The traditional audit pyramid is well known. Junior auditors collected evidence, followed up with clients, mapped documents to controls, selected samples, tested repetitive controls, updated workpapers, and documented results. Senior auditors reviewed that work. Partners made the difficult calls.
The future of audit isn't replacing auditors with AI. It's removing the work that prevents auditors from being great auditors. At Skadi, we think the end state looks very different: auditors become super agents — with AI handling the repetitive work around them: evidence collection, document analysis, control mapping, testing, cross-referencing, anomaly detection, and drafting workpapers. The auditor moves from doing the audit to understanding, challenging, and deciding.
From manual auditor to super agent
We see five levels on the way there. Most firms today sit at Level 0 or Level 1 — and each level decides what kind of auditor your company gets. Here is the ladder from our side: what we build to move an auditor up it, and what the auditor gains at every step.
The auditor does everything by hand
Request evidence, download files, open screenshots, check dates, select samples, compare policies, update spreadsheets, write notes — repeat. Most of the auditor's day goes into proving that something happened rather than understanding whether it matters.
What this gives the auditor
Nothing gained yet. The scarcest thing on the engagement is the auditor's judgment, and it's being spent on paperwork.
The auditor gets faster hands
The auditor starts using general-purpose AI tools. Summarize this policy, explain this evidence, draft this request, rewrite this finding. The writing gets faster; the workflow is untouched.
What this gives the auditor
A few hours back on drafting. What they still decide alone, and still go and fetch themselves, is everything that actually matters.
The auditor gets a copilot
AI moves inside the audit platform. It suggests control mappings, summarizes evidence, drafts testing language, and flags missing documents. Useful — but the auditor still drives every step.
What this gives the auditor
No more blank pages, and nothing obvious slips through. Coverage improves because the system remembers what hasn't been tested yet.
The auditor gets a team that never sleeps
Agents begin doing the work. They request and ingest evidence, understand what's inside it, map it to controls, run routine testing, surface inconsistencies, and assemble the audit trail. The auditor supervises the system instead of clicking through every artifact.
What this gives the auditor
This is the jump in capability. One auditor now carries the volume that used to need a team of juniors — and spends the freed hours on the questions only experience can answer.
The auditor never loses context
The audit runs continuously in the background. Evidence arrives, agents analyze it, controls are tested, exceptions are surfaced, and context keeps accumulating. The human auditor sits where humans are most valuable: judgment.
What this gives the auditor
They arrive at every conversation already knowing the company — its controls, its changes, its weak spots. That's the difference between issuing a report and giving advice.
The auditor becomes the most important part
This may sound counterintuitive. If AI does more audit work, shouldn't auditors become less important? We think the opposite happens.
Today, an experienced auditor can spend an enormous amount of time reviewing screenshots, chasing evidence, checking samples, and documenting work that someone with far less experience could theoretically perform. Remove that layer and you don't eliminate the auditor. You amplify them.
A great auditor can finally spend their time understanding the company. Why was this control designed this way? Does it actually address the risk? Is management overlooking something? Is the evidence technically sufficient but telling us something concerning about the business? What should this company change before that weakness becomes an incident?
That's the auditor we want to build for. Not a human checkbox machine — a super agent with years of experience, complete context about the company, and AI working underneath them.
Audit should create value, not just prove compliance
SOC 2 is our starting point at Skadi. But the bigger idea is assurance.
Companies shouldn't spend months preparing for an audit only to receive a report saying they passed. If we're already analyzing their systems, controls, policies, infrastructure, evidence, and risks, we should be able to tell them something useful about their business. What is weak? What is changing? What doesn't make sense? Where is the real risk? What should leadership pay attention to next?
That's where assurance becomes interesting again. AI doesn't have to replace the auditor. It can finally give the auditor the time, context, and leverage to do the part of the job that actually requires an auditor.
The future of audit isn't fewer auditors. It's auditors with superpowers. We call them super agents.
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