Old School BI vs AI BI, Corporate Burnout, and More
Joe's Nerdy Rants #61 - Weekend reads, podcasts, and other stuff
Old School vs. AI BI
Having done BI on and off for ages, I had a series of conversations this week about BI that left me quite confused about the direction of the field. On the one hand, I’m hearing from non-BI vendors that BI vendors will have a tough time because of AI. On the other hand, I hear from BI vendors nothing but excitement about AI. What gives?
Both arguments have merit, and the reality is somewhere in between.
Old-school BI (manually generated dashboards and reports) will remain, mostly because of the Lindy Effect. Some certain behaviors and workflows are ingrained in people, and glancing at dashboards and reports is one of them. The challenge for old-school BI is adoption and utilization. A 2022 study by BARC states, “The percentage of employees actively using BI/analytics tools is currently 25% on average, reflecting minimal growth in the past seven years weʼve been tracking this metric.” I recently spoke with the CEO of BARC, Carsten Bange1, and he doesn’t seem bullish on old-school BI.
The ability to chat with your data via AI BI is neat, but the reality is most of the key metrics a company cares about are already captured in Old School BI dashboards. It’s the classic Pareto distribution, where 20% of dashboards will cover 80% of what you need to know to run your business. So, AI BI will allow you to explore the “other” questions. Throw AI agent workflows into AI BI, and now you have a team of robot analysts working nonstop to improve your business. The latter is interesting, as I’m more interested in the actions people take from BI and analytics, not just if people get nifty “insights.” Insights don’t mean much if they’re not executed (although doing nothing is sometimes a wise move). AI BI agents have far broader implications for companies, especially when integrated with operational workflows. Theoretically, a company could someday be run by bots. But, given the poor data quality in most companies, I don’t see this happening for a while (unless bots can also fix the underlying data).
All of this goes back to the adoption of BI/analytics tools. Will AI BI magically increase BI and analytics adoption and usage, which has been treading water for years? Time will tell, and I’m skeptical. But I hope to be proved wrong.
Corporate Burnout
I'm not sure what’s happening, but this week alone, I had several conversations with friends who are BURNED OUT on their Big Tech jobs. These people are established in their careers and entered 2025 feeling, “Is this it?!” More bullshit, more responsibilities (because lots of people were already fired), and more Hunger Games infighting. My bestie, Carly Taylor, posted a mic drop on burnout the other day. The general feeling I’m hearing is, “What am I doing with my life?!”
People who are fed up with their jobs are nothing new—that’s why labor unions exist. Modern capitalism has ruled the West for decades, and shareholder value has grown at all costs. What’s different now is that we’re entering a new era of Late-Stage Capitalism, where workers and employers openly show disdain and are occasionally combative. There’s no pretense that workers and employers care about each other. This is alarming, but it’s reality.
Given the new US administration, the worker and employer relationship will be far less compassionate than before. Worker rights will be stripped as deregulation runs rampant. 2025 is the Gordon Gecko “Greed is Good” 1980s, but where Terminator and RoboCop are sorta real. Your Big Company very likely doesn’t care about you. If you’re an employee at a Big Company and in the rat race, here’s my take - be greedy. If you can, leave and become a vendor or competitor of your former company. Get the money. Be ruthless. Look out for number one. Or, leave and do something entirely different. There is a life outside of data and tech, and I know many people who left the rat race and are FAR happier with their lives.
One last thing. I’d like to open my newsletter to guest or collaborative articles. My ask - please have already written in public and share some examples of your writing. Have a voice and strong opinions. If you’re interested, message me.
Have a wonderful weekend,
Joe
Cool Weekend Reads & Listens
Tech & AI
Things we learned about LLMs in 2024
How AI-assisted coding will change software engineering: hard truths
Why AI Progress Is Increasingly Invisible | TIME
How to measure the impact of engineering in 2025 - LeadDev
Biz & Culture
Why probability probably doesn’t exist (but it is useful to act like it does)
Stop speedrunning to a dystopia - by Erik Hoel
Podcast
Freestyle Fridays - Old School BI vs AI BI (Spotify)
Dave Colls and David Tan - Effective Machine Learning/AI Teams (Spotify)
Freestyle Fridays - The Year Ahead (Why Data Modeling Matters, AI, Being Human, etc) (Spotify)
Simba Khadder - Feature Stores, Reinforcement Learning, and More (Spotify)
Gordon Wong - What We're Stoked for in 2025 (Spotify)
Matt Housley - End of 2024 Chat, Advice on Consulting, Leaving a Job, AI, and More (Spotify)
Way more over at the Joe Reis Show, available on Spotify, Apple Podcasts, or wherever you get your podcasts. It will soon be available on YouTube.
Upcoming Events
First up, I’m back co-hosting with my good friends, Ciaran Dynes (Chief Product Officer) and Mark Balkenende (Vice President of Product Marketing) from Matillion. This time, we’re talking about data management trends in 2025.
When: January 23rd at 8am PT/11am ET/4pm GMT
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London - March TBA
Snowflake and/or Databricks - June TBA
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Joe Reis
A podcast with Carsten is dropping next week, by the way
"But, given the poor data quality in most companies, I don’t see this happening for a while (unless bots can also fix the underlying data)".
Exactly where my mind is. Almost all mid/large size enterprises putting 'AI' in their company strategy but few ever ask if they are 'AI ready'. Particularly on the users who are going to use the AI-enabled BI tool.
If the Business Operation team, for example, doesn't even have idea what data points are useful/relevant to the business and how they are harvested (hello, talk to the Data Eng or Product person!), or basic understanding of data schema and better yet SQL, adding AI agent on top of current reporting database is not going to help. Feeling pretty much putting the cart in front of the horse, IMO. In that scenario, I would suggest double down on data literacy instead of/in addition to AI adoption to improve efficiency
Shane Gibson has some cool views on the BI v AI/BI debate. From a BI and analytics maturity curve perspective, repeatability is one of the desired states and the non-determinstic nature of AI can be counter productive when applied to BI. I don't think the old school will ever go, but I think BI and AI will end up complimenting each other well.