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Nov. 3, 2026
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The Hackett Group, Inc. (NASDAQ:HCKT) reported a transition toward a delivery model enabled by its proprietary artificial intelligence platforms to drive operating leverage and expand margins. Management stated that the market is shifting from experimental technology adoption toward transformation-led initiatives that require deep process expertise and benchmark intelligence to quantify value. The company integrated its benchmarking assets and transformation intellectual property into a suite of platforms designed to accelerate software implementations and enterprise-wide process reimagination. Management noted that client decision-making continues to be influenced by macroeconomic factors and concerns regarding the realization of returns on artificial intelligence investments. The firm is currently aligning its consultant base and resource staffing with the productivity improvements provided by its digital tools to support its financial objectives for 2027.
Operator: Good evening, and welcome to The Hackett Group Third Quarter Earnings Conference Call. [Operator Instructions] Please be advised, the conference is being recorded. Hosting tonight's call are Mr. Ted Fernandez, Chairman and CEO; and Mr. Rob Ramirez, Chief Financial Officer. Mr. Ramirez, you may begin.
Robert Ramirez: Thank you, operator. Good afternoon, everyone, and thank you for joining us to discuss The Hackett Group's third quarter results. Speaking on the call today and here to answer your questions are Ted Fernandez, Chairman and CEO of The Hackett Group; and myself, Ramirez, Chief Financial Officer. A press announcement was released over the wires at 4:05 p.m. Eastern Time. For a copy of the release, please visit our website at www.thehackettgroup.com. We will also place any additional financial or statistical data discussed on this call that is not contained in the release on the Investor Relations page of our website.
Before we begin, I would like to remind you that in the following comments and in the Q&A session, we will be making statements about expected future results, which may be forward-looking statements for the purposes of the federal securities laws. These statements relate to our current expectations, estimates and projections and are not a guarantee of future performance. They involve risks, uncertainties and assumptions that are difficult to predict and which may not be accurate. Actual results may vary. These forward-looking statements should be considered only in conjunction with the detailed information, particularly the risk factors that are contained in our SEC filings. At this point, I would like to turn it over to Ted.
Ted Fernandez: Thank you, Rob, and welcome, everyone. Thank you for joining us to discuss The Hackett Group's third quarter 2026 results and more importantly, the continued progress of our AI transition strategy. As we normally do, I'll open the call by providing overview comments on the quarter. We'll then turn it over back -- turn it over to Rob to comment on detailed operating results, cash flow and guidance. We will then review our market strategy-related comments, after which we will open it up for Q&A. We continue to build momentum as the market increasingly recognizes that meaningful ROI from AI transformation requires more than technology.
It requires deep transformation expertise and IP to reimagine critical processes, along with AI benchmarks to accurately quantify the value opportunity. These capabilities are closely aligned with Hackett's globally recognized transformation expertise and proprietary benchmarking and process intelligence. At the same time, the expanding use of our AI platforms, XT and AIX, across our primary enterprise transformation and software implementation offerings is beginning to improve sales and delivery productivity. As these benefits scale across our client base, we expect them to drive increasing operating leverage and margin expansion, strengthening our confidence in our growth and profitability prospects for 2027. Over the past 2 years, we have systematically built an integrated portfolio of proprietary AI-enabled platforms.
Hackett is an expert and ROI-led AI-enabled enterprise transformation company, with our platforms and domain expertise connected through the Hackett Intelligence layer. This layer combines our proprietary domain-specific Hackett Solution Language Model with our globally recognized benchmarks with transformation and software implementation intelligence to uniquely turn generic large language model imprints into actionable client-specific solutions, guided by measurable value and ROI, clearly our moat. XT and AIX are central to our transition. XT applies Hackett's benchmarking intelligence, best practices, capability maturity models and transformation expertise to identify performance gaps, quantify value, reimagine future-state processes and operating models, and develop decision-ready transformation solutions.
AI extends our implementation expertise and embedded intelligence to improve software implementation, speed, quality, productivity, as well as value realization. Together, these platforms will allow us to bring Hackett-specific AI-enabled acceleration and enhanced value realization to more than 90% of our current engagements. Last quarter, we indicated that the third quarter would be our inflection point for revenue, margin and profitability growth. For the third quarter, we reported net revenues of $68.9 million and adjusted diluted earnings per share of $0.39, which were at the midpoint and relative to EPS, at the high end of our previously provided guidance.
Revenue grew sequentially despite fewer available days from the second to the third quarter, and adjusted EPS was both sequentially up and also up on a year-over-year basis. Adjusted gross margins improved 80 basis points sequentially from the second quarter, and as compared to last year, 230 basis points. We also expect Q4 adjusted gross margins to significantly improve on both a sequential and year-over-year basis. We believe this revenue, margin and profitability progression provides early evidence of the benefits we are beginning to capture from our platform-enabled delivery model, the related resource alignment and the other related productivity actions that we've taken.
Client interest in AI adoption and broader digital transformation remains strong, but clients are increasingly demanding trusted value and ROI that supports the targeted initiatives. The key difference is, they are transformation-led, which clearly provides a clear indication that clients have moved from the AI-first tech approach. These engagements require the comprehensive reimagination of critical business processes and the related operating model changes, also rely on the modernization of enterprise application environments and data foundations required to support meaningful AI enterprise transformation solutions. Importantly, clients are generally pursuing what we describe as extended AI initiatives. These are AI opportunities that emerge or extend from broader enterprise transformation and application engagements rather than relying exclusively on stand-alone technology-first AI programs.
This pattern plays directly to our strengths. It allows us to build on our trusted client relationships, address larger transformation opportunities and incorporate AI scope into nearly all of our new engagements. We are encouraged by 3 developments. First, our XT and AIX platforms are beginning to improve the outcome and economics of how we sell and deliver our work by increasing productivity, strengthening client value propositions and supporting broader solution scope. Second, clients are moving from AI experimentation toward measurable enterprise value realization, which aligns directly with our enterprise transformation, software implementation, benchmarking and process-led expertise.
Third, the progression in our gross margins and our fourth quarter outlook increasingly reflect the operating and financial benefits we expected from resource alignment, delivery model transition and platform adoption. Beyond our enterprise transformation and enterprise application pursuits, we continue to help organizations architect and execute their agentic enterprise architecture plans that support their AI centers of excellence, leveraging our AI Explorer and ZBrain platforms. We also continue to discuss expanded collaboration with all 3 of our active channel partners, which we expect to evolve into more meaningful structured go-to-market initiatives.
On the balance sheet side, we expect to continue generating strong cash flow from operations, as Rob will point out when he speaks to our fourth quarter guidance, providing flexibility to support our dividend, repurchase shares, reduce debt and continue to invest in the development of our strategic AI platforms. With that, let me ask Rob to provide additional details on our operating results, cash flow and fourth quarter outlook. I will return with strategic and market commentary following Rob's remarks. Rob?
Robert Ramirez: Thank you, Ted, and welcome, everyone. I will start by reviewing our third quarter performance and conclude with a detailed discussion on our financial outlook for the fourth quarter of 2026. I will comment separately on the revenues of our Global S&BT, Oracle Solutions and SAP Solutions segments, as well as the total company. Our Global S&BT segment includes the benchmarking and business transformation offerings, executive advisory programs and our OneStream and eProcurement implementation offerings. Our Oracle Solutions and our SAP Solutions segments include the results of our Oracle and SAP offerings, respectively. Please note that we will be referencing both total revenues and revenue before reimbursements in our discussion.
Reimbursable expenses are primarily project travel-related expenses passed through to our clients that have no associated impact on our profitability. During our call today, we will also reference certain non-GAAP financial measures, which we believe provides useful information to investors. Specifically, all references to adjusted financial measures will exclude reimbursable expenses, noncash stock-based compensation expense, all acquisition-related cash and noncash compensation expenses and reversals, amortization of intangible assets and other nonrecurring items, including our AI transition charge. We have included reconciliations of GAAP to adjusted non-GAAP financial measures in our press release filed earlier today and will post any additional information based on the discussions from this call on the Investor Relations page of the company's website.
Given the significant operating changes due to our AI transition strategy, most of my commentary will focus on sequential financial performance in order to best review our progress. As Ted mentioned, our third quarter revenue before reimbursements improved sequentially to $68.9 million from $68.3 million in last quarter and came in at the midpoint of our range, while adjusted earnings per share of $0.39 was at the high end of our guidance. As expected, Q3 demonstrated improved sequential revenues on fewer available billable days, as well as sequential and year-over-year adjusted EPS growth.
Additionally, Q3 included improved gross margins, reflecting the increased sales and delivery productivity gains from the use and adoption of our AI-enabled delivery platforms, along with the corresponding headcount reductions. As Ted mentioned, the value of our expertise and IP in helping organizations and channel partners is becoming increasingly evident. We are also beginning to realize the benefit of actions being taken to align our resources with the productivity potential of our AI-enabled platform delivery model and any AI-related disintermediation impact. Our platform delivery model is changing how work is priced, staffed, managed and delivered.
As we continue to increase the use of our 2 primary AI platforms, XT for enterprise transformation and AIX for software implementation engagements, we expect to capture increased sales and delivery productivity benefits. Total revenues before reimbursements from our Global S&BT segment were $36.6 million for the third quarter of 2026, a sequential increase of 3%. Clients continue to question the underlying ROI value of AI initiatives, which has led to elongated decision-making throughout the year. This concern has also emphasized the critical role and value that our Hackett benchmarking and enterprise transformation IP provides organizations in their efforts to accurately reimagine critical workflows and estimated ROI and achieve targeted valuable realization and business outcomes.
Total revenues before reimbursements from our Oracle Solutions segment were $15.9 million for the third quarter of 2026, a sequential increase of 4%, reflecting increased use and favorable impact of our Oracle AIX platform to help sell and implement Oracle solutions. We expect sequential improvements in revenue per available day and gross margin both across our S&BT and Oracle segments as the differentiation and acceleration, enabled by our XT and AIX platforms, fundamentally enhances our ability to attract new clients and execute existing engagements.
Total revenues before reimbursements from our SAP Solutions segment was $16.4 million for the third quarter of 2026, a sequential decrease of 6% due to lower VAR software sales when compared to the previous quarter as expected. We expect the normal year-end increase in software sales, although Q4 software revenue is expected to be lower when compared to the $10 million record fourth quarter reported last year. Total company adjusted gross margin on revenues before reimbursements was 44.9% in the third quarter of 2026, up from 44.1% in the previous quarter and 42.6% in the third quarter of the previous year. As expected, we reported sequential gross margin improvements across all segments.
More importantly, we expect further margin improvements in Q4, consistent with our guidance. Adjusted SG&A was $16.6 million or 24.1% of revenues before reimbursements in the third quarter. This is compared to $17.4 million or 25.5% of revenues before reimbursements in the prior quarter. This decrease is primarily due to AI transition productivity actions taken. Adjusted EBITDA was $15.4 million in the third quarter of 2026 or 22.4% of revenues before reimbursements as compared to $15.3 million in the prior year or 21.2% of revenues before reimbursements.
GAAP net income for the third quarter of 2026 totaled $3.6 million or diluted earnings per share of $0.14, as compared to $4.4 million (sic) [ $2.547 million ] or $0.09 in the previous year. The company's cash balances were $12.6 million at the end of the third quarter, as compared to $14.2 million at the end of the previous quarter. Net cash provided from operating activities in the quarter was $1.8 million, primarily driven by net income adjusted for noncash activity, partially offset by increases in accounts receivable. During the quarter, we repurchased 226,000 shares of the company's stock for an average of $10.85 per share at a total cost of approximately $2.5 million.
Our remaining stock repurchase authorization at the end of the third quarter was $16.3 million. Given the increase in VAR-related revenue over the last 2 years that carry multiyear terms and consistent with last quarter, we revised our DSO calculation to exclude those revenues and receivables. Our DSO was 64 days compared to 56 days in the previous quarter. The increase in DSO is primarily driven by milestone deliverable terms on several large technology engagements. At its most recent meeting, subsequent to quarter-end, the company's Board of Directors declared the fourth quarter dividend of $0.12 per share for its shareholders of record on December 24, 2026, to be paid on January 8, 2027.
The balance of the company's total debt outstanding at the end of the third quarter was $86.1 million. During the quarter, the company amended and restated its credit facility to extend the maturity date and increase its borrowing capacity to $125 million. Before I move to the fourth quarter of 2026, I would like to remind everyone of the seasonality of our business. Specifically, the increased holiday and vacation time that is historically taken in the fourth quarter will decrease our available billing days by approximately 6% to 8% when compared to the third quarter. One additional factor included in our fourth quarter guidance is the impact of our 53-week fiscal year.
Approximately every 6 years, our fiscal calendar includes an additional week, making this year's fourth quarter a 14-week quarter. Given the year-end timing of the additional week, it essentially carries a full week of payroll-related costs, while generating limited incremental revenue due to the holidays. We expect this calendar effect to reduce fourth quarter adjusted diluted EPS by approximately $0.03 per share, and that impact is fully reflected in our guidance. For the fourth quarter, we expect total net revenues of $68 million to $70 million, adjusted gross margin of approximately 48.5% at the midpoint and adjusted diluted earnings per share of $0.39 to $0.41, which assumes a GAAP effective tax rate on adjusted earnings of 26.5%.
This guidance is despite fewer available billing days and the additional week in fiscal 2026. This outlook continues to support our increasing momentum, which is further reinforced by recent wins, increasing lead flow and higher overall market activity. Our expected fourth quarter gross margin of approximately 48.5% compares to 46.6% in Q4 of the previous year, which benefited from record VAR revenues of more than $10 million that carried high margins. We do not expect to repeat that level of VAR revenue in the fourth quarter of 2026. The expected margin improvement provides further evidence of stronger underlying delivery economics across the business.
As already mentioned, the fourth quarter has fewer available days because of the greater concentration of holidays and vacation time. When taking into consideration the decrease in available days, Global S&BT and Oracle revenues would be flat to slightly lower but would represent a meaningful improvement in revenue per available day, while the expected sequential increase in SAP provides an additional contribution to our outlook. Taken together, our fourth quarter outlook reflects improving revenue productivity and delivery economics despite the difficult prior year VAR comparison and the approximate $0.03 per share impact from the additional week in 2026.
As a result of the continuing transition of our business to AI platforms-related delivery, the company expects to incur an AI transition charge in the fourth quarter of approximately $1 million. We expect adjusted SG&A and interest expense for the fourth quarter to be approximately $19.8 million. We expect fourth quarter adjusted EBITDA as a percentage of revenues before reimbursements to be in the range of approximately 23% to 24%. Lastly, we expect cash flow from operations to be up on a sequential basis by approximately $20 million (sic) [ $15 million ] to $20 million with a corresponding decrease in accounts receivable of $4 million to $5 million.
Consistent with our normal capital allocation strategy, the cash flow would be used to pay down debt or repurchase stock. At this point, I would like to turn it back over to Ted to review our market outlook and strategic priorities for the coming months.
Ted Fernandez: Before I start with my strategic and market comments, let me just make a quick correction. Rob meant to say $15 million to $20 million as being the cash flow from operations versus the $20 million to $20 million that he mentioned.
Robert Ramirez: Yes, $15 million to $20 million.
Ted Fernandez: Looking forward, let me share our view of the near and long-term demand environment and the opportunity it creates for Hackett. Demand for digital transformation remains strong, although client decision-making continues to be affected by macroeconomic concerns and competing investment priorities, as organizations determine how to move from AI experimentation to scalable enterprise value solutions. The central issue is no longer whether AI will matter. It is how organizations identify the right opportunities, redesign the work around them, validate expected ROI and deploy solutions with client-specific process context, data, controls and governance required to perform reliably at scale. The market is increasingly recognizing that high-impact AI solutions require more than generic inference and compute models and technical implementation talent.
They require deep process expertise, benchmark intelligence and an understanding of the company-specific operating context to reimagine work, validate requirements and quantify value. Forward-deployed technical engineers are important, but they must be complemented or led by forward-deployed business expertise and deep domain expertise and IP. This development plays directly to Hackett's capabilities, brand permission and trusted executive relationships. Our message to the market is clear. Organizations should not simply deploy more AI tools.
Sustainable ROI requires them to reimagine how work gets done, understand about the underlying value of their differentiated strategic knowledge, or [ alpha ], and determine how to embed it in their business through proprietary models and solutions and leverage that knowledge to redesign processes, roles, data and controls. We are applying that same principle internally as we transform how Hackett sells and delivers its expertise and IP, leveraging our Hackett AI platforms. We believe this is creating a new category of platform-enabled solution services. Our objective is to productize and scale Hackett's intelligence and expertise, while capturing client-specific context required for complex enterprise transformation and software implementation initiatives.
The result is a model that can increase speed and consistency, improve delivery economics, expand addressable opportunities, and create higher margin and potential recurring revenue over time. AI transformation is not technology-first, it is process-first, domain-specific, context-rich and transformation-driven. That creates significant market opportunity for Hackett. Clients and strategic partners need a trusted independent way to capture and validate their current operating reality and compare performance with peers, digital world-class and emerging AI world-class performance standards, identify and prioritize value initiatives and convert those opportunities into implementation-ready solutions with measurable value realization plans. We are uniquely positioned because we're not simply advising clients about AI.
We are embedding our benchmark intelligence, best practices, domain expertise and transformation methods into proprietary platforms that help identify and validate and realize the measurable value. Our current platform portfolio connects enterprise transformation, software implementation, agentic automation and data assurance into execution-ready intelligence through a common Hackett Intelligence layer. XT is the transformation intelligence and solution design platforms within that ecosystem. It brings together client operating data, strategic priorities, stakeholder insight within Hackett process and performance intelligence to prioritize opportunities, design future-state and build those value cases. AIX is our intelligence into software implementation and data, utilizing or extended through our XDA platform, helping improve delivery quality, reduce implementation risk and accelerate value realization.
Our portfolio, including AI XPLR and ZBrain, provides key complementary capabilities across AI opportunity identification, agentic workflow design, orchestration, build and governance. The financial progress is beginning to connect our strategy to the economics of the business. While quarterly mix will continue to affect reported margins, we believe that the trend demonstrates how increasing Hackett AI platform adoption creates scalable delivery, which can improve Hackett's growth and earnings profile. As adoption expands, we expect to improve sales effectiveness, delivery productivity, solution consistency, while also supporting broader engagements and additional high-margin and recurring revenue opportunities. The early operating evidence strengthens our confidence in Hackett's growth and margin prospects for 2027 and beyond.
We have just begun to realize the benefits of our AI transition strategy. On talent, we remain focused on aligning our associate base with the skills, behaviors and delivery methods required by our AI platform-enabled model. This includes equipping our professionals to use the platforms effectively, redesigning staffing and governance, while continuing to recruit experienced delivery and market-facing leaders with strong technology agility. Overall turnover remained at acceptable levels during the quarter, and we expect that trend to continue. Finally, we believe we have the client base, IP, platforms and offerings required to grow organically.
We will continue to evaluate acquisitions and alliances that strategically leverage our intelligence and expertise, enhance our platform ecosystem and add complementary capabilities that can accelerate our scale. As always, I will close by congratulating our associates on their continued innovation and contributions and thanking them for their tireless focus on our clients and our people. Those conclude my comments. Operator, please open the call for questions.
Operator: [Operator Instructions] The first question is from George Sutton with Craig-Hallum.
George Sutton: Ted, you made some compelling points about the AI piece of the story really just beginning for you and a lot of momentum you're seeing. Q4 is going to be a little odd because of the calendar and because of the VAR comparison from last year. I'm wondering if we could just look a little further forward and try to understand when we really start to see the dynamic impacts of what you're seeing in AI momentum. And I'll bet $100 you're on mute.
Ted Fernandez: Thank you, George. I said that we believe that we should expect net revenue growth early in 2027, which should allow us to not only do that, but to also continue to increase the gross margins and operating leverage that we will increasingly get through the adoption of our AI platforms. I mean, when we're saying we're early, we are early. And how early? Gosh, 10% of the way.
So, I mean, the scale opportunity, the operating leverage opportunity from the platforms is really very unique and very different than our traditional model, and that expands as adoption happens both within the organization -- I mean, we're expecting to execute entire engagements within -- inside of the platforms and to expand that, as I said, to more than 90% of the opportunities that we're able to field going into 2027.
So the combination of those things, George, is that, as we say, it really -- our prospects for 2027 are very good, and we just need to keep executing, doing all the hard things, change management, getting everybody trained, understanding how to utilize the platforms, how we curate information, how we validate the opportunity -- the outcomes closely with clients. But there is no doubt that the acceleration, as well as the enhancement of scope that come from the platforms, is very powerful.
George Sutton: You mentioned that all 3 of your go-to-market partners, I don't remember the exact term you used, could become more formal programs or more significant programs. I wondered if you could just layer in a discussion on that.
Ted Fernandez: I think the most important thing that we learned from our previous experience early in the year is that it's really critical for us to be -- to participate with a partner in a co-led situation where not only the capability of our platform, but the expertise of our people is brought to bear when somebody is trying to actually develop a strong business case for a new client and to validate and measure that accurately. What that is forcing us to do is to simply say -- let's put it this way.
If they've asked for the IP, if they want access to what we call our -- let's start with our AI world-class benchmarks, but the broader Hackett Intelligence layer. I mean, we're putting very significant prices on that -- on how somebody would buy that on a 3-year basis with very high annual amounts. That conversation then drives someone, at least for now, to a conversation that if you're interested in leveraging us to help you optimize your opportunities and your clients that you need to give us -- you need to let us be actively involved and have a meaningful participation in both the work and the revenue that's generated.
The clients -- the strategic partners we're currently involved with, all 3 agree and understand how important it is to not only utilize our IP, but the value of the platforms, I think, surprises them. And then, they know that our professionals in front of clients, when speaking to value realization and ROI capture, is really, really strong. So I think they accept that.
So what happens when you have that kind of conversation, then it immediately requires you to have a more structured conversation as to then the nature of the opportunities you're going to have because we'd be working with some of their most significant opportunities, or at least helping them with some, either in the pursuit or helping them with the execution and value capture on those that they've already got in place. So that's why we -- look, we continue to believe that from those conversations, those relationships will expand. And who knows? Maybe some of them can evolve to something much more.
George Sutton: So I know that Rob was hoping for a question himself. And Rob, the question is, your operating cash flow, sequentially from Q3 to Q4, it sounds like it could be 2 to 3x what it was last year and significantly more if your original script numbers were right. So can you just walk through what is going to drive that?
Robert Ramirez: It's not 2 to 3x last year, George. Last year, cash flow from operations, if I remember correctly, it was about $20 million. And we expect -- again, in Q4, what we're targeting this year, again, is another $15 million to $20 million. So it's not 2 or 3x last year, if that was your question.
George Sutton: Okay. Maybe I was looking at the wrong comparison.
Operator: [Operator Instructions] The next question in the queue is from Jeff Martin with ROTH Capital Partners.
Jeff Martin: Ted, could you verify that you said, starting early in 2027, you expect net revenues to show year-over-year growth?
Ted Fernandez: As early as possible, Jeff. That's our target, as early as possible. But yes, because -- so the question is, the disintermediated portion of our revenue played its way all the way through? Since we're touching the clients now so broadly and deploying these platforms across nearly all of our services that we provide -- or our primary 2 to start with. We believe we're very close to that. So new business will come in, will be sold at higher margins. And depending on the nature of the work, the platform is going to allow us to do that with higher margins than anything we've ever achieved historically.
Jeff Martin: Do you mind segregating the Global S&BT segment with respect to when you expect a year-over-year inflection in terms of the results into a growth?
Ted Fernandez: Do you mean specifically to GSBT or to software implementation or AI? Are you saying address SBT or the other 2?
Jeff Martin: SBT, please.
Ted Fernandez: Well, the most significant thing for GSBT is that we recently launched a platform. It's the Version 2 of XT that really -- that powerfully integrates just all the critical transformation elements. And that capability allows us to capture client context and critical information to create a very powerful baseline solution for a client in really -- let's just say, in half time just for -- just to kind of throw out a target out there -- in half time from our traditional way.
But it not only allows us to do that in half time, it also increases scope because this XT platform not only captures what we would historically address in an enterprise transformation opportunity, but as you can imagine, every single area of the business has to evaluate or at least get a sense for what that extended agentic opportunity is. So we are able to get in front of a client, bring the -- our transformation expertise to bear, work through sophisticated best practices, capability model assessments, operating model assessments but being led by digital and world-class -- digital and AI world-class benchmarks that really signal the performance -- identify the performance gap very, very accurately.
So our ability to not only size, what we would call, traditional work and value, now extend that into AI, which is material to where a digital world-class, which we define pre-LLM would be, so that expanded scope is then significant. So this ability to get in front and be able to have a very powerful detailed conversation and discussion with the client, put together a prioritized set of initiatives, that can extend -- that does 3 things: evaluates the opportunity with your existing automation footprint, looks through to the extended agentic capabilities that we're seeing inside of Oracle, SAP and virtually any enterprise company, and go all the way and extend it into custom agentic workflows.
This allows us to have a powerful enterprise transformation conversation and allow the client to decide sequencing or extent, how aggressive based on their strategic objectives and also their capabilities and how mature their underlying infrastructure and capabilities are. It's incredibly powerful. And so, to me, the biggest difference in 2027 relative to GSBT is that we've got a very strong and very broad platform in XT that allows us to frame value for clients very broadly, very detailed, and I'm going to say, hard to match time. And I don't know anyone who extends their benchmarks all the way out below subprocess levels and extend that all the way out to AI world class today.
So we just think we're well positioned to get in front of clients and be more compelling than we've ever had and to demonstrate value to them in a time frame that allows us to -- what we hope that it will allow us to maintain real continuity with the client so that we can get ahead of the curve instead of proposing ideas, having things thoughtfully reviewed and having gaps of time for both us and the client. So it impacts clients. It impacts us. And at the end of the day, I think it gives the client a very powerful and complete look of what their enterprise transformation objectives or opportunities are.
So we'll find out more as we continue to get in front of new opportunities with XT. What we know is, with AIX, because of the wins we've already experienced, is that similar capability, but primarily focused on the requirements, configuration, build, test part of an enterprise application engagement that our capability is cutting edge, is the way I would describe it. And yes, so what are our limitations? The scale of the organization, but it's not the capability of the organization. So we're going to find out.
Jeff Martin: Okay. One more, if I could. Could you talk about how your sales pipeline and sales lead generation has evolved over the course of the year? I know channel partners was intended to be a big part of that. And given what happened with the one partner earlier this year, that may have changed. So I wanted to throw that out there.
Ted Fernandez: Well, we clearly did expect, I'll call it, third quarter assistance, which obviously we didn't need, but that we thought could then like accelerate, okay, the -- accelerate performance in transaction if it would have played out. But what we now know is that the right way to do it was not the way we were -- kind of had structured it, which was to transfer more IP and outcome than to actually co-lead and participate in some of these meaningful opportunities in a more meaningful way.
So when we now look at the opportunities we're now evaluating, even though in number, they don't come close to what we thought we would see relative to exposure and numbers with that previous relationship, but the total dollars could still be meaningful. So the goal, though -- the goal is that some of those relationships or one of those relationships goes from, I'll call it, meaningful participation in terms of deal size to more structured volume. Then we would really get the most powerful impact we would like to get. So we'll find out.
Operator: The next question in the queue is from Vincent Colicchio with Barrington Research.
Vincent Colicchio: Yes. Ted, how much of your current sales pipeline is now attributable to AI-related opportunities? And how does that compare to 6 months ago?
Ted Fernandez: Well, what's incredibly different is that we've kind of flipped it on its ear because we were measuring our AI opportunities at the beginning of the year based on AI-first or AI-direct AI automation kind of solution and implementation. So what's really changed in our favor is that, in fact, first that clients delayed that AI-first acquisition. You still see people struggling to drive large volume and deals relative to tech-led deals.
So what's happened for us is that since 90% of our lead flow come from a request for enterprise transformation assistance or software implementation assistance, modernizing a client system but driving that into some strong value propositions, I'm going to say that nearly all of our new enterprise transformation opportunities and software implementation opportunities now include an AI component. So from a volume perspective, we are extending to AI through a more traditional entry point, which allows us to sell into our traditional buyers. But there's also the other phenomenon that's happening.
The other dynamic is that clients appear to be increasingly more comfortable, given the ROI concerns that were voiced at the beginning of the year, to adopt or develop AI strategies that come from extending enterprise transformation or software implementation initiatives.
And I believe that the majority of the clients -- more than the majority, in fact, are going to develop AI strategies that extend from traditional enterprise transformation initiatives, but that extend all the way to AI, and traditional software implementation initiatives, which now SAP, Oracle -- I'll just speak to our 2 largest channel partners -- have their own agentic layers that they're introducing through extended capability so that you will see AI emerge from the agentic extensions of an SAP and Oracle, probably more volume, maybe -- dollar numbers may be lower -- than you would have gotten from an AI-first direct kind of opportunity, which today, right, the one organization that has clearly distinguished itself with that AI-first opportunity in very strategic industry areas is Palantir.
But everyone else, I think, is going to see clients move and adopt through the channel that I'm describing, extending versus direct AI-first, unless they've got something they're really excited about. And obviously, they make the right financial commitment to see that through.
Vincent Colicchio: And the strategic partner that -- where you had an issue, is there any new news to talk about there?
Ted Fernandez: Not a single word that we've said. All of our work has been through the 3 existing ones and others, but these are the 3 that we've spent more meaningful time with.
Vincent Colicchio: And then, one last one. Can you provide some color on the JV, if anything is new there to report?
Ted Fernandez: No. The fact is that the JV, to some extent, right, now is the beneficiary of the way we are able to extend from enterprise transformation and software implementation deals that extend into AI. So it's getting increased opportunities. Well, let's not say the JV because the JV was responsible for the licensing of the potential -- the licensing that could come from AI XPLR and ZBrain. All of the AI implementation work that we do is not in the JV, but it's in Hackett. So the JV specifically -- look, licensing opportunities in those areas are still further away.
The deployment of the engineers to assess, design agentic workflows and deploy them utilizing AI XPLR and ZBrain continue to pick up momentum.
Operator: And at this time, I show no further questions. I will now turn the call back over to Mr. Fernandez.
Ted Fernandez: Thank you, operator. Let me thank everyone for participating in our third quarter earnings call. We look forward on reporting our fourth quarter and the annual results sometime in early February. Thanks again for participating.
Operator: This concludes today's call. Thank you for your participation. You may disconnect at this time.
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