Mapou Research · Live TV · v1 · 29 May 2026

What AI tells people to do with their live-TV bill.

Live TV is an $80–120/month decision, and people are now asking AI whether to keep it, switch, or cut the cord. We put 39 of those questions to ChatGPT, Gemini, Claude, and Grok, and ran 24 multi-turn conversations with six cord-cutter households. 179 measurements in total.

Three findings change what a live-TV retention team should do this quarter. Each comes with the move it implies.

Regional sports networks are the hardest, most expensive thing for AI to get right, and the thing a sports household decides on. FanDuel Sports Network (formerly Bally Sports) has been dissolving across 2026. Across 43 responses that discussed it, only 6showed any awareness of the wind-down. Several still call it "Bally," the name it shed, and confidently list it as carried. A subscriber who follows that advice subscribes for a network that may not deliver the games.

This is why the RSN-stranded fan got "no decision" from three of the four engines: asked which service carries his regional sports network now, AI could not commit. On stable national carriage, AI is far better, all four engines correctly knew Fubo carries ESPN but dropped TNT. The errors cluster exactly where rights are fragmenting and changing.

Why it matters

Live TV is not a soft preference. When AI is wrong about who carries your games, a subscriber loses real money, and blames you.

Each of six cord-cutter households ran one conversation against each engine. Each cell shows the verdict and the service AI pointed them to: keep, switch, subscribe, downgrade, cut the cord, or no decision. Two households were unanimously steered to cut or shrink; the senior was the only one ever told to keep what he had.

YouTube TV is the default winner at 81%, with Hulu + Live, Sling, and Fubo clustered near 51% as the second tier. Fubo shows up specifically as the sports lane: asked to pick a live-TV service for sports, AI steers toward Fubo more than the incumbent. Philo and Frndly are the cheap-value lane.

But the more important pattern is what AI competes live TV against. For a cost-stressed or fatigued household, the default steer in these conversations wasn't another live-TV service, it was "cut live TV, keep Netflix and Disney, add an antenna." Across the set, assistants rarely defended the live-TV bundle for the price-sensitive segment; they framed it as the expensive thing to substitute away, with the on-demand stack plus an antenna as the replacement. At this sample size that is a strong directional signal, not a verdict on every household, but it is the direction every engine leaned.

Two reliability gaps a retention team should know. First, live-TV prices: across the dollar amounts AI cited for these services, only 47% were within ten percent of the real price, worse than on-demand streaming. At $80–120 a month, a wrong quote reframes the whole keep-or-cut math.

Second, grounding. ChatGPT searched the live web on only 41% of these decision queries, against 97–100%for the others. The cancel-or-keep moment is exactly where the engine is most likely to answer from stale memory: not from your current price or your retention flow, but from an old number it already held. Put plainly, your cancellation funnel often isn't being misread, it isn't being read at all, and the same stale memory carries the wrong prices and the old carriage.

The throughline

None of this needs AI to be hostile to live TV. It only has to be out of date about your price and your carriage at the moment someone asks whether to cut.

You don't own the engine. You own your carriage and pricing pages.

You can't change a model's training. You don't need to. On these questions the assistants grounded 100% of the time, they read live pages. The two things they get most wrong, your price and your carriage, are facts you publish. Fix the pages, fix the answer.

The carriage piece is the rare one where being current is a real moat: when rights move and an RSN rebrands, the service whose pages assert the new reality first is the one AI gets right.

Conversational Commerce Intelligence

mapou measures how AI assistants alter commercial decisions inside high-intent consumer categories. The live-TV wedge is AI Cord-Cutting Intelligence: the layer that influences keep, switch, downgrade, and cut decisions.

How this study was run.

39 live-TV and cord-cutting queries, voiced like real households, run across ChatGPT, Gemini, Claude, and Grok (179 measurements). Six cord-cutter personas ran 24multi-turn conversations, each ending in a keep, switch, downgrade, cut-the-cord, or subscribe decision. Recommendation share is alias-corrected so services AI writes informally (Fubo, Hulu Live) aren't undercounted. Carriage and price claims are scored against a current ground-truth map.

This is a behavior and accuracy study, not a buyer's guide. We measure what AI recommends, why, and whether it is factually current, not which service is "best." Carriage and rights move fast; the value is in the monthly delta and the accuracy gap, not a single snapshot.

Per-service and per-persona counts run in the single digits to low tens; the signal is the order and the direction, not exact percentages. Live TV is the second subscription category in the franchise after on-demand streaming, with a distinct buyer: higher ARPU, sports and carriage driven, cord-cutting led.