Ah, the dream of eternal growth. Startups salivate at the thought, while ponderous incumbents shudder. And why shouldn't they? Complexity is the graveyard of corporate ambition. It's where nimble startups go to get fat and happy, only to wake up one day realizing they've become the lumbering giants they once sought to dethrone. Then they get disrupted by a new wave of startups, ad infinitum. It's the Circle of Corporate Life, choreographed not by Elton John, but by Clayton Christensen. But what if we could use AI to manage this complexity? It's a tantalizing proposition, isn't it? There's a reason why modern corporate buzzword bingo includes terms like "data-driven decision-making" and "automated workflows." Humans, bless their hearts, are not very good at managing complex systems. We forget things. We get emotional. We can't crunch large datasets in our heads. Basically, our hardware hasn't had an upgrade in millennia, but the software we're running—globalized capitalism, democracy, 24-hour news cycles—keeps getting more demanding. Let's start with the romantic notion of the startup. Here you have a small team, working diligently in a metaphorical (or sometimes literal) garage. Communication lines are short. Every team member understands the core business inside and out. A decision can be made in a quick meeting or even a Slack message. Life is good. Contrast that with a large corporation. Decisions meander through labyrinthine corridors of middle management, get stuck in endless meetings and sub-meetings, and sometimes die quiet, unnoticed deaths in the neglected corners of an SAP system. The same complexity that allows large corporations to operate at scale also cripples their ability to move swiftly. And here is where AI could theoretically swoop in like some sort of corporate superhero. Imagine an AI that could process and analyze all internal communications, workflow data, and external market conditions in real-time. It could flag bottlenecks, automatically reroute resources, and even suggest strategic shifts. Essentially, it would be a complexity-navigation system, constantly updated with real-time data. Sound far-fetched? Companies like Palantir have already been offering a rudimentary version of this vision to government agencies for years. But let's not don our rose-colored AR glasses just yet. An AI system can be as flawed as the humans who program it. Garbage in, garbage out, as the saying goes. There's also a question of control. Who gets to program the corporate AI? The C-suite? Middle management? A rogue intern with a penchant for chaos theory? And then there's the issue of job displacement. Sure, you could automate a lot of managerial tasks. But what do you do with the surplus of middle managers? You could retrain them, but to do what exactly? More importantly, what does this centralization of decision-making power do to corporate culture, not to mention the balance of power in society at large? Now, let's ratchet up the complexity a bit more and talk about governments. If corporations are complex, governments are complex squared. A government has to manage not just profit and loss, but also social welfare, public opinion, foreign relations, and sometimes even the laws of physics. Theoretically, AI could be a godsend here as well. It could optimize tax collection, manage public services, even suggest legislative changes based on real-time data analysis. However, the potential pitfalls are not just bigger; they're monumental. We're talking about software glitches that could lead to diplomatic incidents, or worse. And then there's the ethical dimension. Who gets to program the values of a government AI? What if the AI suggests a policy that is mathematically optimal but ethically dubious? Let's not forget that algorithms can perpetuate existing biases, essentially hardcoding systemic issues into what appears to be an impartial system. Moreover, the efficiency gains from automating decision-making could be offset by a loss in the perceived legitimacy of human governance. People tend to accept decisions from human leaders because they believe there's an understanding of shared human experience and values. Strip that away and replace it with an algorithm, and you might get a system that is more efficient but less respected and ultimately less stable. So where does this leave us? AI offers tantalizing possibilities for managing complexity, both in the corporate world and in government. The gains in efficiency could be revolutionary. However, the risks are not to be underestimated. The questions of control, ethics, and societal impact loom large. It's not enough to ask if we can build these systems; we must also ask if we should. In the final analysis, AI as a complexity management tool is a double-edged sword. It has the potential to cut through the Gordian knots that have stymied organizations both large and small. But like any powerful tool, it can also cause great harm if not wielded carefully. Before we rush headlong into this brave new world of algorithmic governance, we would do well to tread carefully, pondering not just the economic implications, but the human ones as well. After all, what's the point of building a more efficient system if it ends up being one that we wouldn't want to live in? Thanks for reading Matt’s Substack! Subscribe for free to receive new posts and support my work.