INDEX REPORT · NEXUSOX RESEARCH
2026 Q2 Small Business AI Growth Index
A transparent 0-100 index measuring small-business readiness across ten AI-adoption categories, built for the Q2 2026 foundational edition.
EXECUTIVE SUMMARY
The Small Business AI Growth Index scores a business from 0 to 100 across ten readiness categories, from website and content readiness through automation and execution maturity.
In this Q2 2026 foundational edition, category weights and scoring rules are fully published, but the illustrative scores below are modeled demonstration data, not a measured sample of real businesses.
The index is designed so that future editions can substitute verified NexusOX scan data or user-submitted data for the demonstration figures without changing the scoring structure or the page layout.
KEY FINDINGS
- In the modeled Q2 2026 dataset, the composite index for a typical small business clusters around the high-40s out of 100, driven down most by automation readiness and follow-up readiness.
- Website readiness and content readiness score meaningfully higher than automation and follow-up readiness in the modeled set, suggesting the presence gap is smaller than the operational-response gap.
- AI visibility readiness sits near the middle of the distribution, consistent with the qualitative pattern NexusOX's public scanner tool observes: most sites publish some identity and service information but incomplete structured data.
CHARTS AND TABLES
Category scores (modeled, 0-100)
Every figure above is labeled by dataset type. See "Data labeling" below for definitions.
METHODOLOGY
Category weights
Each of the ten categories is weighted equally at 10 points toward the 100-point composite in this foundational edition. Future editions may publish revised weights if evidence supports differential impact on outcomes; any change will be versioned and documented.
Scoring rules
Each category is scored 0-10 based on a fixed rubric of observable or reported signals (for example, website readiness considers whether a live site exists, whether it is mobile-usable, and whether core business facts are present).
Data requirements
A full score requires either a public-website scan, a completed self-assessment, or verified account data. Categories with insufficient data are marked "insufficient data" rather than scored as zero.
Confidence level
This Q2 2026 edition is published at Foundational confidence: structure and methodology are final, but the underlying scores shown are modeled demonstration data pending a verified data-collection wave.
Missing-data treatment
Categories without sufficient source data are excluded from the composite and disclosed in the report footnotes rather than defaulted to a score.
Update methodology
The index architecture (research_metrics, research_observations tables; see /RESEARCH_ARCHITECTURE.md) is built so verified data can replace modeled figures in a future revision without a page rebuild, following the same versioning and revision-date process used for every NexusOX Research report.
RECOMMENDED ACTIONS
- Start with a single readiness category scoring lowest and address it before broadening scope.
- Automation and follow-up readiness are the categories most likely to be low without technical rework — prioritize a follow-up workflow before a full AI platform rollout.
- Re-run the index quarterly using the same rubric so movement in your own score is measured against a fixed baseline rather than the demonstration figures shown here.
DEFINITIONS
- AI adoption readiness
- Whether a business has evaluated, piloted, or deployed AI-assisted tools in any part of its operations.
- Automation readiness
- Whether repeatable workflows (lead intake, follow-up, scheduling, billing) are automated rather than fully manual.
- Execution maturity
- Whether a business has a documented, repeatable process for acting on new recommendations or findings.
LIMITATIONS
- Figures in this edition are modeled demonstration data and do not describe a measured sample of real businesses.
- The equal-weighting scheme is a simplifying starting assumption, not an empirically validated model of which categories most affect business outcomes.
- The index does not measure revenue, profitability, or growth directly; it measures operational and technical readiness signals believed to be associated with AI adoption.
DATA LABELING
NexusOX Research distinguishes six categories of information in every report: Public-source data, NexusOX product-test data, User-submitted data, Modeled estimate, Demonstration data, Verified measured result. This Q2 2026 foundational edition uses modeled and demonstration data only, clearly marked on every chart and table above. It contains no independently verified survey results, customer performance data, or measured market samples.
CITE THIS REPORT
NexusOX Research. "2026 Q2 Small Business AI Growth Index." Q2 2026, NexusOX, https://www.nexusox.com/research/small-business-ai-growth-index-q2-2026.
@misc{nexusox_small_business_ai_growth_index_q2_2026,
title = {2026 Q2 Small Business AI Growth Index},
author = {{NexusOX Research}},
year = {2026},
note = {Q2 2026 edition},
url = {https://www.nexusox.com/research/small-business-ai-growth-index-q2-2026}
}
FUTURE EDITIONS