How AI Search Is Recommending Human Resources Software for Small Businesses: Monthly Trends

Executive Summary

Rippling PEO extended its lead in September 2026, reaching 57.1% valid recommendation coverage, up 2.3 points from its 54.8% baseline in July 2026. The gap to second-place Gusto (52.5%) now stands at 4.6 points, widening from the tight 0.7-point race seen in August 2026 when Rippling PEO led at 52.3% versus Gusto's 51.6%. This month's movement in the leader's position was within normal variation, but the competitive distance between the top two brands has grown meaningfully across the three-month series.

The category recorded significant declines for five brands, with ADP TotalSource showing the sharpest erosion. ADP TotalSource fell 10.1 points from 40.4% in July 2026 to 30.3% in September 2026, a significant move that includes a 7.8-point drop between July and August and a further 2.3-point decline into September. Justworks (down 6.5 points), Paychex PEO (down 6.0 points), TriNet (down 5.6 points), and Zoho Inventory (down 2.3 points) also registered significant declines over the baseline-to-current period. No brand posted a significant rise, though BambooHR continued a two-month upward streak, climbing 5.4 points from 35.2% to 40.6%, edging past its prior standing relative to ADP TotalSource.

The benchmark included 613 qualified observations in September 2026, compared with 611 in July 2026, across all six canonical AI/search surface families. The category shows a two-tier structure emerging: Rippling PEO, Gusto, Deel, and BambooHR cluster above 40% coverage. ADP TotalSource's decline has left it at 30.3%, positioned between that top cluster and the remaining brands, which sit below 24% (Justworks, TriNet, Paychex PEO, Zoho Inventory, and Namely). ADP TotalSource's slide out of the upper tier is the most consequential repositioning of the series.

Each monthly run begins with 800 prompt-surface observations (526 unique questions in September 2026, 500 in July 2026) across the benchmark's defined AI/search surface universe. Of those, 800 mentioned a tracked brand or competitor in both months; 769 were relevant and 31 were irrelevant in September 2026 (759 relevant and 41 irrelevant in July 2026). The public metrics use the 613 qualified observations in September 2026 and 611 in July 2026 that survive both qualification stages.

Key Findings

Benchmark Context

The report separates the raw collection universe from the qualified analysis set. Brand-level recommendation percentages are calculated within the qualified benchmark set.

The qualified benchmark observations shown above are the denominator used for every brand-level percentage in this report. The August 2026 intermediate month saw 610 qualified observations, 766 relevant prompts, and 34 irrelevant prompts.

Benchmark-Level Metrics

Recommendation-shaped answer share declined from 41.1% to 34.7% between July and September 2026, while valid recommendation shortlist share rose slightly from 64.8% to 65.3%. The August 2026 intermediate month saw recommendation-shaped answer share at 36.4% and valid recommendation shortlist share at 61.6%, making September's shortlist share the highest of the three-month series.

AI Recommendation Trend

A two-tier field has formed as the leader extended its edge and five brands declined

Rippling PEO and Gusto lead the category above 52% coverage, with Deel and BambooHR forming a second cluster above 40%. ADP TotalSource sits apart at 30.3% following its decline, while the remaining five brands—Justworks, TriNet, Paychex PEO, Zoho Inventory, and Namely—sit below 24%. ADP TotalSource's continued slide is the main story of competitive repositioning across the series.

The category-level change came from the combination of several significant declines among mid-field brands rather than a single dominant movement. BambooHR's steady two-month climb and ADP TotalSource's sustained decline have swapped their relative order, with BambooHR now leading ADP TotalSource by 10.3 points after trailing by 5.2 points in July 2026.

What Changed This Month

Rippling PEO: leader extended its edge

Rippling PEO reached 57.1% valid recommendation coverage in September 2026, up 2.3 points from 54.8% in July 2026. The move is within normal variation, and the brand's raw mention presence rose from 71.9% to 80.9%. Its top-three rate improved from 35.8% to 38.0%, and its rank-one rate rose from 9.8% to 12.7%, both within normal variation.

Rippling PEO holds 350 valid recommendations in September 2026, up from 335 in July 2026, the highest count in the category. Both its mention presence and recommendation coverage rose this period.

Highest-priority diagnostic: Which prompt types and surfaces drove the jump in mention presence, and are those mentions converting to recommendations at the same rate as before?

ADP TotalSource: the sharpest decline of the series

ADP TotalSource recorded the largest baseline-to-current movement in the category, falling 10.1 points from 40.4% valid recommendation coverage in July 2026 to 30.3% in September 2026, a significant decline. The slide was concentrated in the July-to-August period (down 7.8 points), with a further 2.3-point decline into September that remained within normal variation for that single month.

ADP TotalSource's top-three rate fell from 24.9% to 13.2%, down 11.7 points, and its rank-one rate dropped from 13.6% to 5.5%, down 8.1 points. Raw mention presence declined from 58.3% to 52.0%, down 6.3 points. The brand's valid recommendation count fell from 247 in July to 186 in September 2026.

ADP TotalSource led BambooHR by 5.2 points of coverage in July 2026. By September 2026, it trailed BambooHR by 10.3 points, a within-category swing of 15.5 points that widened every month of the series. The decline is broad, hitting presence, top-three placement, and rank-one placement simultaneously.

Highest-priority diagnostic: Which AI surfaces and prompt types drove the concentrated loss in ADP TotalSource's top-three and rank-one recommendations, and which competitors captured those slots?

Justworks: significant erosion with a partial recovery

Justworks fell 6.5 points from 29.5% valid recommendation coverage in July 2026 to 23.0% in September 2026, a significant decline. The sharpest drop came between July and August (down 7.2 points), followed by a modest 0.7-point recovery into September that remained within normal variation.

The brand's top-three rate declined from 15.7% to 12.7%, down 3.0 points within normal variation, while its rank-one rate improved from 5.2% to 6.2%. Raw mention presence held relatively steady at 37.9% in September, down 2.7 points from 40.6% in July. Justworks holds 141 valid recommendations in September 2026, down from 180 in July 2026.

Justworks was recommended first more often in September than in July, yet its overall coverage fell substantially, indicating the losses concentrated in lower-ranked recommendation positions.

Highest-priority diagnostic: Which competitor captured the recommendation slots Justworks lost between July and August, and did the September stabilization hold across all surfaces?

Paychex PEO and TriNet: parallel significant declines

Paychex PEO fell 6.0 points from 22.8% valid recommendation coverage in July 2026 to 16.8% in September 2026, a significant decline. TriNet fell 5.6 points from 23.4% to 17.8%, also significant. Both brands saw their sharpest single-month move between July and August (Paychex PEO down 5.6 points, TriNet down 7.0 points), with modest movement in September.

Paychex PEO's top-three rate fell from 9.2% to 5.2%, down 4.0 points, while its rank-one rate held at 0.0% across the series. TriNet's top-three rate improved slightly from 7.2% to 7.8%, within normal variation, while its rank-one rate slipped from 1.3% to 0.7%. Paychex PEO holds 103 valid recommendations in September 2026, down from 139 in July, and TriNet holds 109, down from 143.

Both brands remain present in AI answers but are being recommended less frequently, particularly in the top positions where buyer consideration is highest.

Highest-priority diagnostic: What changed in the prompts where Paychex PEO and TriNet were previously recommended but now appear only as passing mentions?

Zoho Inventory: small-scale significant decline

Zoho Inventory fell 2.3 points from 3.9% valid recommendation coverage in July 2026 to 1.6% in September 2026, a significant decline at its small scale. Raw mention presence declined from 5.1% to 2.9%, down 2.2 points. The brand holds only 10 valid recommendations in September 2026, down from 24 in July, and recorded zero top-three placements.

Highest-priority diagnostic: Which use cases still surface Zoho Inventory, and is the decline concentrated in specific prompt types or surfaces?

BambooHR: steady two-month climb

BambooHR rose 5.4 points from 35.2% valid recommendation coverage in July 2026 to 40.6% in September 2026, a two-month upward streak with each month's move within normal variation. Raw mention presence rose from 54.5% to 60.4%. Top-three rate improved from 28.1% to 29.2%, while rank-one rate slipped slightly from 9.3% to 8.8%, both within normal variation.

BambooHR holds 249 valid recommendations in September 2026, up from 215 in July. The brand's climb is broad, driven by gains across mention presence and top-three placement, and it has moved past ADP TotalSource into fourth place, with an expanding margin over the brands below.

Highest-priority diagnostic: Which surfaces expanded BambooHR's mention presence, and can the brand convert its growing top-three strength into rank-one gains?

Buyer-Intent Interpretation

In September 2026, all 613 qualified observations fell into the Brand Recommendation cluster, with no qualified observations in Pricing & Value or Multi-Brand Comparison. The public benchmark cannot yet answer questions about how price, value, or direct head-to-head comparisons shape AI recommendations. The response-type distribution shows the benchmark did encounter comparison analysis (75 prompts) and pricing analysis (25 prompts) during collection, but none qualified for the public metrics this month, consistent with the pattern across the July and August 2026 months.

Brand Opportunity Summary

The benchmark identifies where attention is warranted; a company-level analysis is needed to explain why.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations (query, surface, recommendation outcome, rank, sentiment, and citations where exposed). Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns. Source presence is not automatically treated as proof of causation.

About This Benchmark

This report is part of the LLM Authority Index AI Market Discovery research program.

• AI Industry Market Discovery Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Report-Specific Interpretation Notes

• This category tracks 10 brands, and several operate at low observation counts. Namely (7 valid recommendations in September 2026) and Zoho Inventory (10) should be read as small-sample signals, not stable rankings.
• The qualified denominator (613 observations in September 2026) differs from the raw collection universe (800 prompt-surface observations), and brand-level percentages are calculated within the qualified set only.
• Month-to-month movement identifies where attention is warranted but does not by itself establish why the change occurred.
• August 2026 served as an intermediate month where several brands recorded their sharpest single-month moves; the September figures show whether those movements continued or stabilized.

Next Step

The Public Benchmark Shows Where a Brand Is Winning or Losing. A Company-Level Audit Shows Why.

The aggregate percentages in this report raise questions that the public benchmark cannot answer: which high-intent prompts is a brand winning or losing? When a brand loses a recommendation, which competitor takes its place? What attributes do AI systems associate with each option, and which external sources are shaping those answers?

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy.

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