S1: Most companies aren't anywhere near ready for AI, and it's
S1: not that they aren't using AI, it's that they can't
S1: use AI. Most of the frustration people have with AI
S1: not being able to do what they want is actually
S1: them not being able to describe what they want. I've
S1: consulted for the world's largest companies hundreds of startups, tons
S1: of mid-sized companies, and lots of companies in the global 1000.
S1: And the number one issue I see is unclear and
S1: constantly changing vision and goals. AI is about execution, and
S1: it's quite powerless when it doesn't know what to execute.
S1: Companies that know exactly what they want are thriving with AI,
S1: and the better the AI gets, the more they will
S1: crush it. But this is a small percentage of companies,
S1: because only a small percentage of companies are self-aware and
S1: together enough to give AI proper instructions. You can't optimize
S1: what you don't understand, and it's foolish to scale something
S1: that you shouldn't be doing in the first place. People
S1: talk about companies not being ready for AI, and I
S1: don't think they realize how bad the problem is. this
S1: is not a technical maturity issue. It's a whole lot
S1: more fundamental than that. A massive percentage of companies are
S1: haphazardly successful despite themselves. It's not super clear what they
S1: were trying to accomplish or how exactly they're doing it,
S1: but they have a few tricks that work that they're
S1: decent enough at executing, that they're still around. But if
S1: you were to walk into the company and say, okay,
S1: describe to me what you're trying to do and what
S1: your strategies are and your challenges are and what your
S1: work streams are, they would either stare blankly at you
S1: or laugh in your face. It would take them weeks
S1: to put together a project to find that out, and
S1: then months to actually do the project. And of course,
S1: by the time you got done, it would be out
S1: of date. I honestly believe the vast majority of companies
S1: are in grave danger because they are essentially chaotic black
S1: boxes that barely work. Having the board or leadership tell
S1: everyone in a company to use AI is like looking
S1: at a screen of nothing but static and saying, we
S1: got to scale this thing. So worker says, cool, boss.
S1: Do me a favor and point to the thing you
S1: want me to improve. And the boss, like, pauses for
S1: a little bit and says, yeah, great question. Let's get
S1: some meetings together to figure that out. AI is mostly
S1: useless in these companies, and unfortunately, that means many, if
S1: not most companies. Their narrative right now is that AI
S1: isn't helping enough companies yet. So what's the problem? When
S1: will AI get good enough? Maybe AI isn't as good
S1: as people thought. What's hilarious and easy to see is
S1: that the company's AI is helping are somehow, magically the
S1: same companies that already know what they're doing. They can
S1: tell you very quickly the problem or problems that they're
S1: solving for customers. The problem with existing solutions that their
S1: solution solves, the goals that they have for the company,
S1: the metrics associated with those goals, the challenges that are
S1: stopping them from reaching their goals, the strategies that they
S1: are pursuing to overcome those challenges, the projects that they're
S1: doing to implement those strategies, the work that's being done
S1: within those projects by what people and how much it's
S1: costing them. And crucially, companies that know what they're doing
S1: give largely the same answers to these questions across different
S1: quarters and years. A sure sign of a flailing company
S1: is when their departments mean massive amounts of time claiming
S1: to have these answers. But the answers significantly change every
S1: quarter because everything is constantly in flux. So people are
S1: basically just writing down whatever they think makes them look
S1: good as a manager or as a department or whatever.
S1: It takes them weeks to prepare, only to be discarded
S1: a few weeks later when the process starts over again.
S1: AI can basically do nothing for these companies. In fact,
S1: it could even make it worse because now it helps
S1: people flail more impressively, like with more backflips and charts
S1: and stuff. And you may ask, well, if they're so bad,
S1: how are these companies still around? And the answer is
S1: simple most of their competition is just as bad. So
S1: what's the point of all this? A few things I
S1: think we can take away from this. AI has barely
S1: even started in the enterprise, because only a tiny fraction
S1: of companies have the self-knowledge and ability to articulate themselves
S1: well enough to be ready for AI. Two, we should
S1: stop looking at AI as the problem, or even technology
S1: as the problem. The issue is not being able to
S1: describe one's company clearly, including its goals, workflows, operations, decisions, teams,
S1: and spending in a clear and consumable fashion. Three companies
S1: who are unable to do this are in grave danger
S1: from the companies who can. For the primary danger to large,
S1: unwieldy companies is that it's now possible for a smaller
S1: company to function with the strength of a much larger one.
S1: And it's far easier for a small company to be
S1: able to answer the questions above. And because of this,
S1: all existing companies are about to face extraordinary downward force,
S1: and only companies who have their shit together will stay
S1: afloat and rise. AI is a remarkably small part of
S1: who will win or lose in this initial phase. AI
S1: is what the winners will use to fight each other
S1: in the new world. But right now, the game is
S1: figuring out who's going to make it there. The number
S1: one question you should be asking yourself as a company
S1: is not what AI can do for you, but whether
S1: or not your company is in the state where AI
S1: can help at all. And if not, you need to
S1: get into that state as quickly as possible.