Same challenge, different context: Why incident response and eDiscovery need automation
Authored by Lynita Hinsch
Originally published in the January 2026 issue of Magnet Unlocked. Want to be the first to see new content? Sign up for our monthly newsletter, Magnet Unlocked.
Lately, I’ve been hearing a recurring theme: the volume of both data and investigations are straining teams in ways remote collection previously did.
What’s interesting is that I’m hearing this equally from incident response teams and eDiscovery groups. Two functions with very different goals, but who are facing what is, effectively, the same storm and the same fatigue.
That’s because the volume is accelerating faster than the headcount ever could.
In these conversations, I keep coming back to the same point: Automation isn’t a luxury anymore; it’s the only sustainable option.
What strikes me most is how often I hear two groups describe the same problem in different languages:
- “We’re overwhelmed because we have ten incidents queued and no time or not enough resources to analyze all the data .”
- “We’re overwhelmed because we have ten collections to manage, with different custodians, date ranges, and issues than our current resources can handle.”
Same pressure. Same bottleneck. And increasingly, the same solution.
How incident response approaches an investigation
On the incident response side, the goal is simple: find the single artifact that explains the intrusion path attack.
In a business email compromise investigation, that usually starts with a narrow aperture, the compromised mailbox. From there, the workflow kicks in pulling tenant logs, reviewing authentication patterns, correlating IPs and MFA events, checking for forwarding rules and OAuth consents, and assembling a coherent timeline that shows the attacker’s movements.
It’s predictable work, but it’s also repetitive, and the data volume continues to grow.
Considerations for eDiscovery
Meanwhile, eDiscovery teams are echoing the urgency but from a different vantage point.
Their fear isn’t about missing the intrusion vector; it’s failing to collect defensibly. When a user goes on legal hold, or an organization prepares for litigation, the mandate is strict, collect everything you’re supposed to, preserve it correctly, hash it, log it, and demonstrate repeatable handling.
Teams describe the strain of juggling departing employees, onboarding, holds, and ad‑hoc requests all while ensuring every collection is defensible months or years down the line.
How automation can help for both functions
When I talk about automation, I don’t mean it as a buzzword. I mean automation in the practical, unglamorous sense:
- Reducing the manual “glue” between steps
- Eliminating repeatable handoffs
- Letting systems execute the workflows we’ve already memorized
In incident response, that means allowing a single examiner to queue multiple multi-source acquisitions, push them through standardized processing like generating timelines automatically, applying known bad indicators, flag suspicious rules or authentications, processing in other tools, and out putting results and reports to a consistent structure, with hashes, metadata, and provenance intact. The examiner still does the reasoning; the platform orchestrates the output.
In eDiscovery, it’s the same philosophy. Automate the departing employee workflow, the legal hold refresh, the collection packet creation, the hashing, the audit log generation, the standardized storage and naming, and the notifications to legal or HR. When you can queue it once and trust that it runs the same way every time, you reduce both the risk and the mental load while staying compliant.
How automation can help law enforcement labs too
Law enforcement labs are seeing similar issues, skyrocketing caseloads and exploding data volumes have outgrown the manual workflows they were built on.
Even though the core forensic process hasn’t changed: acquire, process, analyze, report. The scale now creates backlogs and burnout that delay urgent, victim centric investigations.
Just like the private sector, practical automation has become essential, handling repeatable steps like processing, reporting, and standardized logging so examiners can focus on analysis instead of administration.
The role of AI
There’s another layer emerging, one that customers are starting to voice with a mix of curiosity and anxiety: What happens when AI becomes part of the evidence trail?
If AI tools draft summaries, transform logs, or touch data before we examine it, that creates metadata, lineage questions, and governance implications that incident response and eDiscovery will both have to answer. We’re not debating “whether” to use AI anymore, it’s already happening. And automation with strong provenance tracking becomes the best defense.
Automation is helping give time back
So, the pattern keeps repeating, different missions, different anxieties, but the same operational squeeze. And behind them, a single practical truth.
Automation is becoming a main player in DFIR across the spectrum.