Post by Sylwester Majewski

When the AI hype meets hard engineering reality, human expertise wins. A fascinating story circulating the media highlights a massive shift in strategy: 𝐅𝐨𝐫𝐝 reportedly rehired 350 veteran engineers after an automated AI platform failed to deliver the specialized work it was intended to replace. As the industry gets more familiar with AI, we are collectively waking up to its structural shortcomings. At 𝐅𝐌 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞, we are seeing almost identical patterns play out across the global fintech and brokerage sectors. Many fintech executives are realizing that AI cannot solve core requirements in key intelligence areas. Here is why generic AI models fall short when it comes to true strategic search and market analysis: • 𝐓𝐡𝐞 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐯𝐢𝐭𝐲 𝐓𝐫𝐚𝐩: AI is an excellent productivity tool for drafting, summarizing, and basic automation. But when it comes to the true value of investigative search, it cannot provide anything that isn’t already available to your competitors. • 𝐓𝐡𝐞 𝐅𝐫𝐞𝐞-𝐃𝐚𝐭𝐚 𝐋𝐢𝐦𝐢𝐭𝐚𝐭𝐢𝐨𝐧: Large language models train on widely available, public, and free internet data. If an AI can scrape it in seconds, it means every other broker in the market already has access to it. It offers zero competitive edge. • 𝐓𝐡𝐞 𝐍𝐞𝐜𝐞𝐬𝐬𝐢𝐭𝐲 𝐨𝐟 𝐕𝐞𝐫𝐢𝐟𝐢𝐞𝐝 𝐃𝐚𝐭𝐚: High-tier business insights require unique, proprietary, and strictly verified datasets, which is not being shared online. Just like Ford discovered with automotive engineering, synthetic automation is no substitute for human-led depth. True competitive intelligence requires digging where algorithms cannot reach. If your strategic decisions are based purely on what a public AI chatbot spits out, you are running the exact same playbook as the rest of the street. https://lnkd.in/dpTcmbSj #CFD #Forex #Intelligence #Research #Data #BusinessInsights