How AI Picks Its Sources When Buyers Search for Productivity Software (Q2 2026)

Highlights

• The dataset: Over 250,000 AI source citations underpin this analysis, produced by prompts specific to the collaboration and productivity software industry. The AI responses from four AI models span 12 countries over the course of Q2 2026.
• techradar.com climbed from #21 to #6 (+262%): The biggest riser in the second half of the window.
• Reddit is the single most-cited domain overall: It is the only top-three source ChatGPT and Grok agree on.
• 67% of Google AI Overview's citations are from commercial domains: Vendor and product pages make it the most vendor-heavy model.
• 87% of top-cited domains differ between any two models: The lowest pair, Google AI Overview and Microsoft Copilot, shares just 5%.

Which sources should you target to get cited as a collaboration and productivity software brand?

The four models are, functionally, four different research assistants reading four different slices of the web. Each model's distinctive sources tell the story:

A collaboration-software brand optimizing for one AI model is absent from roughly 87% of the domains the other models prefer.

How have AI source rankings changed over time in the collaboration and productivity software industry?

We split the ~16-week window at its midpoint and re-ranked the top domains by citation volume in each half. Several sources moved sharply.

The biggest climber is techradar.com, whose citation count more than tripled to vault from outside the top 20 into the top 10, consistent with the models increasingly favoring fresh tech-press reviews. On the downside, several vendor and platform domains (wrike.com, pcmag.com, linkedin.com) lost ground, and youtube.com fell from the single most-cited source to seventh.

These are relative rank movements, not evidence of absolute decline for any one domain. The reliable signal is the reshuffling of the ordering, AI source rankings in this category are volatile on a multi-week horizon, and a domain's position is not a moat. Track them in the live AI visibility rankings.

What type of content do AI models cite for collaboration & productivity tools?

The category mix differs sharply by model, this is where each engine's distinct shape comes from. We classified every cited domain into content categories.

Two patterns stand out. Google AI Overview is the most vendor-heavy model in the category, two-thirds of its citations go to commercial domains, often the software makers' own marketing and product pages. Microsoft Copilot, by contrast, routes more than a quarter of its citations to editorial and review media, the trade press (digital project management blogs, software-comparison sites) is its center of gravity. ChatGPT is the most community-driven and least commercial of the four: a quarter of its citations are user-generated content (Reddit threads, forums) and fewer than 40% are vendor sites.

For a productivity brand, the practical reading is blunt: your own product pages are a viable path into Google AI Overview, but on Microsoft Copilot you mostly get there by being written about, and on ChatGPT by being discussed.

Do AI models cite local-language content for collaboration & productivity tools?

Using a country-code top-level domain (ccTLD) proxy, counting a citation as "local" only when it lands on the market's own ccTLD, local domains account for just 22.5% of citations in non-English markets. The remaining 77.5% point to non-local domains, the overwhelming majority of them generic .com properties answering in or about English.

This is a proxy, and it undercounts: a local-language article hosted on a .com (or on youtube.com, linkedin.com) reads as "non-local" here. So the true local-content share is higher than 22.5%. Even allowing for that, the direction is clear, the productivity-software conversation these assistants surface is anchored to a global, English-first body of vendor and review content, and local-ccTLD publishers capture under a third of citations even in the strongest market.

Which AI model relies most on local sources for collaboration & productivity tools?

The headline localization rate hides a large per-model spread. Breaking the local-ccTLD share out by model and market shows two very different strategies.

Microsoft Copilot is consistently the most localized model, it leads or near-leads in every market and reaches nearly half local-ccTLD citations in French and Dutch. Google AI Overview cites local sources strongly in some markets (Dutch, German) but barely registers local French content in this dataset. Grok and ChatGPT are the most English-default: across most markets they keep local-ccTLD citations near or below 20%, regardless of the language the user asked in.

For brands operating in European markets, the lesson is that local-language SEO pays off very differently depending on the assistant, it is close to a prerequisite for Microsoft Copilot visibility, and close to optional for Grok.

Should collaboration & productivity tools optimize for each AI model separately?

Yes, almost entirely. We took each model's most-cited domains and measured how many each pair shares. The average across all six model pairs is 13.4%, with a range of 5.3% to 33.3%.

The only pair with meaningful agreement is Grok and Google AI Overview, which both lean heavily on a shared core of vendor and community content (slack.com, asana.com, reddit.com, youtube.com). Every other pair shares fewer than a third as many sources. Microsoft Copilot is the outlier in every direction, it shares at most three domains with any other model, because it draws disproportionately on review-media and how-to content (thedigitalprojectmanager.com, happeo.com, cloudwards.net) that the others largely ignore.

How many sources does each AI model cite per answer?

The models also differ enormously in how widely they cite. Grok pulls in 27.8 distinct sources per answer on average, about 3.5x ChatGPT's 7.9.

The breadth gap compounds the fragmentation: Grok not only cites different domains, it cites four times as many of them, so the probability that any single brand appears at all is far higher on Grok than on the narrow, top-heavy ChatGPT and Microsoft Copilot answers. A brand's odds of being cited are partly a function of which model the user happens to ask.

Context

This analysis draws from Temso's AI visibility monitoring platform, which tracks how brands appear in AI model responses across Grok, Google AI Overview, Microsoft Copilot, and ChatGPT. The dataset covers collaboration- and productivity-software questions across 12 markets and seven languages over roughly sixteen weeks (mid-March to late June 2026). It is built from the source citations attached to those answers: 417,018 total source records, of which 256,211 were actually cited in a response.

It measures what AI models cite, not the underlying quality or accuracy of any cited page. These findings reflect citation behavior for collaboration- and productivity-software prompts in the monitored markets, and may not generalize to all brands, prompt types, or other industry verticals. Localization is measured with a ccTLD proxy and therefore understates local-language content hosted on generic domains.

Methodology

How we measured this

We tracked four AI models responding to collaboration- and productivity-software prompts in local languages across 12 markets. Each response was parsed to extract source citations: the URLs, domains, and metadata referenced. Domain categories (commercial, editorial, UGC, reference, institutional) were assigned from a global domain registry. Cross-model overlap was measured on each model pair's top-20 most-cited domains, the share of domains the two lists hold in common. Temporal analysis split the observation period at its midpoint and compared domain rankings in each half.

The analysis covers over 250,000 cited sources. Sample sizes exceeded recommended thresholds for every reported finding; the smallest per-cell breakdown (German citations for ChatGPT, n = 1,869) still clears the minimum. Localization is measured by a country-code-domain proxy (the source records carry no detected content language), so those figures are directional lower bounds and exclude English-language prompts, which sit overwhelmingly on generic domains. Model coverage varied across the observation window, so ranking movement is interpreted as relative rank change, not absolute decline.

Frequently asked questions

Do different AI models cite the same sources for collaboration-software questions?

No, barely. Any two of the four models share just 13.4% of their top-20 cited domains on average, meaning roughly 87% of the sources one model leans on are absent from another's top list. The strongest pair (Grok and Google AI Overview) still only overlaps a third of the time.

Which AI model cites a brand's own website most often?

Google AI Overview. Two-thirds (66.9%) of its citations go to commercial domains, frequently the vendors' own product and marketing pages. ChatGPT is the opposite end, under 40% of its citations are vendor sites, so owned content carries you furthest on Google AI Overview and least far on ChatGPT.

Where do review sites and the trade press matter most for productivity software AI visibility?

On Microsoft Copilot. More than a quarter (25.7%) of Microsoft Copilot's citations go to editorial and review media, software-comparison sites and project-management blogs, the highest of any model. If your category coverage lives on third-party review sites, Microsoft Copilot is where it pays off.

Does writing content in the local language help in non-English markets?

It depends heavily on the model. Across non-English markets, only about 22.5% of citations land on a local-ccTLD domain (a conservative proxy), but Microsoft Copilot reaches nearly 50% local in French and Dutch, while Grok and ChatGPT stay near or below 20% almost everywhere. Local-language content is close to mandatory for Microsoft Copilot visibility and close to optional for Grok.

Which model cites the most sources per answer?

Grok, by a wide margin, about 27.8 distinct sources per answer versus 7.9 for ChatGPT, a 3.5x gap. Because Grok casts a far wider net, any given brand is more likely to appear somewhere in a Grok answer than in the narrower ChatGPT or Microsoft Copilot responses.

Do AI source rankings change, or are they stable?

They move. Over an eight-week split, techradar.com climbed 15 places into the top 10 (citations up 262%) while wrike.com and pcmag.com each dropped about ten places. A domain's position in these rankings is not a moat, it shifts on a multi-week horizon.

What single source do these models agree on most?

Reddit. It is the most-cited domain overall and one of the very few sources that appears high on both ChatGPT's and Grok's lists, a reminder that community discussion, not vendor copy, is common ground across otherwise divergent models.

What does this mean for a collaboration-tools brand's AI strategy?

There is no single "AI search" to optimize for, there are at least four, each rewarding a different content mix. Owned product pages win on Google AI Overview, third-party reviews win on Microsoft Copilot, community presence wins on ChatGPT, and broad coverage wins on Grok. A balanced presence across owned, earned, and community content hedges against the 87% of sources that don't carry over between models.