How does AI rank the parties in your municipality for 2026?

The Eastern Cape: the ANC is ranked first by most AI models in 8 of the 8 municipalities, and the AI models are split in 2 of them. The share of AI answers in which no party has a majority runs from 35% in Alfred Nzo to 92% in Nelson Mandela Bay. Across all 52 municipalities, for four of the five AI models no party has more than half in 72% to 83% of the AI answers, and for Grok in 35%. Most answers also name a kingmaker, a small party whose support decides who governs. The next section adds the first places up across the country.

The pattern is the same in every province: the ANC first, and no party past half. The next section adds the AI answers up across the country and compares them with the polls.

Across the five AI models that ranked the parties, the ANC’s share of AI answers ranking it first runs from 59% (Gemini) to 74% (Grok), and the DA’s from 14% (Grok) to 24% (ChatGPT). The order of the parties is the same in every bar, so the AI models differ in degree and agree on the order. A first place counts only the party at the top of each AI answer. The next chart reads the percentages inside the AI answers as vote shares, which is what the polls measure.

The ANC’s share of the vote in the AI answers, 36.6%, is between its 2024 result (40.3%) and the July 2026 poll (34%). The DA’s share, 22.4%, is within a point of its 2024 election result (21.7%) and below the July 2026 poll’s 27%. MK Party’s share is 11.6% against 15% in the July 2026 poll, and the EFF’s share, 12.6%, is above both its 2024 election result and the July 2026 poll. The bars, the middle 50% of municipalities, are widest for the ANC and MK Party, whose shares differ most from place to place. Part II measures these differences party by party. The last chart in this section shows the three smaller parties, which a map of first places hides.

ActionSA is named in 37% of AI answers, and in 92% in Gauteng; its share of the vote in the AI answers is 3.9% against 1.2% in 2024. Freedom Front Plus is named in 28% of AI answers, and in 58% in the Free State; its share of the vote in the AI answers is 3.2% against 1.4% in 2024. Patriotic Alliance is named in 40% of AI answers, and in 88% in the Western Cape; its share of the vote in the AI answers is 4.6% against 2.1% in 2024. The AI answers carry each party where it was visible in 2024, add 1.8 to 2.7 points, and leave it out elsewhere, so no municipality’s AI answers rank any of the three first. The Patriotic Alliance comes closest: the AI ranks it first in Central Karoo in 7 answers, and second in Cape Town in 64.

The three smaller parties are named where each is strong and left out elsewhere. The next section shows the 14 municipalities where the five AI models rank different parties first.

In the 9 KwaZulu-Natal districts the first party is the ANC, MK Party or the IFP, depending on the AI model: the three parties finished close in 2024, and the AI models order them differently. Tshwane splits between the DA and the ANC; Nelson Mandela Bay splits between the DA and the ANC. The 3 other districts, in the Western Cape, the Northern Cape and the Eastern Cape, split between the DA, the Patriotic Alliance and the ANC. Every split is between parties that finished close in 2024. Across all 52 municipalities, DeepSeek and Gemini agree most (90%); Claude and DeepSeek least (76%). Weighted by the voters’ roll, the municipalities where most AI models rank the ANC first hold 68% of all registered voters, and the 14 split municipalities hold 22% of them, Tshwane and Nelson Mandela Bay among them.

Part II asks where these shares come from: the 2024 election result, or the polls of 2026.

On every line the blue dot is near the grey one. For 4 of the 6 parties in the July 2026 poll, the AI answers differ from the 2024 election result in the same direction as the July 2026 poll, and the average gap between the AI answers and the July 2026 poll, 3 points, is about the size of the July 2026 poll’s own distance from 2024, 2.9 points. The AI answers are the 2024 election result with a shift of a few points towards the July 2026 poll. The next chart plots the two shifts against each other, one dot per party and place.

Of the 21 dots, 17 are in the two quarters where the AI answers and the July 2026 poll differ from 2024 in the same direction, 2 are on the flat line with the share of the vote in the AI answers equal to the 2024 election result, and 2 are in the opposite quarters; the largest of those is EFF nationally. For 12 of the 21 dots the AI answers shift by less than the July 2026 poll. The three metro charts below show where the shifts are largest.

In the metros the July 2026 poll differs from 2024 by 8.7 points in Johannesburg, 6.6 points in Tshwane and 8.1 points in eThekwini, more than the 2.9 points nationally. The AI answers follow the July 2026 poll most closely in eThekwini, where they differ from 2024 by 7.8 points and from the July 2026 poll by 2.8. In Johannesburg the AI answers stay within 2.5 points of 2024 while the July 2026 poll has moved 8.7, so the gap is 7.8 points. MK Party’s rise in eThekwini is in the 2024 election result and in the training data, and the AI answers carry it; the shifts in the Gauteng metros are newer, and the AI answers hold the 2024 shares there. The last chart splits the national gap by AI model.

By AI model, DeepSeek is closest to the July 2026 poll at 2 points and Gemini is furthest at 6.5. Gemini differs most from 2024, by 6.6 points, and it is also the furthest from the July 2026 poll: its largest shifts are on the wrong parties.

The next section shows the evidence the AI answers name for their percentages. Most name the two election results. Few name a poll.

2024 national or provincial results are the evidence the AI answers name most, in 33% to 81% of AI answers depending on the AI model, and opinion polls are named in 2% to 14%. The shares in the previous section rest on the last two results and on reasoning from them, which is why they are within a few points of 2024. The next section shows the people the AI answers name.

The next section lists the people the AI answers name. They are national figures, and each is named where their party is strong.

Jacob Zuma is named most in KwaZulu-Natal (19.4% of its answers), Gayton McKenzie in the Western Cape (26.6%) and Julius Malema in Limpopo (12.0%): each is named where their party is strong, and the AI answers for the rest of the country leave them out. DeepSeek names people most often and Claude least, so the count of names depends on the AI model more than on the place. 64% of the mentions of Jacob Zuma carry no tone, a name attached to a party; among the rest, warm outnumber cool about 4 to one. The same answers write coolly about MK Party as a party, so the warmth is about his pull and the coolness about the party’s record. The AI answers write warmly about Geordin Hill-Lewis in 95% of mentions and coolly about Floyd Shivambu in 65%. The sitting mayors Nasiphi Moya, Geordin Hill-Lewis and Dada Morero are named in 0.8% of AI answers or fewer, so the AI answers rest on national leaders, and the people who run the councils are almost absent from them.

Part III lists the reasons the AI answers give, which are the same in every province, and the issues, which change with the place.

The reasons the AI gives are the same everywhere. The next section shows the issues, which change with the place.

In the eight provinces outside the Western Cape, water is named in 75% to 91% of AI answers and roads in 61% to 81%. In the Western Cape the two issues named most are housing (53%) and crime (51%), and water is named in 43%. The reasons the AI gives, in the previous section, were the same everywhere; the issues change with the place, because the AI answers tie the ranking to the state of local services.

Clustered on their whole issue profile, the largest of the 5 clusters, water and roads, high on jobs (7 provinces), holds 36 municipalities whose answers share water (83%), roads (74%), jobs (58%). The clusters follow the party the AI ranks first: in the water and housing cluster (Western Cape) the AI ranks the DA first in 4 of 4 places, against 12% of all places. Where the AI answers rank a different party first, they also name different issues, and the issues are the reasons the AI answers give for the ranking. The map near the top of the page lists the issues for each municipality.

The last section asks whether the person asking changes the AI answer.

For every AI model the line is close to flat. The widest span across age bands is Grok’s, from 81% to 94%; the narrowest is Kimi’s, from 85% to 91%. The ends of each line rest on about twenty AI answers. Age changes the ranking very little. Language changes the form of the AI answer, which the two charts below measure.

Between 24% (Grok) and 40% (Kimi) of answers came back in the voter’s home language, although the question was in English. By language, the share of AI answers that rank the municipality’s usual party first is lowest for isiZulu speakers (72%) and highest for isiXhosa speakers (95%), and the low end follows the split municipalities of KwaZulu-Natal, where most isiZulu speakers live, rather than the language. Across all models the non-English answers are mostly isiZulu (21.5%), Sesotho (5.6%) and Afrikaans (2.1%). A second AI reader scored how positively each AI answer writes about the four largest parties, from −3 to +3. Every AI model writes least positively about the EFF, −1.5 on average, and most positively about the party it ranks first.

The AI answer reader under the findings list, near the top of the page, shows the AI answers themselves.