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psychology

AI Decision Co-pilot

When a reviewer opens an access review item, the AI co-pilot shows its suggested decision (Approve, Reject, or "needs more info") together with the reasoning. The reviewer can accept, modify or override - always in the driver's seat.

The challenge

Reviewers click "approve" because they have nothing else to do

98%

Approval rate in typical access reviews. Nobody really decides.

no context

Reviewer sees a user-role pair and that is it. No usage, no risk, no peers.

hours

Spent clicking through items, with the same default for each.

Reviewers approve everything because rejecting takes investigation time they don't have. The agent levels the playing field: it surfaces the same information for every item and proposes a defensible decision.

How the agent works

Human-in-the-loop, every step of the way

STEP 1
visibility

Observe

Agent reviews each open item before the reviewer opens it: usage signal, peer comparison, SoD context, recent role changes.

STEP 2
psychology

Evaluate

Forms a recommendation: Approve, Reject or "needs more info", with confidence score and rationale.

STEP 3
bolt

Act or escalate

Presents the recommendation to the reviewer alongside the raw facts. Reviewer accepts, modifies or asks for more.

STEP 4
verified

Human reviews

Final decision is reviewer's. Agent learns from disagreements and improves over campaigns.

check_circle Every agent decision is explainable, reviewable and reversible.
In the platform

Where it shows up in smartGRC

Access certification - reviewer queue
smartReview
JN
J. Nowak . Finance Controller
Reviewing access to: SAP_FI_POSTING + SAP_FI_APPROVE
psychology AI SUGGESTION confidence 0.76
Recommend: REVOKE one role

User holds both POSTING and APPROVE - a P2P SoD conflict (RISK-FI-04). User has posted in 30/90 days, but never approved her own postings (mitigated by manual control MC-021). Cleanest fix: remove SAP_FI_APPROVE since the user does not actually approve.

SoD conflict MC-021 applies No usage gap risk

Illustrative mockup from the smartReview certification flow. The AI SUGGESTION panel shows verdict + rationale next to Accept / Keep / Need more info.

psychology

Reasoning, not decisions

Reviewer always decides. Agent presents the case: history, conflicts, mitigating controls. Confidence score makes it clear when to dig deeper.

speed

Hours back per campaign

Reviewers handle 100+ items in the time it used to take for 20. Decisions are more consistent because everyone sees the same evidence.

play_circle

See decision copilot live

Open the interactive UX preview and explore the agent end-to-end.

Sample reasoning

How the agent thinks

Every decision is accompanied by readable reasoning so your team can audit and refine the agent's behavior over time.

SUGGEST: REJECT m.dabrowski / Z_HR_VIEWER
$ evaluate
user: michal.dabrowski · role: Z_HR_VIEWER
logins via role: 0 in 90 days
$ recommendation
✓ no usage since assignment 6 months ago
✓ no peers in same dept have this role
✓ no upcoming project requiring it
? user could re-request if needed
$ decision
SUGGEST: REJECT · confidence 0.87
SUGGEST: APPROVE a.kowalski / Z_BASIS_ADMIN
$ evaluate
user: arek.kowalski · role: Z_BASIS_ADMIN
logins via role: 47 last 30 days
$ recommendation
✓ heavy active usage
✓ matches job function (Basis admin)
✓ peer pattern: all 4 Basis admins have it
✓ no SoD violations
$ decision
SUGGEST: APPROVE · confidence 0.94
Expected impact

What this changes for your team

Estimates based on customer interviews and benchmarking from comparable agent deployments. Real numbers will vary.

5x
Decision speed

Reviewer can decide in seconds with full context vs minutes of investigation per item.

Better
Decision quality

Reject rate aligns with real usage data, not reviewer fatigue.

No "approve-all"
Decision integrity

Auditors see varied, defensible decisions, not 98% rubber-stamping.

Trained
Continuous improvement

Agent learns from human disagreements and improves between campaigns.

Related agents

Other agents in smartReview

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