朋友们，今天给大家讲一个经典的职场甩锅故事，只不过主角是一家市值几十亿美元的上市公司。
主角叫Monday.com，做项目管理SaaS的，也算AI概念股吧。最近发布财报，业绩不及预期，股价应声大跌。怎么向投资者交代呢？你猜他们怪谁？
怪AI。
对，你没听错。不是怪经济不好，不是怪竞争激烈，不是怪自己产品没做好——怪AI。管理层在财报电话会上说了，收入增长放缓是因为公司正在进行“AI转型”，研发投入增加了，客户需要时间迁移到AI功能上，新的定价模式还在探索中，巴拉巴拉巴拉。
一句话总结：业绩差是因为我们在搞AI，搞AI需要花钱，所以业绩差是正常的，你们要理解。
“AI转型”：一个完美的筐
你品你细品。“AI转型”这个词，简直是为上市公司量身定做的完美背锅侠。
为什么？因为它有三大优点：
第一，无法证伪。你说你在搞AI转型，谁能说你没搞？你招了几个AI工程师、买了多少GPU、做了几个内部项目——这些都是“转型投入”，外人没法精确核算。反正钱花了，效果好不好以后再说。
第二，政治正确。现在谁不说自己在搞AI？你说你不搞AI，投资者先跑一半。你说你在搞AI但短期影响了业绩——投资者虽然不满意，但至少觉得你方向是对的，只是需要时间。同样是业绩不及预期，“因为我们在搞AI”和“因为我们不行了”，股价反应能差十万八千里。
第三，永远有下一次。AI转型是个筐，什么都能往里装。这季度业绩差？因为AI投入。下季度业绩还差？因为AI还在投入。大后年业绩还差？因为AI转型还没完成。只要AI这个概念还热，这个借口就能一直用下去。
当然了，Monday.com不是第一个这么干的，也不会是最后一个。TechCrunch的报道标题说得很直白——Monday.com是“最新一个”把业绩不好怪在AI头上的科技公司。“最新一个”这个词用得妙，说明前面已经有一串了，后面还会有更多。
AI：我到底招谁惹谁了
AI这两年也是够忙的。
涨的时候，什么利好都往AI身上靠。营收增长了——因为AI战略。用户多了——因为AI功能。股价涨了——因为AI想象空间。AI就是个聚宝盆，什么好事都是它的功劳。
跌的时候呢？业绩不好怪AI投入太多，裁员怪AI效率提升，订单少了怪客户在等AI功能，连产品做不出来都能怪“大模型能力还不够”。
合着AI是涨也AI、跌也AI，功也AI、过也AI。AI就像个老实人，有好事的时候大家抢着往自己身上揽，出了问题的时候第一个推出去挡刀。
朋友们，教大家一个识别套路的小技巧：如果一家公司业绩好的时候说“都是我们团队努力的结果”，业绩差的时候说“主要因为AI转型的短期影响”——那你就要小心了。真正在AI上拿到实实在在成果的公司，业绩好的时候会归功于AI，业绩不好的时候会找真正的原因。只有那些没什么真东西的公司，才会把AI当万能挡箭牌。
对了，最后给大家提个醒：
1. 看科技公司财报的时候，但凡看到“AI转型”“战略投入”“短期阵痛”这些词，多留个心眼，别被概念忽悠了。
2. 真正的AI商业化，看收入结构里有没有AI相关的具体收入项，而不是听管理层讲故事。
3. 如果一家公司连续几个季度都在用“AI投入”解释业绩不佳，那大概率不是AI的问题，是公司的问题。
今天就槽到这里，明天继续。
Friends, today I'm telling you a classic workplace buck-passing story — except the protagonist is a public company worth billions of dollars.
The star is Monday.com, the project management SaaS company — also considered an AI concept stock. They recently released earnings, missed expectations, and the stock tanked accordingly. How do you explain it to investors? Guess who they blamed.
They blamed AI.
Yeah, you heard me right. Not the economy. Not fierce competition. Not their own product shortcomings. AI. On the earnings call, management said revenue growth slowed because the company is undergoing an “AI transformation” — R&D spending is up, customers need time to migrate to AI features, new pricing models are still being explored, blah blah blah blah.
One-sentence summary: Poor results are because we're doing AI, doing AI costs money, so poor results are normal — you should understand.
“AI Transformation”: The Perfect Basket
Let that sink in. The term “AI transformation” is basically the perfect scapegoat tailor-made for public companies.
Why? Because it has three great qualities:
First, it's unfalsifiable. You say you're doing AI transformation — who can say you're not? You hired a few AI engineers, bought some GPUs, ran a few internal projects — all of this counts as “transformation investment,” and outsiders can't precisely audit it. Money's been spent, whether it's working or not — we'll see later.
Second, it's politically correct. Who doesn't say they're doing AI these days? Say you're NOT doing AI and half your investors bail immediately. Say you ARE doing AI but it's hurting short-term results — investors aren't happy, but at least they think your direction is right, it just needs time. Same missed earnings, but “because we're doing AI” versus “because we're failing” — the stock reaction can be night and day.
Third, there's always a next time. AI transformation is a basket you can throw anything into. This quarter's bad? Because AI investment. Next quarter's still bad? Because AI is still investing. Two years from now still bad? Because AI transformation isn't complete yet. As long as AI is hot, this excuse keeps on giving.
Of course, Monday.com isn't the first to do this, and it won't be the last. The TechCrunch headline put it bluntly — Monday.com is the “latest” tech company blaming poor results on AI. That word “latest” is clever — it implies there's already a long line of them, and more are coming.
AI: What Did I Ever Do to You?
AI has had it rough these past couple of years.
When things are going up, every bit of good news gets credited to AI. Revenue growing? Because of AI strategy. More users? Because of AI features. Stock going up? Because of AI's upside potential. AI is a cornucopia — everything good is because of AI.
When things are going down? Poor results blamed on too much AI investment. Layoffs blamed on AI efficiency gains. Fewer orders blamed on customers waiting for AI features. Even products that never ship get blamed on “LLM capabilities not being there yet.”
So basically up is AI, down is AI, credit is AI, blame is AI. AI is like that nice guy everyone takes advantage of — when things are good, everyone takes credit; when things go wrong, he's the first one pushed under the bus.
Folks, here's a little trick for spotting the pattern: if a company says “it's all thanks to our team's hard work” when times are good, but says “it's mainly the short-term impact of AI transformation” when times are bad — watch out. Companies that are actually getting real results from AI credit AI when things go well and find real reasons when they don't. Only the ones with nothing substantial use AI as a universal shield.
Oh, and a few reminders before we wrap up:
1. When reading tech company earnings reports, whenever you see phrases like “AI transformation,” “strategic investment,” or “short-term growing pains” — stay alert, don't get fooled by buzzwords.
2. For real AI commercialization, look for specific AI-related revenue line items in the income structure, not just management storytelling.
3. If a company keeps using “AI investment” to explain poor results quarter after quarter — it's probably not AI's problem. It's the company's problem.
That's enough cao for today. More tomorrow.
实用提醒：①看财报遇到“AI转型”“战略投入”多留个心眼；②真正的AI商业化要看具体收入项，不是听故事；③连续几季度都用AI解释业绩差的，大概率是公司本身的问题。
Practical tips: 1. When you see 'AI transformation' or 'strategic investment' in earnings reports, stay alert. 2. Real AI commercialization shows up in specific revenue line items, not just storytelling. 3. If a company blames AI for poor results quarter after quarter — it's probably the company, not AI.
Monday.com · AI transformation · earnings blame · universal scapegoat · AI commercialization · tech earnings · rant
