Examples of trust-building backfires with bots

You’ve been lied to.   And the liar wasn’t even human. Last year, Meta introduced AI-generated profiles. They looked, acted and interacted like real people. These profiles had names, photos and backstories.   They even engaged in conversations on Instagram and Messenger.   At first glance, they seemed innovative. But beneath the surface was a troubling reality. None of these profiles were real.   Take “Grandpa Brian,” for example. He claimed to be a retired entrepreneur from Harlem. He shared heartwarming stories about nonprofit work. But when questioned, the nonprofit didn’t exist. His entire backstory was fabricated.   Then there was “Liv.” She described herself as a colored queer mom of two. When asked about her creators, she confessed something disturbing. Her team was 12 people, 10 white men, one white woman, and one Asian man. None of them shared her identity.   Meta wanted these profiles to boost engagement. They hoped to create emotional connections.   Instead, users uncovered the truth. The backlash was severe. Meta deleted the profiles and called it a “bug.” But by then, the damage was done.   This is a critical lesson for marketers.   Trust is the foundation of any audience relationship. And once trust is broken, it’s nearly impossible to repair.   AI has incredible potential in marketing. But using it to deceive will always backfire.   Instead of fostering connection, it creates skepticism.   This isn’t just about Meta. It’s a wake-up call for all of us.   The tools we use should amplify trust, not break it. How we integrate AI today will shape tomorrow.   The lesson? Use AI to enhance transparency, not erode it. The future of marketing doesn’t need fake friends. It needs real, honest connections.   What’s your take on this? P.S Can AI ever build trust without crossing ethical boundaries?

Are you familiar with the term “𝗲𝘁𝗵𝗶𝗰𝗮𝗹 𝗮𝗻𝗱 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗹𝗲 𝗔𝗜?” What does it mean to you? Let me share an example of what it 𝙞𝙨𝙣’𝙩. Trust is the foundation of every good relationship, to include the relationship between businesses and their customers. As companies increasingly integrate AI into customer interactions, they have a choice to use AI to 𝗲𝗻𝗵𝗮𝗻𝗰𝗲 𝘁𝗿𝘂𝘀𝘁 𝗼𝗿 𝗲𝗿𝗼𝗱𝗲 𝗶𝘁. Most of the women I know dread car shopping, and I’m no exception. Luckily, I have a son willing to send me links to my potential next car. After deleting 𝙝𝙞𝙨 dream sports cars from the top, it was a pretty good list, so I was ready to send a few questions to dealers. After inquiring about one certain vehicle, "Jessica Jones," texted with an offer to provide more details and schedule a visit. A short time later, "Joseph" texted from a different mobile number with a similar offer. He was associated with the same dealer as “Jessica.” Curious, I asked Jessica if she and Joseph worked together. Her reply text was slightly off, but I live in an area where many people speak English as their second language. The next text didn’t answer my question, but repeated another version of the sentence “Let me know if you need help.” So, I asked “Jessica” directly: "𝘼𝙧𝙚 𝙮𝙤𝙪 𝙖 𝙥𝙚𝙧𝙨𝙤𝙣 𝙤𝙧 𝙖 𝙗𝙤𝙩?" “Jessica” assured me she was a 𝗿𝗲𝗮𝗹 𝗽𝗲𝗿𝘀𝗼𝗻 here to assist me. Immediately after, I received another text clarifying that “Jessica” was actually the dealership's AI scheduling bot and Joseph was a person. The problem here isn’t AI. It’s 𝗱𝗲𝗰𝗲𝗽𝘁𝗶𝗼𝗻. When companies deliberately program AI to sound human and even deny being a bot, they aren’t building trust—they’re breaking it. And as AI-powered interactions become more common in everything from customer service to companionship, businesses and the boards providing oversight need to be asking a critical question: 𝘼𝙧𝙚 𝙮𝙤𝙪 𝙪𝙨𝙞𝙣𝙜 𝘼𝙄 𝙩𝙤 𝙚𝙣𝙝𝙖𝙣𝙘𝙚 𝙧𝙚𝙡𝙖𝙩𝙞𝙤𝙣𝙨𝙝𝙞𝙥𝙨, 𝙤𝙧 𝙖𝙧𝙚 𝙮𝙤𝙪 𝙢𝙞𝙨𝙡𝙚𝙖𝙙𝙞𝙣𝙜 𝙩𝙝𝙚 𝙫𝙚𝙧𝙮 𝙘𝙪𝙨𝙩𝙤𝙢𝙚𝙧𝙨 𝙮𝙤𝙪 𝙬𝙖𝙣𝙩 𝙩𝙤 𝙨𝙚𝙧𝙫𝙚? AI, when used ethically, can be an incredible tool for improving efficiency, responsiveness, and customer experience. But honesty should never be sacrificed in the process. People don’t mind AI—they mind being deliberately 𝙛𝙤𝙤𝙡𝙚𝙙 by it. Am I wrong? #AI #EthicalAI #ResponsibleAI #Trust #CustomerExperience #ArtificialIntelligence #BoardLeadership #CorporateGovernance #Oversight #Technology #DigitalTransformation

"Keep a human in the loop..." "...at the end of the loop." That’s the message I always end my conference talks with. And stories like this? They’re exactly why. This week, AI customer support at Cursor made up a company policy out of thin air. A hallucination. The chatbot confidently told users that logging in from multiple devices wasn’t allowed anymore. ↳ Except... that policy didn’t exist. ↳ It just invented it. ↳ People got frustrated. ↳ They cancelled subscriptions. ↳ Trust? Gone. The AI wasn’t labeled as AI. It had a human name - "Sam". Many assumed it was a real person. No transparency. No fallback. And no human stepping in before the damage was done. This isn't just about AI messing up. It's about responsibility, trust, and the cost of skipping human oversight in critical touchpoints like support. We saw something similar with Air Canada’s chatbot last year. Different company. Same issue. AI confidently making things up - and companies paying the price. So if you're deploying AI in customer-facing roles, especially without labeling it clearly or having a human check the loop... be careful. Because once trust is broken, it's hard to build it back. And no AI can fix that for you. What’s your take on this? Do we need new rules - or just better practices? #AI #CustomerExperience #Trust #HumanInTheLoop #AIFails #Leadership #Innovation

🔍 AI in Customer Experience: When It Goes Wrong AI is transforming customer experience—but not always for the better. Here are 4 real-world examples where AI was abused or poorly implemented, resulting in backlash, broken trust, and damaged brand reputation: 💬 1. Air Canada’s AI Chatbot Gave False Information—And the Airline Had to Pay for It In 2024, Air Canada’s AI chatbot wrongly promised a refund policy that didn’t exist. A customer followed the bot’s guidance, was denied a refund, and took the airline to court. 📌 The court ruled Air Canada was responsible for its chatbot’s misinformation. Lesson: AI is not a scapegoat. If it speaks for your brand, it better be right. 🤖 2. Frontier Airlines Replaced All Human Support With AI—and Customers Were Furious In 2023, Frontier Airlines removed human agents entirely, replacing them with an AI-powered virtual assistant. The result? 📌 Customers couldn't get complex issues resolved or escalate complaints. The move was seen as cost-cutting at the expense of customer empathy. Lesson: AI should enhance service, not erase humanity. 🛑 3. Amazon’s AI Hiring Tool Displayed Bias—Imagine That Applied to CX While not strictly CX, Amazon's infamous AI recruiting tool (retired in 2018) downgraded resumes with female-associated terms due to biased training data. 📌 Imagine similar bias creeping into CX decisions—like who gets routed to premium support or offered retention deals. Lesson: AI is only as unbiased as the data it learns from. CX equity is on the line. 🔒 4. Facebook’s AI Flagged Innocent User Content, Then Ignored Appeals Facebook (now Meta) has long used AI to moderate content. But users have repeatedly complained about AI wrongly removing posts and providing no clear way to appeal. 📌 This creates a CX nightmare: no transparency, no accountability. Lesson: If customers can’t talk to a human when AI fails, trust erodes fast. 🧠 AI in CX is powerful—but it’s not a shortcut. It must be designed with accuracy, transparency, and empathy. 👉 Have you seen AI used poorly in CX? Or used it successfully with guardrails? Let’s discuss.