2026
The things we do with data & AI today that future us will look at and say: wait, what?
How are we using data & AI today that will seem painfully cringe 20 years from now?
We asked 20 data & AI leaders from trailblazing companies to name the habits and assumptions our future selves won’t believe we once worked by or cared so much about.
Here’s what they said.
Bradley Levy Director of Analytics at AlphaSense
Analysts building dashboards
Gone are the days of fighting with your dashboard containers. Analysts of the future will become first-class partners uncovering deep insights while driving outsized impact, at a speed we never thought possible.
Ofir Ehrlich Co-Founder & CEO of Eon
How companies had enormous amounts of data they barely touched or understood
It was like owning a library with millions of books that nobody had ever read.
Jane Smith Field Chief Data & AI Officer at ThoughtSpot
The hidden human cost of AI
We’ll cringe at how we treated AI-generated output as free or productive simply because it was instant to produce. Every confidently wrong analysis still had to be read, understood, and cleaned up by a human. Future us will know all too well that one lazy prompt might save 30 minutes but ultimately create hours of work for everyone downstream.
Adi Glasman VP of Engineering at Zendesk
How we made humans speak SQL because our data couldn’t speak business
So much data work still involves translating natural business questions into schemas, joins, and hand-maintained metric definitions. In 20 years, it may seem absurd that people had to understand the data model, instead of the data model understanding them: their intent, context, terminology, and required level of trust.
Thomas Mazzaferro Member at Forbes Technology Council
Executives running companies using dashboards
A dashboard tells you what happened. An intelligent operating system will increasingly tell you: what happened → why → what will happen → what should we do → what happens if we do it → execute the decision → learn from it.
Silja Märdla Head of Analytics Engineering at Bolt
The AI slop we put up with
Future us will surely cringe at how hard we tried to use AI on data, simply because we were so determined to make AI make us more efficient. I personally can’t wait to move past that phase and reach a point where AI-assisted data work actually results in better work, where data agents have the context they need to produce results we can trust, and we humans can focus our expertise where it matters most.
John Wernfeldt Managing Director of Data & AI Governance at Northridge Analytics
"We appointed data owners"
Said proudly, in a steering committee, as if that was the achievement. No job description, no hours in anyone’s calendar, just a name in a slide next to a domain. I think in twenty years we’ll look back at that the way we now look at putting someone’s name on a fire safety poster and calling the building safe.
Doing stuff in the cloud
Probably in on-premise data centers deployed in space.
Arthur Wang Principal Data Engineer at Babylist
Having to navigate to some custom web UI to interact with a service
You mean I have to leave my terminal or Claude app? Hard no. Everything’s going to be consumable via MCP, API, or CLI in the future.
Malcolm Hawker Chief Data Officer at Profisee
Thinking it's impossible to quantify the business value of data
Lauren Anderson Sr. Director, Insights, Analytics & Data Science at F5
Slapping an AI agent on top of a legacy dashboard
We spent 15 years teaching executives to look at the same five bar charts. Giving them a sophisticated, autonomous chatbot just to ask those same five questions faster completely misses the point. The real superpower of AI won’t be answering the questions we already know to ask. It’ll be uncovering the things we didn’t even know we should be asking.
Salma Bakouk Co-Founder & CEO of Sifflet
The concept of "Data Governance"
Treating data as a product was one of the best shifts this industry has made. The fact that we still discuss data governance as a separate function is a sign we never fully committed to that idea. In software, you don’t bolt SLAs onto a product after it ships. Reliability, ownership, and quality are designed in from the start.
Eynat Guez Co-Founder & CEO of Papaya Global
The algorithm said so
Just as we now cringe at open-plan offices that traded privacy and focus for efficiency, we’ll cringe at how readily we traded human judgment for automated decision-making. We let machines make consequential choices about people’s lives based on data, often without a human checking the reasoning, questioning the inputs, or taking responsibility for the outcome. Perhaps the real progress will be giving machines what open-plan offices never had: clear boundaries.
Shachar Meir Data Advisor, Former Dir. of Data Engineering at Meta
Data professionals who don't understand the business or product
Human involvement in anything other than asking questions
Gathering, cleaning, modeling and analyzing data are all going to be commoditized and cheap. The impactful part would be bringing curiosity and creativity into formulating questions that we as a society want answers to.
Sol Rashidi CSO, Data & AI at Cyera
We’re taking books, poetry, artwork, esoteric practices, photographs, inventions, rituals and ceremonies, and all the natural and human-made beauty in this world, and pixelating the heck out of it. Turning everything into bits, bytes, and vaporized digital packets until nothing exists in its original form, detached from the very people who created it.
Efrat Aran Data Lead at OurRitual
Money
The idea that we once optimized data and the insights we drew from it to extract profit will feel cringe to us, maybe even immoral. In the future, we’ll use data to optimize for meaning, not money. How will that work? We’ll just have to wait and see, won’t we?
About Euno,
but make it cringe.
Once upon a time, sorcerers tried to harness AI for the enterprise. They soon discovered AI had no clue how to make sense of data. Then came Euno, bestowing the right context upon every agent worthy of being knighted. Ever since, enterprise kingdoms have rolled out AI across their business realms, at scale and with trust.
Once upon a time, sorcerers tried to harness AI for the enterprise. They soon discovered AI had no clue how to make sense of data. Then came Euno, bestowing the right context upon every agent worthy of being knighted. Ever since, enterprise kingdoms have rolled out AI across their business realms, at scale and with trust.
And data & AI lived happily ever after.
And data & AI lived happily ever after.
Enter the Eunoverse



