100 Extra Crown

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The 2026 World Cup was therefore the culmination of five years of development that had embedded AI throughout Kambi’s trading operations.

“In simple terms, what we have undertaken is a shift from machine-assisted human trading to human-assisted machine trading,” Lamb explains.

The shift means that rather than spending their time pricing and managing established markets, traders can now apply their expertise where human judgement has the greatest value, including developing and testing new products. AI removes many of the practical limits on what can be offered and priced, and manages the resulting scale and complexity. The result is greater efficiency for Kambi and a better service for its partners and their customers.

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Two operators alone – Kalshi and Polymarket – topped the combined $1 billion mark in NFL trading activity over the first six days of Week 1, according to numerous measures this week. During the period, Kalshi recorded NFL volume of $983.4 million, according to DeFi Rate, earning the pole position by a large margin. Mahomes and the Kansas City Chiefs thrashed the Denver Broncos 31-10 on Monday Night Football, capping the largest week for prediction markets ever.

Even before the primetime matchup in Kansas City, it became abundantly clear that the industry would shatter previous marks for weekly activity. The AFC West showdown bolstered the already robust totals. Overall, volume for the week hit a record $15.9 billion, according to Bank of America, up 16% from a week earlier.

The pure-play prediction market-operators, Polymarket and Kalshi, emerged from Week 1 as the clear winners. On one hand, Kalshi’s market share lead narrowed over its competitors, falling to 82% for the week ended 13 September, down from 86% a week earlier.

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However, 38% expressed concern that adopting AI might reduce the personal, human touch in VIP management. 

Within the survey, none of the respondents selected AI or automation as their primary tool for managing VIP portfolios.

Instead, spreadsheets and business-intelligence dashboards each accounted for 30%, and CRM platforms followed at 24%. Only 15% used AI/automation tools in any capacity, and then only as secondary aids.