Key Takeaways

• BEAD-funded broadband projects will touch an estimated 3,954,030 utility-owned poles across 2,053 electric utility service territories, based on 188,287 planned aerial fiber route-miles.
• About 40% of all BEAD aerial fiber will be deployed across electric cooperative territories, which are disproportionately represented relative to cooperatives’ share of electric customers (13%).
• Pole attachment regulation is scattershot. The FCC has jurisdiction over poles owned by investor-owned electric utilities (IOUs) in 27 states; in the other 23 states, IOU poles are regulated by state public utility commissions. Regulation of poles owned by electric cooperatives and municipal electric utilities differs across all 50 states – some leave these entities entirely unregulated; some regulate one but not the other; and some regulate both.
• Pole-related costs could range from $534M to $4.63B nationwide, depending on make-ready charges and pole replacement rates. Even our base scenario estimates $1.25B in total pole-related costs. Costs that are unexpectedly high could strain deployment budgets, slow deployment, lead to defaults, and deprive communities of broadband.
• Unresolved electric utility pole issues have long impacted broadband deployment. NTIA has sought to address the regulatory patchwork in the BEAD context by extending the reach of the FCC’s rules. The FCC has signaled a willingness to act more quickly in resolving pole disputes. However, it remains to be seen if these approaches will translate to more streamlined and cost-effective access to utility poles, especially given ongoing quarrels involving utilities already subject to the FCC’s rules.

Overview

The BEAD program will fund construction of broadband infrastructure to nearly 4 million unserved and underserved locations across the United States. A significant portion of this build-out will use aerial fiber, which requires attachment to utility poles. Planned aerial deployment totals about 188,287 route-miles, or 41.8% of total BEAD fiber miles.

Utility poles are plentiful. By some estimates there are some 180 million poles across the country. Leveraging poles to deploy fiber is cost-effective – the Fiber Broadband Association estimates that aerial deployments cost half as much as burying fiber – and can speed network construction. However, negotiating access to poles can be fraught as ISPs must navigate a patchwork of regulated and unregulated electric utilities of varying sizes and sophistication. These interactions can quickly become adversarial, delaying projects and raising costs.

This analysis overlays 3,855,167 BEAD-funded locations across 6,265 projects against 2,053 electric utility service territory boundaries to investigate how BEAD deployments will span utility service territories. We focus on electric utility-owned poles, which comprise the vast majority of poles across the country – upwards of 70% according to recent estimates – and because many pole-related disputes between parties involve electric utilities.

We then apply planning assumptions to estimate utility-pole touches and related costs. Our goal is not to duplicate subgrantee cost estimates, which formed the basis for their BEAD applications. Indeed, applicants should have planned for reasonable pole-related costs. However, in practice, recent history is replete with examples of ISPs encountering higher-than-expected pole costs, including instances where pole owners have attempted to unlawfully shift the cost of curing pre-existing violations to new attachers. These actions can cause significant delays and have even made broadband projects uneconomic despite significant grant dollars.

Given these stakes, we present a spread of potential pole-related costs to offer insight into how higher-than-expected pole costs could impact BEAD, and why policy interventions are needed to mitigate project delays or defaults.

BEAD Aerial Miles by Utility Ownership Type

The following table is based on the latest available compiled state BEAD Final Proposal data, which includes a mix of draft, submitted, and approved final proposals from state broadband offices.

Most notably, a disproportionately large share of BEAD deployments will take place across electric cooperatives’ service territories, as compared to their share of total utility customers. In other words, about 40% of all aerial BEAD fiber deployment may involve poles owned by cooperatives, who, collectively, serve 13% of all electric customers in the U.S.

Why Utility Ownership Type Matters: FCC oversight extends only to private investor-owned electric utilities (IOUs) in 27 states; public utility commissions in the other 23 states regulate IOU poles. Municipal electric utilities and electric cooperatives are exempt from FCC oversight, and many states do not regulate these entities.

Under this framework, FCC oversight would extend to about 10% of the utility poles that BEAD will touch.

BEAD will touch millions of poles that are not regulated by the FCC, where there are fewer guardrails in place to provide predictability and consistency in how pole-related costs are set. For example, one study found that the attachment rates for pole owners subject to regulation (IOUs and private companies) were significantly lower than those exempt from regulation, such as municipalities, cooperatives, and public utilities. BEAD recipients may encounter higher-than-expected pole fees from these entities, which could drive up costs and trigger delays or defaults.

To address this patchwork, NTIA requires that “poles owned within the [state’s] jurisdiction that are not currently subject to state or FCC pole attachment regulation will be governed by FCC rules through the federal interest period.” Its stated goal is to “reduce the regulatory burden on BEAD participants.” How these rules are applied and enforced, though, remains to be seen. Cooperative advocates have expressed their displeasure at this federal encroachment into the state-by-state regulatory approach that has evolved for these entities over the last few decades. Moreover, recent disputes involving ISPs and electric utilities underscore the myriad possibilities for the latter to attempt to circumvent seemingly clear rules governing pole access. It is notable that some of these parties are back before the FCC with new complaints about pole practices (see below for further discussion).

Given this continued uncertainty, even after commendable steps taken by the FCC and NTIA to address these barriers, it remains likely that ISPs will encounter unexpectedly high pole-related costs in some instances.

Pole Touches and Cost Exposure

The following section uses planning assumptions to estimate utility-owned poles touched and cost exposure from BEAD aerial route-miles. These are intended to illustrate the magnitude of potential costs and are not exact engineering estimates. The “low” and “high” scenarios represent the cumulative result of picking all low and high assumptions, respectively, and are intended to act as lower and upper bounds.

Methodology

Methodological details and sources for our model estimates are available in the full report.

Takeaways & Recommendations

From a policy perspective, utility poles remain an area that is long overdue for reform. Continuing forward with the status quo may delay BEAD projects and could result in project defaults if ISPs encounter substantially higher-than-expected costs.

How could this happen? BEAD subgrantees were required to estimate, to the best of their ability, pole-related costs in their applications. Those estimates informed the final proposed cost for the project. In practice, the Benefit of the Bargain round implemented by the Trump NTIA operated largely as a reverse-auction, with lowest bids winning in most instances. This left little room for buffers or contingency funds to address higher-than-expected costs of key inputs, from the materials needed to build a network to the costs associated with gaining access to poles, ROW, and easements.

The preceding analysis highlights the wide variability and significant unpredictability in the costs associated with accessing, placing attachments on, and replacing electric utility poles. These costs vary widely from utility to utility, and from state to state. This reflects the highly fragmented nature of oversight of pole disputes involving ISPs and electric utilities, which creates numerous opportunities for these entities to attempt to shift the costs of maintaining their poles to ISPs.

Electric utilities are natural monopolies that, in the absence of regulation, will seek to maximize profits. This is why private IOUs are subject to exacting public utility regulation. Nearly every action taken by an IOU must be scrutinized and approved by a regulatory body, and even then, regulators generally defer to utilities, yielding ever-higher electric rates in most states across the country (in the robustly competitive broadband sector, by contrast, prices have barely budged in a decade).

Municipal utilities and cooperatives, on the other hand, have been left to mostly govern themselves. Indeed, the primary accountability mechanism for these entities is the electorate. This creates an incentive for these entities to keep electric rates low lest officials be voted out of office or kicked off the co-op board. This dynamic also creates incentives to shift costs to third parties to make up for revenue shortfalls resulting from maintaining low rates. A version of this dynamic is evident in the dozens of municipal electric and cooperative systems governed by the Tennessee Valley Authority, a federal entity that is required by statute to keep electric rates as low as possible. TVA has accomplished this goal in part by devising pole formulas that allow for greater cost-shifting to ISPs than the FCC allows, all in the name of keeping electric rates “as low as feasible.”

The possibility of pole disputes is not theoretical. Rather, disputes happen all the time, and many are becoming more contentious given the high stakes and costs associated with rural broadband deployment. A recent dispute involving Comcast and Appalachian Power Company, a major IOU in Virginia, illustrates how these conflicts tend to unfold.

Comcast must negotiate access to Appalachian’s poles to support buildout in parts of the state. As part of that process, Appalachian estimated the costs to prepare its poles for Comcast’s equipment. Those costs were critical to the applications Comcast submitted for BEAD funding, so accuracy and fairness were of paramount importance. However, Comcast noticed that Appalachian sought to charge it to replace poles with pre-existing safety violations. Since Comcast did not cause those violations, it filed a complaint with the FCC and argued that having to shoulder the costs was unreasonable. The FCC sided with Comcast and found that Appalachian’s attempted cost-shifting violated its rules. The FCC reaffirmed that costs should be shared based on who caused them, meaning providers can only be charged for the additional improvements needed to attach their equipment, not for correcting old violations they did not create.

This was a major ruling that underscored the willingness of the FCC to act promptly in the application of established pole attachment rules. In theory, such prompt, direct application would seem to provide stability and predictability, especially with NTIA extending the reach of the FCC’s pole approach more broadly in the BEAD context. However, Comcast and Appalachian Power are back before the FCC, with the ISP having brought another complaint about how the utility is pricing access to its poles.

If this dynamic is not addressed and uncertainty remains, it is likely that ISPs will encounter higher-than-expected pole costs. Per the analysis above, using the base case as a reasonable proxy for what pole-related costs are expected to be by subgrantees, then costs could increase severalfold as they approach the “high” threshold estimate. This could prove ruinous to many projects.

Key Takeaways

• Multi-dwelling unit (MDU) locations make up a small share of broadband serviceable locations but a much larger share of units (e.g., apartments, offices, etc.).
• Among BEAD-awarded locations, 278,571 (7.2%) are MDUs, accounting for 879,582 units (19.7%).
• Among remaining unfunded locations, 96,082 (8.6%) are MDUs, but they account for 369,757 units (26.6%).
• MDUs are thus somewhat overrepresented among remaining unfunded locations relative to BEAD awards, particularly in terms of housing units.
• Most MDU locations are small (2 to 4 units), but a handful of very large buildings account for a disproportionate number of units.
• Most Medium and Large MDUs in remaining unfunded areas sit in well-served neighborhoods. 81% of Medium and 74% of Large MDU units are surrounded by locations that are 80–100% served. Small MDUs show a wider range of neighborhood service levels.

Background

A single “Broadband Serviceable Location” (BSL or “location”) can contain many units. For example, an apartment building may have dozens or hundreds of units. The FCC’s Broadband Serviceable Location (BSL) Fabric includes a unit_count for each location, which allows for analysis that accounts for this distinction.

Multi-dwelling units present unique deployment considerations. While serving a single MDU location can bring broadband to many households at once, the economics of MDU deployment differ from single-family homes. Factors such as building access, inside wiring, and landlord cooperation can impact deployment in ways that don’t apply to single-dwelling units (SDUs).

This analysis examines the MDU composition of both BEAD-awarded locations and remaining unfunded locations to provide context for ongoing discussions about broadband deployment priorities.

MDU Composition: BEAD Awards vs. Remaining Unfunded

Using the FCC’s Fabric (version 7) unit counts, we classified each location as either an MDU (more than 1 unit) or SDU (exactly 1 unit) and compared the two groups.

A few patterns are apparent:

• MDUs are a small share of locations in both groups (7.2% of BEAD, 8.6% of remaining), but a much larger share of units (19.7% of BEAD, 26.6% of remaining).
• The MDU unit share is higher among remaining unfunded locations (26.6%) than among BEAD awards (19.7%). This means that, when counting housing units rather than locations, a larger proportion of the unfunded gap is attributable to MDUs.
• In total, roughly 369,757 housing units in MDU buildings lack funded 100/20 Mbps service after accounting for BEAD awards and other funding programs.

MDU Size Distribution

MDUs range widely from a duplex up to large apartment buildings with hundreds of units. The table below breaks down MDU locations by unit count.

Among remaining unfunded MDUs:

• Small buildings (2–4 units) dominate by location count, making up 89.5% of MDU locations. These are often duplexes, triplexes, and fourplexes that may face deployment challenges similar to SDUs.
• Large buildings (100+ units) are few but contain many units. Just 80 locations with 100+ units account for 48,588 units, more than any other size category except 2 to 4.

Service Level of Areas Around Remaining Unfunded MDUs

A useful way to contextualize remaining unfunded MDUs is to analyze the level of service in the area immediately around them. In other words, are they in areas where nearby locations typically have service, or are they in largely unserved territory? To explore this, we examined the share of locations within approximately half a mile of each MDU that are served with 100/20 Mbps terrestrial service.

The table and chart below show housing units by MDU building size and neighborhood served share.

A couple of patterns stand out:

• Medium and Large MDUs are most often in well-served neighborhoods — 81% of Medium (5–25 unit) and 74% of Large (26+ unit) MDU housing units are in neighborhoods that are 80–100% served. For these buildings, broadband infrastructure may already be at the curb and might already be inside.
• Small MDUs are more evenly distributed across neighborhood types, with 63% of their units in mostly unserved or mixed service areas.

Methodology

This analysis uses the “including satellite BEAD” scenario from our updated remaining unfunded locations analysis. BEAD-awarded locations include all technology types, including satellite (technology code 61). Remaining unfunded locations are those in the BFM without 100/20 Mbps terrestrial service that are not covered by BEAD or another deployment program (after also excluding state “No BEAD” locations, except those marked as too expensive to serve).

Unit counts are drawn from the FCC’s Fabric version 7 active BSL data. Locations not matched to the Fabric are assigned a default unit count of 1.

Neighborhood service levels are estimated using the FCC’s National Broadband Map. For each remaining unfunded MDU, we identify all locations within approximately half a mile using H3 resolution-8 hex grid cells (covering the location’s cell plus its six immediate neighbors). The share of those locations with at least one provider reporting terrestrial 100/20 Mbps service defines the “neighborhood served %” for that MDU.

Data Sources

• Broadband Funding Map (BFM): FCC location-level funding data
• BEAD Final Proposal data: State-reported BEAD award and “No BEAD” location lists
• FCC Fabric version 7: Broadband Serviceable Location data with unit counts
• FCC National Broadband Map: Provider-reported availability data (June 2025)

Key Takeaways

• We use FCC and BEAD data to determine the relative size of service territory expansion that will be underwritten with federal grants. To do so, we calculate an ‘expansion ratio’ by dividing the number of BEAD awarded locations by FCC reported locations. This is equivalent to the percent expansion of a given ISP’s territory.
• Why does this matter? The goal of this analysis, the first in a series aimed at getting to know the BEAD subgrantees, offers essential context for understanding the scale of the awards won by ISPs of different sizes. Intuitively, ISPs with smaller expansion ratios may find it more manageable to build BEAD-funded networks given their experience. Conversely, ISPs with a higher expansion ratio may encounter difficulty in expanding their service territory at such a large scale since they lack the bona fides of more established providers.
• This dynamic has been evident in previous federal funding programs, notably RDOF, where some of the largest awards were rescinded by the FCC because of concerns about the ability of relatively small providers to greatly scale their networks. The ACLP discussed these concerns in a previous analysis focused on ensuring that prospective BEAD subgrantees were rigorously vetted prior to award.

Data Summary

Analysis Overview

After more than three years, BEAD grants finally appear to be poised for award by the 56 states and territories that received a proportionate share of the $42B+ available to bolster broadband availability. Some states, like Louisiana, have received all the necessary federal approvals to begin deploying these funds. NTIA continues to review and approve these awards on a rolling basis.

So, who won BEAD funds? The ACLP has parsed all available Final Proposal data and identified approximately 519 different subgrantees (when grouped by parent company). Many of the winners are familiar, but some are not, and some appear to be completely unknown.

The following analysis is the first in a series that we will publish on BEAD subgrantees. This analysis offers a straightforward look at the extent to which BEAD recipients will use their funds to expand their service territories. To do so, we calculate an expansion ratio as such:

An expansion ratio below 1 means the subgrantee will use BEAD funds to pass fewer locations than currently exist in its footprint. An expansion ratio above 1 means the subgrantee will use BEAD funds to more than double the size of their current footprint.

Why does this matter? In short, the following analysis provides essential context to understanding the scale of awards won by entities of different size. Many of the largest ISPs in the country won sizeable BEAD awards, but, per the analysis below, those funds will only expand their current service territory in a very marginal way. Conversely, numerous new or small ISPs have received BEAD awards that will subsidize deployments that will significantly multiply their current service territory. Subsequent analyses will offer additional information about these firms.

Intuitively, ISPs with smaller expansion ratios may find it more manageable to build BEAD-funded networks given give their experience and existing scale. Conversely, ISPs with a higher expansion ratio may encounter difficulty in expanding their service territory at such a large scale since they lack the bona fides of more established providers. Time will certainly tell whether this dynamic holds true. The ACLP will be closely watching.

Expanding 1% or Less

80 providers received a BEAD award 1% or less of their FCC footprint. Here are the top 10 by BEAD locations.

Expanding 1%–10%

201 providers received a BEAD award between 1% and 10% of their FCC footprint. Here are the top 10 by BEAD locations.

Expanding 10%–50%

85 providers received a BEAD award between 10% and 50% of their FCC footprint. Here are the top 10 by BEAD locations.

Expanding 50%–100%

18 providers received a BEAD award between 50% and 100% of their FCC footprint. Here are the top 10 by BEAD locations.

Expanding 100% or More

24 providers received a BEAD award exceeding their FCC footprint. Here are the top 10 by BEAD locations.

Unmatched Providers

108 providers couldn’t be matched to FCC data. Here are the top 10.

This includes new market entrants like Amazon Kuiper, but also likely reflects FCC Registration Number (FRN) mismatches between BEAD and FCC datasets, unmatched subsidiary companies, providers who haven’t filed availability data with the FCC, or other data issues.

Methodology

BEAD data comes from states’ BEAD Final Proposal files compiled by BroadbandExpanded and available here. FCC data comes from the National Broadband Map as of 2025-06-30.

States/territories included (54): AK, AL, AR, AS, AZ, CA, CO, CT, DC, DE, FL, GA, GU, HI, IA, ID, IL, IN, KS, KY, LA, MA, MD, ME, MI, MN, MO, MP, MS, MT, NC, ND, NE, NH, NJ, NM, NV, NY, OH, OK, OR, PA, RI, SC, SD, TN, TX, UT, VA, VT, WA, WI, WV, WY

Providers are matched by FRN (FCC Registration Number). Each BEAD subgrantee may have multiple FRNs; these are matched against FCC data and aggregated. The expansion ratio is BEAD locations divided by FCC locations.

Providers with multiple subsidiaries sharing the same FCC provider ID are consolidated in the tables above.

Of note, the location counts in this post and in our report do not incorporate unit counts, and look only at raw Broadband Serviceable Location (BSL) counts as provided in BEAD Final Proposal data files and from the National Broadband Map.

Additional information, including tables of all ISPs included in the analysis, the states in which they will provide BEAD-funded service, and a detailed methodology is available in our PDF report.

Key Takeaways

• After canceling a $26M broadband grant in Cortland and Cayuga counties, New York is racing to reallocate those, and additional, federal funds through a new MIP Round 4 before the end-of-year CPF deadline.
• In January, Cortland County issued an RFP seeking a partner to apply for MIP Round 4 funding.
• An ACLP analysis of the Cortland County RFP data found that 93% of Top and Medium Priority locations and 99% of Low Priority locations already have 100/20 Mbps broadband service, consistent with the pattern of overbuilding seen in previous MIP rounds.
• ConnectALL has not provided updates on the status of any MIP projects, and with less than a year until the statutory completion deadline, it remains unclear whether these networks are on track for completion.

Over the last several years, New York State has used over $210 million in federal Capital Projects Funds (CPF) to engage in massive overbuilding of private broadband infrastructure. In two previous analyses, the ACLP detailed the extent to which the state, via its Municipal Infrastructure Program (MIP), chose to use these resources to subsidize duplicative broadband infrastructure across huge swaths of the state. Specifically, the ACLP found that, of the 85,000+ locations to be passed by the 13 projects awarded MIP grants in rounds 1 and 2, 89% already have access to a broadband connection. The ACLP projected a similar rate of overbuilding for MIP grants allocated after round 2.

The state now appears on track to continue funding overbuilding as it races to meet an end-of-year deadline for completing projects built with CPF funds.

What’s Happening in Cortland

In December 2025, it was reported that ConnectALL, the state office administering the MIP, had canceled a $26M grant that was earmarked for broadband projects in Cortland and Cayuga counties. Apparently, the state did not have confidence that the project would be substantially complete by the end of 2026, the statutory deadline for CPF-funded projects.

On January 12, 2026, ConnectALL announced that “up to $36 million” in additional funding would be available in a new Round 4 of the MIP. Curiously, ConnectALL did not disclose that the funding being allocated in this round stemmed from the canceled Cortland/Cayuga project.

The next day, Cortland County issued an RFP seeking “partners to form a public-private partnership to expand broadband infrastructure countywide through New York State’s ConnectALL Municipal Infrastructure Program (MIP) – Round 4 reopened January 12, 2026.” The selected partner would join the county in formally applying for the funds available in MIP Round 4. (It is unclear if Cayuga County has taken similar steps.)

In its RFP, Cortland County identified “critical points of interest by priority (1-3) as well as unserved locations as provided by the ConnectALL office” that it wished to connect with MIP grant funds.

The ACLP sought to determine the extent to which these locations might already be served with broadband. To do so, we started with the geographic data files provided in the county’s January 2026 broadband RFP. These show the various “Top,” “Medium,” and “Low Priority” parcels (properties) which the project seeks to serve. These parcels were then merged with data from the FCC’s National Broadband Map to determine what proportion of locations (i.e., buildings) on those parcels already have access to 100/20 Mbps or faster terrestrial broadband service. The results of this analysis are summarized in Table 1.

Overall, 93% of Top and Medium Priority and 99% of Low Priority locations are already served. These findings are consistent with the significant overbuilding underwritten by ConnectALL with MIP funds. In contrast, only 37% of the “BEAD Program Points” which were included in the RFP data files are already served, a much lower rate of overbuilding. The full results of this analysis, along with a detailed methodology, are available in our full report.

What’s Next

Only one entity – Archtop Fiber – responded to the Cortland RFP. Per that response, Archtop is “in the midst of an aggressive, 3,000-mile fiber-optic construction push to provide broadband across the Hudson Valley, including Sullivan County.” Indeed, Archtop previously secured nearly $30M in MIP funds to “serve over 22,000 homes and businesses with 253 miles of fiber and fixed wireless on twelve towers” in Sullivan County. According to our analysis of that award, Archtop’s project in Sullivan County will overbuild 91% of those locations.

Whichever entity ultimately wins the available Round 4 MIP funding will have less than a year to complete its deployment. More broadly, it remains to be seen whether any of the MIP projects are on track to meet the statutory deadline for substantial completion. ConnectALL has not provided any updates on the status of these networks. Its inability or unwillingness to publicly acknowledge that it terminated the Cortland/Cayuga award does not inspire confidence that it will be forthcoming if additional projects are struggling or appear unable to meet the December 31 deadline.

Key Takeaways

• Cal Advocates’s estimate of “consumer harm” is built on unrealistic assumptions. The calculation treats every location as a subscribing household buying gigabit service at the highest promotional price. In reality, many subscribers choose lower (and cheaper) tiers, some households don’t subscribe, and some locations are vacant. When the report’s own regression coefficients are applied to actual subscribers, the implied figure falls below $93 million, less than one-tenth of the headline claim, and even that number is suspect given the many other methodological issues.
• Cal Advocates uses an outcome-driven model to yield supportive results. It chooses benchmark and monopoly prices to maximize the competitive “gap” between markets with and without multiple gigabit providers. The “competitive” benchmark uses the lowest promotional prices across multiple speed tiers, while the “monopoly” price uses each provider’s highest 1 Gbps promotional price—an apples-to-oranges comparison that inflates the claimed harm.
• The study’s own results undermine its conclusions. The models yield wildly inconsistent results across providers. If competition were a uniform driver of pricing, we would expect more consistent patterns. Sub-gigabit providers are associated with higher prices in several statistically significant models, the opposite of what a competition story would predict. And Comcast, one of the four major providers studied, was excluded from the regression because its pricing didn’t fit the model. More fundamentally, the analysis shows correlation, not causation. Without a more rigorous research design, one cannot conclude that competition caused the observed price differences.
• The policy recommendations outrun the evidence. Subsidizing new gigabit builds in areas that already have one gigabit provider is classic overbuilding, which is wasteful and not the highest-value use of limited broadband funds.

Overview

In January 2026, the California Public Utilities Commission’s Public Advocates Office (“Cal Advocates”) released a report examining broadband competition and pricing in four California cities: San Mateo, Oakland, Los Angeles, and San Diego. (Public Advocates Office 2026a) The headline finding was attention-grabbing: “Californians could save more than $1 billion annually if competitive pricing prevailed statewide.” (Public Advocates Office 2026a, 4)

The report makes an appeal to intuition. Where multiple gigabit providers compete, promotional prices are lower. Where a single provider dominates, prices are higher. Therefore, policies should support additional gigabit network builds. (Public Advocates Office 2026a, 5, 19)

However, a careful review of the study’s methodology reveals significant problems. The $1 billion figure rests on inflated assumptions, apples-to-oranges price comparisons, and a calculation that is disconnected from the report’s own statistical models. When applied consistently, those models imply a figure less than one-tenth as large. The report’s own regression results, provided in the technical appendices, show that competition explains only a small fraction of price variation. (Public Advocates Office 2026b, 13–15) And the statistical analysis demonstrates correlation but cannot establish causation.

This post walks through the key methodological concerns. The goal isn’t to dismiss the fundamental economic principle that competition leads to lower prices, but to highlight why the magnitude of the study’s claimed harm is overstated and the policy conclusions are premature. Notably, these methodological shortcomings echo those we identified in an earlier set of broadband studies submitted to the CPUC, which similarly relied on selective data, narrow technology-specific framing, and outcome-oriented analysis to support sweeping policy conclusions. (Santorelli and Karras 2021, 23–33)

A Lofty $1 Billion Estimate

The report’s primary attention-grabbing claim is that California consumers could save $1.13 billion annually if gigabit competition prevailed. This number appears in Table 5 and drives the report’s policy urgency. (Public Advocates Office 2026a, 18) But the calculation involves several assumptions, each of which inflates the final figure.

Weak Regression Results

Notwithstanding the myriad other issues with the analysis, the study’s own regression results are inconsistent.

The technical appendices provide the actual regression output, (Public Advocates Office 2026b, 13–15) and the results are weaker than the main report’s confident policy assertions suggest.

Correlation Is Not Causation

The report’s regression analysis purports to show that the number of gigabit providers is correlated with lower promotional prices. (Public Advocates Office 2026a, 14–15) But the report then draws causal inferences that the methodology cannot support.

Promotional Prices Are the Wrong Metric

The entire analysis is based on promotional prices, which raises several concerns: (Public Advocates Office 2026a, 11)

Other Methodological Concerns

• Frontier’s Exclusion. Frontier, a major fiber competitor, was excluded from the pricing analysis “due to its ongoing merger with Verizon.” (Public Advocates Office 2026a, 6) But Frontier appears as a meaningful competitive presence in the overlap tables: 80% of Charter’s lowest-priced tier in LA has Frontier overlap. (Public Advocates Office 2026b, 8–9) The merger doesn’t change the fact that Frontier’s current network presence affects competitive dynamics, and its exclusion may bias the report’s modeling. Moreover, the rationale is applied inconsistently: Charter and Cox—two of the three providers included in the regression—are themselves in a pending merger, yet neither was excluded on those grounds.

• Sampling Methodology Is Undisclosed. The appendices reveal sample sizes but not selection methodology. (Public Advocates Office 2026b, 2–3) Were locations chosen randomly? Stratified by neighborhood characteristics? Convenience-based? The phrase “selected sample locations” does significant work but is never explained. (Public Advocates Office 2026a, 8)

• The 10% Overlap Threshold. Appendix B excludes competitors with less than 10% geographic overlap as not representing “meaningful competitive pressure.” (Public Advocates Office 2026b, 4–11) This is an arbitrary threshold that could omit localized competitive effects.

• Excel-Based Regression With Apparent Errors. The regression tables show #NUM! errors and suspicious values (like standard errors of exactly 0) in several cells. (Public Advocates Office 2026b, 13–15) These errors, along with the table formatting, suggest the analysis was conducted in Excel rather than a proper statistical package. For a study of purported policy significance, the use of Excel raises concerns about, among other things: robustness checks, diagnostic testing, correct standard error specification, and reproducibility.

• Contradictory Overlap Patterns. The appendix reveals that some pricing patterns contradict the assertion that more competition brings about lower prices. For instance, Comcast’s lower-priced set in San Mateo shows less competitive overlap than its higher-priced set, and AT&T’s San Mateo pricing requires a “concentration” explanation rather than the simple provider counts used in the regression. (Public Advocates Office 2026b, 4–7)

Policy Implications

The report recommends that public investments “prioritize areas where consumers have only one gigabit provider.” (Public Advocates Office 2026a, 5, 19) This conclusion requires believing that:

• Correlation between provider counts and prices reflects causation (unproven)
• Promotional prices reflect sustained consumer welfare (questionable)
• Conditions enabling multiple providers in San Mateo can be replicated elsewhere (not analyzed)
• Subsidizing additional gigabit builds is higher-value than other uses of limited funds (not analyzed)

More broadly, the report’s exclusive focus on gigabit provider counts reflects a technology-specific view of competition that ignores the role of other platforms. Fixed wireless, 5G, and satellite services all exert competitive pressure, and consumers increasingly rely on non-wireline options for internet access. A technology-neutral assessment of competition would likely paint a different picture than one that counts only gigabit wireline providers. (Santorelli and Karras 2021, 37–38)

Key Takeaways

• According to the FCC’s Broadband Funding Map, 3,379,711 locations across the U.S. are currently without 100/20 Mbps terrestrial service.
• After accounting for BEAD awards, 1,101,356 locations without 100/20 Mbps service remain unfunded. When the number of units at a location is factored in (e.g., apartment units in a building), 1,342,667 units remain unfunded.
• Of the remaining unfunded locations, approximately 53.8% are “underserved” (have 25/3 Mbps service but not 100/20 Mbps).
• According to BFM data, 33.7% of BEAD locations already have 100/20 Mbps terrestrial service (wired or fixed wireless), suggesting that BEAD may involve overbuilding beyond the 20% allowed for in the program rules.
• This updated analysis underscores the need for a BEAD Reserve Fund, which the ACLP first proposed last October. Using remaining BEAD dollars to seed a Reserve Fund and deploying those resources as part of a second round of BEAD would ensure that the goal of the program is realized: that as many unserved and underserved locations as possible receive broadband service via BEAD.

Overview

This analysis estimates the number of broadband serviceable locations (BSLs) without 100/20 Mbps terrestrial service that remain unfunded by any program even after accounting for BEAD awards.

Updated Methodology

To identify locations that could be eligible for a second round of BEAD we:

1. Start with the FCC’s Broadband Funding Map (BFM), which provides a pre-computed list of locations that are unserved or underserved.
2. Set aside any location that is funded by another deployment program using the BFM’s award data from 5 federal entities spanning 15 broadband deployment programs.
3. Set aside locations which were intentionally not given a BEAD award by states, as identified in Final Proposal “No BEAD” data. These exclusions happened for a variety of reasons; we set aside all except those marked as ‘too expensive to serve.’
4. Count how many unserved/underserved locations that are currently unfunded will be covered by BEAD, and how many will remain.

This process differs slightly from our previous analysis, which manually identified unserved locations from National Broadband Map availability data. Since the pre-computed BFM location lists are generated by the FCC, we now utilize those lists instead of performing this portion of the analysis on our own.

Remaining Unfunded Summary by State

Current Status of BEAD Funded Locations

We compare the BFM locations against BEAD Final Proposal data compiled from 54 states and territories. We match BEAD award locations against the full BFM dataset to determine their current service status:

• 55.2% of BEAD locations are without 100/20 Mbps (both residential and business terrestrial service is not available)
• 33.7% have residential, business, or both types of terrestrial 100/20 Mbps service, or faster
• 11.1% do not match to any BFM location

Terrestrial includes wired, licensed, and unlicensed fixed wireless. If the definition of service is narrowed, the percentage of BEAD locations that are already served per BFM data decreases:

• 33.7% have terrestrial 100/20 Mbps (wired + all fixed wireless)
• 24.1% have wired or licensed fixed wireless 100/20 Mbps
• 5.5% have wired 100/20 Mbps

Regardless of what definition is used, it appears that BEAD deployments will involve some overbuilding of already served locations.

Key Takeaways

• We analyzed GIS data for 7 of the 14 projects that applied for funding as part of the $200M Texas Middle-Mile Grant Program. The other 7 projects did not provide GIS data necessary for this type of analysis.
• We found that 98.0% of locations within 1 mile of the proposed network routes already have access to terrestrial broadband at 100/20 Mbps or faster. This suggests the routes primarily traverse well-served corridors.
• This finding is consistent even when the distance from the route is increased to 5 miles (98.1%) or 10 miles (98.1%). This further underscores how well-served these corridors are.
• Program rules require applicants to “make all efforts possible to avoid overbuilding where existing middle-mile infrastructure already exists.” The state has made clear that it will prioritize projects that complement rather than duplicate existing infrastructure. That half of the proposals would significantly overbuild existing infrastructure appears to contravene the program’s focus.
• As the ACLP has noted extensively elsewhere, using public funds to overbuild existing middle-mile and last-mile infrastructure is wasteful and should be avoided lest these duplicative networks fail to attract enough customers to financially self-sustain. Officials in Texas and anywhere else that might be contemplating a similar program should study the myriad struggles and failures that have arisen when publicly-funded middle-mile networks overbuilt private infrastructure.

This post provides a summary of our full report, which includes a detailed methodology, and by-project estimates of served percentages.

TMM Overview

The Texas Middle-Mile (TMM) program, which is being administered by the state’s Broadband Deployment Office, is a $200M grant program that seeks to “strengthen network resiliency, support open-access networks to increase affordability for end-users and improve high-speed internet access by reducing the cost of connecting unserved or underserved areas to the internet backbone.”

Applications were accepted between August and November 2025, and the state released data submitted by applicants regarding network routes in January 2026.

Analysis

Using middle-mile network route data from applicants, we compiled a list of broadband serviceable locations within approximately 1 mile of the routes. We then utilized data from the National Broadband Map to determine which of these locations are already served.

On aggregate, 98.0% of locations within 1 mile of the proposed network routes already have access to terrestrial broadband at 100/20 Mbps or faster. This suggests the routes primarily traverse well-served corridors. Our finding is consistent even when the distance from the route is increased to 5 miles (98.1%) or 10 miles (98.1%). This further underscores how well-served these corridors are. Per-project estimates are in our full report.

Unfortunately, only 3 out of the 10 applicants, covering 7 out of 14 projects, provided data in a format allowing for geographic analysis. The other 7 applicants/projects provided only PDF documents containing images of their routes and are thus excluded from the analysis.

We expect that most other applications would yield similar results if we had access to geographic data. For example, the city of Brownsville recently submitted an application for funding to help it expand its burgeoning municipal fiber network to serve adjacent areas. That proposal will likely yield significant overbuilding.

Program rules require applicants to “make all efforts possible to avoid overbuilding where existing middle-mile infrastructure already exists.” The state has made clear that it will prioritize projects that complement rather than duplicate existing infrastructure. That half of the proposals would significantly overbuild existing infrastructure appears to contravene the program’s focus.

As the ACLP has noted extensively elsewhere, using public funds to overbuild existing middle-mile and last-mile infrastructure is wasteful and should be avoided lest these duplicative networks fail to attract enough customers to financially self-sustain. Officials in Texas and anywhere else that might be contemplating a similar program should study the myriad struggles and failures that have arisen when publicly-funded middle-mile networks overbuilt private infrastructure.

Background

Launched as a full FTTH system, the Lawrenceburg Municipal Utilities project represented one of Indiana’s first small-city fiber deployments. Despite significant capital investment, the network did not achieve a subscriber base large enough to offset operating and debt-service costs. Financial problems persisted for several years, and in 2020, the Indiana State Board of Accounts issued an audit finding that LMU had failed to account for losses associated with the fiber initiative, including misstated or unreported expenditures tied to the broadband project.

The audit revealed that the fiber network contributed to significant financial discrepancies within the utility, prompting increased scrutiny from both state auditors and local officials. These findings reinforced the city’s growing concern that the municipal broadband model was fiscally unsustainable for a system of Lawrenceburg’s size.

Failure and Transfer to Private Sector

Unable to resolve the ongoing financial issues or scale the network to profitability, Lawrenceburg eventually sought a private sector exit. In December 2022, the city announced it would sell its FTTH system to Altafiber (formerly Cincinnati Bell) for $3 million, transferring both ownership and operational responsibility to the private ISP.

The sale represented a substantial loss relative to the city’s original $10 million investment, underscoring the severity of the project’s financial underperformance. Altafiber noted that it would assume management and future expansion to the city’s fiber network, integrating it into the company’s regional infrastructure plans.

Takeaways

The Lawrenceburg network case illustrates several key challenges for municipal broadband:

1. Financial Instability – The project led to an accumulation of unrecoverable losses. The Indiana SBOA audit showed that broadband expenditures were not properly accounted for, revealing systemic fiscal management and highlighting the risk that small municipalities face when operating capital-intensive utilities without sufficient financial controls.
2. Insufficient Subscriber Base – Despite the high cost of deploying a citywide FTTH system, LMU failed to attract enough customers to cover operational expenses. As Local12 reported, the project was losing significant amounts of money even before the city explored a sale.
3. Below-Cost Divestiture – The ultimate sale of the system for $3 million, compared to the $10 million invested, demonstrates how much municipal broadband projects can expose taxpayers to long-term financial losses when adoption and revenue targets are not met.

Arianna is a 3L at New York Law School.

Benton’s Headline Misses the Mark

A recent Benton Institute post declared “Broadband Prices Increased in 2025.” But the data discussed in the piece tell a more nuanced and far less alarming story for consumers.

According to the FCC Urban Rate Survey (URS) data cited by Benton, price declines were widespread across the plans most households actually use:

“Prices for mid-tier plans … declined 8.5% in real terms between 2024 and 2025,” and “lower tier plans also witnessed price declines” of 13.4 percent.

Fixed wireless prices fell even more sharply:

“Fixed wireless service saw price declines of 20.0% from 2024 to 2025.”

The reason the average advertised broadband price appears to rise is clearly acknowledged:

The increase is driven by the growing availability and adoption of “expensive high-speed plans … driving up average broadband prices.”

This could suggest a voluntary shift by a subset of consumers toward ultra-high-speed premium offerings, not an across-the-board increase in the cost of internet service. And even this apparent phenomenon is by no means definitive: looking at FCC data from 2024 and 2025, the actual average rates paid for some ultra-high-speed plans (e.g., 500/50 Mbps, 2000/1000 Mbps) have decreased, not increased.

Benton’s analysis omits other important context regarding the sample of prices provided by the Urban Rate Survey. For example, regarding “lower-tier plans,” Benton claims:

“…there are fewer of them on offer, at least as represented in the URS.”

The last part of that statement – “…at least as represented in the URS” – is key. The URS contains only a “random sampling” of service offerings submitted to the FCC by ISPs. It is not exhaustive and can be incredibly misleading if major ISP offerings are omitted. For example, the latest URS does not include low-income offerings from at least two large ISPs: Charter (e.g., Spectrum Internet Assist) and Cox (e.g., Connect2Compete).

In addition, according to data collected by the National Digital Inclusion Alliance (NDIA), mid-size and larger ISPs tend to offer a variety of low-income packages to qualifying customers for $30 or less. These offerings are typically available across much of an ISP’s footprint. This means most Americans likely have access to at least one broadband plan for $30 or less per month, contingent on income or other qualifications.

Consequently, Benton’s conclusion that low-income households have fewer options for low-cost Internet is simply misleading.

Prices in Context

Placing broadband prices in a broader inflation context further undermines the idea of growing consumer affordability issues. Our own analysis of data from the BLS shows that internet prices have increased far more slowly than prices overall and much more slowly than other essential services:

• From 2016 to 2025, household internet prices rose by roughly 11 percent.
  
• Over the same period, overall consumer prices increased by about 37 percent.
  
• Electricity, natural gas, and water/sewer prices rose by 46, 61, and 45 percent respectively.

Taken together, the evidence points to a consistent pattern over time, as flagged in Benton’s piece:

An “overall pattern of steady prices,” with real declines for many commonly purchased broadband services.

Benton’s headline claim that “prices increased” relies on averages distorted by consumer upgrades to premium plans. For most households, broadband has become cheaper in real terms and has grown more affordable relative to other essential goods and services.

Key Takeaways

• Analysis of data from the BLS shows that broadband price growth over the last decade has been much lower than overall consumer prices, and much lower than the growth in cost of other essential household services.
• As policymakers and others contemplate the future of the broadband sector and potential approaches to affordability concerns, they should keep in mind that the prevailing regulatory approach to this sector has yielded significant and lasting consumer benefits.
• The results of our analysis are also available in the Data section of BroadbandExpanded under Broadband Prices and will be updated as new data becomes available.

Price Trends

Internet connectivity has become an essential service for nearly every American. For those households that subscribe to a broadband service, it is also a recurring monthly expense. The affordability of those connections continues to be a hot-button topic as parties debate whether broadband prices are too high and whether it is appropriate for government to intervene to address the issue.

Considering this discussion, the ACLP used the Consumer Price Index to investigate the growth of monthly internet costs in comparison to other essential household expenses over the last several years. The growth in prices of these various costs, compared to their levels ten years ago, is summarized in the graphic below. We have also made this graphic available in the Data section of BroadbandExpanded under Broadband Prices and plan to update it periodically as new data becomes available.

Between January 2016 and September 2025:

• The cost of household internet service increased in price by approximately 11%.
• The cost of household utilities such as electricity, piped gas, and water/sewer rose approximately 46%, 61%, and 45% respectively during these years, levels drastically higher than internet service.
• Overall consumer prices increased by about 37% percent.

While the affordability of a broadband connection continues to be a barrier to adoption for some households, in the broader context of consumer price trends, the cost of internet access services has seen comparatively little increase in recent years. In “real” terms (i.e., when considering overall consumer inflation), a home internet connection has become cheaper and makes up a smaller proportion of total household expenditures than it did in the past.

Discussion of “real” prices, despite the terminology, is not immediately intuitive and sometimes invites criticism, largely from those pointing out that a typical customer is unlikely to see the price on their bill go down. Contextualizing prices in regards to overall consumer prices can help illustrate this point: it is not that dollar prices for broadband are decreasing, but that they have grown much more slowly than overall consumer prices, and thus are likely to make up a smaller proportion of a household’s total spending.

Trends in Context

Several recent analyses have also observed that broadband prices have remained static or decreased. However, none of those analyses placed this significant trend within the broader context of household expenditures on other necessities, namely electricity and gas service. As depicted in the chart above, the prices for those utility services have increased significantly over the last few years, outpacing inflation and, in a growing number of cases, leaving consumers with ever-higher monthly bills for essential services.

Comparing broadband price trends with those in the electric, gas, and water sectors is imperfect given their vastly different market dynamics and regulatory approaches, but it is instructive nonetheless for several reasons.

First, the broadband, gas, and electric markets are similar in that most customers in the U.S. purchase these services from a private entity, e.g., a private ISP like Comcast or an investor-owned utility like ConEd (this dynamic is flipped in the water sector, where most Americans receive service from a public entity).

Second, these sectors are resource-intensive and require significant ongoing capex to maintain and modernize networks. For example, in 2024, broadband capex sector-wide was approximately $90 billion. That same year, electric IOU capex eclipsed $178 billion. Electric rates typically reflect capex (among other factors), which means that, in general, the more an electric utility invests in its network, the higher its rates will be because, as a regulated monopoly, it is guaranteed to recoup those investments, plus a set rate of return. Broadband ISPs, on the other hand, vie for customers in a robustly competitive market, where competition “regulates” prices.

Third, there are some who wish to subject broadband ISPs to the same regulatory framework as electric, gas, and water utilities. Given the pricing trends depicted above, this makes little sense and could lead to broadband price increases and other consumer harms, like less innovation and fewer service options.

In sum, as policymakers and others contemplate the future of the broadband sector and potential approaches to affordability concerns, they should keep in mind that the prevailing regulatory approach to this sector has yielded significant and lasting consumer benefits.

Methodology

This graphic was generated using the Consumer Price Index from the United States Bureau of Labor Statistics (BLS). The BLS collects and analyzes data on employment, pricing and productivity in the US market. More specifically, the Consumer Price Index-Urban (CPI-U) tracks the price of goods and services included in a “market basket” for urban consumers over time and is the most common measure of inflation. Data is collected via quarterly surveys and weekly diaries from consumer households, and the ‘urban’ CPI data covers roughly 93 percent of the US population.

The datasets included in the graph are:

• Internet: Internet services and electronic information providers in U.S. city average, all urban consumers, not seasonally adjusted (CUUR0000SEEE03)
• Electricity: Electricity in U.S. city average, all urban consumers, not seasonally adjusted (CUUR0000SEHF01)
• Piped Gas: Utility (piped) gas service in U.S. city average, all urban consumers, not seasonally adjusted (CUUR0000SEHF02)
• Water & Sewer: Water and sewerage maintenance in U.S. city average, all urban consumers, not seasonally adjusted (CUUR0000SEHG01)
• Overall CPI: All items in U.S. city average, all urban consumers, not seasonally adjusted (CUUR0000SA0)

Takeaways

The Axcess Ontario case illustrates several key challenges for municipal broadband:

1. Structural Limits of Middle-Mile Models – The county built a 200-mile open-access fiber ring to connect schools, businesses, and government sites but did not provide last-mile service to households, which meant no direct subscriptions, no steady revenue, and limited adoption. Without ISPs scaling up residential service, much of the network’s capacity sat unused, and without direct last-mile connections, revenue depended entirely on wholesale leases to ISPs, which proved insufficient.
2. Private Sector Advantage – Empire Access, with an existing customer base and capital, was able to scale the network in ways the county could not, confirming the role of private ISPs in delivering sustainable expansion. After acquiring the system, Empire Access committed to expand fiber-to-the-home gigabit internet, phone, and security services to communities such as Canandaigua, Geneva, Naples, and Victor, demonstrating how private ISPs are better positioned to translate middle-mile infrastructure into sustainable consumer broadband networks.
3. Fiscal Risk Management – Although officials claimed the lease-to-own arrangement would allow recovery of the $5.5 million investment, the project highlights how municipal broadband can expose taxpayers to long-term risks if adoption falls short. These risks include stranded assets when networks remain underutilized, ongoing operating deficits and debt obligations if revenues cannot cover costs, opportunity costs that divert resources from other public services, and the danger of technological obsolescence if a publicly owned network falls behind private sector upgrades.

Arianna Roberts is a 3L at New York Law School. Amina Cecunjanin-Music is a 3L at New York Law School.