreement to accelerate processing times and upgrade core infrastructure. And TheMathCompany, a global data and analytics company, has deployed Cognizant's neuro business process workflow across multiple business operations processes. It resulted in over 40% improvement in the research task turnaround times and faster and higher quality resolution of their customers. We are also moving beyond delivery to underwriting results. We signed a major engagement with a leading insurance brokerage committing to more than 50% productivity improvement over five years through AI and operations operating model redesign. We won on the strength of our domain expertise, reimagining the core workflows and the accelerated delivery using AI tools from our partner ecosystem. As we execute these four shifts, our AI builder model expands where we create value across three categories. First, traditional work done dramatically more productively. Second, old things in new ways. And third, entirely new things that did not exist before AI. First, traditional work done more productively. This includes autonomous software engineering or vector-one work, which over the past two years has driven both consolidation and productivity-led engagements. A great example of our success in this area is Novartis, which selected Cognizant earlier this year for a five-year engagement to transform its global IT operation. Building on a relationship that spans more than 20 years, we expect to leverage our neuro AI platform to create a unified AI model that combines automation, full stack observability, and agentic capabilities. This is where our AI builder strategy is aimed, helping clients move from labor-intensive operations to intelligent self-service and increasingly autonomous technology environments. Second, old things in new ways. Here, we see a significant pipeline across secure AI services, mainframe modernization, SAP S/4HANA migration, and SaaS reimagination — long-standing enterprise challenges that AI can now solve far faster for a fraction of the cost. Cybersecurity is a clear example. AI is turning security from a cost center into a remediation opportunity as machines expose vulnerabilities at unprecedented speed. We are positioned for this moment by combining frontier models with a 5,000-person security practice and all the leading frontier program partners, including CrowdStrike, Palo Alto Networks, Zscaler, Anthropic, OpenAI, Microsoft, and Red Hat. We see a strong pipeline forming across these partnerships. Third, entirely new things made possible by AI including context engineering, reinvention of business flows, industrialization of business operations, and physical AI. With physical AI, as intelligence begins to govern physical environments, we believe a new domain of autonomous operations will open. We launched our sovereign physical AI platform-as-a-service to position Cognizant ahead of this "iPhone moment" for robotics and infrastructure. This builds directly on a capability we have built over the past decade. More than 10,000 of our associates have trained AI and machine learning models for the world's largest technology companies. We are now repurposing that expertise for the enterprise through our AI model training and data services. For example, for a global automotive manufacturer we train models on the company's products, technical data, and visual content to achieve accuracy that generic models cannot match, automating complex processes and unlocking value from knowledge the company already owned. Public sector is emerging as a meaningful business as organic and inorganic gain traction. In Q2, Cognizant Government Solutions, building on our Belcan acquisition, secured a landmark engagement with the state of Iowa to modernize its IT infrastructure. We have a growing pipeline in defense, federal, and state government, including AI infrastructure and citizen experience, while TriZetto expands the opportunity to health agencies, including our work supporting the Department of Veterans Affairs in partnership with Signature Performance. This builds on our long-lasting UK public sector practice. For example, with the Home Office, we developed and support the foundational data platform behind the UK's migration and border systems. In Q2, we won expanded Home Office work across software engineering, testing, delivery, and managed services for critical case working systems, improving case worker productivity and reducing manual intervention. And for His Majesty's Revenue and Customs, we recently won additional work to help configure low-code services in support of build and DevOps functions that is valued at more than $250 million over the life of the deal, including option years. Our AI builder strategy is also gaining traction outside the U.S. For example, a global pharma company in Europe selected Cognizant as the sole partner to build and scale its enterprise data, AI, and agentic AI capability through a three-year agreement covering 68 projects initially. As the client's official AI builder, Cognizant will translate their agentic AI vision into a production-grade governed enterprise platform spanning all business domains globally. Cognizant also helped a large European bank to industrialize its mortgage process by building a mortgage operations agent which brings multiple specialized agents together to support complex decision-making, analyze business rule outcomes, propose remediation paths, and generate clear and actionable insights. To conclude, we are in the midst of a profound transformation with a clear vision for the industry's future and confidence in the expansive AI-led opportunity ahead. Our actions — deploying interdisciplinary talent, shifting to outcome-based models, and opening new value pools — are designed to drive sustainable growth. As we redefine Cognizant, we remain focused on our growth, on our goals of delivering top-tier growth, consistent margin expansion, and EPS growth ahead of revenue. Thank you to our associates, clients, and shareholders for your continued dedication, partnership, and trust. With that, I will turn the call over to Jatin.
Thank you, Ravi, and thank you all for joining us. We are pleased with our second quarter performance highlighted by industry-leading growth and steady adjusted operating margin expansion. We achieved these results while continuing to invest including in the completed acquisition of Astreya, new frontier skilling initiatives, expanded partnerships, and our AI labs and platform-led offerings. We also deployed more than $1.1 billion through share repurchases, reflecting our conviction in the long-term opportunity AI creates for Cognizant and our critical role as an AI builder. While market conditions remain complex, we have continued to deliver on our commitments while investing in and evolving our business for the future. Now moving on to the details of the quarter. In Q2, revenue grew 4.1% year-over-year in constant currency to $5.5 billion. Our sequential organic growth was at the high end of our expectations. Year-over-year performance was driven by volume growth, increase in third-party product revenue associated with our integrated offerings strategy, and inorganic revenue from our investment in 3Cloud. From a geographic perspective, growth was once again driven by North America. And from a services perspective, our BPO practice once again led growth while demand remained strong for data and cybersecurity, driven by AI adoption. We are also seeing strong growth from industry-specific AI-led transformation in financial services and life sciences. By segment, financial services again led with healthy growth across banking, capital markets, and insurance clients. Growth is also being driven by strong performance in the UK public sector. We are seeing legacy modernization programs accelerate as clients advance their AI journeys to address significant technology debt. This is also reflected in sustained bookings momentum. Health sciences was stable. Demand remains cautious and cost-driven with plans prioritizing vendor consolidation, legacy modernization, and compliance while discretionary spend faces tight scrutiny and must demonstrate a clear ROI. As Ravi mentioned, TriZetto had a strong quarter. Products and Resources were steady. Clients in retail, consumer goods, travel, and hospitality continue to navigate pressure from geopolitical uncertainty, supply chain disruptions, and elevated oil prices. We are seeing momentum in manufacturing, logistics, energy, and utilities where physical AI and smart manufacturing are creating compelling opportunities for us. Within communications, media, and technology, demand among comms and media customers is muted, consistent with last quarter. With technology customers, demand remains strong, driven by AI-native engineering, digital operations, data, and cloud services. As Ravi noted, we are already seeing momentum with Astreya, and we are confident our joint capabilities can generate attractive growth synergies in the years ahead driven by AI infrastructure buildout. Turning to bookings. We delivered another strong quarter of large deal bookings, signing seven deals each with TCV of more than $100 million, including three new logos. On a trailing 12-month basis, bookings grew 5% and represented a book-to-bill of 1.3. Annual contract value decreased modestly reflecting the impact of lengthening contract duration due to a greater mix of large deals. We are pleased with the growth we have delivered in new and expansion bookings, which grew in the mid-teens in the first half of the year. Moving to margins. During the quarter, we incurred approximately $84 million in costs related to the Project LEAP program we announced last quarter. In addition, as a result of Indian labor code regulations notified by the Indian government in Q2, we recorded an $81 million one-time benefit for a partial reversal of the India defined contribution obligation liability we had originally recorded in 2019. Excluding these impacts, second quarter adjusted operating margin was 16%, up 40 basis points year-over-year. Operational efficiency and favorable currency movements more than offset higher third-party costs and compensation costs, as well as the impact of our recently completed acquisitions. Now to details of EPS, cash flow and capital allocation. Second quarter adjusted EPS was $1.37, up 5% year-over-year driven by revenue growth, margin expansion, and lower share count. EPS was negatively impacted by a higher interest expense associated with $1 billion we borrowed under our revolving credit facility to fund the Astreya acquisition and share repurchase activity in the quarter. DSO was 88 days, up five days year-over-year primarily driven by a change in the business mix. This factor also led to a corresponding increase in payables and therefore the impact was neutral. To cash flow. Second quarter free cash flow was $459 million, bringing year-to-date free cash flow to $652 million. During the second quarter, we deployed $1.1 billion on share repurchases and bought back over 22 million shares at an average price of approximately $51 per share. This includes a $500 million accelerated share repurchase program announced in May. Year-to-date, we have returned $1.9 billion to shareholders through share repurchases and dividends and remain on pace to return about $2.6 billion. This represents more than 10% of our current market cap. We have also deployed $1.3 billion on acquisitions aligned with our AI builder strategy. Finally, we ended the quarter with cash and short-term investments of $1.1 billion. Turning to guidance. For the third quarter, we expect revenue to grow 3.8% to 5.3% year-over-year in constant currency. This includes approximately 200 basis points from our recently completed acquisitions. As we discussed on our last earnings call, our prior guidance range contemplated an improved discretionary spending environment at the midpoint. Instead, macro uncertainty has remained elevated. We have therefore revised our full-year revenue guidance range to 4% to 5.5% growth in constant currency. This includes 150 basis points of inorganic growth unchanged from our prior expectations, but similar to last quarter, our M&A pipeline remains active. We are focused on executing with discipline on opportunities aligned with our AI builder strategy. While discretionary spending has remained pressured, we have maintained good traction on large deals, which we expect to continue to ramp in the back half of the year. Our revised guidance range assumes the discretionary spending environment remains stable at the midpoint, while the high end contemplates an improvement in short-cycle revenue in the fourth quarter. There are no changes to our Project LEAP cost estimates or expected savings, and we continue to expect the program will run through the remainder of the year. Our adjusted operating margin guidance is unchanged at 16% to 16.2%, representing 20 basis points of year-over-year expansion. Our free cash flow conversion guidance for the year remains 90% to 100% of net income. Full-year tax rate is now expected to be towards the low end of our prior guidance range of 25% to 26%. Based on our current expectations, we expect our third quarter rate to be above the high end of the full-year range. We now expect full-year weighted average diluted share count of approximately 460 million, down from our prior estimates due to the pace of repurchases in Q2. Interest expense has also increased modestly reflecting a lower cash balance and the drawdown of our revolver this quarter. As a reminder, the previously disclosed enactment of the Indian Labor Code reforms in 2025 has resulted in a higher run rate of other expenses. We expect this below-the-line cost related to our India defined benefit plan will be around $10 million per quarter for the foreseeable future, consistent with the first half 2026 run rate. This is in line with our estimates in our initial guidance in February, but we are highlighting it to support your model. Our EPS guidance has increased to $5.70 to $5.82 representing 8% to 10% growth versus 7% to 9% growth previously. Finally, we continue to make progress and advance on our evaluation of potential primary and secondary listing in India, and we are working in close collaboration with external stakeholders and regulators. We will make a decision on this once we have visibility of the revised regulatory framework. We are pleased with the progress made to date and remain committed to acting in the best interest of our shareholders. We will provide updates as appropriate. With that, we will open the call for your questions.
分析師問答
Thank you. We will now be conducting a question-and-answer session. If you would like to ask a question, please press star then one on your telephone keypad. You may press star then two if you would like to remove your question from the queue. Participants using speaker equipment, it may be necessary to pick up your handset before pressing the star keys. In the interest of time, we do ask that you limit yourself to one question and one follow-up. Press star then one to register a question at this time. Our first question today is coming from Margaret Nolan of William Blair. Please go ahead.
Hi, thank you. I am hoping you can give us a little bit more commentary on the business momentum in the context of bookings growth compared to last quarter as well as that second half ramp-up that you had previously expected from large deals. Maybe update us on how those signings and ramps are progressing and how it now shapes your second half expectations.
We have continued to have good bookings momentum. Last quarter, we did 22% bookings growth. TTM this quarter has been 5%. If you take the first half, it is 6%. It is a tough compare also because we had two mega deals last year. And last year, we grew by almost 18% in Q2 last year. So keeping all this in context, I think we have done pretty well on bookings, and I actually feel very confident about bookings for the rest of the year as well. Now one of the nuances which we are excited about in our bookings momentum is financial services is really running hot. I mean, you have seen in Q4 we had 9% growth, in Q1 we had 10%-plus and now 12%. So financial services has seen a significant increase in bookings in the first half, and I expect that to remain very strong in the second half. We did seven large deals, three new logos. We are starting to see activation of $50 million to $100 million deals, which have significantly improved. If you take those two mega deals out and compare from last year, $50 million to $100 million deals have gone through a massive bump. $25 million to $50 million deals have gone through a massive bump. The percentage of new business has increased by about 10% in the first half compared to the prior period, which is also good because it translates to new build and incremental revenue for the second half. So we have had a pretty good step-up change in our bookings momentum. When we entered the year in 2025, we were at $27 billion TTM, and we got to $28 billion TTM. In the last two quarters, we are at $29 billion TTM. So we are starting to move up, and bookings are going to be a little bumpy between quarters. But if you look at the aggregate numbers and you look at TTM and you look at the tail velocity of the last two quarters, we feel very excited about the second half as well.
Thank you. And then on the BPO business, you have seen good traction there. Can you talk a little bit more about where you are seeing that traction from an end market? Is it really your vertical expertise that is helping there? Or is it more the partnerships that you outlined with the model providers and others that are important in this space? What is driving the success there, and how can you perpetuate it?
Great question. In fact, BPO has always been a blockbuster service line for Cognizant over the last three years. We continue to lead on industry vertical BPO. When I joined in 2023, the BPO organization was called Intuitive Operations, and it had embedded data, automation, and machine learning then, and now AI-led BPO. I have mentioned this in my remarks as well as in my commentary in the last year: the expansive opportunity of system integration services goes from a $1 trillion market where we build software systems for companies to embedding AI technology into business operations of firms, and that is going to move our market from a trillion dollars to $5 trillion to $6 trillion. It brings data, technology, and process together. So we are very excited about the BPO business. With the strength of model company partnerships we can apply AI not just for software engineering but for business operations, both vertical and horizontal, and platformize that. TriZetto is running at a higher velocity than the rest of the company and the BPaaS business underneath it, which is healthcare operations, is equally running with strong momentum. We want to replicate platform-led, AI-driven agentic business operations across companies. For example, we have a blueprint for Frontier-led F&A and a blueprint for Frontier-led customer operations. We have started to put that in the mix, which effectively means we can embed digital labor and human labor and deliver outcomes through Frontier operators in new archetypal roles. We also have a training capability now in AI data training services. Historically, we did this for the largest technology companies. Now we are transitioning that capability to the Global 2000 because if intelligence is going to be distributed, enterprises will build specialized models. We think we have a unique service to attach to it. We have 10,000-plus associates who work on data training services; that is a part of the BPO organization.
Very helpful. Thank you.
Thank you. The next question is coming from Jim Schneider of Goldman Sachs. Please go ahead.
Ravi, I think relative to your comments about corporates one out of four sort of pausing their AI progress because of cost or return issues. Can you maybe talk about more tactically? You have talked about how Cognizant can address that opportunity, but can you talk more tactically what customers are doing then? If they pause, what is their immediate action? Are they going back to more traditional implementation work or outsourcing work, or are they just pausing until they can get a better handle on the scenario? And how long would you think it would be on average engagement before you can really see for Cognizant a big uptick at customers like that?
Jim, great question. The first chapter of AI adoption was broad-based, open-ended, and experimental; the technology felt magical, so many organizations tried to use it in varied ways. As adoption matures into the second chapter, companies are becoming more deliberate: they focus on token economics and optimizing where to apply advanced reasoning. The step back from clients is often driven by a desire to reassess value: they ask, "Am I spending a lot on tokens and the AI stack and getting commensurate value?" If not, they pause and revisit optimization. The bridges to production value involve assembling context, tribal knowledge, guardrails, and grounding technology into the enterprise's heterogeneity. We see demand for building harnesses that capture context for repeatability; for model routing, which chooses between open-weight and frontier models depending on task; and for learning loops that integrate human and machine effort. We have a methodology called BASIS in our consulting organization that helps reinvent and reimagine these processes. Clients are coming back to us for frontier engineering capacity, Frontier operators, platforms, harnesses, context engineering, and workflow reimagining. Some clients are asking us to deliver AI-infused rate cards that embed pretraining and inference costs. Software engineering is relatively mature; business operations is earlier and represents the larger opportunity because embedding AI into operations is where the significant value pools lie. We are building platforms and services to help clients bridge from experimentation to production, and that heavy lift is what will drive incremental, sustained work for companies like Cognizant.
And then maybe as a follow-up, financial questions or maybe for Jatin. Can you talk broadly to your overall hiring headcount plan in relation to gross margins? I saw it tick down a little bit sequentially. I am assuming a lot of that was just Project LEAP and some efficiencies there. But maybe talk about your hiring plans over the next two or three quarters and to what extent you expect to be able to hold gross margins at or above the current level?
Thank you. As you rightly observed, we have flattish headcount between quarter one and quarter two. We continue to add recent college graduates to the company and have made good progress in the first half. We remain on track to get to approximately 20,000 new early-career hires by the end of the year. Project LEAP is also underway, and as a result, you will see a certain amount of headcount reduction. On balance, we expect headcount should remain range-bound versus increasing, and that is how we are budgeting and planning for the rest of the year. As far as gross margin is concerned, you will have noticed the improvement we were able to execute between quarter one and quarter two, which was roughly 60 basis points. We are still trending a little lower than last year, and we will continue to work on it during the course of the year. I do hope that we continue to show improvement as quarters progress.
Thank you. Our next question is coming from James Eric Friedman of Susquehanna International. Please go ahead.
Hi. Morning and good results here. I wanted to ask about the linearity of the remainder of the year. Jatin, the sequential assumption on Q4 looks like if you are at or just above the midpoint on Q3, you could be flat to slightly down in Q4 sequentially but there is some M&A in there. If you could help us think about how you are thinking about the sequential Q4 in particular on an organic basis, that would be helpful.
Sure. We have modeled it based on the trends we see every year. Superimposed this year are a couple of variables. One is the larger new and expansion percentage of bookings that we have seen from the beginning of this year. We have also seen the ramp-up of deals which are in transition now and which will move to billable volumes in Q3 and Q4. Finally, we do have a view on furloughs. As you know, furloughs are typically represented largely by banking and financial services, and that is continuing to be very robust this year. We have assumed a slightly lower proportion of furloughs coming in Q4. So the assumption is slightly superior sequential growth in Q4 compared to what we have seen traditionally in Q4, which is typically negative because of bill-days impact and furloughs.
Perfect. And then Ravi, I just want to ask about Products and Resources. It has been a couple of years now since Belcan closed. You had a ton of inorganic in the period of comparison in Q3. At a higher level, how is Products and Resources performing relative to what you had expected when you closed the deal?
That is a great question. One of my endeavors is to go beyond financial services and healthcare and create more diversity in our portfolio. We are very pleased with the performance in Products and Resources over the last few quarters. We have gotten good traction and new logos. You have seen mention in my remarks about Belcan and its tailwind with other public sector opportunities we have won using the Belcan engine. That is a great add to our portfolio mix. We are starting to see significant traction with clients on physical AI, which I spoke about. We have built a harness around it called the intelligence spine and recently hired a new leader for oil and gas. We are continuing to make good progress on diversifying our portfolio and Products and Resources is one of the important areas to do so. I believe the AI opportunity will produce leapfrogs of digital enhancement on physical things in Products and Resources, and you will see enterprises use AI to unlock more value in traditionally lower-margin businesses because of the productivity opportunity. Products and Resources is going to be one of our high investment zones in the future, and we will continue to invest to make it a very important portfolio for Cognizant. Thank you.
Thank you. The next question is coming from Darrin Peller of Wolfe Research. Please go ahead.
All right. Hey, thanks, guys. Can you just touch on how you would assess the market right now, especially for the larger deals? How important is pricing in these discussions right now? And when you are having these discussions with customers, what do they look like when large deals come up for renewal? Are they demanding more productivity savings now versus prior?
We have done productivity-led large deals over the last three years and have outperformed on our margin performance versus what we originally assumed. We have done well in winning more than half of the deals, leading to large deal momentum. We have progressively moved into 'old things in new ways,' such as mainframe modernization, SAP migrations, vulnerability remediation, and factory reimagination, which are starting to become large deals. 'New things in new ways' — using AI to do things that did not exist before — are often more modular. So the mix of deals has changed. Regarding productivity, unlike in the past where linear productivity improvements were constrained, AI introduces nonlinearity. You can capture productivity and pass it to clients while remaining margin accretive. Our margin profile and large deals both $50 million-plus and $100 million-plus are trending better than originally assumed. As long as we stay ahead on AI-led productivity across software engineering and business process operations, we can pass on productivity, stay competitive, and remain margin accretive. That flywheel is working well for us, and we expect the shift from software engineering to business process operations to continue because that is where the larger opportunity lies.
That is helpful. Maybe a quick follow-up on the path for scaling the Frontier-certified workforce you described earlier. What degree will this come from new hires versus existing employees, and how will you keep differentiating as other companies develop frontier workforces?
We are doing this at scale. We are hiring at the bottom of the pyramid from outside and building bridges from inside. We have the largest pool of Claude-certified architects and over 10,000 associates receiving badges across multiple model ecosystems. We are training extensively on Gemini and open-weight models. Bending the cost curve and having business context to deploy talent and deliver value at scale is how we differentiate. You need to reinvent flows, audit workflows, integrate agentic work into business processes, and do it at scale at a lower cost. We are combining early-career hiring from outside with upskilling existing employees to create a large pipeline of Frontier engineers and Frontier operators — the former engineers agentic solutions into flows, the latter operates blended digital and human labor. Our 30 years of experience operating at scale gives us an advantage in bending the cost curve and scaling this talent pool.
Thank you. The next question is coming from Tien-Tsin Huang of JPMorgan. Please go ahead.
Hey. Good morning. Thanks a lot. I just want to ask around financial services. It was up double digits and is growing at a premium over other sectors. In the past, we have looked at that sector as a leading indicator that other subsectors would follow. Do you see that being the case here? Should we be encouraged that other sectors will follow, or is there something unique about financial services in terms of their willingness to adopt AI-driven projects?
Absolutely. Financial services has always been a pioneering industry, high on technology spend and creating asymmetry using technology. They are on the cutting edge of AI. We have seen sustained growth: high single digits last year, 9% at the end of Q4, 10%-plus in Q1, and now 12% in Q2. Financial services is active across consolidation and productivity, modernization of landscape with AI, and building new things with AI to generate growth imperatives. I am optimistic financial services will lead the path and other industries will follow, and some industries may leapfrog, particularly industrial clients looking to move directly into physical AI. If you look at our exit rate for the quarter as a company, it is powered by financial services. We are excited about our momentum and expect strong performance as we exit the year.
Good. Thank you for that, Ravi. And then maybe for you both, an update on tokenomics — any update with respect to cost, usage, what you are hearing from your client base? I know you talked a lot about that at your AI event, but any update would be helpful.
Token economics remains a hot topic. The conversation has moved from raw token consumption to optimizing usage: not using tokens where they are not needed, leveraging open-weight models where appropriate, and building specialized models on open-weight bases. Clients are distinguishing between expensive closed frontier models and less costly solutions, capturing learning into feedback loops, and building proprietary alpha. This is particularly important for business operations, which is less mature than software engineering. We are bundling retraining and inference costs with our services and have arrangements with frontier model providers to bundle those services. That means the input factors are human effort, platforms, software, and frontier services, all bundled for an outcome-based output rather than an effort-based one. Crafting that offering is a critical capability we are building.
Our final question today is coming from Bryan Bergin of TD Cowen. Please go ahead.
Hi, good morning. Thanks for taking the questions. I am curious if you can share any kind of rough mix of the managed services business that already incorporates GenAI-led efficiencies? I'm trying to understand the balance of the multi-year book that still needs to go through a cycle of renewals so we can better project the potential crossover point when AI activity can more than offset that existing base compression and other factors.
Our revenue roughly splits into two components: time-and-materials and fixed-price, and fixed-price is now roughly 50% of our revenue. Time-and-materials is typically shorter-cycle business and gets refreshed with each renewal every six to nine months, sometimes 12 to 15 but generally not more than two years. That short-cycle business continuously embeds AI benefits into itself. For the remaining 50%, which is the fixed-price book, contract terms are typically between 24 and 36 months on average, with some longer and some shorter. We started embedding AI into our solutions more actively from the beginning of last year, 2025, so we are roughly halfway through that transition and have probably another half to go.
That is very helpful. Thank you. My follow-up is on Project LEAP. Any further details: how much of the plan have you actioned thus far? Any in-year savings realized here in Q2? Anything important for us to consider regarding pacing of cost and savings through Q3 and Q4?
We continue to execute the program. We took approximately $84 million of Project LEAP-related costs in Q2, of which about $55 million was employee severance and the remainder related to facilities, software, and other items. We have baked the savings from the program into our guidance range and believe we are executing well toward that goal. You should continue to see Project LEAP-related impacts evenly spread between Q3 and Q4 as we move forward.
And we will get full-year benefits next year. Project LEAP reshapes the cost of technology deployment in the market. To a large extent, this is about margins, but it is equally about growth. The question is can we get more growth using a baseline where productivity is shared with clients? That is a key part of the thesis.
That is clear. Thank you.
Thank you. At this time, I would like to turn the floor back over to management for closing comments.
Thank you so much for joining in today. We are very excited about our quarter two earnings. We continue to be in the winner's circle. We have confidence in staying in the winner's circle for the rest of the year and creating some nice tail velocity for the next year. We are excited about the activation of all three swim lanes: productivity, doing old things in new ways using AI, and new things in new ways using AI, which is primarily driving growth imperatives for enterprises. Thank you again for joining the call today.
Ladies and gentlemen, this concludes today's teleconference for Cognizant's second quarter 2026 earnings call. You may now disconnect or log off the webcast at this time and enjoy the rest of your day.