โ๏ธ Air Canada’s chatbot invented a bereavement fare policy โ and the tribunal ruled the airline fully liable.
๐๏ธ It wasn’t a tech failure. What failed was everything ๐ฎ๐ฟ๐ผ๐๐ป๐ฑ it: governance, guardrails, ownership. ๐งโ๐ผ
๐ธ Klarna ๐ธ๐ช projected $40M in AI savings โ a year later, quality dropped and they rehired humans. ๐
โ ๏ธ Same root cause: ๐ฐ๐ผ๐ป๐ณ๐๐๐ถ๐ป๐ด “๐๐ฒ ๐ต๐ฎ๐๐ฒ ๐ฎ๐ป ๐๐ ๐๐ผ๐ผ๐น” ๐๐ถ๐๐ต “๐๐ฒ ๐ฎ๐ฟ๐ฒ ๐๐-๐ฟ๐ฒ๐ฎ๐ฑ๐.”
๐ 98% of orgs feel urgency to deploy AI โ only ๐ญ๐ฏ% are ready (Cisco). ๐ Just 39% see EBIT impact (McKinsey); 5% capture value at scale (BCG). ๐ And 64% of customers prefer no AI in service.
๐ฏ BCG’s 10-20-70 rule explains why: 10% algorithm, 20% data/tech, 70% redesigned processes and people โ the part most skip.
๐งฑ ๐ง๐ต๐ฒ ๐ฑ ๐ฑ๐ถ๐บ๐ฒ๐ป๐๐ถ๐ผ๐ป๐ ๐
๐ ๐๐ฎ๐๐ฎ โ integrated and representative, not just clean
๐ก๏ธ ๐๐ผ๐๐ฒ๐ฟ๐ป๐ฎ๐ป๐ฐ๐ฒ โ only 31% have real AI policies
๐ ๐ช๐ผ๐ฟ๐ธ๐ณ๐น๐ผ๐ โ top performers redesign, not bolt on
๐ฅ ๐ง๐ฎ๐น๐ฒ๐ป๐ โ Pacesetters: 75% AI-proficient staff vs 16% average
๐ ๐ ๐ฒ๐ฎ๐๐๐ฟ๐ฒ๐บ๐ฒ๐ป๐ โ deflection isn’t success
๐จ I’m putting all five into one infographic โ a readiness self-assessment for your team. ๐งญ
โ ๐๐ฎ๐ป ๐๐ผ๐ ๐ป๐ฎ๐บ๐ฒ ๐๐ต๐ฒ ๐ผ๐ป๐ฒ ๐ฒ๐ ๐ฒ๐ฐ๐๐๐ถ๐๐ฒ ๐ฎ๐ฐ๐ฐ๐ผ๐๐ป๐๐ฎ๐ฏ๐น๐ฒ ๐ณ๐ผ๐ฟ ๐ฒ๐๐ฒ๐ฟ๐ ๐๐ ๐ผ๐๐๐ฝ๐๐ ๐ฎ ๐ฐ๐๐๐๐ผ๐บ๐ฒ๐ฟ ๐๐ฒ๐ฒ๐? ๐ If you paused โ that’s why this matters.
๐ฌ Which of the 5 is hardest for your org? I’m reading every reply. ๐
๐ฐ My full article in CMSWire: ๐ https://www.cmswire.com/customer-experience/before-you-scale-ai-in-customer-experience-fix-these-5-things/
#CustomerExperienceย , #AIReadiness , #CXStrategy , #AIGovernance , #CustomerService
