Innovation flux; today's three body problem.
Too much complexity impacts corporate decision making. The rash of new AI technology & ideas has actively slowed down corporate adoption. That, and geopolitics are paralyzing corporate North America.
Have you noticed anything about the last year?
Is it me, or has corporate decision-making dried up? I see this in Sparkgeo’s business development pipeline and, between the lines, in various media articles. And over the last couple of weeks, I’ve reached out to a number of industry leaders to gauge whether this was a local or global effect. It could easily just have been me. It’s not, though; it’s global. One of the leaders joked that it felt like everything just stopped after one LinkedIn post. This pattern seems linked to commercial rather than government activity.
Let me explain.
In a commercial enterprise, it’s actually possible to do nothing. By that, I really mean “nothing new.” Because doing new things involves some risk and investment, and those things are really best done in a consistent environment. While in government, it may seem like nothing is getting done, but generally, there is a lot of busywork behind the scenes to make a new policy happen. So, governments tend to be slow, but rarely actually stop work programs, DOGE aside. In the commercial sector, however, it’s perfectly possible, even advisable, to just stop and wait out a particular storm. The corporate strategy lies in how long one chooses to pause and whether one wants to be first back to market or is happy to be a fast or even a slow follower.
I am talking primarily about innovation and modernization projects, which is the area where I have the most experience.
Today, I am seeing a slowdown in decision-making, and I will take a guess that it’s a combination of two confounding externalities:
1) AI
2) GeoPolitics
Normally, I would tackle these concepts separately, but for the purposes of this discussion, it actually doesn’t matter what the subjects are. What we have are two externalities to a corporation that each cause a freeze in activity while the firm decides how to approach the new situation.
How many LinkedIn AI-generated articles have you seen about AI strategies? If you are tasked with developing an AI strategy, then you will have a very difficult job finishing that piece of work before the next revolutionary technology is developed and deployed. This amounts to a series of crises for the organization. Any corporate AI strategy actually needs to step outside the technology cycle and focus on the corporate philosophy of AI use. Indeed, a corporate philosophy that delineates people from machines and elevates people by using those machines.
But the AI-generated posts on AI strategy might also be telling people to just use more AI, because that’s what AI would say.
The self-licking ice cream cone is always a funny joke, but in this case, it’s at once true and misleading. AI is not a binary debate; it is about nuance, efficiency, and elevating the user with phenomenal tools. Those tools still need a software development life cycle (SDLC), however. To design and manage that lifecycle, you do need some people. There is a huge opportunity for SDLC acceleration, but so often that nuance is lost, and not nearly so click-baity.
Likewise, the geopolitical landscape today is such that something new is happening every week, if not every day. Sometimes we are told what amounts to marketing spin about the start or end of wars, the opening or closure of shipping routes, or the presence or absence of tariffs. Very big, important political and business topics seem to be treated flippantly, leaving those managing a value-creation process to evaluate the contents and likelihood of a particular statement. This is a question of trust, yet I would hazard you against assuming that this is just little boys crying wolf. Some very real things are happening.
A corporation responds to change given enough time. If corporations are anything, they are generally adaptable and resourceful groups of people. As my brother once told me about the markets, eventually, people have to start buying something again. This is true of any corporation; eventually, they have to go back to work again. The innovation teams need to innovate. Well, they do that until the next crisis, and then pause once more. If the time they spend pausing is longer than the time between crises, they never get back to normal. Crisis management becomes the new normal. Now, of course, there is a meta-efficiency here. Corporations will get better at dealing with change; they will build models to efficiently assess the effects of a specific crisis on their operations. They will map 1st-, 2nd-, and 3rd-order effects.
So we have two bodies of important external activity, each somewhat distracting and each spawning regular critical events for a corporation to evaluate. Consider the corporation also as its own body, interacting with one of these bodies: a two-body problem in which equilibrium can be found. But with the addition of the second body, we now have a chaotic three-body problem. In most practical circumstances, a way will be found, as I said, corporations are adaptable. But enterprises will be partially paralyzed from doing new things until one of those bodies diminishes.
I think for the last year (maybe two), corporate North America has been in constant crisis mode. As a result, in terms of innovation, we have seen half-hearted efforts in AI, largely involving vast layoffs followed by rehiring. This feels more reactionary than strategic, more performative than thoughtful.
Those small companies winning right now are those with robust relationships with governments that still want to move forward and are even encouraged by the need to build sovereign capabilities. Increasing sovereign capability without fixing broken procurement processes ensures that those already serving governments will continue to do so. Not necessarily a guarantee of innovation.
From a strategic perspective:
It's time to reconsider organizational structures. AI strategies are necessary, though, perhaps don’t let AI write your strategy. It's absolutely no use being King Canute yelling at the tide coming in. Instead of drowning, it’s far better to apply your nuanced thinking and start to consider an accelerated view of your increasingly complex world.
Keeping your supply chains flexible, diversified and sometimes Sovereign is probably also smart.
In geospatial, having feet in both government and commercial activities seems prudent.
Build as much decentralization and agility as possible.
Companies built for last year’s success are not necessarily well designed for success this year. This is a time to reimagine whatever you are doing; if you don’t think it has changed, then perhaps you're not paying close enough attention.