How AI Search Is Recommending Project Management Software: Monthly Trends

Executive Summary

Asana remains the category leader in September 2026, but the top of the market is compressing under broad-based declines. Asana's valid recommendation coverage fell to 63.6%, down a significant 9.1 points from 72.7% in July 2026. The gap to the next brand, ClickUp at 63.3%, has narrowed to just 0.3 points, down from a 1.7-point lead in July 2026. monday.com trails closely at 61.6%. All three leaders are in significant two-month downward streaks.

The standout riser this month is Atlassian, new to the tracked set in September 2026, entering at 18.0% valid recommendation coverage with 110 valid recommendations. Atlassian's presence reached 29.8% of observations in its first measured month, immediately placing it ahead of Basecamp among tracked brands.

The sharpest decliner was Trello, down a significant 11.7 points from 66.0% in July 2026 to 54.3% in September 2026, including a significant 8.5-point drop from August 2026. Eight of the ten continuing brands declined significantly from baseline, a pattern spread across the field rather than concentrated in one brand. Jira Service Management, which had risen in August, fell back out of the tracked set entirely in September.

Each monthly run begins with 800 prompt-surface observations (443 unique questions in July 2026; 496 in August 2026; 490 in September 2026) across the benchmark's defined AI/search surface universe. Of those, all 800 in each month mentioned a tracked brand or competitor; 780 were relevant and 20 were irrelevant in July 2026, versus 785 relevant and 15 irrelevant in August 2026, and 791 relevant and 9 irrelevant in September 2026. The public metrics use the 677 qualified observations in July 2026, 640 in August 2026, and 610 in September 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 raw collection universe held steady at 800 prompts across all three months, while the qualified set narrowed from 677 to 610 observations. The September 2026 run tested 490 unique questions, up from 443 in July 2026, meaning a broader set of phrasings was evaluated against a smaller qualified denominator.

Benchmark-Level Metrics

September 2026 saw the qualified observation count fall for the second consecutive month, and the share of observations yielding a valid recommendation shortlist dropped 11.1 points from July 2026. The August 2026 rise in recommendation-shaped answers (39.1%) did not hold; September fell to 30.5%, below the July baseline. That combination points to a narrower set of qualifying responses across the category.

AI Recommendation Trend

The category compresses as a new entrant emerges

September 2026 is defined by two forces: a broad decline in valid recommendation coverage across most continuing brands, and the arrival of Atlassian as a new tracked entity at 18.0%. The rankings among the top brands are tightening even as absolute coverage falls, because the declines are distributed across the field rather than concentrated against any single player.

Jira Service Management, present in July and August 2026, does not appear in the September 2026 tracked set, and Microsoft SharePoint was the only continuing brand to gain coverage. No single brand's movement accounts for the shift; the change is spread across the field.

What Changed This Month

Asana

Asana's valid recommendation coverage fell a significant 9.1 points from 72.7% in July 2026 to 63.6% in September 2026, a two-month downward streak. The prior month's decline was a non-significant 4.1 points from August 2026.

Asana's raw presence remained essentially stable at 97.5% of observations in September 2026, down from 98.1% in July 2026. The brand was still almost universally visible. Valid recommendation count fell from 492 in July 2026 to 388 in September 2026, and the brand's top-three rate declined 2.4 points to 44.4%.

Asana is as visible as ever but is being recommended in a smaller share of qualified answers. Its rank-one rate held at 14.6% in September 2026, essentially unchanged from 14.9% in July 2026, so the decline is in shortlist inclusion rather than top placement.

Highest-priority diagnostic: Which prompt types shifted Asana out of the recommendation shortlist, and which competitor captured the recommendation when Asana was excluded?

Atlassian

Atlassian entered the September 2026 tracked set at 18.0% valid recommendation coverage, a significant rise from a baseline of zero because the brand was not previously tracked. It recorded 110 valid recommendations from 182 present observations.

Atlassian's presence reached 29.8% of observations in its first measured month. Its top-three rate was 3.6% (22 top-three recommendations) and its rank-one rate was 1.5% (9 rank-one recommendations), placing it firmly in the middle tier despite the strong entry.

Atlassian's entry is a presence story first: it is being mentioned and shortlisted, but it is not yet converting that into top placement. The brand's raw mention presence of 29.8% in September 2026 gives it a foundation that most tail brands lack, even though its placement rates remain modest.

Highest-priority diagnostic: Which prompts surface Atlassian, and which product-level queries drive its recommendations versus its parent-brand mentions?

Trello

Trello posted the largest decline in the category, with valid recommendation coverage down a significant 11.7 points from 66.0% in July 2026 to 54.3% in September 2026. This includes a significant 8.5-point drop from August 2026, making September the sharper of the two monthly movements.

Trello's presence declined 1.9 points from 90.1% to 88.2% of observations. The larger movement was in top-three placement: the top-three rate fell 6.4 points from 18.0% in July 2026 to 11.6% in September 2026. Valid recommendation count dropped from 447 to 331.

Trello is both slightly less visible and substantially less often placed in the top three, a double movement that distinguishes it from brands like Asana whose presence held steady. The brand remains fourth in the category but has fallen further behind the top three.

Highest-priority diagnostic: Which AI surfaces or prompt categories drove the top-three rate down, and which competitor absorbed those higher placements?

ClickUp

ClickUp's valid recommendation coverage fell a significant 7.7 points from 71.0% in July 2026 to 63.3% in September 2026, a two-month downward streak. Its prior-month decline was a non-significant 3.7 points from August 2026.

ClickUp's presence rose 4.8 points from 90.1% to 94.9% of observations, against the category trend. The decline came from placement: its rank-one rate fell 7.0 points from 14.5% in July 2026 to 7.5% in September 2026, with rank-one count dropping from 98 to 46.

ClickUp is more visible than ever but is being placed first far less often. This is the inverse of monday.com's pattern this period, where first-place wins rose even as coverage fell. ClickUp's rising presence paired with falling rank-one placement is the defining feature of its September position.

Highest-priority diagnostic: Which prompts moved ClickUp out of first place, and which brands captured those rank-one recommendations?

monday.com

monday.com's valid recommendation coverage fell a significant 10.2 points from 71.8% in July 2026 to 61.6% in September 2026, a two-month downward streak. Its prior-month decline was a non-significant 4.0 points from August 2026.

Presence held steady at 95.2% of observations in September 2026, down from 95.6% in July 2026. Yet monday.com's rank-one rate rose 2.9 points to 19.2%, up from 16.3% in July 2026, with 117 rank-one recommendations in September 2026.

monday.com is winning more first-place recommendations than any other brand (117 versus Asana's 89) even as its overall coverage falls. The brand remains the strongest top-of-shortlist performer in the category while losing overall shortlist inclusion.

Highest-priority diagnostic: Which AI surfaces reduced monday.com's shortlist inclusion, and do the surfaces where it ranks first differ from those where it is excluded?

Jira Service Management

Jira Service Management, which rose from 3.8% coverage in July 2026 to 11.1% in August 2026, does not appear in the September 2026 tracked brand set. Its July 2026 baseline reflected 26 valid recommendations.

The brand's August gain did not carry into September tracking. Its series shows a rise followed by an absence from the measured set, a pattern that bears watching if the brand returns in a future month.

Jira Service Management's August gain was real within that month's qualified set, but it did not persist into September tracking. The absence of the brand from the September set is an instrument observation, not a statement about the brand's market position.

Highest-priority diagnostic: If Jira Service Management returns to tracking, which prompt categories produced its August gain, and were those prompts present in September?

Notable gap: Atlassian closes ground on multiple brands

The coverage gap between Atlassian and Trello narrowed from 66.0 points in July 2026 to 36.3 points in September 2026. The gap between Atlassian and monday.com narrowed from 71.8 points to 43.6 points, and the gap to Notion narrowed from 47.7 points to 18.4 points. These gaps narrowed because Atlassian entered the tracking set at 18.0% while the established brands declined, not because Atlassian overtook any of them.

Buyer-Intent Interpretation

In all three months of the series, all qualified observations fell into the Brand Recommendation cluster. The public benchmark collected 677 qualified observations in July 2026, 640 in August 2026, and 610 in September 2026, every one of which was a recommendation-oriented query. No qualified observations landed in the Pricing & Value or Multi-Brand Comparison clusters in any month.

The public benchmark cannot yet answer questions about price perception, value positioning, or head-to-head comparison outcomes. A company-level analysis is needed to explore those commercial questions directly.

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 CiteWorks Studio AI Market Discovery research program.

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

Report-Specific Interpretation Notes

• Small-count movements: Brands such as Microsoft SharePoint (4 valid recommendations in September 2026) and Basecamp (59) have small denominators; their percentage movements should be read with proportionally more caution.
• New entrant versus continuing brand: Atlassian entered the tracked set in September 2026 with no baseline; its 18.0% coverage reflects first-month presence (29.8% of observations) and cannot be compared to a prior month.
• Tracked set changes: Jira Service Management appeared in July and August 2026 but is absent from the September 2026 tracked brand set. Cross-month coverage comparisons for that brand are not possible beyond August.
• Qualified denominator versus raw collection: The public metrics use 610 qualified observations in September 2026, not the 800 raw prompts collected; percentages are calculated within the qualified set.
• Directional analysis: Movement between months identifies changes worth investigating, but does not by itself establish the cause of those changes.

Next Step

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

Beneath the aggregate coverage percentage sit specific questions: which high-intent prompts does the brand win, which competitor takes the recommendation when the brand loses, what attributes does the AI associate with each option, and which external sources shape those answers? For a brand like ClickUp holding rising presence while losing rank-one placement, or Atlassian entering with strong visibility but modest position, the public numbers only indicate where to look.

The public benchmark cannot identify the prompts, competitors, or sources causing the result. A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy, turning benchmark signals into actionable diagnosis.

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