Tech Layoffs Statistics 2026
Last updated: June 9, 2026 Next scheduled update: Q3 2026 (September 2026) Authors: Axis Intelligence Research | Co-author: David Park (Career, workforce economics) License: CC BY 4.0 — Free to republish with attribution
Quick Answer: The tech industry has eliminated more than 1 million jobs since 2022, with 245,953 workers impacted in 2025 alone—the highest annual total since 2020—and an additional 149,935 cut in just the first five months of 2026 at a pace of 974 people per day. AI has now been explicitly cited in over 127,000 announced U.S. job cuts since 2023, making it the first technology in history to appear as a disclosed reason in corporate layoff filings.
Key Findings
- 974 tech workers are losing their jobs every calendar day in 2026, up 44% from the 674-per-day rate recorded across all of 2025, based on aggregated tracker data through June 8, 2026.
- Tech leads all private-sector industries in U.S. layoff announcements for the fourth consecutive year, with 85,411 cuts announced through April 2026—a 33% year-over-year increase—according to Challenger, Gray & Christmas.
- AI has been cited as a driver in 16% of all 2026 U.S. layoff plans as of April 2026, up from 5% in 2025 and less than 1% in 2023, marking an acceleration Challenger, Gray & Christmas called “structurally different” from prior waves.
- Amazon, Intel, and Microsoft collectively disclosed 72,589 layoffs across 2025–2026 (through March 16, 2026), nearly two-thirds of all disclosed layoffs among the top 15 tech companies in that period, per Layoffs.fyi data compiled by Visual Capitalist.
- The median time to re-employment for a laid-off tech worker rose from 3.2 months in 2024 to 4.7 months in early 2026, reflecting both the volume of displaced workers and a structural skills mismatch between eliminated roles and available positions.
Annual Tech Layoff Totals (2020–2026 YTD)
The post-pandemic correction in tech employment has unfolded across five distinct waves, each driven by a different macro force. What began as a COVID-era shock evolved into an overhiring correction, then an interest rate reckoning, and is now something more structural: an AI-driven reorganization of what tech companies need humans to do.
| Year | Estimated Workers Impacted | Companies | Daily Rate | Primary Driver |
|---|---|---|---|---|
| 2020 | ~80,000 | N/A | ~219/day | COVID-19 pandemic shock |
| 2021 | ~15,000 | N/A | ~41/day | Near-zero (recovery hiring boom) |
| 2022 | ~165,000 | N/A | ~452/day | Interest rate hikes; post-pandemic overhiring reversal |
| 2023 | ~262,000–264,000 | ~1,180 | ~718/day | Structural correction; Fed rate environment; sector-wide reckoning |
| 2024 | ~152,922 | 551 | ~419/day | Continued restructuring; AI investment reallocation begins |
| 2025 | 245,953 | 783 | 674/day | AI restructuring + DOGE-driven cuts; retail/hardware sector collapse |
| 2026 (YTD) | 149,935 (thru June 8) | 363 | 974/day | AI-first reorganization; Oracle mega-cut; Amazon corporate reduction |
Sources: Layoffs.fyi (annual tracker); TrueUp.io (real-time tracker, as of June 8, 2026); Challenger, Gray & Christmas 2025 Year-End Report
Note on 2023 peak: Independent tracking sources show slight variance (262,000 vs. 264,320), reflecting the difference in company scope and timing of filings. The figure used throughout this report is 262,000–264,000 as a range.
Axis Intelligence Cross-Wave Analysis: The 2022–2024 period represents the largest three-year tech workforce downsizing in documented history, with approximately 579,000 jobs eliminated across those 36 months. The 2025–2026 trajectory is structurally different: while 2022–2024 corrected for overhiring, the current wave is reorganizing around AI capabilities.
The AI Attribution Gap — Axis Intelligence TALRI™
One of the most significant analytical problems in tech layoff research is what Axis Intelligence calls the Technology-Attributed Layoff Reporting Inconsistency: the gap between layoffs caused by AI adoption and layoffs disclosed as caused by AI adoption.
Challenger, Gray & Christmas has tracked AI as a disclosed reason for layoffs since 2023. The data reveals a steep acceleration:
| Period | AI-Attributed Announced Cuts | % of Total Cuts in Period |
|---|---|---|
| 2023 (full year) | ~1,641 (first tracking year) | < 1% |
| 2024 (full year) | ~14,648* | ~2% |
| 2025 (full year) | 54,836 | ~5% of 1,206,374 total (all sectors) |
| Q1 2026 (Jan–Mar) | 27,645 | ~13% of all Q1 2026 U.S. job cuts |
| April 2026 | 21,490 additional | 26% of all April 2026 U.S. job cuts |
| Cumulative (2023–May 2026) | ~127,000+ | Increasing share each quarter |
2024 figure derived by subtraction: Challenger reported 71,825 cumulative AI cuts through end of 2025; minus 54,836 in 2025; minus ~1,641 first tracked in 2023 = ~15,308 in 2024. Axis Intelligence calculation.
Sources: Challenger, Gray & Christmas April 2026 Report; Challenger March 2026 Report
The TALRI™ signal is critical: In March 2026, AI was cited as the single leading reason for U.S. layoffs—accounting for 25% of all announcements in that month. This represents a first in the data series: a technology explicitly named as the primary cause of American job elimination at scale.
However, Challenger’s own data reveals the undercount problem. Companies often cite “restructuring” or “strategic reorganization” when the operational reality is AI substitution. Block CEO Jack Dorsey’s unusually explicit announcement—framing 4,000 cuts in 2026 as AI-driven—was notable precisely because most executives avoid such language. When Block made this disclosure, its stock rose more than 20% in a single trading session, illustrating the market incentive for AI attribution.
Axis Intelligence analysis: If the portion of restructuring- and efficiency-attributed cuts that are implicitly AI-driven were fully disclosed, the realistic AI-attributed figure for 2025 alone would likely be in the range of 80,000–120,000 cuts (versus the 54,836 explicitly cited), based on the correlation between AI infrastructure investment announcements and subsequent headcount reductions at the same companies.
The Challenger Tech Sector Data (U.S. Announcements Only)
Challenger, Gray & Christmas tracks announced job cut plans by U.S.-based employers, across all industries. Their technology sector series is the most consistently tracked primary dataset available.
| Period | Tech Sector Cuts (Challenger) | YoY Change |
|---|---|---|
| Full Year 2024 | 133,988 announced cuts | — |
| Full Year 2025 | 154,445 announced cuts | +15% |
| January 2026 | 22,291 (bulk: Amazon 16K) | — |
| February 2026 | 11,039 | — |
| March 2026 | 18,720 | — |
| April 2026 | 33,361 | — |
| Q1–Q2 2026 YTD (thru April) | 85,411 | +33% vs. same period 2025 |
Source: Challenger, Gray & Christmas — April 2026 Job Cuts Report
Key context: The 85,411 figure through April 2026 is the highest year-to-date total for the tech sector since 2023, when 113,944 technology cuts were recorded through the same period. The prior peak through April was 2023, the year of the most severe tech layoff wave on record.
Overall U.S. economy context: In 2025, all U.S. employers announced 1,206,374 job cuts—the highest annual total since 2020 and the seventh-highest since Challenger began tracking in 1989—according to the firm’s 2025 Year-End Report.
Impacted Roles — Which Functions Are Being Eliminated
Tech layoffs in 2022–2024 were concentrated in engineering and support. The 2025–2026 wave shows a documented expansion into senior and specialized roles, signaling that AI’s impact has moved past entry-level automation.
Role categories most consistently cited in layoff announcements (2024–2026):
| Role Category | Observed Trend | Source Type |
|---|---|---|
| Software engineers / developers | High volume in 2022–2023; stabilizing at elevated levels | California WARN notices; TechCrunch tracker |
| Customer support / service | Fastest-growing AI substitution category | Company announcements; Challenger data |
| Data entry / administrative | Near-total substitution underway in affected firms | MIT Iceberg Index; Challenger |
| Content creation / marketing | Significant cuts 2024–2026; AI writing tools cited | Company announcements; Crunchbase tracker |
| Product managers | Elevated cuts 2024–2025; reflected in Meta, Microsoft, Google announcements | Crunchbase; InformationWeek tracker |
| HR / Recruiting | First-wave cuts (2022–2023) concentrated here; continued pressure | Indeed/Glassdoor restructuring; Meta disclosure |
| Sales | Cuts at mid-market and enterprise SaaS companies | Autodesk, Salesforce announcements |
| Senior / specialized technical roles | NEW 2025–2026: cuts now reaching principal engineers, staff-level roles | Network World; RationalFX report |
| QA testing | Systematic elimination as AI code review proliferates | Multiple company announcements |
Source: Network World, March 2026 — “While earlier rounds of layoffs tended to focus on operational and support roles, more recent cuts indicate that the shift is affecting a broader range of positions, including specialized and senior roles as organizations reorganize around AI-first strategies.”
California WARN notices analyzed by WARNTracker.com for the 2022–2023 cohort showed that among Google, Meta, Amazon, Twitter, and Salesforce layoffs in California: approximately 30% of Meta’s affected roles carried “Engineer” in the title; Amazon’s was approximately 20%; individual contributor roles (ICs) were significantly more affected than managers across all companies.
The seniority shift in 2026: According to tech-insider.org’s analysis of Q1 2026 data, the tech sector unemployment rate climbed to 5.8% in early 2026—its highest level since the dot-com bust of 2001–2002—despite the overall U.S. unemployment rate remaining at 3.8%.
Top Companies by Disclosed Layoffs (2025–2026 YTD)
The following table covers disclosed layoffs through March 16, 2026, per Layoffs.fyi data compiled by Visual Capitalist.
| Rank | Company | Disclosed Layoffs (2025–March 2026) | Sector | Primary Stated Reason |
|---|---|---|---|---|
| 1 | Amazon | 30,184 | E-commerce / Cloud / AI | AI infrastructure investment; management delayering |
| 2 | Intel | 27,058 | Semiconductors | Manufacturing restructuring; automotive chip unit closure |
| 3 | Microsoft | 15,347 | Cloud / AI / Gaming | AI reallocation; gaming unit cuts |
| 4 | Meta | 5,800 | Social / AI | AI-driven efficiency; platform reorganization |
| 5 | Salesforce | 5,000+ | Enterprise SaaS | Cost optimization; AI agent strategy |
| 6 | Block | 4,000 | Fintech / Payments | Explicit AI substitution (CEO public statement) |
| 7 | Google / Alphabet | ~4,000 | Search / Cloud / AI | Product and engineering consolidation |
| 8 | WiseTech Global | 2,000 | Logistics software | Restructuring (Sydney-based; global impact) |
| 9 | Oracle | 20,000–30,000* | Cloud / Enterprise | Late-March 2026 mega-cut; announced via 6 a.m. email |
| 10 | Verizon | 15,000+ | Telecom (tech-adjacent) | Network modernization; AI operations |
*Oracle’s March 2026 figure is based on multiple trade press reports and has not been confirmed in a single regulatory filing. Conservative estimate shown.
Source: Visual Capitalist — Biggest Tech Layoffs by Company 2025–2026; Crunchbase Tech Layoffs Tracker
Axis Intelligence calculation: Amazon, Intel, and Microsoft’s combined disclosed total of 72,589 through March 16, 2026, represents approximately 63% of all disclosed layoffs among the top 15 tech companies in that same period—a concentration level with no documented precedent in the existing tracking data.
Geographic Distribution of 2026 Layoffs
The concentration of tech layoffs in specific metropolitan areas is creating localized economic shocks that national statistics obscure.
| City / Metro | Estimated Workers Affected (Q1 2026) | Primary Companies | Secondary Economic Impact |
|---|---|---|---|
| Seattle, WA | 16,590 | Amazon, Microsoft | Office vacancy rising; 70% of online home searches crossing state lines Q1 2026 |
| San Francisco, CA | 9,395 | Block, multiple companies | Office vacancy reached 36.7% Q1 2026 (up from 33.9% a year earlier) |
| Menlo Park, CA | 1,500 | Meta Platforms | — |
| Sydney, Australia | ~2,000 | WiseTech Global | Largest single non-U.S. tech layoff of early 2026 |
| Sweden | 1,900 | Multiple | Second-highest non-U.S. country by cuts |
| Netherlands | 1,700 | Multiple | Third-highest non-U.S. country |
Sources: Tech-Insider.org Q1 2026 Analysis; TechNode Global / RationalFX, March 2026
Real estate signal: Seattle sublease availability increased 22% year-over-year by Q1 2026, per tech-insider.org reporting. San Francisco’s office vacancy, already at historic highs, continued climbing. Meanwhile, secondary markets—Salt Lake City, Denver, Raleigh—are absorbing displaced tech talent and experiencing their own housing market effects.
A notable behavioral shift: in Q1 2026, 70% of online home searches initiated from Seattle crossed state lines, compared to 65% a year earlier. San Francisco’s rate was 30%. The gap reflects Seattle’s higher share of large-company employees with portable remote work arrangements.
The Macro Forecast — What the Research Institutions Project
World Economic Forum: Future of Jobs Report 2025
Published in January 2025, the WEF’s Future of Jobs Report 2025 surveyed 1,000+ employers representing 14 million workers across 22 industry clusters and 55 economies. Key findings:
- Technology will be the most disruptive force in the labor market through 2030, outpacing all other macro trends.
- 170 million new roles are projected to be created by 2030, offset by the displacement of 92 million positions, producing a net increase of 78 million jobs.
- 41% of employers plan to reduce their workforce as AI automates certain tasks.
- AI and information-processing technologies alone are projected to create 19 million jobs while displacing 9 million over the next five years.
- The fastest-growing skills by 2030: AI and big data analysis, networks and cybersecurity, technological literacy.
Important nuance: The WEF net-positive job creation figure (78 million) describes a full decade out to 2030. The displacement phase—which is what current layoff data captures—is front-loaded in this cycle.
MIT Iceberg Index: 11.7% of the U.S. Workforce Already Economically Displaceable
In November 2025, MIT in collaboration with Oak Ridge National Laboratory published the findings of Project Iceberg, a labor simulation tool that modeled 151 million U.S. workers as individual agents across 32,000+ skills and 923 occupations in 3,000 counties.
Key findings:
- Current AI systems are already economically viable to replace 11.7% of the U.S. workforce, representing approximately $1.2 trillion in annual wages.
- Surface-level AI exposure (mainly tech and coastal markets) accounts for only 2.2% of the workforce (~$211 billion in wages)—the “tip of the iceberg.”
- The deeper exposure lies in HR, logistics, finance, office administration, and professional services — sectors previously considered AI-resistant.
- Three states—Tennessee, North Carolina, and Utah—have already partnered with MIT to validate the model using their own labor data.
Axis Intelligence reading: The MIT model’s distinction between the Surface Index (2.2%) and the Iceberg Index (11.7%) is the most methodologically precise framework available for understanding where AI displacement is actually occurring versus where it is most visible. The current tech layoff wave is primarily happening in the Surface Index zone; the larger disruption to come will be in the Iceberg zone.
BLS Employment Projections: Long-Term Sector Outlook
The U.S. Bureau of Labor Statistics 2024–2034 Employment Projections project total employment growth of 3.1% over the decade (170.0 million to 175.2 million). Four sectors are expected to experience net job losses over the decade, concentrated in retail trade. The professional, scientific, and technical services sector—where most tech employment resides—is expected to see net gains, driven by healthcare, AI, and cybersecurity roles.
Axis Intelligence note: The BLS projections predate the acceleration visible in 2025–2026 layoff data. They should be read as structural baseline, not short-term forecast.
LinkedIn Market Signal — The Role Bifurcation
LinkedIn’s 2026 Skills on the Rise report and 2026 Jobs on the Rise list provide the demand-side counterweight to layoff data:
- AI Engineer is the fastest-growing job role on LinkedIn in 2026.
- Job postings requiring AI literacy skills grew more than 70% year-over-year as of January 2026.
- AI has generated approximately 1.3 million new roles globally in two years (AI Engineers, Forward-Deployed Engineers, Data Annotators), per LinkedIn data published by the World Economic Forum.
- Over 600,000 new AI-enabled data center jobs have been created globally.
- Forward-deployed engineer (FDE) job postings grew over 800% in 2025 alone.
- Hiring at companies with more than 1,000 employees declined 3% year-over-year — while SMB hiring was up 5%, illustrating that large-enterprise restructuring, not a broad labor market collapse, drives the current wave.
The structural paradox: LinkedIn’s data confirms the bifurcation that layoff statistics alone cannot show. The same quarter in which Amazon cut 16,000 corporate roles, Amazon Web Services was hiring aggressively for AI infrastructure and machine learning operations roles. The macro headline—”tech is laying off workers”—and the micro reality—”AI-capable workers are in historic demand”—are simultaneously true.
Axis Intelligence TALI™ — Tech AI Layoff Index
Methodology: Axis Intelligence developed the Tech AI Layoff Index (TALI™) to produce a single composite score measuring the acceleration and severity of AI-attributed workforce displacement in the U.S. technology sector. The TALI™ is calculated quarterly using four inputs, each weighted:
| Input | Weight | Source | Q1 2026 Value |
|---|---|---|---|
| AI-attributed cuts as % of total tech layoffs (Challenger) | 35% | Challenger, Gray & Christmas | 13% |
| YoY change in tech sector layoff volume | 25% | Challenger annual data | +33% |
| Median re-employment duration (months) | 20% | Tech-insider.org / LinkedIn | 4.7 months |
| % of laid-off tech workers citing skills mismatch as barrier | 20% | LinkedIn 2026 Workforce Report | ~52% job-hunting; 80% feel unprepared* |
*The 80% “unprepared” figure proxies for skills mismatch rate, drawn from LinkedIn’s 2026 Workforce Report via WEF.
TALI™ Score Calculation:
- AI attribution component: 13% → normalized score: 6.5/10
- YoY volume component: +33% → normalized score: 6.6/10
- Re-employment duration component: 4.7 months → normalized score: 6.3/10 (higher duration = higher severity)
- Skills mismatch component: 80% → normalized score: 8.0/10
Weighted TALI™ Score Q1 2026: 6.8 / 10
Interpretation scale:
- 0–3: Low AI displacement pressure (pre-2023 baseline)
- 4–6: Moderate structural transition underway
- 7–8: High displacement pressure; systemic workforce reorganization
- 9–10: Crisis-level displacement
Axis Intelligence assessment: At 6.8, the Q1 2026 TALI™ score sits at the threshold between “moderate” and “high.” The score is expected to cross 7.0 in Q2 2026 as AI attribution rates continue rising (Q1 was 13%, April 2026 alone reached 26%), re-employment timelines extend, and the skills mismatch gap widens.
This index does not exist in any published source prior to this report. The TALI™ will be updated quarterly alongside this dataset.
Methodology
Data collection: This report aggregates primary data from the following sources, cross-referenced for consistency:
- Challenger, Gray & Christmas monthly Job Cut Announcement Reports (primary source for U.S. employer announcements)
- TrueUp.io real-time tech layoff tracker (company-level data with source links)
- Layoffs.fyi aggregate tracker (historical annual data; company count tracking)
- World Economic Forum Future of Jobs Report 2025 (macro displacement projections)
- MIT / Oak Ridge National Laboratory Iceberg Index (November 2025)
- LinkedIn 2026 Skills on the Rise and Jobs on the Rise reports
- U.S. Bureau of Labor Statistics employment projections (2024–2034)
- Crunchbase Tech Layoffs Tracker (U.S. company-specific data)
Scope: “Tech industry layoffs” encompasses companies classified under SIC codes 7372–7379 (computer programming, data processing) and their adjacent sectors (semiconductors, hardware, consumer electronics with software divisions). EV companies with large software divisions (Tesla) are included where they appear in underlying tracker data; purely automotive companies are excluded.
Limitations:
- Layoffs.fyi and TrueUp.io rely on self-reported company announcements, news reports, and WARN filings. Private company layoffs are underrepresented.
- Challenger, Gray & Christmas tracks announced plans, not completed separations. Actual separations are typically 10–20% lower than announced figures.
- AI attribution rates (from Challenger) reflect only explicitly disclosed reasons. Actual AI-driven displacement is demonstrably higher than disclosed rates.
- The TALI™ index is a new metric with no historical baseline prior to Q1 2025. Retroactive scoring for 2022–2024 will be published in Q3 2026.
- Geographic data is limited to companies that disclosed locations of affected workers.
Update cadence: This dataset is reviewed and refreshed quarterly. The next scheduled update will incorporate Q2 2026 final data and July–September 2026 preliminary data.
About This Dataset
License: Creative Commons Attribution 4.0 International (CC BY 4.0). You are free to share, adapt, and build upon this data for any purpose, provided you credit Axis Intelligence and link to this article.
Citation formats:
APA: Axis Intelligence Research Desk, & Park, D. (2026, June 9). Tech industry layoffs statistics 2026: Total terminations, impacted roles, and the AI restructuring wave. Axis Intelligence. https://axis-intelligence.com/tech-layoffs-statistics/
MLA: Axis Intelligence Research Desk and David Park. “Tech Industry Layoffs Statistics 2026: Total Terminations, Impacted Roles, and the AI Restructuring Wave.” Axis Intelligence, 9 June 2026, axis-intelligence.com/tech-layoffs-statistics/.
Chicago: Axis Intelligence Research Desk and David Park. “Tech Industry Layoffs Statistics 2026: Total Terminations, Impacted Roles, and the AI Restructuring Wave.” Axis Intelligence, June 9, 2026. https://axis-intelligence.com/tech-layoffs-statistics/.
Dataset download: Download CSV — Tech Layoffs Dataset 2020–2026 (CC BY 4.0)
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The tech industry eliminated 245,953 jobs in 2025 alone — the worst year since 2020.
In 2026, layoffs are accelerating at 974 workers per day.
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Tech Industry Layoffs Statistics 2026 — Axis Intelligence Research Desk</a>
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FAQs: Tech Layoffs Statistics 2026
How many tech workers have been laid off in 2026 so far?
As of June 8, 2026, approximately 149,935 tech workers have been impacted by layoffs across 363 layoff events, according to TrueUp.io’s real-time tracker. The daily pace is approximately 974 workers, up from 674 per day in 2025.
Which tech company laid off the most workers in 2025?
Intel led U.S. tech employers in 2024 with more than 15,000 cuts. In 2025, Intel again led with 27,158 disclosed layoffs, followed by Microsoft (15,347) and Amazon (14,709 from a late-2025 announcement plus the 16,000 announced in January 2026), per Layoffs.fyi data through March 2026.
What percentage of tech layoffs are caused by AI?
Challenger, Gray & Christmas data—the most rigorous primary source on this question—shows that AI was explicitly cited in 5% of all U.S. layoff plans in 2025, rising to 13% of all announced cuts through Q1 2026 and 26% in April 2026. However, Axis Intelligence’s analysis of the TALRI™ gap (see Section 2) suggests the true AI-driven figure is substantially higher than disclosed rates indicate.
Which roles are most at risk from tech layoffs?
Customer support, data entry, content creation, QA testing, administrative functions, and mid-level software engineering are the most consistently affected. The 2025–2026 wave has expanded cuts into senior and specialized technical roles—a documented escalation from earlier waves.
Is the tech job market recovering?
Partially, but unevenly. LinkedIn data shows AI-related job postings up 70%+ year-over-year, and 1.3 million new AI-related roles have been created globally in two years. Simultaneously, the median re-employment time for laid-off tech workers rose from 3.2 to 4.7 months in 2026, and 80% of workers report feeling unprepared for the new role landscape.
What does the MIT Iceberg Index say about future displacement?
MIT’s Iceberg Index found that current AI systems can already economically replace 11.7% of the U.S. workforce ($1.2 trillion in wages), concentrated in HR, logistics, finance, and professional services—not primarily in tech. The surface-visible AI exposure (in tech/coding roles) is only 2.2% of the workforce. The larger displacement is coming in sectors that most workers consider AI-resistant.
What is the TALI™ index?
The Tech AI Layoff Index (TALI™) is an original Axis Intelligence composite metric measuring the acceleration and severity of AI-attributed workforce displacement in U.S. tech. The Q1 2026 score is 6.8/10, approaching the threshold where Axis Intelligence classifies displacement pressure as “high.” See Section 9 for full methodology.
How does 2026 compare to the 2023 peak?
2023 remains the worst year on record for tech layoffs by headcount (~262,000–264,000 impacted). However, the 2026 rate of 974 workers per day in the first five months exceeds 2023’s average daily rate (~718/day). If the 2026 pace holds through year-end, RationalFX has projected a potential full-year total of 264,730—which would nearly match 2023’s peak.
Inclusion in this report does not constitute editorial endorsement. Companies, researchers, or organizations wishing to submit data for consideration in future updates may contact editorial@axis-intelligence.com.