I have attended the imaginary funerals for practically everything we do. Technologies change … Terminology changes … Acronyms multiply … Consultants (like moi!) discover new words for old ideas, and suddenly something we have relied on for decades is declared dead. Give it six months, and somebody will bring it back with a new name, a new acronym, and probably a higher price tag. It’s all in the data.
Three of my favorite premature burials are data management, business intelligence, and data governance. All three have been pronounced dead, obsolete, outdated, irrelevant, or replaced at various points during my career. Yet somehow the bodies keep disappearing from the morgue.
In fact, these three old friends are not merely alive. Data management, business intelligence, and data governance are hotter than hell right now. And we have AI – perhaps the hottest kid on the block – to thank for reminding everybody why we needed them in the first place.
Data Management Is Not Dead
Data management has been around since my earliest days in the industry. We talked about databases, data administration (I was a data administrator), data architecture, data modeling, data warehousing, master data, metadata, data quality, and eventually – with the encouragement and assistance of DAMA International – gathered a lot of those disciplines under the broader data management umbrella. None of that was particularly sexy, but it kept the lights on and the numbers reasonably believable.
Then came big data, the cloud, data lakes, lakehouses, data mesh, data fabric, data products, and everything else that promised to change the way we manage data forever. And plenty did change. We built bigger environments, moved them somewhere we could not physically see them, distributed responsibility, and created enough new terminology to keep conference organizers employed indefinitely.
Then AI showed up and asked a wonderfully inconvenient question: “Where is the good data?” Oops.
AI does not eliminate the need to manage data; it magnifies the consequences of managing data poorly. Feed questionable, poorly understood, badly integrated, or context-starved data into increasingly powerful AI, and you do not magically create intelligence. You may simply create much faster and more confident nonsense.
Data management did not die. AI put it on steroids … and handed it a protein shake.
Business Intelligence Is Not Dead
Business intelligence has supposedly been replaced so many times that BI should probably have its own “frequent-dier” program. Analytics was going to replace it, data science was going to replace it, machine learning was going to replace it, and generative AI was going to replace it. Now agentic AI may finally finish the job … except it probably will not.
The fundamental business need never disappeared. People still need to know what happened, why it happened, what is happening now, what might happen next, and what the heck they should do about it. Executives still want answers, managers still want insight, and people still want to know why their number does not match the number on the slide being presented across the table.
Call it business intelligence, analytics, decision intelligence, augmented analytics, conversational analytics, or whatever term becomes fashionable next. Organizations still need to transform data into information that helps people make better decisions. AI simply gives us new ways to ask questions, discover patterns, explain results, anticipate outcomes, and potentially act upon what we learn.
Business intelligence did not die. It learned some new tricks … and discovered that dashboards are not the only way humans can communicate with data.
Data Governance Is Definitely Not Dead
Then there is my personal favorite. Data governance has been declared dead because it became too bureaucratic, too slow, too centralized, too complicated, too focused on meetings, and too disconnected from the actual work of the organization. On some of those charges … most of us may admit … guilty as charged.
But that does not mean data governance is dead. It means bad data governance deserves to be.
If your governance program requires – and allow me to be sarcastic here – 12 committees, 17 approvals, 47 assigned data stewards, a 200-page policy manual nobody reads, and a monthly meeting where everybody spends the first 15 minutes asking why they are there, you may not have a governance problem. You may have a hostage situation.
Non-Invasive Data Governance® takes a different approach. People already define, produce, and use data. They already make decisions about data. Recognize that accountability rather than manufacturing artificial responsibility around it, and formalize governance as part of what people already do.
AI makes that more important, not less. Organizations are preparing to let AI consume their data, interpret their data, generate new data, recommend decisions, and increasingly take action through AI agents.
And we are going to do all of that without formalized accountability, trusted definitions, appropriate context, understood authority, and governed behavior?
What could possibly go wrong?
AI Just Turned Up the Heat
That may be the most entertaining irony of the AI revolution. The newest technology in the room is reminding us how desperately we need some of the oldest disciplines in the room.
- AI needs data management because somebody must make the data usable, understandable, accessible, integrated, and trustworthy.
- AI needs business intelligence because organizations still need to turn information into insight and insight into better decisions.
- AI needs data governance because somebody must be formally accountable for the definition, production, and usage of the data and data-related assets upon which those decisions and actions depend.
And now AI agents are raising the stakes even further. When technology moves from answering questions to recommending actions, taking actions, and eventually becoming increasingly self-directed, context, and accountability stop being nice governance concepts. They become prerequisites.
The funny thing is that we spent years trying to convince executives that these disciplines mattered. Now everybody wants AI … and AI just walked into the executive suite carrying a giant sign that says, “I need your data house in order.”
Thank you, AI. Some of us have been trying to tell them that for decades.
Stop Digging Graves
Perhaps we should become a little more careful about declaring things dead in the data industry. We seem to have a habit of holding the funeral, writing the obituary, burying the discipline, and then inviting it to keynote next year’s conference under a slightly different name.
Data management is not dead. Business intelligence is not dead. Data governance is definitely not dead. They have changed … they are changing … and they will continue to change … because data, technology, organizations, and people continue to change.
After decades in this industry, I find the current situation wonderfully ironic. Three disciplines that have been around for most or all of my career are sitting directly in the middle of the hottest technology conversation of my lifetime.
Data management. Business intelligence. Data governance.
Not dead … not even close. They are hotter than hell. And AI just turned up the thermostat. It’s all in the data.
Copyright © 2026 – Robert S. Seiner and KIK Consulting & Educational Services
Non-Invasive Data Governance® is a registered trademark of Seiner and KIK Consulting.
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