Here’s a fascinating puzzle: We’ve created software systems so complex that we now need software to help us manage our software. And guess what? We don’t have enough people who understand how to manage that software either. Welcome to the infinite regression of modern digital transformation.
Let’s dive into what I like to call “The ServiceNow Paradox.” Picture this: You’re a large organization drowning in manual processes. You discover ServiceNow, a platform that promises to digitize and automate everything from IT helpdesks to HR workflows. It’s like having a digital butler who knows exactly how to handle every business process. Sounds perfect, right?
But here’s where it gets interesting from a cognitive architecture perspective: To implement this digital butler, you need people who understand both the butler’s language (ServiceNow’s technical architecture) AND your household’s specific needs (business processes). And these people are about as rare as quantum physicists who can also perform stand-up comedy.
The fundamental issue isn’t just a shortage of skills - it’s a deeper cognitive challenge. We’ve essentially created a meta-layer of abstraction that requires three different mental models to operate simultaneously:
In other words, we need people who can think like computers while understanding human organizations while also being able to translate between the two. No pressure.
The current solution? “Just get certified!” But this is like saying you can become a master chef by reading cookbooks. ServiceNow University and similar training platforms are essentially teaching people the vocabulary of cooking without letting them near a kitchen. Sure, you might know what “mise en place” means, but good luck running a restaurant kitchen on your first day.
And here’s where it gets really meta: The very platform that’s supposed to automate and simplify business processes requires such complex knowledge to implement that it creates its own complexity problem. It’s like needing a PhD in butler management to hire a butler who’s supposed to make your life simpler.
The experience gap is particularly entertaining. Companies want experienced ServiceNow professionals, but to get experience, you need… a job working with ServiceNow. It’s the old “entry-level position requiring 5 years of experience” joke, except now it’s about a platform that’s supposed to solve exactly these kinds of organizational inefficiencies.
What’s particularly fascinating is how this reflects a broader pattern in human cognitive evolution. We’ve always created tools to extend our capabilities, but we’ve reached a point where our tools have become so sophisticated that they require their own ecosystem of meta-tools and meta-knowledge to operate them.
The solution? We need to fundamentally rethink how we bridge the gap between human cognition and computational systems. Programs like Optimum’s CareerPath are onto something - they’re essentially creating a cognitive apprenticeship model that allows people to gradually build up the multiple mental models needed to work with these systems.
But here’s the real kicker: As we add AI capabilities to platforms like ServiceNow, we’re not actually reducing the complexity - we’re just shifting it to a different level. Now we need people who understand not just the platform and business processes, but also how AI interfaces with both.
What we’re really seeing is the emergence of a new kind of cognitive infrastructure. Just as cities needed new kinds of workers when they built physical infrastructure like electricity and plumbing, our digital infrastructure needs a new class of knowledge workers who can think across multiple levels of abstraction.
The irony? We might need to automate the process of training people to work with automation platforms. Perhaps ServiceNow needs to create a ServiceNow instance to manage the process of creating new ServiceNow experts. And if that sentence made your head hurt, well… welcome to the future of work.
In the meantime, if you find someone who understands ServiceNow, business processes, AND can explain both to others, don’t let them go. They’re not just employees - they’re cognitive translators for the digital age. And they’re worth their weight in digital gold.
Because at the end of the day, the biggest challenge in digital transformation isn’t the technology - it’s the human capacity to understand and work with increasingly abstract systems. We’re not just facing a talent gap; we’re facing a cognitive architecture challenge that goes to the heart of how humans interact with complex systems.
And that’s something no amount of certification courses can solve… at least not until we create an AI that can teach humans how to teach AIs how to automate the process of teaching humans. But that’s a paradox for another day.