Companies Are Just a Graph of Algorithms

Companies Are Just a Graph of AlgorithmsAI is about to see your company as a series of components to be optimizedMay 6, 2024 #ai #business #ethics #future #innovation #productivity #society #technology #recommended #top Architect-meeting… I think the reason so many people don t understand how big AI is going to be is that they don t understand that everything is an algorithm. Specifically, they don t realize that companies are just a collection of algorithms. Well, let s say that your company takes pictures, cleans them up, stylizes them, and adds a caption—which customers can then download in a large format. Let s call the company Memories. The company started in the early 2000 s, founded by an artist/photographer, and here s how it works: Simple enough, and for anyone into computers you will recognize this as a series of steps, aka—an algorithm. Also, each one of these steps is an algorithm itself, just like the full set of algorithms. So you could break the Upload step into its own piece. And you can keep going. Each of those steps can be broken down even further—it s algorithms all the way down. But the sending and processing pieces aren t the only flows that make up the business. You also have: As you continue the process, you start seeing a full picture of all the different pieces that make up the business. I think of this as a graph of algorithms. I use the word graph because it allows me to think of the relationships between the different components and describe them using an action—such as send to or receive, or whatever. This process of breaking down processes of any kind—and especially for an entire business—is powerful on its own. If you were to have done this exercise for any business in 2022 it would have given that business a significant advantage. It allows you to see all the pieces, how they fit together, and figure out what to optimize or even eliminate from the workflow. But when you add AI to the mix, things get truly extraordinary. AI excels at both discrete task execution and determining how things fit together, and every single one of your company s workflow components becomes ripe for optimization or elimination. AI-deniers are simply not realizing how opaque most businesses are, how much waste there is in their processes, or the level of redundancy and inefficiency. AI is about to end that, and consultancies like Accenture, KPMG, and McKinsey will be leading that push. They will come to your executive leadership team and offer something like the following. And the result will inevitably be a smaller, tighter company that not only saves money but has fewer humans required to run it. Once AI has been used inside a company—in this way—it s just one step away from a workflow that continuously analyzes these business components/algorithms. The system will constantly be asking things like: Ok, I see these 6 components for your marketing department, let s look at one of those: Cool, well we at AI-Consulting-Corp have questions: And this isn t limited to marketing. Every single department has the same pattern—customer support, HR, hiring, you name it. The entire process is just steps. Steps that can be articulated and visualized. AI will do so much of this very soon, often better than most humans. You ve probably never seen your company in this way, but AI soon will. Every one of those items is just another algorithm. And the better AI gets, the fewer humans will be doing those pieces. (In a follow-up I ll talk about what human jobs I think are likely to remain in this model.) You might be inclined to say that your company doesn t just receive images to optimize and send them back to the customer. Your company is special. You have harder steps. Or more steps. It s way more complicated than I m making it out to be. That just means a bigger graph. And just because it ll be a lot for a human to process in one go doesn t mean it ll be hard for AI. No matter how special the product or company, it still operates as a pipeline of steps. Again, understanding all the pieces and how they fit together—and being able to explain that well to decision-makers—is AI s strength. It really doesn t matter what kind of business you re in. Anything you—or anyone else does—can be broken down into steps like this. I m not trying to scare you. Or make you hate AI. Or look into becoming Amish. I m telling you what s coming and that you need to get ready for it—both as a business owner who wants to compete in this new model, and/or as a worker in these companies. The upside here is that businesses are about to become way more efficient. Which means more productivity, more output, and ultimately a lot more new things in the world. This same process will also make it easier for people to start businesses, including those who had no chance in 2022 or before. But there will be downsides—especially from the loss of many easy-to-automate human jobs. My advice is not to be depressed,

Companies Are Just a Graph of Algorithms

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