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The 2026 VertexCompOps Index

How enterprises govern indirect tax and compliance —
and how the ones that govern it differently tend to run it differently

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A double-blind study of 750 IT, tax, and finance decision makers
in the United States, United Kingdom, Germany, and France

Contents

Foreword1
Executive summary2
Why indirect tax governance matters now3
Part I — The governance lens4
Part II — The capability lens8
Part III — Across both lenses18
What this means for your organization22
Beyond the data: a Vertex perspective24
Methodology25
About Vertex26
Appendix A — Exhibit index27

Foreword

Indirect tax is one of the few functions in an enterprise where determinations are made continuously, the exposure is lasting, and the conversation is still episodic and after the fact.

Every transaction a company completes carries a tax determination — even an exempt sale requires a decision that it is exempt, and usually a certificate to prove it. Most are made by software, in milliseconds, without a person reviewing them. They add up to a position the company will one day have to defend — to a tax authority, an auditor, occasionally a customer who noticed something first. Yet at most enterprises, the people accountable for those determinations reach the board only when something has already surfaced.

We set out to test whether that matters. We believe the working relationship between tax, finance, and IT is central to how well indirect tax and compliance function. Vertex calls this discipline Compliance Operations (CompOps™): continuously integrating tax, IT, finance, and audit response into a coordinated operating rhythm. So to answer the question of what distinguishes one enterprise from the next in its tax and compliance posture, we asked 750 tax, finance, and IT professionals across global enterprises how and where indirect tax and compliance fits within their strategic and operating agendas. We looked at the question two ways. First, we categorized finance and tax leaders by how often indirect tax reaches their board or executive committee. Second, we segmented all 750 enterprises into four tiers of AI capability in indirect tax and compliance. Then we asked what differs between the groups on outcomes neither arrangement was built on: where errors surface, how fast tax authorities get answers, how long a tax change takes to go live.

Both lenses point the same way, and neither is explained by company size. Enterprises that govern indirect tax differently tend to run it differently. They catch more of their own errors and rely less on chance and on making tax changes by hand. Where indirect tax reaches the board regularly, they also answer tax authorities faster. This is a study of one point in time, so it cannot prove which comes first. But the pattern is consistent, and it is not a matter of scale.

We have also published what the data does not support. Enterprises that govern indirect tax closely report no fewer returns needing rework and spend no fewer hours on manual compliance work than those that do not. But critically, they are more likely to find their errors themselves. And about half of all enterprises still take the more conservative tax treatment when they cannot prove a position — whatever their governance or their AI capability. Even enterprises that review indirect tax as a standing board item are more likely than others to say that half or more of their tax reserve exists because they cannot readily prove the position, not because the law is unclear.

For the more than four in ten enterprises where indirect tax reaches the board only when a problem arises, if at all, the opportunity is to put it on the agenda before one does.

For everyone, the gap that remains is proving the integrity of the original tax decision — especially when it must be defended under scrutiny.

We present this Index to help enterprises see how their indirect tax and compliance posture compares with that of their peers, so that their decisions can be proved and their outcomes improved over time.

Allison Cerra
Chief Marketing Officer, Vertex, Inc.
1The 2026 Vertex CompOps™ Index

Executive summary

The Index looks at indirect tax through two separate lenses. Each finding below belongs to one lens, or — for the last two — to both. The report never mixes the two cuts inside a single finding.

Governance
Capability
How enterprises are sorted
How often indirect tax and compliance is discussed at board or executive-committee level
An AI Capability Score from 0 to 100, built from ten questions on data readiness, enablement, governance, and deployment
Who answered
Finance and tax leaders (n=369)
All 750 respondents
Groups used in this report
Board-engaged
(standing item or periodically, 57%)
vs.
board-absent
(only when a problem arises, or rarely/never, 43%)
Tier 1 · least capable (20%),
Tier 2 · developing (39%),
Tier 3 · advanced (28%),
Tier 4 · most capable (13%)

The seven findings

  1. #1
    Governance
    Indirect tax largely has no standing seat at the board.

    Only 16% of enterprises discuss indirect tax and compliance as a standing board item. More than two in five (43%) do so only when a problem arises or rarely, if ever.

  2. #2
    Governance
    Board-engaged enterprises catch more of their own errors and answer tax authorities faster.

    Board-engaged enterprises report significantly better outcomes than board-absent enterprises. They are one-quarter as likely to learn of their errors from an external party (4% vs. 16%), nearly twice as likely to answer a tax-authority notice within five business days (48% vs. 26%), and half as likely to make and check taxability changes entirely by hand (13% vs. 26%).

  3. #3
    Capability
    Enterprises with more advanced AI capability in indirect tax report better outcomes beyond the capability score.

    Nearly one in four of the least capable enterprises (23%) say an external party most often identifies their errors, and one in five (20%) needs more than 30 business days to put a taxability change live. In the most capable tier (n=34), no respondent reports either.

  4. #4
    Capability
    Each step up the tiers involves a different discipline.

    Moving from the least capable tier (Tier 1) to Tier 2 is associated with making and checking fewer tax changes entirely by hand. Advancing from Tier 2 to Tier 3 goes with a deliberate governance approach. Moving from Tier 3 to the most capable tier is accompanied by consolidating tax rules in a dedicated tax engine and absorbing compliance mandates faster.

  5. #5
    Capability
    The market’s AI vocabulary outruns its AI.

    Despite respondents seeing a precise definition, no more than 45% of self-described AI agent workflows actually qualify. This gap reflects market terminology confusion rather than intentional deception. Consequently, self-reported stats require scrutiny. To address this, the study uses a ten-question capability score, measuring relative performance across tiers rather than relying on any single figure at face value.

  6. #6
    Cross-lens
    Neither lens is explained by company size.

    Size does not explain governance or capability. Surprisingly, large enterprises (10,000+ employees) comprise 34% of the least capable tier, despite being only 18% of all organizations studied. What separates enterprises is how they prioritize and run indirect tax — for example, whether IT funds it as a strategic priority — rather than how big they are.

  7. #7
    Cross-lens
    Proving the position remains unsolved.

    Regardless of board cadence or tier, about half take the conservative treatment when they cannot prove a position. And among enterprises holding indirect tax reserves, nearly three-quarters say at least a quarter of the reserve exists because they cannot readily demonstrate the position, rather than because the law is unclear.

2The 2026 Vertex CompOps™ Index

What the two lenses say together

Seen through either lens, the enterprises that treat indirect tax as a strategic matter look different in daily operation. The two lenses overlap: 13% of board-engaged enterprises sit in the least capable tier, against 34% of board-absent enterprises. Capability accounts for some of the difference between board-engaged and board-absent organizations, but not all of it. Among developing and advanced enterprises, those that discuss indirect tax regularly at the board level still report better outcomes on several measures.

The limits are just as clear. Governance and capability correspond to catching more errors internally and, on the governance lens, answering faster. Governance does not correspond to fewer returns needing rework or fewer manual hours. And neither lens changes how often enterprises take the conservative treatment when they cannot prove a position.

Why indirect tax governance matters now

This report is framed by two compounding pressures, concepts developed by Vertex. The first is Defensibility Drift™: the gap between the decisions a business makes at the point of transaction and its ability to prove those outcomes to authorities across an accelerating patchwork of jurisdictions. The second is Compliance Operations (CompOps) Drag™: the manual rework, integration friction, and delayed audit response created by fragmented tax, ERP, e-commerce, and reporting systems that were never designed to run continuous compliance in real time.

The two differ in origin — drift arrives from outside, drag is built inside — but they compound. A mandate arrives that the organization cannot absorb quickly. The workaround it adopts adds another seam to the architecture. The next mandate is harder still. Left ungoverned, drift and drag compound into a vicious cycle of complexity. Governed end to end, from determination to defense, the same lifecycle compounds the other way — into a virtuous cycle of control, where outcomes are accurate and audits are answerable. Vertex's Decision-to-Defense™ approach treats every determination as an outcome to prove, defend, and improve, all governed as one continuous flow across the transaction lifecycle.

The financial consequence of unmitigated drift and drag is what Vertex calls the Compliance Confidence Gap™: the distance between what enterprises could book, claim, or release from reserves with defensible confidence and what they conservatively report, forgo, or hold in reserve because they cannot prove every determination. This study measures both sides of it — how often enterprises take the more conservative treatment when they cannot prove a position, and how much of their reserves exist for the same reason (Finding 7).

Both pressures are governance problems before they are technology problems. An organization that reviews indirect tax only when something surfaces has no mechanism for noticing either pressure until it has already produced a consequence. That is why this report starts with the board.

3The 2026 Vertex CompOps™ Index

Part I — The governance lens

Finding 1 · Governance lens

Indirect tax largely has no standing seat at the board

Only one in six enterprises (16%) reviews indirect tax as a standing board or executive-committee item. For 43%, it reaches that level only when a problem arises, or rarely at all.

Across the finance and tax leaders surveyed, 15.7% say indirect tax is a standing item reviewed on a regular cadence. Another 41.5% say it is discussed periodically, as part of broader finance or risk updates. For 32.4% it comes up only when a specific problem or event arises — an audit, a penalty, a major regulatory change — and for 10.5% it is rarely or never discussed at that level.

Put differently, the board reviews indirect tax as a standing item at a minority of enterprises, and at more than four in ten it sees the function only after something has already gone wrong or is about to.

Exhibit 1

How often indirect tax reaches the board

Survey question:

How often is indirect tax and compliance discussed at the board or executive-committee level at your organization?

Base: Finance and tax respondents, “don’t know” excluded, n=369. Shares do not sum to exactly 100% because of rounding.

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StandingPeriodicallySpecific problem/eventRarely/never
BOARD-ENGAGED57%
BOARD-ABSENT43%

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View chart values
MeasureStandingPeriodicallySpecific problem/eventRarely/never
Board cadence15.7%41.5%32.4%10.5%

Board-engaged: 57%. Board-absent: 43%. Shares are rounded; segment widths are normalized to 100%.

4The 2026 Vertex CompOps™ Index
Finding 2 · Governance lens

Board-engaged enterprises catch more of their own errors and answer tax authorities faster

Compared with board-absent enterprises, board-engaged enterprises are one-quarter as likely to learn of their errors from an external party, nearly twice as likely to answer a tax-authority notice within five business days, and half as likely to make and check taxability changes entirely by hand.

The two groups run their operations differently on almost every measure the study captured. Board-engaged enterprises most often catch errors through automated controls or AI (63% vs. 35%) and are half as likely to rely on someone noticing by chance (10% vs. 19%). When a tax rule must change, they are half as likely to make and check the change entirely by hand (13% vs. 26%), and far less likely to need more than 30 business days to put it live (2% vs. 11%). When a regulation changes, 61% have a defined or proactive process to catch it before it takes effect, against 38%.

The difference shows up in how enterprises face the tax authority, too. Board-engaged enterprises are one-quarter as likely to say an external party — a tax authority, auditor, customer, or vendor — most often finds their errors (4% vs. 16%), and nearly twice as likely to answer a tax-authority notice within five business days (48% vs. 26%).

Two cautions apply. Board-engaged respondents are more likely to be C-suite (40% vs. 29%), so some of the gap may reflect who answered. And board-engaged enterprises are concentrated in the upper capability tiers (13% sit in the least capable tier, against 34% of board-absent enterprises), which may account for some of the difference.

Exhibit 2

Operating outcomes: board-engaged vs. board-absent

Survey questions:
  • When indirect tax errors are identified, who or what most often identifies them?
  • On average, how long does it take your organization to respond to an indirect tax authority notice?
  • Suppose your tax team determines that a product or service must be taxed differently in one or more jurisdictions. From the point that decision is made, how long does it typically take for the change to be live and applied to transactions across your systems?
  • When that taxability change is implemented, how is the work primarily carried out?
  • Compared to similar organizations, how effectively does your organization adapt to changes that impact indirect tax and compliance?
  • How many business days of effort does a typical indirect tax audit request consume?

Base: Finance and tax respondents, “don’t know” excluded. Board-engaged n=210–213; board-absent n=154–156, depending on the question.

MeasureBoard-engagedBoard-absent
Errors most often identified by an external party (tax authority, auditor, customer, or vendor)4.0%15.7%
Errors most often identified by automated rule-based controls or AI62.7%35.0%
Errors most often noticed incidentally by someone internal9.7%19.1%
Tax-authority notice answered within five business days48.3%26.0%
Taxability change made and checked entirely by hand12.8%25.8%
Taxability change takes more than 30 business days to go live2.2%10.8%
Defined or proactive process to catch regulatory change before it takes effect60.7%38.3%
A typical audit request consumes 20+ business days of effort (directional only)18.9%32.3%

All differences shown are statistically significant except the grey row, which is directional. The study measured where errors are most often identified, not how many occur or are caught.

5The 2026 Vertex CompOps™ Index

The gap extends to AI

Board-engaged enterprises are also further along with AI in indirect tax. Among them, 54% say AI now operates autonomously or handles routine work in their tax workflows, against 21% of board-absent enterprises. They are more likely to have a dedicated budget (63% vs. 45%) and a named executive owner (61% vs. 41%) for AI in indirect tax, to monitor AI accuracy after deployment (64% vs. 44%), and to report significant or transformational value from their AI (48% vs. 31%). They are also more likely to convene a standing tax, IT, and finance forum on a defined cadence (56% vs. 40%).

All these measures are also inputs to the AI Capability Score in Part II, and board-engaged enterprises are concentrated in the upper tiers. The data in this section describes the governance lens; it is not independent evidence for it.

Exhibit 3

AI in indirect tax: board-engaged vs. board-absent

Survey questions:
  • In your organization’s use of AI in indirect tax and compliance workflows, which best describes how work is typically completed today?
  • Based on your experience so far, how much measurable value has your organization realized from AI in indirect tax and compliance workflows?
  • Please indicate whether each of the following is in place at your organization today.
  • And please indicate whether each of the following governance practices is in place.

Base: Finance and tax respondents. Board-engaged n=213; board-absent n=156. “Don’t know” counted as not in place.

These measures also feed the AI Capability Score in Part II.

MeasureBoard-engagedBoard-absent
AI operates largely autonomously, or handles routine tasks while people handle exceptions54.1%21.1%
A dedicated budget for AI in indirect tax and compliance62.5%45.3%
A named executive owner accountable for AI in indirect tax and compliance61.3%41.5%
Post-deployment monitoring of AI accuracy63.5%43.5%
Significant or transformational measurable value from AI47.6%31.4%
A standing cross-functional tax, IT, and finance forum with a defined cadence56.3%40.3%

All differences are statistically significant. All six measures are also AI Capability Score inputs.

6The 2026 Vertex CompOps™ Index

The surprising lack of differences

There are two key areas where no statistically significant differences are found. Board-engaged enterprises report no fewer returns needing rework after the first pass (26% vs. 27% say more than one in ten) and no fewer manual hours (55% vs. 57% spend 100 or more hours a month on manual compliance work). Governance does not appear to mean fewer errors or fewer manual hours. It corresponds to catching more of those errors internally, answering for them faster, and relying less on chance.

The propensity for an enterprise to feature indirect tax on the board agenda more regularly also does not differ significantly by size. Enterprises with more than $1 billion in revenue, and those with 10,000 or more employees, make up statistically similar shares of both the board-engaged and board-absent groups.

Exhibit 4

What board engagement does not change

Survey questions:
  • What share of your indirect tax filings or returns require correction or rework after the first pass?
  • Approximately how many full-time employee-equivalent hours per month does your team spend on manual indirect tax and e-invoicing compliance work?
  • Approximately, what is your organization’s global annual revenue?
  • Approximately, how many employees does your organization have globally?

Base: Finance and tax respondents. Board-engaged n=209–213; board-absent n=152–156.

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Board-engagedBoard-absent
More than 10% of returns need correction or rework
100 or more manual hours per month
Annual revenue above $1 billion
10,000 or more employees
0%10%20%30%40%50%60%70%

Select a bar to see the source context.

View chart values
MeasureBoard-engagedBoard-absent
More than 10% of returns need correction or rework25.8%27.0%
100 or more manual hours per month55.3%56.9%
Annual revenue above $1 billion53.6%60.7%
10,000 or more employees14.6%16.3%

No row shows a statistically significant difference.

7The 2026 Vertex CompOps™ Index

Part II — The capability lens

Within the CompOps Index, every enterprise receives an AI Capability Score from 0 to 100 for indirect tax and compliance, built from ten questions spanning data and system readiness, enablement, governance, and deployment. Scores are grouped into four capability tiers. Throughout Part II, tiers are always named with their qualifier:

Tier / capabilityAI Capability ScoreShare of enterprises
Tier 1
least capable		0–3020%
Tier 2
developing		31–5439%
Tier 3
advanced		55–7028%
Tier 4
most capable		71–10013%

How to read Part II

Because the score is built from AI questions, comparing tiers on any of those same questions only restates how the score was constructed. Part II therefore compares tiers only on measures that are not score inputs — where errors surface, how fast changes go live, how enterprises absorb mandates, where tax rules live, and how often indirect tax reaches the board.

The inputs appear once, in Exhibit 6, as definitions.

Finding 5 shows that self-reported AI vocabulary runs ahead of what the software does. That is why the score combines ten questions rather than resting on any one, and why its value lies in the comparisons between tiers — on outcomes the score does not include — rather than in any single AI figure taken at face value.

Exhibit 5

The distribution of AI Capability Scores

Survey question:
  • Composite score, 0–100, from ten questions (listed in Exhibit 6).

Base: All respondents, n=750. Weighted.

Hover, focus or tap a mark for its context.

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SHARE (%)TIER 1 · 20%TIER 2 · 39%TIER 3 · 28%TIER 4 · 13%
30/3154/5570/71
25%20%15%10%5%0%
0–10
11–20
21–30
31–40
41–50
51–60
61–70
71–80
81–90
91–100

Capability score band

Select a bar to see the source context.

View chart values
MeasureShare
0–104%
11–207%
21–309%
31–4013%
41–5018%
51–6020%
61–7016%
71–8010%
81–903%
91–1000.4%

Tier 1 · 20%; Tier 2 · 39%; Tier 3 · 28%; Tier 4 · 13%.

8The 2026 Vertex CompOps™ Index
Exhibit 6

How the tiers are defined.

Survey question:
  • One representative answer is shown for each of the ten questions that make up the AI Capability Score.

Base: All respondents, n=750 (Tier 1 n=137; Tier 2 n=295; Tier 3 n=218; Tier 4 n=100), except the time-to-second-agent row (asked of 649) and the deployment-approach row (709).

These questions build the score. They describe the tiers; they are not findings about them.

Score input (answer shown)Tier 1 · least capableTier 2 · developingTier 3 · advancedTier 4 · most capable
Data readiness
1. Data and systems ready now for an AI agent to operate0.8% ▼9.9% ▼50.7% ▲90.0% ▲
Enablement
2. Tax function mostly independent or fully self-sufficient in adopting AI tools8.1% ▼24.0%34.3% ▲47.2% ▲
Governance
3a. A dedicated budget for AI in indirect tax and compliance8.9% ▼50.9% ▼82.5% ▲99.6% ▲
3b. A named executive owner accountable for AI in indirect tax and compliance15.1% ▼54.1%76.1% ▲92.8% ▲
4. Post-deployment monitoring of AI accuracy (one of eight practices asked)16.2% ▼60.2%75.6% ▲88.0% ▲
Deployment and results
5. AI operates autonomously, or handles routine tasks with people on exceptions5.5% ▼34.8% ▼62.1% ▲90.8% ▲
6. AI agent live and scaling in data quality and reconciliation (one of seven workflows asked)0% ▼15.9% ▼36.7% ▲68.0% ▲
7. AI agents handle most or all of monitoring compliance controls (one of twelve activities asked)3.4% ▼38.3% ▼67.2% ▲91.6% ▲
8. Broad, simultaneous rollout of AI agents across multiple workflows3.3% ▼15.6%22.6%39.6% ▲
9. Second AI agent live within three months of the first25.2%14.8% ▼29.1%49.8% ▲
10. Transformational impact from AI on how work is done0% ▼4.7% ▼12.9%51.2% ▲

▲ / ▼ = significantly higher / lower than all other respondents in the same banner group (FDR-corrected, p = 0.1). Unmarked = no significant difference flagged.

9The 2026 Vertex CompOps™ Index
Finding 3 · Capability lens

Enterprises with more advanced AI capability report meaningfully better outcomes — on measures the score does not include

On measures that play no part in the questions used to identify the tiers — where errors surface, how long a tax change takes to go live, how quickly mandates are absorbed, how regulatory change is caught — the least and most capable tiers look like different operations.

The study did not measure how often errors occur. It measured who most often catches them, where a material difference was found. Nearly one in four of the least capable enterprises (23%) say an external party most often finds their indirect tax errors. Among the most capable (n=34), none do.

There is also a significant difference in the amount of time required to effectuate tax changes. One in five of the least capable needs more than 30 business days to put a single taxability change live across its systems; among both the advanced and most capable tiers, none does.

Proactive, automated monitoring of regulatory change is uncommon in the two lower tiers (9% and 10%), then rises to 34% at Tier 3 and 55% at Tier 4. IT leaders at the most capable enterprises are the most likely to absorb a new e-invoicing or real-time reporting mandate in under a month (27%, against 7–10% in every other tier), and 85% describe indirect tax as a funded strategic priority on the IT roadmap, against 5% in the least capable tier.

The gap in answering a tax-authority notice within five business days, while large, is not statistically significant across tiers (30% at Tier 1, 57% at Tier 4). That said, as shown in Exhibit 2, it is significant when viewed through the governance lens.

Exhibit 7

Operating outcomes across the four tiers

Survey questions:
  • When indirect tax errors are identified, who or what most often identifies them?
  • Suppose your tax team determines that a product or service must be taxed differently in one or more jurisdictions. From the point that decision is made, how long does it typically take for the change to be live and applied to transactions across your systems?
  • Compared to similar organizations, how effectively does your organization adapt to changes that impact indirect tax and compliance?
  • When a new e-invoicing or real-time reporting mandate takes effect in a market where you operate, how long does IT typically need to achieve compliance?
  • How would you characterize indirect tax and compliance systems on your IT organization’s priority roadmap?
  • On average, how long does it take your organization to respond to an indirect tax authority notice?

Base: Finance (F) and tax (T) measures: Tier 1 n=77–80, Tier 2 n=157, Tier 3 n=103, Tier 4 n=34. IT measures: Tier 1 n=55–56, Tier 2 n=138, Tier 3 n=114–115, Tier 4 n=65–66.

Measure (respondents)Tier 1 · least capableTier 2 · developingTier 3 · advancedTier 4 · most capable
Errors most often identified by an external party (F&T)23.4% ▲6.3%4.2%0%*
Taxability change takes more than 30 business days (F&T)20.2% ▲5.4%0% ▼0%*
Proactive, automated monitoring of regulatory change (F&T)9.0% ▼10.2% ▼33.9% ▲55.2% ▲
New mandate absorbed in under one month (IT)8.4%6.7%10.0%27.1% ▲
Indirect tax a strategic IT priority with dedicated investment (IT)4.8% ▼31.9% ▼56.5% ▲85.1% ▲
Tax-authority notice answered within five business days (F&T) — not significant by tier29.8%35.4%44.2%57.3%

▲ / ▼ = significantly higher / lower than all other respondents in the same banner group (FDR-corrected, p = 0.1). Unmarked = no significant difference flagged.
* Tier 4’s 0% figures (n=34; 95% confidence interval 0–10.2%).

10The 2026 Vertex CompOps™ Index

Europe and the United States: where capability sits

Europe and the United States do not differ significantly on board cadence (20.6% vs. 13.8% standing item), which is why this comparison sits with the capability lens rather than the governance lens. They do differ on execution. European enterprises are significantly less likely to fund indirect tax as a strategic IT priority, to monitor regulatory change proactively, or to run a standing tax, IT, and finance forum — and significantly more likely to keep tax rules hard-coded in ERP customizations or spreadsheets. They are also, directionally, more likely to sit in the least capable tier (25% vs. 18%). The regulatory expectation is highest where the operating discipline is lower (see Sidebar 3).

Exhibit 8

Europe vs. United States: similar at the board, different in execution

Survey questions:
  • How often is indirect tax and compliance discussed at the board or executive-committee level at your organization?
  • How would you characterize indirect tax and compliance systems on your IT organization’s priority roadmap?
  • Compared to similar organizations, how effectively does your organization adapt to changes that impact indirect tax and compliance?
  • And please indicate whether each of the following governance practices is in place. (“A standing cross-functional Tax, IT and Finance forum with a defined cadence”)
  • When a sales transaction occurs, something has to decide how it’s taxed... Where do those tax rules primarily live and get maintained in your environment today?

Base: Varies by question — see table. European results are pooled across the UK, Germany, and France; country-level figures are not reportable.

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EuropeEurope (not significant)United StatesUnited States (not significant)
Bases (EU / US)
Indirect tax is a standing board item (finance & tax)
Not significant
100 / 269
Indirect tax is a strategic IT priority with dedicated investment (IT)
124 / 251
Proactively monitor and automatically update systems before changes take effect (finance & tax)
100 / 274
Standing tax, IT, and finance forum with a defined cadence (all)
225 / 525
Tax rules mainly hard-coded into ERP customizations or spreadsheets (IT)
123 / 251
In Tier 1 · least capable
Not significant
225 / 525
0%10%20%30%40%50%60%

Select a bar to see the source context.

View chart values
MeasureEuropeUnited States
Indirect tax is a standing board item (finance & tax)20.6%13.8%
Indirect tax is a strategic IT priority with dedicated investment (IT)31.7%50.4%
Proactively monitor and automatically update systems before changes take effect (finance & tax)13.0%23.1%
Standing tax, IT, and finance forum with a defined cadence (all)47.7%57.4%
Tax rules mainly hard-coded into ERP customizations or spreadsheets (IT)15.7%4.8%
In Tier 1 · least capable24.8%18.0%

Significance flags: rows 2–4 Europe lower / US higher; row 5 Europe higher / US lower than all other respondents in the same banner group (FDR-corrected, p = 0.1). Unmarked = no significant difference flagged.

11The 2026 Vertex CompOps™ Index
Finding 4 · Capability lens

Each step up the tiers involves a different discipline

Moving up the tiers, enterprises rely less on manual effort, govern indirect tax more deliberately, and absorb regulatory change faster. Each step has its own signature.

01

The difference between Tier 1 and Tier 2:
reduced manual execution

Almost half of Tier 1 finance and tax leaders (45%) say taxability changes are made and checked entirely by hand, against 13% at Tier 2. One in five of the least capable enterprises needs more than 30 business days to put a change live, against 5% at Tier 2. And four in ten Tier 1 IT leaders say the tax rules are spread across systems with no single source of truth, or hard-coded into ERP customizations and spreadsheets, against one in six at Tier 2.

The least capable tier is also the one that expands AI without evidence of benefit. Among enterprises that have extended AI beyond a first workflow, 16% of Tier 1 required measured, documented time savings first, against about half in every tier above. Like its more advanced counterparts, the least capable tier checks that AI is accurate; unlike them, it rarely checks that AI has paid off.

02

The difference between Tier 2 and Tier 3:
increased governance

This is where the two lenses meet most visibly in the data. Standing board attention barely moves between Tier 1 and Tier 2 (6% to 7%, both significantly below average). It more than triples to 24% at Tier 3. Also between Tier 2 and Tier 3, there are measured differences in proactive, automated regulatory monitoring (10% to 34%) and the prioritization of indirect tax as a funded IT roadmap investment (32% to 57%).

03

The difference between Tier 3 and Tier 4:
dedicated architecture and faster response

At the top of the tiers, the architecture changes. The most capable tier is the only one where a dedicated tax engine that other systems call for every transaction is the most common answer (49%, against 26% at Tier 3). Tier 4 IT leaders are almost three times as likely to absorb a new mandate in under a month (27% vs. 10%), and two-thirds (68%) say indirect tax was scoped in from the start of their most recent major systems initiative, against 47% at Tier 3. Standing board attention more than doubles again, from 24% at Tier 3 to 54% at Tier 4.

12The 2026 Vertex CompOps™ Index
Exhibit 9

What changes at each step up the tiers

Survey questions:
  • When that taxability change is implemented, how is the work primarily carried out?
  • Suppose your tax team determines... how long does it typically take for the change to be live and applied to transactions across your systems?
  • When indirect tax errors are identified, who or what most often identifies them?
  • When a sales transaction occurs... Where do those tax rules primarily live and get maintained in your environment today?
  • What had to be true before your organization expanded to the next workflow?
  • How often is indirect tax and compliance discussed at the board or executive-committee level at your organization?
  • Compared to similar organizations, how effectively does your organization adapt to changes that impact indirect tax and compliance?
  • How would you characterize indirect tax and compliance systems on your IT organization’s priority roadmap?
  • When a new e-invoicing or real-time reporting mandate takes effect in a market where you operate, how long does IT typically need to achieve compliance?
  • In your organization’s most recent major systems initiative — ERP migration, e-commerce platform, or finance transformation — how was indirect tax and e-invoicing compliance handled?

Base: Finance and tax (F&T) measures: Tier 1 n=77–80, Tier 2 n=157, Tier 3 n=103, Tier 4 n=34. IT measures: Tier 1 n=55–56, Tier 2 n=138, Tier 3 n=114–115, Tier 4 n=65–66. Expansion-gate question: Tier 1 n=28, Tier 2 n=265.

Step 1 — Reduced manual execution

MeasureTier 1 · least capableTier 2 · developing
Taxability change made and checked entirely by hand (F&T)45.4% ▲13.1%
Change takes more than 30 business days (F&T)20.2% ▲5.4%
Errors most often found by an external party (F&T)23.4% ▲6.3%
Tax rules spread across systems or hard-coded / in spreadsheets (IT)39.9% ▲16.8%
Measured, documented time savings required before expanding AI (Tier 1 n=28)15.8% ▼49.5%

Step 2 — Increased governance

MeasureTier 2 · developingTier 3 · advanced
Indirect tax a standing board item (F&T)7.1% ▼23.7% ▲
Proactive, automated monitoring of regulatory change (F&T)10.2% ▼33.9% ▲
Indirect tax a strategic IT priority with dedicated investment (IT)31.9% ▼56.5% ▲

Step 3 — Dedicated architecture and faster response

MeasureTier 3 · advancedTier 4 · most capable
Tax rules in a dedicated engine other systems call for every transaction (IT)26.1%48.7% ▲
New mandate absorbed in under one month (IT)10.0%27.1% ▲
Indirect tax scoped in from the start of the last major systems initiative (IT)46.6%68.2% ▲
Indirect tax a standing board item (F&T; Tier 4 n=34)23.7% ▲54.2% ▲

▲ / ▼ = significantly higher / lower for that tier versus all other respondents. Every step shown is also significant between the two adjacent tiers.

13The 2026 Vertex CompOps™ Index
Exhibit 10

What has to be true before AI is extended to the next workflow

Survey question:
  • What had to be true before your organization expanded to the next workflow?

Base: Respondents who expanded AI beyond a first workflow, “don’t know” excluded, n=609. Tier 1 n=28; Tier 2 n=265; Tier 3 n=217; Tier 4 n=99.

Gate applied before expandingTier 1 · least capableTier 2 · developingTier 3 · advancedTier 4 · most capable
Measured and documented time savings (Only gate separating Tier 1)15.8% ▼49.5%47.9%52.6%
A defined accuracy threshold sustained over a set period (Common everywhere)53.9%42.3% ▼58.5%52.6%
A clean audit or internal review48.7%44.2%40.7%56.7%
Successful handling of a defined volume of exceptions46.1%47.7%56.3%55.1%
Security or risk sign-off42.1%44.2%48.6%56.3%
Executive approval at a defined gate28.9%44.7%45.0%49.4%
Nothing formal — we expanded when it felt right7.9%1.8%2.4%2.4%

▲ / ▼ = significantly higher / lower than all other respondents in the same banner group (FDR-corrected, p = 0.1). Unmarked = no significant difference flagged.

Exhibit 11

Where the rules that decide how a transaction is taxed live

Survey question:
  • When a sales transaction occurs, something has to decide how it’s taxed — whether it’s taxable, at what rate, and whether any exemption applies. Where do those tax rules primarily live and get maintained in your environment today?

Base: IT respondents, “don’t know” excluded, n=374. Tier 1 n=55; Tier 2 n=138; Tier 3 n=115; Tier 4 n=66.

Hover, focus or tap a mark for its context.

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Dedicated engineEngine + ERP custom rulesHard-coded / spreadsheetsSpread / no single source
100%75%50%25%0%
Tier 1Least capable
Tier 2Developing
Tier 3Advanced
Tier 4Most capable
4 in 10 fragmented or hard-codedOnly tier where a dedicated engine is the most common answer

Select a bar to see the source context.

View chart values
MeasureDedicated engineEngine + ERP custom rulesHard-coded / spreadsheetsSpread / no single source
Tier 1 · least capable18.2%42.0% ▼19.6% ▲20.3% ▲
Tier 2 · developing13.4% ▼69.8% ▲5.7%11.1%
Tier 3 · advanced26.1%60.5%5.9%7.5%
Tier 4 · most capable48.7% ▲37.7% ▼7.1%6.5%

▲ / ▼ = significantly higher / lower than all other respondents in the same banner group (FDR-corrected, p = 0.1). Unmarked = no significant difference flagged.

14The 2026 Vertex CompOps™ Index
Finding 5 · Capability lens

The market’s AI vocabulary outruns its AI

Nearly every enterprise can date its “first AI agent” in indirect tax. Far fewer list AI agents among the tools they use, fewer still name agents as their most advanced AI in tax, and fewer than half of first-agent workflows do the two things that define an agent as described for respondents.

Respondents were given a definition before they answered: an AI agent is software that can take multi-step actions on its own — retrieving data, applying rules, and completing a task within a defined workflow — rather than only answering questions or generating text for a person to act on.

Under this definition, nearly all respondents (93%) can provide a go-live date for their organization’s first AI agent in an indirect tax or compliance workflow. Fewer (38%) list AI agents among the technologies they use, and 22% name agents as the most advanced AI in their tax workflows. Yet, when asked what the agent in their first workflow does without a person starting or finishing the step, 45% say it moves to the next step unprompted and 49% say it writes the result back into the system of record. Both are needed to meet the definition respondents were shown, so no more than 45% of those first-agent workflows meet it.

This is not a finding about enterprises overstating their capability. It is a finding about a category that has not agreed what an agent is. The vocabulary arrived from vendors — including this one — and buyers inherited a word without a stable definition. Readers should weigh this definitional confusion before taking self-reported AI adoption figures in this category at face value.

Exhibit 12

From “we have an agent” to what the agent actually does

Survey questions:
  • Approximately when did your organization’s first AI agent go live in an indirect tax or compliance workflow?
  • Which of the following technologies does your organization use for indirect tax and e-invoicing compliance workflows? (“AI agents that execute tasks within a workflow”)
  • And thinking specifically about indirect tax and e-invoicing compliance workflows, what is the most advanced form of AI currently used in that area?
  • Thinking about that workflow, which of the following does the agent do without a person initiating or completing the step?

Go-live date: 698 of 750 respondents gave a date. Technologies and most advanced AI: all respondents, n=750. Agent actions: respondents describing their first agent workflow, n=649.

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100%80%60%40%20%0%
750
Gave a go-live date for their first AI agent in indirect tax
750
List “AI agents that execute tasks within a workflow” among technologies used
750
Name agents as their most advanced AI in indirect tax workflows (with human oversight 15.9% + independently executing approved tasks 5.6%)
649
Agent writes the result back into the system of record
649
Agent moves to the next step without being prompted
649
Agent does both (ceiling; share doing both not reported)
BASE

Respondents were given the following definition: “By ‘AI agent,’ we mean software that can take multi-step actions on its own — retrieving data, applying rules, and completing a task within a defined workflow — rather than only answering questions or generating text for a person to act on.”

Select a bar to see the source context.

View chart values
MeasureShare
Gave a go-live date for their first AI agent in indirect tax93%
List “AI agents that execute tasks within a workflow” among technologies used37.8%
Name agents as their most advanced AI in indirect tax workflows (with human oversight 15.9% + independently executing approved tasks 5.6%)21.5%
Agent writes the result back into the system of record49.0%
Agent moves to the next step without being prompted44.5%
Agent does both (ceiling; share doing both not reported)≤44.5%
15The 2026 Vertex CompOps™ Index
Exhibit 13

When the first AI agent went live, by tier

Survey question:
  • Approximately when did your organization’s first AI agent go live in an indirect tax or compliance workflow?

Base: Respondents giving a date, n=698. Tier 1 n=94; Tier 2 n=286; Tier 3 n=218; Tier 4 n=100.

Hover, focus or tap a bar for its context.

Within 3 mo3–6 mo6–12 mo1–2 yrMore than 2 yr

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Most recentOldest
Tier 1 · least capable
More than half went live in the last six months.
Tier 2 · developing
Tier 3 · advanced
Tier 4 · most capable

Select a bar to see the source context.

View chart values
MeasureWithin 3 mo3–6 mo6–12 mo1–2 yrMore than 2 yr
Tier 1 · least capable21.8% ▲34.0% ▲33.6% ▼9.5%1.1%
Tier 2 · developing3.5% ▼22.3%57.2% ▲15.0%2.1% ▼
Tier 3 · advanced5.0%20.9%46.1%18.3%9.7% ▲
Tier 4 · most capable6.0%20.0%34.0% ▼26.8% ▲13.2% ▲

Perhaps unsurprisingly, the newest agent claims come from the least capable tier. Among Tier 1 respondents who gave a date, 22% say their first agent went live in the last three months — significantly more than any other tier — while Tier 4 is the tier most likely to date its first agent one to two years back (27%) or more than two years back (13%).

▲ / ▼ = significantly higher / lower than all other respondents in the same banner group (FDR-corrected, p = 0.1). Unmarked = no significant difference flagged. Tier 2 totals 100.1% due to rounding; widths normalized to 100%.

The three functions do not agree on AI’s value

Finance — the function that typically approves the spend — is the least convinced of AI’s value in indirect tax and compliance workflows. Only 35% of finance leaders report significant or transformational value from AI, against 50% of tax leaders and 52% of IT leaders. Finance is also significantly more likely to report no measurable value yet (10%) or only limited or unclear value (15%). Tax leaders are also the most likely to say they use AI agents (51%, against 29% of finance). Whoever builds the internal case for continued investment is therefore presenting to the function least persuaded that the money already spent has generated a return.

Interestingly, this insight connects to Finding 4. The one gate Tier 1 conspicuously lacks — measured, documented benefit before extending AI — produces exactly the evidence finance is missing.

16The 2026 Vertex CompOps™ Index
Exhibit 14

Three functions, three readings of AI in indirect tax

Survey questions:
  • Based on your experience so far, how much measurable value has your organization realized from AI in indirect tax and compliance workflows?
  • Which of the following technologies does your organization use for indirect tax and e-invoicing compliance workflows? (“AI agents that execute tasks within a workflow”)

Base: All respondents. Finance n=250; Tax n=125; IT n=375.

Hover, focus or tap a bar for its context.

FinanceTaxIT
Significant value across multiple workflows
Transformational impact on how work is done
Significant or transformational (sum of two rows above)
Limited or unclear value
No measurable value yet
Use AI agents that execute tasks within a workflow

Select a bar to see the source context.

View chart values
MeasureFinanceTaxIT
Significant value across multiple workflows23.1% ▼40.9%38.4% ▲
Transformational impact on how work is done12.2%8.7%13.5%
Significant or transformational (sum of two rows above)35.3%49.6%51.9%
Limited or unclear value15.3% ▲9.9%9.2%
No measurable value yet10.1% ▲2.6%5.2%
Use AI agents that execute tasks within a workflow29.3% ▼51.3% ▲39.5%

▲ / ▼ = significantly higher / lower than all other respondents in the same banner group (FDR-corrected, p = 0.1). Unmarked = no significant difference flagged.

17The 2026 Vertex CompOps™ Index

Part III — Across both lenses

The last two findings hold on both lenses. They are the only findings in which governance cadence and capability tier appear side by side, and each is shown separately rather than combined.

Finding 6 · Cross-lens

Neither lens is explained by company size

The largest enterprises are the most likely to sit in the least capable tier, and size does not differ significantly between board-engaged and board-absent enterprises. Whatever separates the leaders, it is not scale.

On the capability lens, enterprises with 10,000 or more employees make up 18% of those studied but 34% of the least capable tier — nearly twice their share — and are significantly under-represented at Tier 3 (11%). Enterprises with more than $1 billion in revenue show the same pattern: 71% of Tier 1 against 59% overall, and significantly fewer at Tier 3 (51%). Within the most capable tier, both are close to average.

On the governance lens, revenue and headcount do not differ significantly between the two groups: 54% of board-engaged and 61% of board-absent enterprises have more than $1 billion in revenue; 15% and 16% have 10,000 or more employees.

If scale drove capability, the largest enterprises would cluster at the top of the tiers. They cluster at the bottom. The study did not measure indirect tax spending, so it cannot say how much budget contributes, though a dedicated AI budget is one of the questions that defines the tiers. A benchmark showing that bigger companies do better offers enterprises nothing they can act on. A benchmark showing no advantage from scale points to how an enterprise prioritizes and runs indirect tax — including whether IT funds it as a strategic priority, which rises from 5% at Tier 1 to 85% at Tier 4 — rather than to its size.

Exhibit 15

Scale does not explain either lens

Survey questions:
  • Approximately, how many employees does your organization have globally?
  • Approximately, what is your organization’s global annual revenue?

Base: Capability lens: all respondents, n=750. Governance lens: finance and tax respondents, board-engaged n=213, board-absent n=156. Weighted.

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Headcount ≥10,000Annual revenue >$1BHeadcount avg 17.8%Revenue avg 58.5%
80%70%60%50%40%30%20%10%0%
17.8% avg58.5% avg
Tier 1
least capable
Tier 2
developing
Tier 3
advanced
Tier 4
most capable
Board-engaged
Board-absent
Nearly 2× their share.
33.9% vs 17.8% overall

Select a bar to see the source context.

View chart values
MeasureHeadcount ≥10,000Annual revenue >$1B
Tier 1 · least capable33.9% ▲71.0% ▲
Tier 2 · developing15.0%56.1%
Tier 3 · advanced11.4% ▼51.3% ▼
Tier 4 · most capable15.2%62.0%
Board-engaged14.6%53.6%
Board-absent16.3%60.7%

Headcount avg 17.8%; revenue avg 58.5%. Tier 1 headcount: nearly 2× their share, 33.9% vs 17.8% overall.

▲ / ▼ = significantly higher / lower vs. all other respondents. Board-engaged vs. board-absent differences are not significant.

18The 2026 Vertex CompOps™ Index
Finding 7 · Cross-lens

Proving the position remains unsolved

About half of enterprises take the more conservative tax treatment when they cannot prove a position — and that share does not differ significantly by capability tier or board cadence. Governance and AI capability correspond to catching more errors internally; neither, as measured here, closes the Compliance Confidence Gap.

This report measures both sides of the Compliance Confidence Gap: how often enterprises take the more conservative treatment when they cannot prove a position, and how much of their reserves exist because the position cannot be readily demonstrated.

Finance and tax leaders were asked how often, when their team cannot confidently prove a determination would hold up at audit, their organization takes the more conservative treatment — treating an uncertain transaction as taxable, declining to claim an exemption, or not reclaiming eligible indirect tax. Overall, 52% do so always or most of the time, with no statistically significant difference by tier or by board cadence.

Reserves tell the same story. Nearly three-quarters of enterprises (74%) hold reserves or accruals against indirect tax exposure. Among them, 73% say at least a quarter of that reserve exists because the organization cannot readily demonstrate its position — not because the law is genuinely unclear. Enterprises that treat indirect tax as a standing board item are significantly more likely to put that share at half or more (38%, against 20% overall).

One reading is that board attention makes the Compliance Confidence Gap more visible without closing it. An outcome that is correct but cannot be proven is still paid for — in overpaid tax, unclaimed exemptions, and reserves carried on the balance sheet against positions that could have been defended.

Exhibit 16

The Compliance Confidence Gap

Survey questions:
  • When your team cannot confidently prove that an indirect tax determination would hold up at audit, how often does your organization take the more conservative treatment — for example, treating an uncertain transaction as taxable, declining to claim an exemption, or not reclaiming eligible indirect tax?
  • Does your organization hold reserves or accruals against potential indirect tax exposure?
  • Of that [reserve], approximately what share exists because your organization cannot readily demonstrate the position, rather than because the tax law itself was genuinely unclear?

Base: Finance and tax respondents, “don’t know” excluded. Conservative treatment n=371; reserves n=369; share of reserve n=259 (those holding reserves). Standing-item base on reserve share n=40.

Panel 1 · Conservative treatment · “Always / most of the time”

52% (52.4% exact). No significant tier difference. Board cadence: standing 58.9% · periodic 50.8% · problem-only 50.6% · rarely/never 57.8% — none flagged.

52% (52.4% exact)
0%100%
No significant tier difference

Select a bar to see the source context.

View chart values
MeasureConservative treatment
Tier 1 · least capable45.8%
Tier 2 · developing47.9%
Tier 3 · advanced63.2%
Tier 4 · most capable57.3%

Panel 2 · Hold reserves / accruals against indirect tax exposure

74% (73.8% exact); ≈3 in 4 respondents hold reserves.

74% (73.8% exact)

≈3 in 4 respondents hold reserves

Tier 1 70.7%
Tier 2 77.0%
Tier 3 71.4%
Tier 4 72.9%

Panel 3 · Share of reserve attributable to inability to demonstrate position

Among reserve holders only (n=259). Percentages of organizations holding reserves.

Hover, focus or tap a bar for its context.

<25% attributable25–<50% attributable≥50% attributable
Reserve holders

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View chart values
Measure<25% attributable25–<50% attributable≥50% attributable
Reserve holders27.0%53.1%19.9%

73% of reserve holders have ≥25% attributable to unprovable positions. 38% (38.4% exact) of standing-item reserve holders have ≥50% attributable.

Percentages rounded for display. Reserve-share distribution: reserve holders only. Standing-item 38.4% is significantly higher.

19The 2026 Vertex CompOps™ Index

What we could not explain

One pattern in the data has no settled explanation, and we publish it rather than leave it out.

The most capable enterprises build tax into major systems projects from the start — but not by bringing tax people in earlier.

Two-thirds of Tier 4 IT leaders (68%) say indirect tax was scoped in as a core requirement from the start of their most recent ERP migration, e-commerce platform, or finance transformation — significantly more than any other tier. Yet when asked at what stage tax stakeholders are typically brought into technology projects, these enterprises are no more likely than anyone else to say “at requirements and design” (35%, against 44% overall).

The developing tier (Tier 2) shows the reverse gap: it is significantly the least likely to have scoped tax in from the start (28%) and, directionally, the most likely to have added it later in the project (43%).

Four explanations fit the pattern, though none was tested with this survey:

IT owns the agenda.

At more capable enterprises, IT may carry enough indirect tax fluency to write the requirements without tax specialists in the room. It fits two other findings: 85% of the most capable IT leaders call indirect tax a funded roadmap priority, and Tier 4 most often scopes tax in from day one. The study did not ask who owns the indirect tax agenda.

The rules are already encoded.

A dedicated tax engine may carry the requirements, so tax input at the project level matters less. Tier 4 is the tier most likely to run one (Exhibit 11).

Project volume.

More capable organizations may run more projects, diluting the share where tax joins at requirements.

Definitions.

IT leaders at more capable organizations may hold a stricter view of what counts as the requirements stage.

20The 2026 Vertex CompOps™ Index
Exhibit 17

Tax is scoped in early at the top of the tiers — without earlier tax involvement

Survey questions:
  • In your organization’s most recent major systems initiative — ERP migration, e-commerce platform, or finance transformation — how was indirect tax and e-invoicing compliance handled?
  • At what stage are indirect tax and e-invoicing compliance stakeholders typically brought into technology projects that touch sales transactions?

Base: IT respondents, “don’t know” excluded. Scoping n=374; stage n=373. Tier 1 n=55–56; Tier 2 n=136–138; Tier 3 n=115; Tier 4 n=66.

Scoped in early ≠ tax in the room early.

Most recent initiative

Hover, focus or tap a bar for its context.

Scoped in from the start, as a core requirementIncluded, but added later in the projectAddressed reactively, after go-live
Tier 1 · least capable
Tier 2 · developing
Tier 3 · advanced
Tier 4 · most capable

Select a bar to see the source context.

View chart values
MeasureScoped in from the start, as a core requirementIncluded, but added later in the projectAddressed reactively, after go-live
Tier 1 · least capable44.7%38.5%10.5%
Tier 2 · developing28.2% ▼42.9%22.5%
Tier 3 · advanced46.6%31.6%15.0%
Tier 4 · most capable68.2% ▲16.2% ▼11.0%

Stage tax stakeholders typically join

Hover, focus or tap a bar for its context.

At requirements and designDuring build and configurationDuring testing / UAT
Tier 1 · least capable
Tier 2 · developing
Tier 3 · advanced
Tier 4 · most capable

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View chart values
MeasureAt requirements and designDuring build and configurationDuring testing / UAT
Tier 1 · least capable62.3%14.4%12.3%
Tier 2 · developing38.1%31.6%19.0%
Tier 3 · advanced44.6%31.2%10.3%
Tier 4 · most capable35.1%31.8%23.4%

Reading the evidence

Early scoping is strongest in Tier 4. 68.2% scope tax in from the start, significantly higher than other respondents. Tier 2 is significantly lower at 28.2%.

Tier 2 more often adds tax later. 42.9% include tax later in the project—the largest reported share, but not flagged as significant. Tier 4 is significantly lower at 16.2%.

Early scope is not an early seat. Tier 4 reports 68.2% scoped in from the start, but only 35.1% say tax stakeholders join at requirements and design. These are separate measures, not a respondent-level pathway.

Joining stage shows no significant tier differences. The data flags no significant tier differences in when tax stakeholders typically join. The muted comparison shows reported variation, not a ranked finding.

▲ / ▼ = significantly higher / lower than all other respondents in the same banner group (FDR-corrected, p = 0.1). Unmarked = no significant difference flagged.

21The 2026 Vertex CompOps™ Index

What this means for your organization

Four questions worth answering

When did indirect tax last reach your board or executive committee?

If the answer is “when something went wrong,” you share a posture with the 43% of enterprises where indirect tax reaches the board only when a problem arises, if at all — a group four times as likely to learn of its errors from outside.

Where do your indirect tax errors surface?

If you usually learn from a tax authority, an auditor, or a customer, you share that with nearly one in four enterprises in the least capable tier.

Where do your tax rules live?

Four in ten least-capable enterprises keep them spread across systems or hard-coded in ERP customizations and spreadsheets. Every rule change is multiplied by the number of places it must be made.

How long does one taxability change take to go live?

Measure it from the tax team’s decision to the change going live across every system. One in five enterprises in the least capable tier needs more than 30 business days. From the advanced tier upward, none does.

22The 2026 Vertex CompOps™ Index

Three disciplines that separate the steps

Stop doing tax changes by hand.

Manual change-and-check is the clearest marker of the least capable tier (45%, against 13% one step up).

Put indirect tax on a governance cadence.

Standing board attention, proactive regulatory monitoring, and funded IT priority all rise sharply at the same step from developing (Tier 2) to advanced (Tier 3) enterprises.

Consolidate the rules, and prove benefit before you expand.

A dedicated tax engine is the most-capable tier’s signature; measured benefit before extending AI is the gate the least capable tier skips.

These are the practices that differ most between tiers, not steps guaranteed to move an organization between them.

How the findings map to the indirect tax lifecycle

Read together, the findings touch every stage of the indirect tax lifecycle. Exhibit 18 organizes them that way. It is a map of what the study found at each stage, not a test of the framework.

Exhibit 18

The findings across the indirect tax lifecycle

Base: Summary of figures from Exhibits 1, 2, 3, 7, 10, 11, and 16; bases as shown in each.

Lifecycle stageWhat the stage requiresWhat the study foundExhibit (lens)
Govern (coordinates the four operational pillars)End-to-end control across the lifecycle, from determination through defenseOnly 16% review indirect tax as a standing board item. Board-engaged enterprises are more likely to run a standing tax, IT, and finance forum (56% vs. 40%).1, 3 · governance
DetermineAccurate tax calculation at the moment of transaction49% of the most capable tier run a dedicated tax engine. Four in ten of the least capable keep rules spread across systems or hard-coded.11 · capability
ProveEvidence through an audit-defensible source of tax truth23% of the least capable tier most often learn of errors from an external party. Among reserve holders, 73% say at least a quarter of the reserve exists because the position cannot be demonstrated.7 · capability; 16 · cross-lens
DefendAudit, notice, appeal, and litigation readinessBoard-engaged enterprises are nearly twice as likely to answer a tax-authority notice within five business days (48% vs. 26%). The gap is not significant across capability tiers.2 · governance; 7 · capability
ImproveAdapting controls and tax logic as regulations and risk changeProactive, automated regulatory monitoring rises from 9% (least capable) to 55% (most capable). Only 16% of the least capable required measured time savings before extending AI.7, 10 · capability

Stage definitions reflect Vertex's lifecycle framework. Figures are repeated from the exhibits cited, and each keeps its original base and lens.

23The 2026 Vertex CompOps™ Index

Beyond the data: a Vertex perspective

The study's most persistent result is the one neither lens explains. About half of enterprises take the more conservative treatment when they cannot prove a position, whatever their board cadence or capability tier. Among those holding reserves, nearly three-quarters attribute at least a quarter of them to positions they cannot readily demonstrate. Board attention and AI capability correspond to catching more errors internally. As measured here, neither corresponds to proving more positions.

Our view is that proof cannot be assembled after the fact. It is a property of the determination itself: the rule applied, the data used, the jurisdiction and the treatment, recorded at the moment the decision is made. An organization that captures that record as it transacts has an audit-defensible source of tax truth before anyone asks for it. One that does not must reconstruct it under scrutiny.

That is the premise of the Decision-to-Defense approach: govern indirect tax and compliance end-to-end, so that every determination becomes an outcome to prove, defend, and improve. In practice, that means determining tax accurately at the point of transaction and maintaining a continuous audit trail of every compliance decision, so that the record is ready for audit at any moment. This is how Vertex approaches indirect tax and compliance today.

This section is Vertex's point of view. It is not a finding of the study.

24The 2026 Vertex CompOps™ Index

Methodology

Sample and fielding

ParameterSpecification
Total completes750, double-blind (respondents were not told the sponsor)
GeographyUnited States 525; United Kingdom, Germany, and France 225 combined. European results are pooled; country-level figures are not reportable.
FirmographicsMinimum $250 million revenue and 1,000 employees. Weighted: 58.5% above $1 billion; 17.8% with 10,000+ employees.
FieldingAugust–September 2026, Emerald Research Group. German and French instruments professionally translated.
WeightingResults weighted; effective sample size 678 (90%).
FunctionsIT n=375; finance n=250; tax n=125 — each with authority over or influence on enterprise indirect tax and compliance technology decisions (59.5% final decision makers; 36.7% heavily involved; 3.8% somewhat involved)

The two lenses

Governance lens.

Finance and tax respondents only (n=369), grouped by board or executive-committee cadence. “Board-engaged” = standing item or periodically; “board-absent” = only when a problem arises, or rarely/never.

Capability lens.

All respondents, grouped by an AI Capability Score (0–100) built from ten AI questions (listed in Exhibit 6). Tiers: 0–30, 31–54, 55–70, 71–100. No finding compares tiers on a score input.

Interpretive limits

  1. Cross-sectional: the study describes differences between organizations at one point in time. Relationships are written as “tend to,” never as cause.
  2. The two lenses overlap: board-engaged enterprises skew toward upper tiers (13% in Tier 1, against 34% of board-absent enterprises). Within tiers, the governance gap narrows but persists on several measures in the developing and advanced tiers; it largely disappears in the least capable tier, and the most capable tier is too small to read (board-absent n=9).
  3. Board-engaged respondents are more likely to be C-suite (40% vs. 29%); some differences may reflect who answered.
  4. The study measured where errors are identified, not how often or how quickly they occur.
  5. Small cells: Tier 4 n=34 on finance and tax measures; Tier 1 n=55–56 on IT measures; Tier 1 n=28 on the expansion-gate question; rarely/never board cadence n=35–37.
  6. AI capability findings rely on respondents’ descriptions of their software, not technical audit.
  7. Sidebars are external context from public sources, not findings of this study, and were current at the time of writing.

Significance

▲ and ▼: a column is significantly higher (▲) or lower (▼) than all other respondents in the same banner group, using a false-discovery-rate correction at p = 0.1 (90% confidence).

Comparisons between combined groups (board-engaged vs. board-absent) and between adjacent tiers were tested separately by Emerald Research Group, also using a false-discovery-rate correction at the 90% confidence level.

25The 2026 Vertex CompOps™ Index

About Vertex

Vertex is the Decision-to-Defense™ global indirect tax and compliance company.

Vertex helps enterprises bring control to indirect tax and compliance across the full transaction lifecycle — from tax determination and e-invoicing through reporting, filing, and audit defense — to make outcomes easier to prove and improve over time.

Trusted by more than 60% of the Fortune 500, Vertex combines decades of tax expertise, deep global tax and compliance knowledge, and embedded integrations to help organizations operate globally with confidence. With headquarters in North America and offices in South America and Europe, Vertex's purpose is to ensure businesses and communities thrive through trusted transactions.

26The 2026 Vertex CompOps™ Index

Appendix A — Exhibit index

#ExhibitFindingLens
1How often indirect tax reaches the board1Governance
2Outcomes: board-engaged vs. board-absent (+ Sidebar 2)2Governance
3AI: board-engaged vs. board-absent2Governance
4What board engagement does not change2Governance
5Distribution of AI Capability ScoresFrameCapability
6How the tiers are defined: all ten inputsFrameCapability
7Operating outcomes across four tiers3Capability
8Europe vs. US (+ Sidebar 3)3Regional
9What changes at each step (three tables)4Capability
10Expansion gates, four tiers4Capability
11Where tax rules live4Capability
12Agent claim ladder5Capability
13First agent go-live by tier5Capability
14Three functions5Function
15Scale vs. both lenses6Cross
16The Compliance Confidence Gap7Cross
17Scoped in early without earlier involvementOpen q.Capability
18The findings across the indirect tax lifecycleMultipleCross