You can't fix a problem you don't understand. Many organizations today misunderstand who's accountable for information accuracy, a situation that would have been unthinkable thirty years ago.
These myths persist because they're comforting. They let us believe someone else owns the problem, allowing Records and Information Management professionals to focus on technical tasks while accountability questions drift unanswered through the organization. But when a regulator asks "who verified this data?" or litigation demands "who stood behind this claim?", comfort won't help you.
Here's what's actually true.
Myth 1: The System Captures Accountability Automatically
Reality: Your EDRMS captures custody, not attestation.
When you implemented that electronic document management system in the late '90s or early 2000s, it recorded who uploaded a file, who declared it a record, and what classification it received. What it didn't record was who took responsibility for the content being accurate.
In the paper era, a signature on correspondence meant someone stood behind the information. That person was accountable for its accuracy and implications. Even when a secretary signed on behalf of an executive, accountability didn't shift, the named individual remained responsible.
Modern systems broke this chain. They track workflow and metadata but remain silent on attestation. You know who filed the document. You don't know who verified it was correct.
This isn't a software limitation. It's a design choice that Information Governance professionals accepted without building a replacement mechanism for accountability.
Myth 2: The Author Field Solves the Problem
Reality: "Author" in digital systems means creator, not guarantor.
Your system's author field typically identifies who drafted a document or who's listed in the file properties. It doesn't mean that person verified the information, approved it for distribution, or accepted responsibility for its accuracy.
Consider the hospital nursing station example: multiple nurses recorded patient vital signs on a single chart throughout the day. Each entry was made contemporaneously with the observation and signed by the nurse who recorded it. From a legal perspective, these records were accepted as exceptions to the hearsay rule precisely because accountability was explicit on every line.
Now picture the same information flowing through an electronic health record system, summarized by one clinician, updated by another, and potentially processed by AI for trend analysis. Who's accountable for the accuracy of the final output? The original observer? The summarizer? The system administrator? The algorithm's training team?
The author field can't answer that question because it was never designed to.
Myth 3: AI Makes Information More Accurate
Reality: AI increases the distance between observation and output, obscuring accountability further.
AI doesn't inherently introduce more errors than human processes. But it does add processing layers that make accountability harder to trace. When an AI system summarizes, transforms, classifies, or recombines information, each step moves the final output further from the original observation.
Ask yourself: if a regulator questions the accuracy of an AI-generated summary in your records, who in your organization is prepared to stand behind it? The business user who prompted the system? The IT team that deployed the model? The vendor who trained it? The original authors of the source documents?
Without explicit accountability frameworks, the answer is usually "no one." And that's a governance failure, not a technology problem.
Myth 4: Content Accuracy Isn't an IG Responsibility
Reality: If you design the framework, you own part of the outcome.
You don't control what information business units create. But you absolutely control the framework within which it's captured, managed, and reused. You write the procedures governing record declaration. You design the Business Classification Scheme. You set retention rules and disposition authorities.
If those procedures don't include checkpoints for accuracy validation, you've built a system that can't answer basic accountability questions.
Look at the paper-world examples that worked: documented procedures governed how correspondence was prepared and sent. Formal processes dictated how patient information was recorded and by whom. The reliability of those records was a direct outcome of those procedures.
When accountability for accuracy is no longer determined by a signature, what remains are the rules, structures, and systems that determine how information enters your organization and whether it can be trusted. That's Information Governance territory.
Myth 5: Someone Else Will Figure It Out
Reality: No one else is positioned to solve this.
Business units create content but don't think in terms of recordkeeping frameworks. IT deploys systems but doesn't set governance policy. Legal intervenes during disputes but can't redesign your everyday processes.
Information Governance professionals are the only ones with both the mandate and the skill set to address accountability systematically. You understand the lifecycle. You know where records enter the system, where they're transformed, and where they're relied upon for decisions. You can identify the points where accountability needs to be explicit.
If you don't claim this responsibility, it remains unclaimed. And when the organization faces an audit or litigation and someone asks "who was responsible for verifying this information was accurate?", the silence will be deafening.
What to Do Instead
Build accountability into your procedures at specific lifecycle points:
At capture: Require attestation for records that will be relied upon for compliance, legal, or operational decisions. This doesn't mean every email needs a signature, but critical records should have a named individual accepting responsibility for accuracy.
At transformation: When information is summarized, classified, or processed by AI, document who reviewed the output and accepted it as accurate. Make this a required step in your workflow, not an optional one.
At disposition: Before records are destroyed under a Records Disposition Authority, verify that accuracy requirements were met during the retention period. If accountability was never established, that's a red flag for your audit trail.
In your Records Control Schedule: Add a metadata field for "accuracy attestation" where appropriate. Not every record type needs it, but those supporting financial reporting, regulatory compliance, or legal claims certainly do.
You won't ever guarantee that information is true. But you can ensure that someone, somewhere in your organization, is prepared to stand behind it. That's the difference between a recordkeeping system and a reliable one.
