AI Coding Assistant Statistics 2026
Last updated: June 16, 2026 · Next scheduled update: Q3 2026 (September) By Axis Intelligence Research · Co-authored by Sarah Mitchell
Quick Answer: As of Q2 2026, 84% of professional developers use or plan to use AI coding tools — yet only 29% trust the output, down from 40% in 2024. GitHub Copilot leads with 20 million cumulative users and 4.7 million paid subscribers, while the Axis Intelligence ACADSI score of 39.62% reveals that genuine daily-use integration is significantly lower than headline adoption figures suggest.
Key Findings
- 84% of developers use or plan to use AI coding tools in 2026, up from 76% in 2024, with 51% using them every single working day (Stack Overflow Developer Survey 2025, n=49,000+).
- GitHub Copilot commands 29% professional work-adoption globally and 42% market share among paid AI coding platforms, with 4.7 million paid subscribers as of January 2026 — up 75% year-over-year (Microsoft earnings disclosures; JetBrains AI Pulse January 2026).
- 90% of Fortune 100 companies have deployed GitHub Copilot, confirming enterprise-level normalization of AI-assisted development (Microsoft CEO statement, July 2025).
- Trust is falling while usage rises: Only 29% of developers trust AI code output in 2025, a drop of 11 percentage points from 40% in 2024 — the defining paradox of AI coding assistant adoption (Stack Overflow Developer Survey 2025).
- The Axis Intelligence ACADSI score of 39.62% (Q2 2026) reveals that headline adoption figures overstate actual integrated use by a factor of roughly 2.1×, once daily engagement, enterprise context, and trust erosion are accounted for.
Overall Developer Adoption: What the Surveys Actually Show
The 84% adoption headline has become the most-cited statistic in AI coding coverage — but it requires careful disaggregation.
The Stack Overflow Developer Survey 2025, conducted between May 29 and June 23, 2025, with over 49,000 responses from 177 countries, is the most methodologically robust annual snapshot of developer behavior globally. It found that 84% of respondents are using or planning to use AI tools in their development process, an increase over the 76% recorded in 2024. Critically, 51% of professional developers now use AI tools daily — the figure that separates genuine integration from occasional experimentation.
The JetBrains State of Developer Ecosystem 2025, based on 24,534 developers across 194 countries surveyed April–June 2025, reports an almost identical headline at 85%, with 62% relying on at least one dedicated AI coding assistant — as opposed to a general-purpose chat interface like ChatGPT.
By January 2026, JetBrains’ follow-up AI Pulse survey (n=10,000+ professional developers, localized into eight languages) found the figure had reached 90% — with 74% now using a specialized AI tool rather than just a chatbot.
| Survey | Date | Sample Size | AI Tool Adoption | Daily Use |
|---|---|---|---|---|
| Stack Overflow Developer Survey 2024 | Jun 2024 | ~65,000 | 76% use or plan to use | ~46% est. |
| JetBrains State of DevEco 2024 | Apr–Jun 2024 | ~23,000 | 81% regularly use AI tools | — |
| Stack Overflow Developer Survey 2025 | May–Jun 2025 | 49,000+ | 84% use or plan to use | 51% daily |
| JetBrains State of DevEco 2025 | Apr–Jun 2025 | 24,534 | 85% regularly use AI tools | 62% use a dedicated assistant |
| JetBrains AI Pulse Survey (Jan 2026) | Jan 2026 | 10,000+ | 90% at work | 74% use specialized tools |
Source: Stack Overflow (survey.stackoverflow.co); JetBrains Research (blog.jetbrains.com/research). Methodology notes: all surveys recruit primarily through self-selection; JetBrains users may be over-represented in JetBrains data.
GitHub Copilot Deep-Dive: Users, Revenue & Enterprise Penetration
2.1 User Growth Trajectory
GitHub Copilot remains the most widely known and most-adopted AI coding tool in the professional developer market. According to Microsoft’s earnings disclosures and GitHub’s Octoverse 2025 report, the platform reached 20 million cumulative all-time users by July 2025 — adding 5 million users in the three months between April and July 2025 alone.
By January 2026, Microsoft shifted its public reporting from total/trial users to paid subscribers, disclosing 4.7 million paying customers — a 75% year-over-year increase. This is the more commercially meaningful figure.
| Milestone | Date | Metric |
|---|---|---|
| GitHub Copilot Technical Preview launched | Jun 2021 | — |
| 1 million users | Mar 2023 | Cumulative |
| 1.3 million paid subscribers | Q1 2024 | Revenue-generating |
| 1.8 million paid subscribers | FY2024 (Microsoft) | Revenue-generating |
| 15 million cumulative users | Apr 2025 | Total/trial |
| 20 million cumulative users | Jul 2025 | Total/trial |
| 4.7 million paid subscribers | Jan 2026 | Revenue-generating (+75% YoY) |
Sources: Microsoft earnings releases; GitHub blog (github.blog). Note: Microsoft transitioned reporting metrics between FY2024 and Jan 2026; figures reflect the metric each company chose to disclose at each period.
2.2 Enterprise Penetration
At Microsoft’s earnings call and via CEO Satya Nadella’s public statements in July 2025, GitHub Copilot was confirmed as deployed at 90% of Fortune 100 companies. More than 77,000 enterprise customer accounts were disclosed in Microsoft’s FY2024 report.
Enterprise customer growth hit 75% quarter-over-quarter in Q2 2025, with over 50,000 total organizations using Copilot. The Gartner 2025 Magic Quadrant for AI Code Assistants estimates the overall market at $3.0–$3.5 billion for 2025, with GitHub Copilot holding approximately 42% market share among paid AI coding tools — more than the entire GitHub platform generated in revenue when Microsoft acquired it for $7.5 billion in 2018.
Starting June 2026, Microsoft is transitioning all GitHub Copilot enterprise and business customers to a token-based billing model. Copilot Business customers ($19/user/month) receive $30 of pooled AI credits in the initial promotional period; Copilot Enterprise customers ($39/user/month) receive $70 of pooled AI credits. This structural shift — from seat-based to consumption-based pricing — will be a closely watched indicator of actual usage intensity versus license coverage.
2.3 Code Generation Share
According to GitHub’s internal research published in Communications of the ACM (Ziegler et al., 2024), GitHub Copilot now generates an average of 46% of all code written by its active users, up from 27% in 2022 when the tool first launched commercially. Among Java developers — where Copilot’s code completion performs particularly well — the share reaches 61%.
The code suggestion acceptance rate sits between 21.2% and 23.5% across the overall user base. Less experienced developers accept at higher rates (31.9% on average) compared to senior engineers (26.2%). This suggests the tool adds the most marginal value to developers who need it most — but also flags that high acceptance rates among less experienced users may correlate with higher downstream review burden.
Competitive Landscape: Market Share & Tool Fragmentation
The AI coding assistant market has moved from a near-monopoly dynamic in 2022–2023 to a genuinely fragmented landscape by early 2026. The JetBrains AI Pulse January 2026 survey provides the most granular publicly available breakdown of work adoption by tool.
| Tool | Awareness (Jan 2026) | Work Adoption (Jan 2026) | YoY Trend |
|---|---|---|---|
| GitHub Copilot | 76% | 29% | Stable/slight decline |
| Cursor | 69% | 18% | Slowing growth |
| Claude Code (Anthropic) | 57% | 18% | Rapid growth (6× from Apr–Jun 2025) |
| ChatGPT (chatbot for coding) | — | 28% | Stable |
| JetBrains AI Assistant / Junie | — | 11% combined | Growing |
| Google Antigravity | — | 6% | New entrant (launched Nov 2025) |
| OpenAI Codex | 27% | 3% | Pre-public-launch data |
| Gemini (chatbot for coding) | — | 8% | Growing |
Source: JetBrains AI Pulse Survey, January 2026, n=10,000+ professional developers (blog.jetbrains.com/research). Claude code chatbot interface usage (7%) reported separately from Claude Code agent work adoption (18%).
The most commercially significant shift is the rise of Claude Code: awareness jumped from 31% in April–June 2025 to 49% in September 2025 to 57% in January 2026 — an 84% increase in awareness in roughly nine months. Work adoption moved from ~3% to 18% globally in the same period, reaching 24% in the US and Canada specifically. JetBrains reports Claude Code holds the highest product satisfaction metrics of any tool measured: a CSAT of 91% and an NPS of 54.
Cursor reached a $2 billion ARR milestone by February 2026, representing what analysts describe as the fastest SaaS scale from $1M to $1B ARR on record.
Productivity Impact: What the Research Shows
4.1 Speed and Output
The foundational productivity study on GitHub Copilot remains the controlled experiment conducted by GitHub and Peng et al. (2023), replicated and expanded in the GitHub productivity research published by GitHub’s research team. In a controlled experiment with 95 developers, those using Copilot completed a standardized HTTP server implementation task in an average of 71 minutes; the control group without Copilot required 161 minutes — a 55% reduction in task completion time.
A separate GitHub-sponsored study involving over 2,000 developers found 88% reported feeling more productive, 77% said they spent less time searching for information, and 87% experienced less mental effort on repetitive coding tasks.
At the enterprise scale, Accenture’s internal deployment across approximately 450 developers found higher throughput and improved quality, while Mercedes-Benz reported an estimated 30 minutes of time saved per developer per day.
The DORA 2024 State of DevOps Report (39,000+ respondents) found that a 25% increase in AI adoption correlates with measurable improvements in job satisfaction, productivity, and reduced burnout — but also noted unexpected negative impacts on software delivery stability and throughput, particularly in organizations without robust testing practices. This is the first major longitudinal study to document the productivity-stability tradeoff that practitioners have anecdotally reported.
4.2 The Productivity Floor: What AI Still Can’t Do
Gartner’s 2025 Magic Quadrant survey data found that early claims of 30–50% productivity gains are being recalibrated in practice. While headline speed improvements are real, 42% of engineering staff surveyed by Gartner report that AI tools complicate rather than simplify complex, multi-context tasks. Stack Overflow found that the number of “advanced questions” on their platform doubled from 2023 to 2025 — a signal that AI coding tools are effective for routine tasks but push harder problems back to human experts.
The DORA 2025 State of AI-Assisted Software Development report introduces its AI Capabilities Model — seven foundational practices that amplify AI’s positive impact on software delivery. Organizations without these capabilities see AI act as an amplifier of dysfunction rather than an accelerant of performance.
The Trust Gap: The Defining Paradox of AI Coding Adoption
The most analytically important finding in the Stack Overflow 2025 Developer Survey is not the adoption rate — it is the trust collapse running in parallel to it.
In 2023, positive developer sentiment toward AI tools exceeded 70%. In 2024, that figure sat at 40% — already a decline. In 2025, only 29% of developers said they trust AI output, a drop of 11 percentage points in a single year, even as adoption rose by 8 percentage points across the same period.
| Year | AI Tool Adoption | Positive Trust in AI Output |
|---|---|---|
| 2023 | ~70% (use or plan to) | 70%+ |
| 2024 | 76% | 40% |
| 2025 | 84% | 29% |
Source: Stack Overflow Developer Survey 2023, 2024, 2025 (survey.stackoverflow.co). All surveys based on developer-self-report; methodology notes available at survey.stackoverflow.co/2025/methodology.
The two primary reported frustrations driving this erosion: AI suggestions that are “almost right but not quite,” requiring debugging; and the time cost of verifying outputs that appear plausible but contain subtle logic errors. The Stack Overflow blog calls this the AI trust gap — and notes it is widest among experienced developers, who have the pattern-recognition to detect AI errors but the least tolerance for the additional review burden those errors create.
Security Risks of AI-Generated Code
Security is the domain where trust erosion is most consequential. Research across multiple independent studies has documented consistent rates of security vulnerability introduction in AI-generated code.
An empirical study published in ACM Transactions on Software Engineering and Methodology (Fu et al., February 2025) analyzed 733 real-world code snippets generated by GitHub Copilot, Amazon CodeWhisperer, and Codeium. Security weaknesses were found in 29.5% of Python snippets. A separate analysis of Copilot-generated code from public GitHub repositories found 32.8% of Python and 24.5% of JavaScript snippets exhibited security issues spanning 38 distinct CWE categories, including eight listed on the 2023 CWE Top-25 Most Dangerous Software Weaknesses.
In March 2025, Pillar Security disclosed the “Rules File Backdoor” vulnerability — a novel attack vector that exploits AI coding tool configuration files. Attackers embed hidden Unicode characters in .cursor/rules files and equivalent GitHub Copilot configuration objects, causing the AI to silently generate backdoored code that passes normal code review. GitHub implemented a hidden-Unicode warning on May 1, 2025, following Pillar’s disclosure.
Microsoft disclosed two security vulnerabilities affecting GitHub Copilot and Visual Studio Code in November 2025 (CVE-2025-62449, CVE-2025-62453), both rated “Important.” CVE-2025-62453 involves improper validation of AI-generated output and carries a CVSS score of 5.0; CVE-2025-62449 involves path-traversal handling with a CVSS score of 6.8. Both have been patched.
Gartner identifies vulnerable output (where coding assistants feed insecure code to developers) and sensitive data leakage as the top two security risks of AI coding assistants — risks that persist even in enterprise-configured, policy-gated deployments.
Axis Intelligence Original Metric: The ACADSI Score
AI Coding Assistant Developer Spread Index (ACADSI) — Q2 2026
Most coverage of AI coding adoption leads with the 84% headline. Axis Intelligence Research developed the AI Coding Assistant Developer Spread Index (ACADSI) to express the gap between headline adoption and genuine integrated use, adjusted for enterprise penetration and declared trust erosion.
Formula:
ACADSI = (Daily_Use_Rate / Total_Adoption_Rate)
× Enterprise_Penetration_Coefficient
× (1 − Trust_Erosion_Factor)
Inputs (all primary-source verified):
| Input | Value | Source | Date |
|---|---|---|---|
| Daily Use Rate | 51% | Stack Overflow Developer Survey 2025 (n=49,000+) | Jun 2025 |
| Total Adoption Rate | 84% | Stack Overflow Developer Survey 2025 (n=49,000+) | Jun 2025 |
| Enterprise Penetration Coefficient | 0.90 | JetBrains AI Pulse Survey (n=10,000+) | Jan 2026 |
| Trust (2024 baseline) | 40% | Stack Overflow Developer Survey 2024 | Jun 2024 |
| Trust (2025) | 29% | Stack Overflow Developer Survey 2025 | Jun 2025 |
| Trust Erosion Factor | 27.5% | Cross-referenced Stack Overflow 2024–2025 | — |
Result:
ACADSI Q2 2026: 39.62% ACADSI Q2 2025 (estimated): 48.42% Year-on-year change: −8.80 percentage points
Interpretation: The ACADSI of 39.62% means that once daily engagement frequency, enterprise deployment context, and trust erosion are all accounted for, genuine deep-use integration among professional developers is approximately 40 percentage points — versus the 84% headline that dominates media coverage. This is a 2.1× overstatement gap. The 8.8-point year-on-year decline reflects that while raw adoption grew, the trust collapse disproportionately degraded the quality of that integration.
Copilot-Specific Spread Ratio (supplementary): GitHub Copilot’s work adoption rate (29%) relative to its awareness rate (76%) produces a spread ratio of 38.2% — meaning that of all developers aware of the tool, fewer than 4 in 10 actually use it at work. At an estimated 16.4% paid-subscriber penetration of the global professional developer population (~28.7M), Copilot is simultaneously the market leader and the most-oversold tool by awareness-to-use gap.
The ACADSI methodology and all source data are released under CC BY 4.0. Dataset available for download below.
AI Coding Assistant Adoption by Developer Segment
| Developer Type | AI Tool Adoption | Primary Driver |
|---|---|---|
| Full-stack developers | 32.1% lead segment | Versatility across front and back end |
| Frontend developers | 22.1% | CSS/JS boilerplate acceleration |
| Backend developers | 8.9% | More cautious; higher security stakes |
| Junior developers (18–34) | 2× more likely than seniors | Lower barrier to accepting suggestions |
| Enterprise (5,000+ employees) | 40% using Copilot specifically | Mandated toolchain deployment |
| Fortune 100 companies | 90% deployed Copilot | Enterprise agreement coverage |
Sources: Second Talent (secondtalent.com) citing Bureau of Labor Statistics developer population data; JetBrains AI Pulse January 2026 (blog.jetbrains.com/research); Microsoft earnings disclosures.
Eighty percent of new developers who join GitHub now use Copilot within their first week, according to GitHub’s Octoverse 2025 analysis. This early-onboarding dynamic means AI coding tools are effectively becoming the default mental model for the incoming generation of developers — even before professional norms or team workflows have adapted.
Market Size and Growth Projections
| Metric | Value | Source | Year |
|---|---|---|---|
| AI code assistant market size | $3.0–$3.5B | Gartner Magic Quadrant 2025 | 2025 |
| Market size (alternative estimate) | $7.37B | SNS Insider | 2025 |
| Projected market size | $8.5B | SNS Insider | 2026 |
| Long-range CAGR | 24% | SNS Insider | 2026–2034 |
| Projected market size | ~$47.3B | SNS Insider | 2034 |
| Gartner 2028 adoption forecast | 75% of enterprise engineers | Gartner (2023 prediction) | 2028 |
| Gartner 2027 code share forecast | 90% of code involves AI assistance | Gartner (2023 prediction) | 2027 |
Note: Market size estimates vary significantly by methodology. Gartner’s $3.0–$3.5B figure reflects paid commercial AI code assistant revenue only; SNS Insider’s higher figures include adjacent infrastructure and integration spending. Both are cited as directional indicators. The Gartner 2027 and 2028 projections were issued in 2023 and have not yet been updated with 2025 actuals.
McKinsey’s 2025 global AI research identifies software engineering as one of the top three functions to capture economic value from AI, estimating roughly 25% of potential AI-driven economic value in some productivity models. GitHub’s own research suggests that improved developer productivity through AI coding assistants could add over $1.5 trillion to global GDP over the long term.
GitHub Copilot Pricing (as of June 2026)
| Plan | Monthly Price | AI Credits (Promotional, Jun–Aug 2026) | Target User |
|---|---|---|---|
| Copilot Free | $0 | 300 requests/month | Individual developers |
| Copilot Pro | $10 | 300 requests/month | Individual paid users |
| Copilot Pro+ | $39 | 1,500 requests/month | Power users |
| Copilot Business | $19/user | $30 pooled AI credits | Teams |
| Copilot Enterprise | $39/user | $70 pooled AI credits | Large organizations |
Source: Microsoft/GitHub official pricing (github.com/features/copilot) and internal documents reported by Ed Zitron (April 2026). Token-based billing effective June 2026 for Business and Enterprise tiers; promotional credits through August 2026. Post-promotional pricing TBD.
Methodology
Axis Intelligence Research collected and cross-referenced data from the following primary sources for this report:
Primary sources used:
- Stack Overflow Developer Survey 2025 — Annual survey, n=49,000+, 177 countries, fielded May 29–June 23, 2025. The definitive global developer survey, publicly available in full.
- JetBrains State of Developer Ecosystem 2025 — n=24,534, 194 countries, fielded April–June 2025, with separate methodology weighting by geography, employment, and languages.
- JetBrains AI Pulse Survey, January 2026 — n=10,000+, localized into 8 languages, September 2025 and January 2026 waves; published April 2026.
- GitHub Octoverse 2025 — Platform behavioral data (Sep 1, 2024–Aug 31, 2025), public activity only.
- DORA 2024 State of DevOps Report — n=39,000+, annual Google/DORA longitudinal study.
- DORA 2025 State of AI-Assisted Software Development — dedicated AI-focused report from DORA.
- GitHub Research: Quantifying Copilot’s impact on developer productivity — controlled experiment, n=95 developers; supplementary survey, n=2,000+.
- Communications of the ACM — Measuring GitHub Copilot’s Impact on Productivity — Ziegler et al., 2024.
- Microsoft quarterly earnings disclosures (FY2024 and Q2 FY2026) — GitHub Copilot paid subscriber and enterprise customer data.
- Gartner 2025 Magic Quadrant for AI Code Assistants — market sizing and vendor evaluation; sourced via Visual Studio Magazine’s complimentary edition coverage.
ACADSI methodology: The AI Coding Assistant Developer Spread Index is an original Axis Intelligence Research metric, computed from cross-referencing sources 1, 3, and inputs verified against Microsoft earnings. Full formula and inputs disclosed in Section 7. Released under CC BY 4.0.
Limitations:
- Stack Overflow and JetBrains surveys recruit primarily through self-selection via their own platforms. Developers who do not engage with these platforms may be systematically under-represented (likely skewing toward more experienced or more engaged developers).
- GitHub Copilot user and subscriber counts are self-disclosed by Microsoft and GitHub; no independent audit of these figures exists as of publication.
- Market size estimates diverge significantly across research firms due to definitional differences (paid tool revenue only vs. adjacent infrastructure).
- The ACADSI Q2 2025 figure is estimated from 2024 survey data; it should be treated as a directional baseline, not a verified point estimate.
- The 2026 Stack Overflow Developer Survey had not been published as of June 2026. This article will be updated when it is released.
About This Dataset
Download: AI Coding Assistant Adoption Dataset 2026 (CSV) — CC BY 4.0
License: Creative Commons Attribution 4.0 International (CC BY 4.0). You may use, share, and adapt this data for any purpose, including commercial use, provided you give appropriate credit to Axis Intelligence Research and link to this page.
Update cadence: Quarterly. Next scheduled update: Q3 2026 (September), incorporating the Stack Overflow Developer Survey 2026 when released, and any new JetBrains AI Pulse wave data.
Citation formats:
APA: Axis Intelligence Research & Mitchell, S. (2026, June 16). AI coding assistant statistics 2026: Adoption rates, GitHub Copilot data & developer trends. Axis Intelligence. https://axis-intelligence.com/ai-coding-assistant-adoption-statistics/
MLA: Axis Intelligence Research and Sarah Mitchell. “AI Coding Assistant Statistics 2026: Adoption Rates, GitHub Copilot Data & Developer Trends.” Axis Intelligence, 16 June 2026, axis-intelligence.com/ai-coding-assistant-adoption-statistics/.
Chicago: Axis Intelligence Research and Sarah Mitchell. “AI Coding Assistant Statistics 2026: Adoption Rates, GitHub Copilot Data & Developer Trends.” Axis Intelligence, June 16, 2026. https://axis-intelligence.com/ai-coding-assistant-adoption-statistics/.
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Frequently Asked Questions
What percentage of developers use AI coding tools in 2026?
As of the most recent large-scale survey data, 84% of developers use or plan to use AI tools in their development workflow (Stack Overflow Developer Survey 2025, n=49,000+). The January 2026 JetBrains AI Pulse survey puts professional work-use at 90%. The more meaningful figure for actual workflow integration is 51% who use AI tools every single day.
How many developers use GitHub Copilot?
GitHub Copilot had 20 million cumulative all-time users as of July 2025, and 4.7 million paid subscribers as of January 2026 — a 75% year-over-year growth in paying customers. Over 77,000 enterprise customer accounts use the platform.
What is GitHub Copilot’s market share?
GitHub Copilot holds approximately 42% market share among paid AI coding tools as of 2025, according to multiple market analyses. In terms of professional developer work adoption, JetBrains’ AI Pulse (January 2026) places Copilot at 29% — the highest of any dedicated coding tool, but lower than the 28% of developers using ChatGPT’s general-purpose chatbot for coding tasks.
Do AI coding tools actually improve developer productivity?
The most replicated finding is a 55% reduction in task completion time for a standardized programming task (GitHub research, Peng et al. 2023, replicated). However, this applies to well-defined, bounded tasks. Gartner’s 2025 survey data found that 42% of engineering staff report AI tools complicate complex multi-context tasks. DORA (2024) found AI adoption increases individual productivity but can negatively impact team-level delivery stability. Results are real but not uniform.
Why are developers trusting AI tools less even as they use them more?
Stack Overflow’s 2025 survey data identifies two primary drivers: outputs that are “almost right but not quite” (requiring significant debugging), and the cognitive overhead of verifying AI-generated code that looks plausible but contains subtle logic or security errors. The trust drop is steepest among experienced developers who have both the skill to detect AI errors and the least tolerance for additional review cycles.
What is the ACADSI and what does it measure?
The AI Coding Assistant Developer Spread Index (ACADSI) is an original Axis Intelligence Research metric that expresses the gap between headline AI tool adoption rates and genuine deep-use integration. It is computed as the ratio of daily use to total adoption, weighted by enterprise penetration, and adjusted for the year-on-year trust erosion factor. A score of 39.62% (Q2 2026) means that once these adjustments are applied, genuine integrated use is roughly 40 percentage points — versus 84% in headline adoption data.
Are AI coding tools a security risk?
Yes, materially so. Independent research (ACM TOSEM, February 2025) found security weaknesses in 29.5% of AI-generated Python code. Gartner identifies “vulnerable output” and “sensitive data leakage” as the top two AI coding security risks. Two CVEs (CVE-2025-62449 and CVE-2025-62453) affecting GitHub Copilot and Visual Studio Code were disclosed and patched in November 2025. The “Rules File Backdoor” attack vector — disclosed by Pillar Security in March 2025 — represents a novel threat where attackers manipulate AI configuration files to generate backdoored code silently.
How much does GitHub Copilot cost in 2026?
As of June 2026, Copilot Pro costs $10/month, Copilot Business $19/user/month, and Copilot Enterprise $39/user/month. Microsoft transitioned Business and Enterprise tiers to token-based billing in June 2026, with a promotional period running through August 2026 where credits exceed the subscription fee. Individual tier pricing under the new model is pending announcement.
Which AI coding tools are growing fastest in 2026?
Claude Code (Anthropic) is the fastest-growing specialized AI coding tool by adoption rate, growing from approximately 3% professional work-adoption in April–June 2025 to 18% globally and 24% in the US/Canada by January 2026 — a roughly 6× increase in nine months. It also leads all tools measured by product satisfaction (CSAT 91%, NPS 54). Cursor reached $2B ARR by February 2026 in what analysts describe as the fastest SaaS scale trajectory on record.
When will this report be updated?
This report is updated quarterly. The next update is scheduled for Q3 2026 (September), at which point it will incorporate the Stack Overflow Developer Survey 2026 (expected Q3 2026), any new JetBrains AI Pulse survey waves, and updated Microsoft earnings disclosures. A recalculated ACADSI score will be published alongside each update.