← back to rankingBRO · Brown & Brown, Inc.
Insurance - Brokers · mkt cap $19.2B · calls: Q1 FY2026 vs Q4 FY2025
35.0 conviction · conf-adj 35
conf 3/10 partial
enthusiasm:24.0 · trend:8 · quantifies:0 · impact:0 · under_radar:5 · credibility:0 · business_impact:4 · disruption:-6 · commitment:-4 · confirmation:4
Enthusiasm latest 8 / prev 2 (rising)
BRO’s AI narrative jumped sharply in Q1 FY2026: a full prepared section plus Q&A, versus Q4 FY2025’s generic technology/innovation mentions with no AI-specific substance. Management quantifies operational impact (50k+ hours saved; scaling agents past 25% of submissions) and frames AI as productivity/growth enabler—not headcount replacement—while stressing early-stage, multiyear execution and minimal small-account revenue exposure. Credibility is moderate-to-good on cost/productivity claims (specific live tools and hour savings) but weak on revenue/margin attribution (no AI-linked revenue or margin dollars yet).
GROUNDED NEXT-FY IMPACT vs CONSENSUS
Grounded on actual base — revenue $6.0B · net income $1.1B · net margin 17.7% · diluted EPS 3.16
These are next-fiscal-year annual uplift estimates, not next-quarter numbers.
Aggregate next-FY est. rev uplift: % · next-FY EPS uplift: % · vs analysts: inline · priced in: medium (model's call-read: high; verdict above is the hard-data one used for ranking) · confidence: 3/10
| Claim | Figure | Arithmetic | Next-FY Rev % | Next-FY EPS % |
|---|
Submission-process automation >25% (Specialty Distribution programs/wholesale)
productivity · soft | >25% of end-to-end submission process | 25% is a share of a subprocess, not of revenue or a disclosed cost/throughput base; no $ opex, labor $, or segment revenue for that pool anywhere in inputs to convert to rev or NI | | |
Carrier billing portal labor saved >50,000 hrs/yr
cost · soft | >50,000 hours annually | Hours disclosed but $/hour fully-loaded cost is NOT in any claim/base, so the $ conversion is unanchored. Illustrative only: 50,000 x ~$65/hr = $3.25M pretax; x(1-0.21)=$2.57M after-tax; /adj NI $1,336M = ~0.19% EPS (~$0.01). Real but immaterial; not aggregated because $/hr is invented, not disclosed | | |
Retail disintermediation exposure 1-2% of Retail revenue (commercial/EB <$25k + monoline personal)
engagement · soft | 1%-2% of total Retail revenues | Downside disintermediation exposure, NOT an AI uplift; Retail's share of total $5,956M not disclosed -> 100 x (0.01-0.02 x Retail_$) / 5,956M is indeterminate -> cannot size | | |
<$25k premium segmentation threshold
other · soft | under $25,000 premium | Customer-segmentation threshold only; no % revenue, units, or $ impact quantified | | |
Tech/data foundation started >10 yrs ago
other · soft | over 10 years ago | Historical context; no quantified forward impact | | |
Assumptions: Tax 21%. EPS sized against the adjusted base (adj NI ~$1,336M / EPS ~4.25) to match consensus, not the lower/distorted GAAP base ($1,054M NI, $3.16 EPS). Default incremental net margin would be GAAP 1,054/5,956 = 17.7% if any $ revenue claim existed, but none does. The only number-bearing cost claim (>50,000 hrs) cannot be anchored to $ because no $/hour is disclosed anywhere in the inputs, so it is left soft and excluded from aggregates. BRO is an insurance broker -> pure AI ADOPTER, zero supplier side. Forward Powell statements (incremental revenue growth, market-share capture, margin improvement) are qualitative and excluded from math.
Top line: No anchored AI revenue claim. The >25% submission-automation figure is a process-completion share with no revenue/throughput base disclosed, and the only Retail number (1-2% of Retail revenue) is downside disintermediation exposure, not uplift, and is indeterminate without Retail $. Forward topline statements ('incremental revenue growth,' 'market share capture,' 'new revenue channels') are entirely qualitative -> est_rev_uplift_pct = null, not zero-by-evidence.
Bottom line: The only number-bearing cost claim — >50,000 hours saved on the carrier billing portal — would size to only ~$3.25M pretax / ~$2.57M after-tax = ~0.19% of adjusted net income (~$0.01 EPS) at a stylized $65/hr, but no $/hour is disclosed in the inputs, so it stays soft and out of aggregates. Either way it is immaterial. Broader 'operating leverage / margin improvement' language is unanchored. Aggregate adopter next-FY EPS uplift: null.
[impact n/m (all claims soft/unanchored)] Consensus already moves revenue +25% (FY24->FY25, $4,747M->$5,946M, vs actual $5,956M) and EPS +13% ($3.76->$4.25). No hard, anchored AI uplift can be added above that trajectory: the one number-bearing cost item (~$0.01 EPS at an assumed rate) is both immaterial and unanchored, and everything with real upside (25% submission automation, market-share capture, margin expansion) is qualitative. The GAAP-vs-adjusted EPS gap is accounting/adjustment mix, not a quantified AI delta. Nothing in the quantified set points above consensus.
MODEL CONSENSUS (impact)
partial
Agree adopter-only, all pcts null, priced_in high. Key reconciliation: hours-saved claim left soft because no $/hour is disclosed; aggregates and verdict made more conservative.
Conflicts reconciled
- math[carrier billing].soft/eps_uplift_pct: X=false/0.19 vs Y=true/null -> used Y (soft=true,null) because the $/hour conversion is not disclosed anywhere in inputs, so the $ figure is invented, not anchored
- est_eps_uplift_pct: X=0.19 vs Y=null -> used null since its only contributor is the now-unanchored hours claim
- vs_analyst_expectations: X=inline vs Y=unclear -> used inline, better justified given priced_in=high and nothing material above consensus
- confidence: X=4 vs Y=2 -> used 3 (average), lowered after moving the hard claim to soft
| Field | Opus 4.8 | GPT-5.5 |
|---|
| Rev uplift % | – | – |
| EPS uplift % | 0.19 | – |
| Priced in | high | – |
| vs analysts | inline | – |
| Confidence | 4 | – |
| Top line | No anchored AI revenue claim. The >25% submission-automation figure is a process-completion share with no revenue/throughput base disclosed, and the only Retail number (1-2% of Retail revenue) is downside disintermediation exposure, not uplift. Forward topline statements ('incremental revenue growth,' 'capture more market share,' 'new revenue channels') are entirely qualitative -> est_rev_uplift_pct = null, not zero-by-evidence. | – |
| Bottom line | The single hard, anchored figure — >50,000 hours saved on the carrier billing portal — sizes to only ~$3.25M pretax / ~$2.57M after-tax = ~0.19% of adjusted net income (~$0.01 EPS). Real and disclosed, but immaterial. The broader 'operating leverage / margin improvement over coming quarters' language is unanchored. | – |
| Reasoning | Consensus already moves EPS 3.76 -> 4.25 (FY24->FY25, +13%, ~+$0.49) on +25% revenue. The only quantifiable AI contribution is ~$0.01 EPS (~0.19%), roughly 2% of that step-up and well inside the modeled trajectory. Everything with real upside potential (25% submission automation, market-share capture, margin expansion) is unanchored, so nothing in the quantified set points above consensus. | – |
Rows highlighted where the two models disagreed.
QUANTIFICATIONS
Submission-process automation (Specialty Distribution programs/wholesale): more than 25% (scaling now / forward (agents "will automate"), both)
“We're scaling AI agents that will automate more than 25% of the end-to-end submission process for many of our programs and wholesale businesses, achieving material cost reductions and removing throughput limits.”
Labor hours saved (carrier billing portal platform): more than 50,000 hours annually (already ("already saving"), bottomline)
“This platform is already saving more than 50,000 hours annually and continues to be rolled out across the company.”
Retail revenue exposure — commercial/EB under $25k premium + monoline personal: between 1% and 2% of total Retail revenues (current mix (disintermediation risk framing), topline)
“In Retail, commercial and employee benefits account under this threshold, and monoline personal lines represents between 1% and 2% of total Retail revenues.”
Small-account premium threshold (disintermediation / AI exposure framing): under $25,000 in premium (current customer segmentation, topline)
“This slide frames how we think about our customers that pay under $25,000 in premium.”
Data/tech foundation timeline: over 10 years ago (past — platform rationalization start, both)
“Our technology and data journey commenced over 10 years ago, specifically when we began platform rationalization and data standardization across our business.”
PAST (realized)
- Q1 FY2026 | Powell: "Our technology and data journey commenced over 10 years ago, specifically when we began platform rationalization and data standardization across our business."
- Q1 FY2026 | Powell: "We're in the early stages of a multiyear journey that has already delivered value through enhanced capabilities."
- Q1 FY2026 | Powell: "Here are just a few of our AI-powered solutions that are live and delivering value."
- Q1 FY2026 | Powell: "This platform is already saving more than 50,000 hours annually and continues to be rolled out across the company."
- Q1 FY2026 | Powell: "In Retail, our policy checking agents automate traditionally manual proposal comparison and policy reviews"
- Q1 FY2026 | Powell: "We've built a proprietary platform that electronically interfaces with carrier billing portals, automatically extracts and validates billing data, flags exceptions for review and then files the customer policy in our agency management system."
- Q4 FY2025 | Powell: "we invested in talent and technology to help us deliver even better solutions for our customers"
- Q4 FY2025 | Powell: "invested in innovation, data and analytics"
CURRENT (now)
- Q1 FY2026 | Powell: "We're scaling AI agents that will automate more than 25% of the end-to-end submission process for many of our programs and wholesale businesses"
- Q1 FY2026 | Powell: "This incremental underwriting capacity is being redirected to high-value revenue growth activities."
- Q1 FY2026 | Powell: "continues to be rolled out across the company" (billing platform)
- Q1 FY2026 | Powell: "Our organization is designed to incubate AI solutions quickly and then deploy the capabilities at scale."
- Q1 FY2026 | Powell: "We're investing in world-class data and AI teammates, enterprise-grade technologies and a strong ecosystem of technology partners."
FORWARD (guidance)
- Q1 FY2026 | Powell: "We believe embracing AI will support incremental revenue growth and operating leverage over the long term."
- Q1 FY2026 | Powell: "We're scaling AI agents that will automate more than 25% of the end-to-end submission process"
- Q1 FY2026 | Powell: "The opportunities created by AI and further industry automation would include higher submission flow and new revenue channels, thereby helping us capture more market share."
- Q1 FY2026 | Powell: "we believe technology is an enabler that will drive incremental revenue growth and margin improvement in the future."
- Q1 FY2026 | Powell: "We feel confident that it will improve the customer experience, the underwriting and placement process, the productivity of our teammates and drive incremental growth in revenue and margins over the coming quarters."
- Q1 FY2026 | Powell: "as we move further into the year, we'll bring more information to you on that" (AI journey)
- Q1 FY2026 | Powell: "going forward, I believe we will do both" (buy and build AI)
TRACK RECORD — PROMISE vs DELIVERY
—/100 (no quantified promises) no-quantified-promises 6 calls reviewed
Across Q4 FY2024–Q3 FY2025 management made no quantified AI/ML/automation targets (no %, $, or dated milestones tied to AI). Q1 FY2026 is the first substantive AI discussion (10+ year data platform, pivot to innovation/AI, productivity goals) but the provided transcript contains no number-plus-timeframe AI commitments to score.
PRICED-IN (REFINED)
MEDIUMEst. revisions rising · Fwd P/E 16.2 · EV/Sales 4.1x
AI claim maps to Retail, Specialty Distribution
Analyst sentiment is migrating up (strongBuy+buy rose from 3 in Jan–Mar 2026 to 5 by May–Jun while holds fell from 15 to 14), and forward consensus embeds solid growth (EPS ~3.50 to ~4.25 and revenue stepping up through FY2025), which partially prices operational upside; recent price-target data is stale (no last-month/quarter updates), so revision signal rests mainly on ratings and estimates. Valuation is mixed: ~16.2x next-FY P/E is not extreme for a quality broker, but ~4.1x EV/Sales is elevated versus a typical mature distributor, so the market is paying a premium multiple without a full AI-specific rerating. AI-driven efficiency and placement productivity would most plausibly flow through client-facing and program lines—Retail and Specialty Distribution—not as a separate segment.
COVERAGE — ENTHUSIASM TRAJECTORY + CATALYSTS
2Q4 FY20242Q1 FY20252Q2 FY20252Q3 FY20253Q4 FY20258Q1 FY2026
AI enthusiasm across 6 calls — trend ↗ rising
Five calls barely mentioned AI; Q1 FY2026 debuted agents, 50k-hour savings, and 25% submission automation targets.
RECENT AI CATALYSTS & NEWS
BUSINESS IMPACT - QUALITATIVE MATERIALITY
5/10 qualitative impact moderate medium-term · mixed evidence
Where AI matters: placement/submission workflow and back-office productivity
Live agents (policy checking, >25% submission routing in Specialty, 50k+ billing hours) show real operational adoption, but disclosed metrics are subprocess/labor savings with no AI-linked revenue or margin dollars and immaterial EPS at company scale.
Caveats: No anchored AI revenue or margin uplift despite rising disclosure intensity; Productivity claims (hours, % of submissions) may not convert to material operating leverage near-term; Small-account digital/direct channels could erode low-complexity retail over time; Multiyear build/partner execution risk as narrative accelerates faster than economics
AI DISRUPTION / CANNIBALIZATION RISK two-sided · 4/10
AI can disintermediate simple <$25k retail/monoline flows (mgmt cites only 1-2% of Retail revenue) and compress transactional placement, but BRO earns commissions on complex relationship-led brokerage—not billable-hour labor—so the core model is more defensible than staffing/consulting.
OPTIONS / MARKET STRUCTURE
option liquidity: fair
proxy inputs — dollar-ADV $185M · beta 0.657 · px $56.59
source: proxy (no options chain on FMP)
FMP /stable/ exposes no options-chain endpoint on this key, so ATM IV, bid-ask spread and open interest are unavailable. Liquidity below is a PROXY from dollar-ADV, beta and price level (a stand-in for option depth), not measured option-market data.
CONFIRMATION — INSIDERS · 13F · LANGUAGE
Mixed — insiders buying, institutions flat, management language 2/10 hedged.
INSIDERS buying 1 open-market buy(s) vs 0 sell(s) — net accumulation
INSTITUTIONS (13F) flat as of 2026-03-31: 98 new / 175 closed positions; 407 increased / 298 reduced; institutional ownership +7.96pp; -75 net 13F holders
MGMT LANGUAGE 2/10 hedged AI appears once in intro; vague value promise, no metrics or rollout proof in excerpt.
commit “we're leveraging these capabilities in combination with artificial intelligence”
hedge “to provide even more value to our customers, teammates and carrier partners”
VERBATIM AI QUOTES
“This quarter, we also wanted to take some time to provide an update on our technology and data journeys with a focus on how we're leveraging these capabilities in combination with artificial intelligence to provide even more value to our customers, teammates and carrier partners.”
— J. Powell Brown, Q1 FY2026
“Our technology and data journey commenced over 10 years ago, specifically when we began platform rationalization and data standardization across our business. These investments were foundational as AI is only effective when built on clean, standardized and scalable data platforms.”
— J. Powell Brown, Q1 FY2026
“Over the past few years, we've been shifting more of our technology focus towards innovation and artificial intelligence.”
— J. Powell Brown, Q1 FY2026
“Our efforts are focused on developing enhanced solutions to increase sales velocity, improve customer interactions and reduce manual, low complexity or repetitive work.”
— J. Powell Brown, Q1 FY2026
“We did not jump directly to AI. We're investing in the fundamentals first, which is enabling us to innovate and deploy AI reasonably, at scale, and in ways that directly support growth across the company.”
— J. Powell Brown, Q1 FY2026
“We view AI as an enabler and an accelerator of our existing strategy.”
— J. Powell Brown, Q1 FY2026
“We're in the early stages of a multiyear journey that has already delivered value through enhanced capabilities.”
— J. Powell Brown, Q1 FY2026
“We believe embracing AI will support incremental revenue growth and operating leverage over the long term.”
— J. Powell Brown, Q1 FY2026
“Now let's talk about how we're building an AI-powered organization with enterprise capabilities that empowers local development to solve real business needs.”
— J. Powell Brown, Q1 FY2026
“Our approach is to combine out-of-the-box AI tools and proprietary Brown & Brown AI products that embed our data workflows and deep insurance knowledge.”
— J. Powell Brown, Q1 FY2026
“We're scaling AI agents that will automate more than 25% of the end-to-end submission process for many of our programs and wholesale businesses, achieving material cost reductions and removing throughput limits.”
— J. Powell Brown, Q1 FY2026
“This incremental underwriting capacity is being redirected to high-value revenue growth activities.”
— J. Powell Brown, Q1 FY2026
“These agents are enabling more processing in the same day, thereby improving the customer experience, accelerating growth through higher win rates and driving stronger underwriting results for our carriers.”
— J. Powell Brown, Q1 FY2026
“In Retail, our policy checking agents automate traditionally manual proposal comparison and policy reviews, improving risk insight while reducing E&O exposure.”
— J. Powell Brown, Q1 FY2026
“We have also created capabilities that pull key features from complex policies to create clear customer summaries, simplify the customer conversations and improve retention.”
— J. Powell Brown, Q1 FY2026
“Lastly, we've built a proprietary platform that electronically interfaces with carrier billing portals, automatically extracts and validates billing data, flags exceptions for review and then files the customer policy in our agency management system.”
— J. Powell Brown, Q1 FY2026
“This platform is already saving more than 50,000 hours annually and continues to be rolled out across the company.”
— J. Powell Brown, Q1 FY2026
“We believe the primary risk is that customers think they no longer need a broker and choose to go direct. This can happen today with or without AI.”
— J. Powell Brown, Q1 FY2026
“The opportunities created by AI and further industry automation would include higher submission flow and new revenue channels, thereby helping us capture more market share.”
— J. Powell Brown, Q1 FY2026
“In summary, we believe technology is an enabler that will drive incremental revenue growth and margin improvement in the future.”
— J. Powell Brown, Q1 FY2026
“We talked earlier about the positive impact of AI on our business. We feel confident that it will improve the customer experience, the underwriting and placement process, the productivity of our teammates and drive incremental growth in revenue and margins over the coming quarters.”
— J. Powell Brown, Q1 FY2026
“We don't view AI as a teammate replacement tool.”
— J. Powell Brown, Q1 FY2026
“AI disintermediates tasks. AI does not disintermediate trust.”
— J. Powell Brown, Q1 FY2026
“Lastly, we invested in talent and technology to help us deliver even better solutions for our customers.”
— J. Powell Brown, Q4 FY2025
“We added to our capabilities, invested in innovation, data and analytics, and most importantly, added over 6,000 new teammates.”
— J. Powell Brown, Q4 FY2025
“As a result of our changing business mix over the years, the addition of Accession, along with our combined synergies, increased contingents, utilization of technology and our continued focus on our balanced profitable growth, which is enabled by our unique decentralized sales and service model, we are increasing our long-term margin target range to 32% to 37%.”
— R. Watts, Q4 FY2025
ANALYST QUESTIONS ON AI
Q (Q1 FY2026, Jian Huang (Bob Huang), Morgan Stanley): My second question really revolves around your AI commentaries about the capabilities that you're adding onto the platform, right? It's more of a buy versus build question. As you're investing in AI, just curious your philosophy around acquiring AI capabilities from third-party vendors versus what are the things that you feel it is necessary to kind of maybe develop internally from a code-based perspective?
A: Powell: "So I think there's really 2 ways to approach AI in a very broad sense. You can do it internally and that's typically where you're nibbling around the sides. And it takes longer typically, but it's probably overall less expensive. Conversely, you decide to partner with some firms that can help you accelerate and make big jumps forward. And I believe that we actually -- or at least to this point, but going forward, I believe we will do both. And so we are not at a point where we're going to discuss who those people are, but the answer is we look at it as sort of a combination. And depending on what we're trying to achieve will dictate what portion of the business and what we're trying to achieve would probably dictate which way we lean into."
Q (Q1 FY2026, Taylor Scott (Alex Scott), Barclays): Just based on what you're seeing with the potential of AI, does it change the amount of growth that's needed to still get that margin improvement? Can you talk a bit about how you're thinking through that over the next few years if we do stay in a softer market here?
A: Powell: "We think that there are opportunities to invest in talented people to help us grow our business going forward. So you can actually underinvest and margins could stay flat or go up. And that's not how we look at it." … "That said, there's absolutely a positive impact from AI and the potential of that going forward." Watts added organic-with-contingents as a margin correlation metric.
Q (Q1 FY2026, Taylor Scott (Alex Scott), Barclays): On the revenue opportunities you see from AI … is it about specializing? Is it about going down market? And then can you elaborate on any investments that are more concrete that we can think through on how you're advancing towards some of that?
A: Powell: "We tried to give you a good peek in the box on the 3 examples that we've used." … "We don't view AI as a teammate replacement tool." … "we absolutely believe it improves the customer experience" … "we talked a little bit about that as it relates to 25% of the stuff in Specialty Distribution going through and routing which makes us more efficient." … "it helps us identify growth opportunities with new or existing customers." … "we've kind of laid out what we want to talk about today. And as we move further into the year, we'll bring more information to you on that."
Q (Q1 FY2026, Yaron Kinar, Mizuho): There is a school of thought that says … maybe AI creates an opportunity for the insurers to take some of that value back. How do you think about that? How do you respond to that?
A: Powell: "They do, in some instances, have a direct model on the very simplistic, not complex, not customized commercial risks. So I think that will continue, but I actually think anytime there's complexity, that leans much more in the favor of the brokerage community. So I actually would not agree with that statement."
Q (Q1 FY2026, Yaron Kinar, Mizuho): Given that … slice of the market [$25,000 or less] tends to go more to the small independent agencies, does that impact your appetite for smaller tuck-in M&A over the long run?
A: Powell: "Depends on those businesses, and we have to evaluate that on a constant and consistent basis going forward. We like small- and medium-sized tuck-in M&A, but we want to understand exactly what they've got in there and then how we would service it and continue to add additional value." … "AI disintermediates tasks. AI does not disintermediate trust."
Q (Q1 FY2026, Brian Meredith, UBS): Do you think [AI] has any effect on kind of long-term commission rates? Or would you charge your clients given the productivity benefits you're likely to see from it?
A: Powell: "I don't like to say never or always. But I actually think that if you look at the way the risk-bearing community is looking to grow … I believe that there -- it's possible, but I don't think it's highly probable." Watts began: "there's the presumption that the cost of technology will not go up" — transcript cuts off mid-answer.