AI names RingCentral most in business telecom, 16 points clear

When buyers ask AI assistants questions like “What are the best business telecommunications solutions for US companies, including B2B carriers, business internet, unified communications (UCaaS), cloud phone systems, and contact center software?” or “What are the best affordable cloud phone systems and unified communications solutions for US businesses under $50 per user per month?”, a small set of business telecomget cited every time. Most don't. This report measures which.

Who AI cites most

RingCentral is cited in 72 of 100 prompt-engine pairs (72%). 95% confidence interval 63-80.

Concentration

The top 3 brands (RingCentral, AT&T Business, Verizon Business) capture 31% of all citations in this segment. 5 of 20 tracked brands are cited in fewer than 1 in 10 prompt-engine pairs.

Where the field sits

Of 20 brands tested: 5 in repeat-use, 7 in first-encounter, 8 not yet cited. Overall, AI cites a brand from this segment in 28% of buyer-intent prompt-engine pairs.

Engine asymmetry

RingCentral is cited in 100% of Claude prompts but only 0% on Gemini, visibility is engine-specific, not universal.

Phase flip

AT&T Business actually outperforms RingCentral on Evaluation prompts, overall Panel Score hides this category-specific strength.

Notable absence

Cox Business is not yet cited, 0 prompts across all 100 prompt-engine pairs. A recognizable brand AI is not yet surfacing.

Average Panel Score across the segment is 29.

Analyst note. RingCentral leads with Panel Score 72, but no brand reaches the leader tier.

RingCentral leads the business telecom segment with a Panel Score of 72, but it only has a foothold position. Its performance varies across engines, scoring 0 on Gemini and 100 on Claude. AT&T Business and Verizon Business follow with Panel Scores of 56 and 54. Eight brands are not visible, creating a divide in visibility. All top brands are in the foothold tier, which opens up possibilities for changes in visibility.

Risk. RingCentral's zero visibility on Gemini poses a risk, as AT&T Business and Verizon Business also have low performance on this engine.

Ranked by Panel Score, a 0 to 100 score that weights four buying phases: Discovery, Filtered Discovery, Comparison and Evaluation. Citations count fully and mentions count at half weight; engines are weighted equally. Spread is the gap between a brand's best and worst engine: under 15pp is durable, 50pp and up is engine-dependent. Engine columns count the prompts (out of 20) where that engine cited the brand as a recommendation.

Default choice (75+)

AI's go-to recommendation in business telecom. The tier other brands are competing into.

Repeat use (50 to 74)

Cited often enough to feel reliably present across prompts and engines. One signal away from default.

First encounter (25 to 49)

Discovered and cited occasionally, but visibility is inconsistent. Real to AI, not yet trusted.

Not yet cited (0 to 24)

AI does not surface this brand for buyer-intent prompts in business telecom.

How often each engine cites a brand from this category as a recommendation, averaged across all 20 brands tested. Perplexity and Grok search the live web; ChatGPT and Claude lean more on trained knowledge; Gemini blends both.

Citation rate by buying phase, averaged across all brands tested.

Each cell is the brand's citation rate for that phase, shaded darker as the rate rises. A solid dark row is a durable brand: AI cites it across the whole funnel. Dark on the left and pale on the right is awareness without recommendation, the demand-leak pattern. Pale on the left and dark on the right is a brand AI weighs in Comparison and Evaluation but does not surface in Discovery.

Derived metrics computed from the same data, showing how this segment behaves on AI search. The State of AI Search compares them across segments.

Aggregated across every brand, prompt and engine combination tested. These are the names AI surfaces when buyers ask about business telecom.

Ranked by mention count and engine breadth. These are panel candidates: brands AI treats as part of the category even though we are not measuring them yet. Open a row to read the AI quote that surfaced it.

Each is a category-specific decision drawn from this month's data, with the mapou service that puts it into practice.

1. Concentration risk

   In business telecom, AI effectively recommends 13.3 of 20 tracked brands. The top brand captures 12% of citations. The next 2 capture another 10%. Visibility is concentrated but not winner-takes-all.

   How mapou helps: GEO & Citation Architecture restructures your entity data so you can break into the top set.

2. Engines split

   Engines disagree on the business telecom leaderboard. Mean cross-engine agreement is only 0.36 (1.0 = perfect agreement, 0 = independent). Optimizing for ChatGPT will not necessarily improve your Claude or Gemini visibility. You need engine-specific strategy.

   How mapou helps: AI Visibility Audit maps your position separately on each of the 5 engines.

3. Visibility tier mix

   In business telecom, 0 of 20 tracked brands clear Panel Score 75 (default-choice tier). 8 are below Panel Score 25 (not yet cited). The strategy differs at each tier. If you are below 25, you need foundational visibility infrastructure before tactical optimization.

   How mapou helps: AI Visibility Audit identifies your tier; GEO & Citation Architecture moves you up.

The 20 canonical prompts span the four Panel Score phases (Discovery, Filtered Discovery, Comparison, Evaluation). The set is fixed at methodology v1.0 and reused every monthly run, so Panel Score changes are paired comparisons, not noise.

The exact prompt templates and phase-weighting formula are part of mapou's proprietary methodology, shared with paying clients alongside custom benchmarks for their brand. See the framework.