2026.10.09 | GP | Insurance | Acrisure Organic vs Inorganic Growth

Primary:

Acrisure, LLC

Associated:

BroadStreet Partners, Inc.

Trucordia Insurance Holdings LLC

AmWINS Group, Inc.

AssuredPartners, Inc.

USI Insurance Services, LLC

HUB International Limited

Higginbotham Insurance Agency, Inc.

Alliant Insurance Services, Inc.

Navacord Inc.

CRC Insurance Services, Inc.

IMA Financial Group, Inc.

The Ardonagh Group Limited

Alera Group, Inc.

GPN

RSC Insurance Brokerage, Inc.

AON

MMC

AJG

BRO

WTW

Howden Group Holdings Ltd.

Viewpoint:

Former Executive

Moderator: Todd Denker (TD)

Michael Zupa (MZ), Former Leader of Transformation Program Management for the East Division - Acrisure

SUMMARY

Overview

The discussion assessed how Acrisure can balance organic growth and acquisitions while evolving from a decentralized insurance brokerage into a technology-enabled financial services platform. The expert viewed AI primarily as a productivity and decision- support tool rather than a near-term replacement for brokers.

AI offers the greatest automation potential in document processing, submissions, renewals, policy comparisons, commissions, and analytics. Relationship-heavy commercial insurance, specialty coverage, wholesale, reinsurance, MGAs, and employee benefits remain dependent on human judgment and carrier access.

Acrisure’s central challenge is integrating data, systems, workflows, and cultures accumulated through extensive acquisitions. Its Auris platform has strong strategic potential, but its value depends on data quality, system connectivity, governance, employee adoption, and measurable workflow improvements.

Key Insights

AI adoption across insurance is still early. Larger productivity and margin benefits should emerge as isolated tools become connected across entire customer workflows. Auris represents a meaningful technology upgrade and places Acrisure in the upper tier for AI ambition, although enterprise- wide benefits remain unproven. Acrisure’s AI opportunity is expected to outweigh disintermediation risk by improving producer capacity, retention, service speed, and cross-selling. Management should prioritize integration and organic value creation before returning to high-volume acquisitions. Cross-selling could become meaningful if AI identifies genuine coverage gaps across insurance, benefits, cyber, payroll, wealth, and specialty services. Centralization creates producer-retention risk. Competitors may recruit advisers by emphasizing reduced autonomy. The company’s entrepreneurial culture is an advantage, but local commercial authority must coexist with centralized data,

10/11/2026 at 11:32 AM UTC

controls, technology, and shared services. The largest threat is execution overload from pursuing system migrations, AI deployment, centralization, branding changes, product expansion, and acquisitions simultaneously.

Competitive Landscape

Company or platform

Positioning

Advantages

Challenges

Acrisure and Auris

Potentially differentiated enterprise AI layer

Broad middle-market distribution, cross-selling potential, reusable workflows

Fragmented systems, inconsistent data, uneven adoption

Aon

Marsh

Established global brokerage technology

Standardized global data and strong placement tools

Less emphasis discussed on Acrisure-style middle-market breadth

Deep risk and actuarial capabilities

Extensive risk data and analytical tools

No specific weakness identified

Palantir infrastructure

Technology foundation supporting Auris

Enables orchestration across existing systems

Success depends on connectivity, accuracy, security, and adoption

Quantitative Insights

Metric

Industry AI maturity

Expert assessment

Approximately the second or third inning

Operating-model change

Expected over 3–5 years

Broader industry restructuring

Expected over 5–10 years

Acquired businesses

Approximately 1,000–1,100

Direct AI disintermediation exposure

About 5%–10%

Business facing pricing or service pressure

About 10%–15%

Expected displacement

Mid-single-digit range

Potential revenue improvement per participating client cohort

Directional 5%–10% over several years

Near-term retention pressure

Elevated over the next 12–24 months

Auris product vision rating

Approximately 4 out of 5

10/11/2026 at 11:32 AM UTC

TD: Hi, everyone. My name is Todd Denker, and I'm the moderator here with Guidepoint. I want to welcome everybody to Acrisure. How can this insurance broker best balance its organic and inorganic growth opportunities amid AI changes teleconference with Michael Zupa? We have a lot of clients submitted questions, and we'll try our best to cover as many of these as we can during the 60-minute call. I know there's another call scheduled for Acrisure on Monday, which will be another opportunity to go through the questions. I now want to introduce our advisor for today, Michael. If you'd like to give us a little background on yourself, that would be great, and then we can begin.

MZ: Yes, so I've been doing finance transformation for about 15 years, management consulting, all types of projects. Where I believe I intersect at this project is I was at Acrisure for 9 months and I was doing a lot of work with shared services, onboarding. They bought out several companies applying AI to... they went from an insurance brokerage to a Fintech company, so applying AI to account reconciliations in the accounting department, cybersecurity, everything like that, acquiring companies, getting that all rolled up. And then also we took some services that we put to a shared service company in Gdansk, Poland. So I believe I should be a value add to this project.

TD: Appreciate it. To start, just from a broad perspective, given your industry exposure, what are your thoughts on the impact of AI to date on the industry?

MZ: So you mean AI in general, not just in Acrisure, just in general?

TD: Right.

MZ: I mean, TD: Right.

MZ: yeah, TD: Right.

MZ: after this, we're going to get into Acrisure and all the specifics there, but just more broadly speaking to start, what are your thoughts on impact?

So I would say that, you know, AI has had a meaningful impact on insurance brokerages definitely, but I see it primary as an efficiency and decision support tool rather than a wholesale replacement for brokers, right? And that's very important. The largest near-term opportunities are in document ingestion, submission preparation, policy comparison, renewal workflows, commission reconciliations. You know, the impact will vary by segment, right? Personal lines and simple small commercial policies, they're more exposed to automation and digital distribution because, you know, those products are standardized and they require less advisory, you know, judgment. But, you know, complex commercial P&C, employee benefits, wholesale, reinsurance, let's say MGA businesses, you know, that will remain more relationship and expert driven. But AI can materially improve placement speed, underwriting analysis, risk selection, carrier matching, portfolio monitoring.

TD: Go ahead.

MZ: Sorry.

TD: No, go ahead. We're getting back.

MZ: No, yeah, that was, I wanted how much detail you wanted me to go into, that's a high level.

TD: Yeah, that's good. And then how far along do you think we are in this journey? Using the baseball analogy, what inning may we be in in terms of the effect AI could have in terms of upending the industry and benefiting the industry?

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MZ: Yeah, good question. So from a baseball inning standpoint, I mean, we're definitely early on in it, right? So I would say probably the second or third inning if you're doing baseball. And I say that because most firms have moved beyond experimentation and then they're starting to implement, you know, target use cases, document extraction, submissions and renewal preparation, service automation, reconciliations, and analytics, but relatively few have redesigned their end-to-end operating models around AI and enterprise scale. So the next several innings would probably involve connecting those point solutions across the full customer journey, like identifying a need, gathering exposure information, matching markets, preparing submissions, binding coverage, servicing policies, managing renewals, and identifying cross-sell opportunities. And that's where the larger productivity and margin benefits will emerge. So true distribution will take longer because, you know, insurance data remains fragmented. Products are regulated and contractually like complex and customers still have value, trusted advice, right? Negotiations, claims, and accountability. So I would expect meaningful operating model changes over the next 3 to 5 years, but a more fundamental reshaping of the distribution, staffing, and industry economics will probably unfold over the next 5 to 10 years.

TD: Okay, great. And now getting into Acrisure more specifically, while you were at the company, did you see firsthand the benefits of its AI technology investments, including that which was acquired from Tulco back in 2020?

MZ: Yeah, definitely. Like I said, they went from an insurance company to a fintech company. And by translating into a fintech company, they really took on AI and tried to take on a lot of the modern edge. So I would describe when it came to the Tulco development, I saw the strategic benefits probably of combining Acrisure's large distribution footprint and the acquired data with AI capabilities that could support document processing, submission and renewal preparation. Customer matching, cross-selling, like I said, the most immediate benefit was probably capacity. They use this to reduce the time employees spent collecting information, reconciling fragmented data, preparing documents, and identifying opportunities manually. So I also saw that the value of the AI investment depended heavily on integrating acquired businesses. Standardizing data and then connecting legacy agency management. Because they had a ton of finance and workflow systems. They acquired so many different companies. The technology itself is not the primary constraint. I'd say data quality, process consistency, adoption, and integration determine pretty much how broadly and quickly the benefits could be realized, some quicker than other based off compatibility issues of older legacy systems.

TD: And how do you think the implementation went in terms of how smooth was it? Were there hiccups along the way? What were your thoughts on that?

MZ: Yeah, some went real smooth that were easily compatible. Some needed to stay on their legacy system a little longer than what we liked. I would say mostly it was obviously done in a phased approach, which was successful. There wasn't overall friction, right? The technology could pretty much demonstrate value in focused use cases. But scaling it across an organization built roughly through about 1,000 acquisitions was much harder because individual businesses had different agency management systems, CRMs, data definitions, levels of technology maturity. The main hiccups in this were not necessarily failures of the AI model themselves. They were foundational issues: obtaining complete and consistent structured data, linking customers and policies across systems, building reliable interfaces, defining ownership of data and exceptions, and then embedding the tools into employing these normal workflows. Adoption also varied because producers and local teams needed to trust the output and understand how the technology would improve their work rather than add another administrative layer. There was also governance considerations around customer information, access permissions, model accuracy, auditability, cybersecurity, and then there's human review. For recommendations, let's say affecting coverage, placement, pricing, the organization could not simply allow an algorithm to operate without an accountable human oversight. Overall, I would not describe the implementation as a single big bang development. It was more effective when introduced use case by use case with measurable baselines, controlled pilots, human review and integration into existing workflows. I'd say if you want

10/11/2026 at 11:32 AM UTC

to talk about the lesson, the lesson was that AI can generate benefits relatively quickly in a contained process, but enterprise-wide value is going to require much more work around data, system integration, process standardization, the controls, and the change management.

TD: Okay, and do you think thus far they've handled the information reasonably as best as they could?

MZ: Yeah, they did it to the best of their ability with 1,100 different entities being combined onto their system. I think they did it to the best of their ability, definitely.

TD: Okay, and what are your thoughts on the Auris AI platform?

MZ: The Auris AI platform?

TD: Yeah.

MZ: So they just started kicking that off and using Auris to its full capabilities. Auris was definitely more enhanced than what they were using before. It was built from capabilities that originated with that Tulco insurance intelligence acquisition that were developed further internally. The intention of Auris was to connect data, workflows, and AI- assisted decision-making across Acrisure rather than operate as a standalone chatbot or an isolated analytics tool. My view on the implementation for that is that the platform's strategic design was strong, but enterprise development and deployment is necessarily complex, right? Auris can support producer insights. It was good with customer and carrier matching, renewal preparation, document analysis, cross-selling and workflow automation. However, its effectiveness is going to depend on connecting fragmented agency systems, standardizing customer and policy data and embedding its recommendations into that day-to-day workflow of producers and service teams. The main friction with that was therefore less about the underlying AI and more about data readiness, integration, user adoption, governance, and the scaling consistent processes across a highly acquired organization.

TD: From what you could tell, do you think they'll successfully be able to pull this off and implement it and maximize the benefits while minimizing the challenges?

MZ: Yes, I would overall say yes, but it is going to depend on a few things, right? So they can pretty much maximize Auris AI by making sure they have to treat it as an operating model transformation rather than simply a technology deployment. The first requirement to pull this off is common enterprise data foundation, consistent customer, policy carrier, producer, commission and product identifiers, clear data ownership. They need to prioritize a limited number of high-value, repeatable use cases where the data is available and the risk is manageable. So strong initial candidates for this would include document ingestion, submission preparation, renewal summaries, policy comparison, producer research, and then each use case should have a baseline for current labor hours, turnaround time, error rate, customer outcome and cost so that the business can prove whether Auris is creating measurable value. And then the third thing that they need to focus on is the implementation should be phased by business type and readiness rather than rolled out simultaneously across every acquired agency, right? Acrisure is going to need to pilot with several representative businesses, compare results with control group, resolve workflow and data issues, and then deploy through repeatable migration waves. What else do we have? The winning formula here is, therefore, I'd say, to standardize the data, select focused use cases, prove value and control pilots, integrate Auris into daily work, retain human judgment, of course, and then scale through disciplined waves. That approach would allow Acrisure to capture the advantage of its enormous distribution network without introducing unnecessary operational or customer risks, in my opinion.

TD: Okay. And is Auris a significant improvement, a big step up versus what they were working with in the past?

10/11/2026 at 11:32 AM UTC

MZ: Yes, it definitely was. They were working with kind of an in-house system that they acquired from... the Tulco Insurance. Right.

TD: Okay. And so does this indicate to you that they've just moved away from their legacy AI investments? Is MZ: Yes, TD: that what you're saying?

MZ: they definitely did. Yeah.

TD: Okay. Does that indicate anything to you or that they made a mistake or just the technology didn't work out?

MZ: No, I would say this is more of a technology upgrade and staying enhanced and staying more aligned with the enhanced systems is what I would say.

TD: Okay, and working with Palantir's technology infrastructure, does that make sense to you? Are you impressed with the product platform?

MZ: Well, it made sense. From a technology and infrastructure, definitely the concept made sense to me. The right decision, I'd say, for Auris is to sit above Acrisure's underlying agency management, the CRM, the policy, the finance and data systems as an orchestration and an intelligent layer, connecting information, applying models and inserting recommendations or even automated steps into existing workflows rather than attempting to replace every core platform at once. So I was impressed by the product's strategic ambition and by the decision to build a reusable enterprise AI operating system instead of deploying disconnected point solutions. So what I would want to validate before calling it fully successful is the depth of the system connectivity, the data quality, the user adaption, the model accuracy, response speed, security. The platform architecture appears differentiated, but the ultimate proof will be whether it producers and service teams use it consistently and whether it improves renewal speed, placement quality, cross-selling, retention, productivity, and margins, in my opinion.

TD: Okay. And was there anything about the platform architecture that you weren't particularly fond of that you felt could be improved upon?

MZ: Yeah, there are those things that can be improved upon. Well, let me think. At a high level, I would say what stands out to me is my main concern would be that I would probably say the AI layer itself, right? It would not be the AI layer itself. It would be the platform's dependence on a highly fragmented, underlying technology and data environment. When customer, policy, carrier, producer, and commission data originate from many agency management systems, CRM documents, and local databases, the architecture can become dependent on numerous point-to-point integrations and data transformation that increases reconciliation work, maintenance costs, and the risk that users receive incomplete or even inconsistent recommendations. So I would strengthen the architecture in about 5 layers, right? If it was me: First, establish an authoritative enterprise data layer with common identifiers and data quality rules. Secondly, you have got to use standardized APIs and reusable connectors rather than creating custom integrations for every acquired agency. It just would be too many. Third, you have got to improve lineage and explainability so users can see the source data and reasoning supporting each recommendation. Fourth, provide strong model monitoring, version control, access management, exception handling, and reliable shutdown or rollback capabilities. And then last, embed Auris directly into producer and service workflows so users do not need to move between separate systems. I would also keep the platform modular, right? At Acrisure, they need to be able to change individual models, data providers, or workflow components without rebuilding the entire platform or becoming locked into 1 model vendor. So my assessment overall is that the strategic architecture is compelling, but the data foundation integration layer and workflow embedding are the areas where continued improvement would create the greatest value, I feel.

10/11/2026 at 11:32 AM UTC

TD: Excellent. And how do you think overall their AI tool stacks up now versus competitors? Do you view it, their platform as being a competitive advantage, disadvantage, or largely in line with what others are doing?

MZ: Off the top of my head, I would kind of say that I'd like to say it's in line. Maybe it's giving them a slight advantage. I would have to place it in the upper tier of insurance brokerage for AI ambition, and particularly among acquisition- led middle market platforms. But I would not yet call it the undisputed industry leader. Auris is differentiated because it is polished as an enterprise operating layer connecting data workflows and AI assistance decisions, not merely a broker chatbot or single use copilot. So compared with the largest global brokers, Acrisure has both an advantage and a disadvantage. Aon's broker copilot is strongly focused on commercial placement and benefits from Aon's standardized global data and workflow scale. That was one company we benchmarked off, while Marsh has deep risk data, actuarial models, and tools such as risk companions. So Acrisure's advantage is the opportunity to apply Auris across a very broad middle market distribution network and multiple services. Its disadvantage is that the approximately 1,100 acquisitions have produced more fragmented systems and less consistent data. So on a product vision, I would score Acrisure very highly, perhaps 4 out of 5. On enterprise-wide maturity and consistently realized value, I would be more measured because adoption, integration, and data readiness will vary across the organization. So if Acrisure successfully connects the acquired business and embeds Auris into producer workflows, it could become a genuine competitive advantage. Today, I would describe it as a strong and potentially differentiated platform whose full economic value is still being proven.

TD: Okay. How concerning are these acquisitions in terms of fragmented systems and the disconnected data that we've been discussing? Do you think this is something they'll be able to successfully address or do you think it'd be too big of a challenge, too big of a hurdle to overcome?

MZ: The acquisitions in terms of the fragmented systems and the disconnected data is just a significant challenge, but I don't believe it's insurmountable. The concern is not simply the number of acquisitions, it's the diversity of agency management systems, CRMs, accounting platforms, local spreadsheets, data definitions, producer arrangements, carrier interfaces, and operating practices accumulate across those businesses. That fragmentation increases the cost of integration and makes it harder to establish a reliable enterprise view of customers, policies, revenue, commissions, renewals, and cross-selling opportunities. So the solution should not be to migrate every acquired business immediately onto one system. That would be expensive, it'd be slow, and it'd be operational risky. A more practical approach is to establish enterprise data modeling and common customer policy, carrier, and producer identifiers, connect priority systems to standardized APIs and reusable data pipelines, and then progressively retire or even consolidate the highest cost legacy platform. So I believe Acrisure can address the issue because it has the scale, the capital, the internal technology capabilities and strategic incentive to do this. Acrisure can also help create value before every core system is replaced, provided the platform has reliable access to standardized data. Success will require discipline, prioritization, strong data ownership, continued investment, and a willingness to accept that some specialized systems will remain. So I would expect the process to take several years rather than several quarters. The greatest risk is not that the technical problem is impossible. It's that attempting too much simultaneously, understanding local complexity or even declaring integration complete before data quality and adoption are stable. So if Acrisure uses a phase model... common data layer first, high value workflows next, and then core system rationalization over time, I believe it can successfully manage the fragmentation and ultimately turn the breadth of its acquired data into an advantage.

TD: And do you think they are moving at the most appropriate pace from what you could say?

MZ: From what I say, yes, you know, they don't want to go too quick. They're getting everything onboarded and they're trying to get it as automated as possible. But from a standpoint, you know, with these layers and these legacy data, you don't want to move through this at too fast of a pace. So I would say given the scale and operational risk, although Acrisure would ideally have begun deeper integration earlier in its acquisition journey, the company

10/11/2026 at 11:32 AM UTC

accumulated substantial integration debt by prioritizing the acquisition velocity and local autonomy. So management now faces pressure to move quickly. But accelerating this could, like I said, disrupt renewals, commissions, producer workflows and customer service. So the appropriate pace is different by layer, right? I don't want to get too into the weeds, but finance, governance, reporting, cybersecurity, procurement, master data, and repeatable shared service activities should move relatively quickly because the benefits are clear and customer disruption is limited. But then when you get to agency management systems, producer compensation, placement workflows, MGA underwriting, and customer facing processes, they're going to move more cautiously through pilots, parallel runs, and phased migration waves. So therefore, I describe the pace as deliberate, but needing strong milestone discipline. I would not measure progress only by how many systems or offices have migrated. I would look for declining manual work, fewer reconciliation acceptance, faster reporting, stable renewal execution, maintain producer and customer retention. And if those indicators are improving, the pace is appropriate. If technology milestones are being completed without operational benefits, then the program may need to be recalibrated rather than merely accelerated, if that makes sense.

TD: It does. And you noted the company shift to be more of a fintech company. Management refers to the company as a global fintech leader. At this point, to what extent would you agree with that assessment?

MZ: They refer to it as a fintech. I would agree that Acrisure has become substantially more technology-enabled. But I would describe it today as a global financial service and insurance distribution platform with meaningful fintech capabilities. And I say that rather than a pure play fintech company. Its core economics will depend heavily on insurance brokerage commission, producer relationships, carrier access, and acquired distribution business. You know what I mean? The fintech description is increasingly credible because Acrisure has invested in proprietary AI through Auris, expanded into payroll, cybersecurity, mortgage, wealth, and other services, and is attempting to connect those capabilities through data and technology. That is material; it's materially different from being a traditional brokerage that merely licenses third-party software. However, in my opinion, a true fintech leader should demonstrate a standardized, scalable technology platform, high levels of automation, consistent data across the enterprise, strong digital customer adoption, and then, of course, measurable technology-driven organic growth and margin expansion. Acrisure has the assets and strategic direction to get there, but the fragmented systems and operating models created by those approximately 1,000, 1,100 acquisitions mean that the transformation is still underway. I would characterize the global fintech leader language as a legitimate, you know, strategic aspiration supported by real investment, not simply marketing, but somewhat ahead of the company's fully realized operating model. The evidence here will be whether Auris and the broader technology platform materially improve producer productivity, customer retention, cross-selling, servicing costs, and organic growth across the entire enterprise.

TD: Earlier in the call, you assessed that AI would be more of an efficiency opportunity, cross-selling opportunity, and you kind of downplayed the risk to the direct distribution model. Could you elaborate on that? Are you not at all concerned about it? Are you only concerned for the personal lines and the less complex lines, or are you not even concerned for that? I'm just curious to see your thoughts in terms of how much of a risk this can be for Acrisure.

MZ: It's a normal risk. It's almost a risk that's unavoidable. That's why we're not really getting too into it and we're not overlooking it. Basically... When it comes to commercial insurance, I'd say AI is more likely to strengthen the direct broker distribution model rather than replace it. It can automate document ingestion, submission preparation, policy comparisons, renewal workflows, certificates, commission reconciliations, as I said. The risk is greatest in standardized personal lines and very small commercial accounts. This is when coverage is simpler and buyers are more price sensitive. Acrisure's core commercial benefits, specialty wholesale and MGA relationships still depend heavily on judgment, carrier access, negotiation, client trust. AI can recommend opportunities, but it generally cannot replicate the broker's accountability or relationships. For Acrisure specifically, the larger opportunity is using its broad customer and product footprint to identify coverage gaps and route qualified opportunities across insurance,

10/11/2026 at 11:32 AM UTC

benefits, cyber, payroll, and specialty capabilities. The main execution challenge is integrating fragmented customer and policy data well enough to generate accurate recommendations without overwhelming producers with low- quality leads. Therefore, I see AI primarily improving efficiency, service capacity, retention, and revenue per customer while posing a more limited near-term threat to relationship-based distribution models.

TD: Just as a rough estimate, nothing specific, approximately what percent of the business do you think could be at risk from AI disintermediation?

MZ: A rough estimate of what percentage could be at risk because of the AI.

TD: Just based on their exposure to personal and small commercial lines, things that may be less complex that may not benefit. Just a ballpark estimate in terms of, you know, where there could be challenges to the business.

MZ: I would say 5% to 10% of Acrisure's business directly exposed to AI-driven, you know. So perhaps 10% to 15% experience some pricing, commission, or service model pressure, right? The greatest exposure would be standardized personal lines, micro commercial accounts, and relatively simple employee benefit cases where customers can compare, purchase, and service coverage digitally. So that does not mean Acrisure would lose that entire revenue pool. Much of it can be defended by deploying its own AI-enabled workflow and offering a hybrid digital plus advisor experience. You know, complex commercial insurance, specialty risks, wholesale placement, MGAs, reinsurance, and sophisticated benefit relationships remain much less vulnerable because they depend on judgment, negotiation, carrier access, and trusted advice. So consequently, I would expect displacement to be measured in the mid-single digits, not a wholesale disruption of Acrisure's distribution model, provided it executes its technology and data strategy effectively.

TD: Okay, and do you think the benefits of AI to the larger commercial lines of business more than offsets the potential displacement whereby the AI demand impacts are actually a net positive development for Acrisure?

MZ: Yeah, I would say that it's definitely a net positive. When it comes to the AI with a large commercial line of business, I believe that AI is likely to be a net positive, particularly across larger commercial, specialty, wholesale, MGA, and employee benefit business. Those segments are difficult... they contain substantial administrative work that AI can streamline: submission preparation, policy analysis, renewal servicing, carrier matching, claim support, compliance documentation, and identification of coverage gaps. The potential benefit, therefore, applies across a much larger revenue base than the portion directly vulnerable to displacement. AI can increase producer capacity, lower service costs, improve response times, strengthen retention, and generate cross-selling without removing the human advisor. The qualification is execution. Acrisure is going to have to integrate its fragmented data, embed AI into everyday workflows, and achieve producer adoption. If it does that effectively, the productivity and revenue benefits should more than offset the mid-single-digit disintermediation risk.

TD: Okay, and do you think carriers want to go direct? Do they want to disrupt the broker model or do they like the way things have historically operated?

MZ: That's tough. I don't know if there's a straight answer. So that kind of depends. Acrisure's direction is not to eliminate or disrupt the human broker. It is to modernize and scale the broker model. So the producer relationship remains central because commercial and specialty clients still need judgment, carrier access, and advice. But Acrisure wants technology and AI to remove administrative work, improve client intelligence, and enable each producer to serve more clients and sell a broader range of solutions. So that strategic shift is from a collection of relatively independent acquired agencies toward an integrated technology-enabled financial service platform. What that means is preserving local relationships and entrepreneurial producer behavior while centralizing data, technology, finance, operations, and specialist capabilities. In effect, Acrisure is trying to disrupt the inefficient infrastructure surrounding

10/11/2026 at 11:32 AM UTC

the broker, not the broker client relationship itself.

TD: Given all the changes taking place, do you think Acrisure by and large is handling things most appropriately, moving at the right speed, making the necessary changes, or is there anything else you would suggest given what they're working with based on all the acquisitions that they've made?

MZ: Yeah, there's a ton of changes that have taken place. They've been handling it mostly appropriately. I think moving in the right strategic direction and the measured pace is understandable given the scale and diversity of approximately 1,100 acquired businesses. Moving too slowly prolongs duplication and fragmentation, but moving too quickly could disrupt producers' renewals, billing, carrier relationships, and customer service. This cannot be treated as a simple technology conversion. My recommendation would be to maintain speed on the common enterprise backbone, master data, cybersecurity, finance, reporting, procurement, treasury, shared services, and reusable technology integration, while moving more carefully on agency management systems, producer compensation, placement workflows, MGA underwriting, and customer-facing processes. I would also sequence migrations by business readiness rather than impose one universal timetable. Retain local finance and operational partners during the transition and then use parallel runs until service and data quality stabilize. Management should judge progress through business outcomes rather than system migration alone. Producer adoption, customer and producer retention, renewal cycle times, service levels, cross-selling conversion, organic growth, manual work reduction. This strategy is directionally sound. The greatest risk is attempting too many changes simultaneously or declaring integration complete before the data workflows and employee adoption are generally stable, in my opinion.

TD: Okay. And could you elaborate how significantly can AI indeed make Acrisure more relevant for clients and enable the company to sell additional solutions? How meaningful is this opportunity? How could they best approach it to fully capitalize on this opportunity?

MZ: Yeah, so this is definitely meaningful for them, right? AI is definitely relevant for the clients, for the company. You know, it could be a very meaningful opportunity, I'd say, because Acrisure serves many clients through only one part of its broader portfolio, right? A commercial insurance customer may also need employee benefits, cybersecurity, payroll, risk advisory, specialty placement, or wealth-related services, but those needs may remain invisible when customer information sits across separate acquired agencies and systems. So AI can improve relevance by creating a unified client profile from policy, claims, renewal, industry, workforce, payroll, and interaction data. It can then identify coverage gaps, lifecycle events, emerging risks, and next best action opportunities. For example, let's say recognizing that a growing construction client has added employees and locations but lacks cyber coverage, updated benefits, or adequate limits. The producer should receive a concise, explainable recommendation at the appropriate point in the renewal or client review cycle rather than a generic sales lead. If executed well, I would view 5% to 10% improvement in revenue per participating client-like cohort over several years as a reasonable directional aspiration, although results are going to vary materially by segment, right? But the best approach would be to establish a reliable customer and household identity across acquired businesses. Start with 2 or 3 adjacent products where the client need and producer referral path are very clear. Embed recommendations into the producer's existing CRM and renewal workflows. Explain why the opportunity was generated and provided supporting client facts. Keep the producer responsible for validating suitability and approaching the client. Track referral acceptance, quote to bind conversion, incremental revenue retention and client complaints, and then use the results to retrain the model and suppress low quality recommendations. Like, the biggest danger is solutions with inaccurate or poorly designed leads. Accuracy creates, you know, the most value when AI makes the broker better informed and more relevant to the client, not when it converts a trusted advisor relationship into indiscriminate product marketing.

TD: Are there additional solutions for Acrisure to seek to expand into as they seek to better capture business with existing clients? Anything out there? Talk about holes in clients' portfolios, but are there any holes in your perspective

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from Acrisure's capabilities?

MZ: Yeah, I mean, I think Acrisure can expand wallet share most effectively through solutions that naturally connect to information already gathered during the commercial insurance and benefit process. The strongest, you know, ones would include cyber risk assessment and managed security, payroll and HR technology, retirement and wealth solutions, claim and risk control services, premium financing, specialized industry consulting. So I would prioritize in 3 tiers. First are immediate extensions such as cyber, employee benefits, payroll, and risk management. This is where the same decision maker and renewal information are often involved. Second are financial solutions such as retirement plans, executive benefits, wealth management, and premium financing. Third and last are more specialized services, compliance support, captive advisory, climate analytics, and vertical specific risk solutions, which they may deepen larger relationships, but they require distinct expertise. So the governing principle should be client relevance rather than simply accumulating products. Acrisure needs to expand where it has a trusted point of access, differentiated data, and credible delivery capability, and a clear referral path. Otherwise, you know, excessive product could create complexity without producing meaningful cross-selling opportunities.

TD: Okay. And the company has talked about its entrepreneurial DNA, that results in client centricity and innovation and what they refer to as an indomitable will to win. What are your thoughts on the company's culture and how, if at all, may this be benefiting them or even changing as a result of all the changes taking place?

MZ: As far as the results, they are definitely client-centric and innovation is a big win for them. Acrisure's entrepreneurial culture is a genuine competitive strength. Many of its businesses were built by founders and producers who operate with strong local ownership, urgency, commercial judgment, and personal accountability for client relationships. That support, responsiveness, the innovation, the producer recruitment, and the willingness to pursue opportunities that other institutions might miss. The complication is that Acrisure is not culturally... it is a collection of many acquired organizations with different histories, incentives, systems, and leadership styles. As the company centralized, employees may interpret standardized processes, common technology, tighter controls, and enterprise branding as a reduction in local autonomy. If handled poorly, that could weaken the very producer energy and client... that creates Acrisure itself. The culture, therefore, needs to evolve from independent entrepreneurship to connected entrepreneurship. Producers and local leaders should retain authority over clients, market relationships, and commercial decisions, but also doing this while accepting common standards for data, finance, cybersecurity, compliance, technology, and even service quality. Management should explain what is being centralized, what remains local, and how enterprise capabilities make producers more successful. The will to win is beneficial when it produces client responsiveness, discipline, execution, and constructive accountability. It becomes less helpful if it encourages excessive growth, inconsistent practices, or resistance to enterprise controls. Acrisure's culture challenge is not to replace its entrepreneurial DNA, but to channel it through a more integrated organization in which local teams retain ownership while benefiting from data, capital, products, and technology for the broader company.

TD: Do you think they're successfully managing this?

MZ: In my opinion, since I left there in March... yes, I think that they are successfully managing it, you know, with a directional success, but the transition is still incomplete, right? Acrisure has articulated the right model: preserve local client relationships and entrepreneurial energy while creating common technology, data, finance controls, and specialist capabilities. And the investment in centralization and AI shows a real commitment to that direction. I think a harder question is whether that model is operating consistently across the entire enterprise with 1,100 acquired businesses; adoption will inevitably vary. Some teams will embrace the enterprise platform. Others may, you know, perceive it as a loss of autonomy. I would have to therefore describe Acrisure as successfully establishing the foundation, but not yet at the point where integration, producer adoption, cross-selling, and operating leverage are uniformly mature. The proof will come, though, through sustained improvement in organic growth, client and producer retention, cross-business referrals, service quality, data reliability, and margins. If those measures improve

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without weakening local decision-making, then management will have demonstrated that it successfully perceived the entrepreneurial culture while gaining the benefits of this scale.

TD: With this transition, do you think this could adversely impact retention? You know, people... advisors were brought in. They were told they would have independence and now the operating model shifting to become more centralized, as you noted. So does that concern you in terms of keeping advisors?

MZ: Yes, that's always going to be, you know, a concern, right? The transition creates, I'd say, a genuine producer retention risk, right? Many agency principals and producers join Acrisure under a decentralized model that emphasizes autonomy, local identity, and entrepreneurial control. So if centralization is perceived as changing that original bargain, particularly through standardized compensation systems, branding, staffing, or approval processes, TD: Right.

MZ: Some may question whether the organization still offers what they originally accepted. So the risks are not uniform. Producers are most likely to leave when they believe the new model interferes with client ownership, compensation economics, carrier relationship, hiring decisions, or even service responsiveness. Many will remain and may become more productive. If centralization removes administrative work, it provides better technology and specialist capabilities and it generates qualified cross-selling opportunities without undermining their commercial authority. So there's also a secondary client retention risk here because clients often identify more strongly with their individual producer and service teams than with the corporate brand. So if a producer departs, right? Then the service deteriorates during system and operating model changes. Clients may follow as well, right? So, Acrisure should therefore monitor producer sentiment, client retention by producer cohort, service levels, and renewal outcomes, not merely total headcount. The best mitigation is to define the new compact clearly. Enterprise functions own infrastructure, data, controls, and repeatable administration while producers retain meaningful authority over advice, placement, and client relationships. Providing transition incentives involving influential producers in decision design, protecting service continuity and demonstrating tangible benefits from the new model will be more effective than relying solely on contractual retention provisions. So, yes, retention could be adversely affected during the transition, especially over the next several renewal cycles, but it's manageable if Acrisure preserves genuine, not merely rhetorical local empowerment.

TD: Yeah. Okay. And would you anticipate Acrisure's competitors to try to highlight this to poach the best advisors away from the company? How concerning is that they, you know, they seek to exploit what's going on at the company and turn it from an advantage to a disadvantage?

MZ: Yeah, well, that's always competitors are always likely to use any uncertainty around centralizations to recruit high-performing Acrisure producers, particularly those with portable books, strong carrier relationships or leadership positions and attractive specialties. The recruiting message would be straightforward for them, right? You join for independence, but the model is becoming more centralized. Come here and regain control over staffing, client service, technology, compensation, local decision making. So the greatest vulnerability would be among producers who believe centralization is increasing administrative friction. It's reducing compensation flexibility, changing their local brand or interfering with service. Rival brokerages may offer transition bonuses, equity, team lift-outs, earn-outs, or promises of greater autonomy. So private equity-backed platforms in regional brokerages can especially be aggressive because 1 strong producer may bring an entire team and meaningful client book. So active defense cannot rely solely on restrictive or compensation, right? It's going to need to demonstrate that the integrated model makes producers more successful through better market access, specialist expertise, AI-enabled productivity, qualified cross-selling, stronger client analytics, and reduced administrative burden. Management is going to have to identify high-value and high-risk producers early, engage them directly, monitor leading indicators such as declining pipeline or team departures, and make sure the new operating model delivers visible benefits before competitors can define the narrative for themselves. Depends.

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TD: And are non-competes beneficial in this regard? Would they help defend against the poachings or not so much?

MZ: It depends how the non-compete, you know, it depends how it's structured. Not all of them are structured the same, it really is going to depend on the wording in it and what they negotiated, particularly for former agency owners who, let's say they receive substantial considerations in the acquisition, but they should not be viewed as a complete retention strategy, right? I'd say that narrowly drafted customer and employee non-solicitation provisions, confidentiality protections, deferred compensation, equity vesting, and sales of business may be more defensible and useful than a broad prohibition on working for a competitor. They can slow a team lift-out and protect customer information. But, you know, litigation is expensive, uncertain, and potentially damaging to morale and the reputation. So the best defense is still economic and cultural. Competitive compensation, meaningful autonomy, excellent service support, differentiated technology, and visible career opportunities. Contractual restrictions can protect the perimeter, but if key producers no longer believe the platform helps them succeed, a non-compete generally delays the problem rather than really solving it.

TD: Okay, and from a client and customer... from a client and advisor retention standpoint, do you anticipate Acrisure to perform any better or worse than the industry overall?

MZ: Yeah, so from the client and customer advisory retention standpoint, as compared to, you know, other industries, I would say I would separate the near-term transition period from the longer-term period, like over the next 12 to 24 months. I would expect Acrisure to face somewhat greater retention pressure than a more fully integrated competitor, particularly among producers and customers affected by system migrations, organizational changes, branding decisions, or even altered service models. Its scale and acquisition history create more moving parts and producer departures can cause corresponding client, you know, attrition. So that does not necessarily mean materially worse performance across the entire company, you know. Acrisure also has strong offsets, right? They establish local relationships, broad carrier access, substantial product capabilities, specialist resources, and increasing technology investment. Many commercial clients are relatively sticky because switching brokers requires effort and disrupts established risk management and renewal processes. So from a longer term, Acrisure could perform in line with or even better than the industry if its centralization produces faster service, broader expertise, more consistent execution, and relative cross-selling while preserving producer autonomy, like I discussed before. My base case would therefore be modestly elevated producer and client retention risk during the transition, followed by improvement as the model stabilizes. The critical indicators would be retention by producer and acquisition cohort, regrettable producer departures, client losses following team changes, renewal service levels, and whether clients using multiple Acrisure solutions demonstrate higher retention than a single product client.

TD: We've discussed how acquisitive the company has been in the past. Given all the changes taking place, both in terms of technology and the cultural shifts and increased centralization, how aggressive do you think they should be with their future acquisitions?

MZ: Yes, that's a good question. You know, based on all these changes that took place, obviously both in terms of technology, culture shifts, the increase in centralization, I would recommend more selective acquisition pace during the next phase rather than returning immediately to the historical volume driven. Acrisure already has significant integration work underway. This is across data, technology, finance, branding, shared services, and culture. Adding large numbers of agencies could increase complexity faster than the organization can remove it. You know, that does not mean stopping acquisitions. I would prioritize deals that fill a clear strategic gap. Specialty and MGA capabilities, attractive geographies, employee benefits, cyber, payroll, or even businesses that deepen existing client relationships and favor targets that can integrate onto the enterprise data and operating standards with limited customization. I'd be more cautious about acquiring another large population of small agencies using incompatible systems unless the economics fully reflect the integration costs. You know, each transaction should pass both a financial screen and an integration capacity test. Is there an accountable integration owner, a funded migration plan, sufficient technology

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and change capacity, and a credible path to retain key producers and clients? Management should also measure acquisition performance using organic growth, producer and customer retention, cross-selling, system migration, and realized synergy, not simply acquired revenue. So I would describe the appropriate posture as strategic. Strategically thought out, but operationally disciplined, right? Fewer, more complementary acquisitions while the enterprise backbone stabilizes, followed by greater activities once Acrisure can onboard businesses to a repeatable integration playbook. Otherwise, additional acquisition risks are going to dilute the benefits of the centralized and AI investments that's already underway as of today.

TD: Okay. And when you talk about potential geographic expansion, does anything stand out?

MZ: Other than probably more in Europe and Poland as they put a shared service there and they want to get, I know they want to get a little more into Europe and Canada, is where I say Europe, UK and Australia, and New Zealand stand out because they have mature commercial insurance markets. They have fragmented broker populations. They establish regulatory frameworks and meaningful opportunities in specialty insurance, employee benefits, cyber, wholesale, and reinsurance. So like I was saying, the London market is particularly valuable as a global specialty and reinsurance hub. Canada and Australia offer market structures that are operationally closer to the US. And then Europe presents opportunity, but integration is more complex because of country-specific regulations, language, employment practices, and distribution models. If you're talking Latin American parts of Asia could provide long-term growth, but I would initially approach those regions through partnerships, specialty platforms, or targeted acquisitions rather than constructing a large retail footprint. You know, the most attractive geography is not simply the fastest growing country. It is one where Acrisure can reuse its technology, data, and carrier relationships and specialty capabilities while operating within a manageable regulatory structure. Given the integration already underway, I would favor concentrated expansion in a few established markets over adding many new functions that create further operational fragmentation.

TD: Okay. And to summarize, we've discussed a lot over the past hour. What would you say are their greatest potential opportunities? What should they be prioritizing? And conversely, what could be the greatest risks and what they should be most acutely aware of?

MZ: Yeah, good question. I'd say the greatest potential opportunities for them is to convert the scale it assembled through acquisition into a generally integrated growth platform, right? It already has extensive distribution, local client relationships, carrier access. The next phase should focus on extracting more value from that existing franchise rather than relying on additional acquisitions. I would prioritize 4 areas. First, complete the common enterprise backbone, customer and policy master data, finance reporting, cyber security, shared services. Then use AI to reduce administrative work across submissions, renewals, servicing, claims support, and finance. Third, drive discipline cross- selling by identifying genuine client needs and routing opportunities. And then last, remain selective. Selective when acquiring in specialty capabilities and attractive geographies, but require every transaction to pass a realistic integration capacity test. The greatest risk is execution overload. Simultaneously centralized operations, migrating technologies, deploying AI, changing the brand, expanding products, and continuing acquisitions. If poorly sequenced, those changes could damage service, frustrate producers, increase employee turnover, and ultimately lead to client attrition. So another risk is centralization could undermine the local entrepreneurship and producer relationship that made the company successful. Acrisure must centralize infrastructure and controls without unnecessarily centralizing client judgment. So the company should prioritize integration before expansion, adoption before additional technology, and organic value creation before acquisition volume, in my opinion.

TD: Great. Well, thanks for the time today. It was a pleasure to speak with you.

MZ: Yes, thank you very much. Let me know if you need a follow-up. I know there was a lot of questions.

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TD: Yeah, we got to go. Thank you. Appreciate it.

MZ: Take it easy.

TD: Take care.

MZ: Okay. Bye-bye.

DISCLAIMER: The statements or opinions expressed today are those of the Advisor and not Guidepoint, who disclaims all liability for the content provided. The Advisor may not disclose material nonpublic or confidential information or any information that would cause the Advisor to breach any duty or obligations. Guidepoint is not a registered investment advisor and the information provided is not intended to constitute investment advice.

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