Keeping Up with the Joneses…AI
The exterior outputs look polished. But what’s happening behind closed doors…or closed chats?
By Jocelyn Little
July 9, 2026
It’s a sunny, beautiful Saturday morning. You walk out the front door, only to find Mrs. Jones pull into her driveway in a shiny, brand new, fancy car. She steps out of the car in her expensive outfit, newest kicks, grabs a bag of Whole Foods groceries, and walks into the house where a swarm of the cutest kids and dogs ever greet her warmly. Her husband, Mr. Jones, gives her an affectionate kiss hello, and the door closes. You have no more insight at that moment into the Joneses’ life once that door closes behind them.
We all know this idiom well. We often talk about how keeping up with the Joneses can lead to financial and personal stress. So what happens when companies across industries are adopting generative and agentic AI, and every influencer is selling “how to’s” on streamlining workflows?
In the age of the AI boom, it’s very easy to get caught up in the rush of keeping up with every AI tool, technique, and technology so that you or your business doesn’t fall behind. You see your competitors easily and quickly generating quality reports, content, marketing campaigns, courses at lightning speed. With so many companies selling their latest and greatest tool or class on how to use those tools effectively, and many for an affordable, “no brainer” price range, it’s easy to hop on the bandwagon. The pressure is increasing to keep up.
So you give it a try. You buy into the advertising promising you to cut your workload in half, produce the workflow of an entire marketing team, and automate jobs that will reduce your operating costs. You begin learning how to utilize these tools to create impressive, creative-looking, and marketable outputs. You begin to develop more shiny products at a faster rate. People applaud your efforts and admire the work being created. Everything looks polished and well made…on the outside.
What these “cost cutting” advertisements are failing to teach you is that your output looks finished before the underlying work is finished — which can cost you much more in the long run.
A polished result can create the illusion of a final, finished product — of completeness. An AI-written article can sound authoritative and full of useful content. AI-generated detailed curriculum can appear to fill a gap between your expertise and where you fall short. A resume looks and sounds professional. Likely much better than you could produce without technology and without taking three times as long to produce it. But appearance is not evidence of quality.
Who verified information? Who fact-checked the details? Who vetted the sources? Is the subject understood well enough to recognize the errors? Was protected material flagged? Who is held accountable when something goes wrong?
The challenge is not that people are unintelligent, incapable, or lazy. There are many highly accomplished, professional individuals with deep expertise in their own fields that utilize the latest tools in technology that allow us to work faster and smarter. Sometimes it’s simply a lack of awareness and understanding of AI governance, copyright and information provenance, and how generative AI produces an output or where it can fail. People fail to know what they don’t know. They cannot question something they don’t know to question.
In the same sense that we need to intentionally resist keeping up with our neighbors (the Joneses), we need to be intentionally cognizant of how we try to keep up with other organizations’ use of technology and AI tools. On one hand, we don’t want to create an unnecessary burden financially and within our own capacity. But on the other hand, just as you don’t know what happens behind closed doors of your seemingly perfect neighbors, you don’t know what happens behind the walls of the next organization. It’s easy to see the polished output the next organization is generating using the advancement of technology and AI. What you don’t see is the work and critical thinking behind AI that may be required…or the lack thereof.
Using AI is a skill. Evaluating AI-assisted work is a completely different skill. AI literacy must extend beyond prompting and tool proficiency. People need a general understanding of model limitations, hallucinations, probabilistic outputs, source verification, provenance, privacy, intellectual property, domain validation, bias, and human accountability.
Historically, professional work production required friction: time, research, specialists, expertise, revision, and review. That friction usually forced organizations to hire knowledgeable people. Generative AI has significantly reduced the friction of production. However, it has not reduced the need for sound judgment. Arguably, the easier production becomes, the more judgment may be required. The emerging divide may not be between people who use AI and those who don’t. It may become the difference between those who can generate with AI and those who can question, evaluate, verify, govern, integrate a human element, and take responsibility for what AI helps them to create. The tool can generate. The human is the critical piece that decides what makes real impact.
Keeping up with the Joneses has always carried an element of danger: making decisions based on outward appearances without understanding the realities behind them. Keeping up with the use of technology and AI means creating outputs at unprecedented scale — but we shouldn’t be asking, “Can we keep up?” Instead, we should be asking, “Do we understand what’s happening behind the closed doors of our own AI-generated work?”
Further Reading Resources: