AI Output Approval Workflow for Spreadsheets: Template + Macro to Capture Sign-Offs

Stop fixing AI outputs by hand: governed approval for spreadsheet results

AI-generated tables and formula outputs can save hours — until a reviewer finds errors and the whole team spends a day cleaning up. If your spreadsheets include machine-generated values, you need a repeatable, auditable sign-off flow that prevents accidental edits, records who reviewed what, and only releases ranges when a human confirms accuracy. Below I share a ready-to-use template, VBA macros and a Power Query recipe to build an AI Output Approval Workflow inside Excel (tested 2025–2026), designed for UK small businesses and operations teams.

Why this matters in 2026 — trends driving governed spreadsheet outputs

Late 2025 and early 2026 sharpened two realities: organisations are using AI for tactical execution at scale, and regulators and auditors demand traceability. Teams report using AI for high-volume data tasks but still hesitate to trust it for strategic decisions. That means most spreadsheet AI workflows will remain machine-assisted — and therefore must be governed.

• Regulatory pressure: guidance and audits increasingly expect record-keeping for automated decisions and data provenance.
• Risk of drift: AI models change, prompts change — without versioned approvals you risk undetected errors.
• Productivity paradox: AI saves time until manual clean-ups eat the gains. An approval layer preserves net benefit.

What this workflow delivers

The pattern below is deliberately practical for Excel users and small teams:

1. Tag AI-populated ranges when an AI tool writes to the workbook.
2. Log each write to a SignOff sheet (timestamp, model, prompt, author, range address).
3. Automatically lock those ranges so they cannot be edited until a reviewer signs off.
4. Provide reviewer actions (Approve / Request Changes) with timestamped audit trail.
5. Feed approvals into a Power Query dashboard for oversight and reports.

High-level architecture (one workbook)

• Main sheets where data lives (e.g., Forecasts, InvoiceExtracts)
• SignOff sheet: an audit table with one row per AI write
• VBA module: Tagging, Locking, Reviewer UI, Export
• Power Query: queries the SignOff table and builds an approval dashboard

Step-by-step implementation

1) Create the SignOff sheet

Create a sheet named SignOff and make it a Table (Insert > Table). Include columns:

• EntryID (unique)
• SheetName
• RangeAddress
• ModelName
• PromptOrDetails
• Author
• AIWriteTimestamp
• Status (Pending / Approved / Changes Requested)
• Reviewer
• ReviewTimestamp
• Notes

2) Tag AI-populated ranges when the AI writes

Whenever your automation writes a block of values, run a macro that:

• Adds an entry to SignOff
• Sets a named range or cell-level comment so the range is visible
• Locks the range and protects the worksheet

Sample VBA macro to tag and lock a range (adapt as needed):

Sub TagAIOutput(sheetName As String, rangeAddress As String, modelName As String, promptText As String, authorName As String)
    Dim ws As Worksheet, so As ListObject
    Dim newRow As ListRow
    Dim entryID As String
    Dim r As Range
    Dim passwd As String

    ' WARNING: don't hardcode sensitive passwords in production
    passwd = "YourSheetPassword"  ' consider storing securely

    Set ws = ThisWorkbook.Worksheets(sheetName)
    Set r = ws.Range(rangeAddress)

    ' Visual tag: cell interior and comment
    r.Interior.Color = RGB(255, 242, 204)  ' pale yellow to mark AI output
    On Error Resume Next
    r.ClearComments
    On Error GoTo 0
    r.AddComment "AI-generated: " & modelName
    r.Comment.Visible = False

    ' Create a stable EntryID
    entryID = Format(Now, "yyyymmddhhmmss") & "-" & Right(WorksheetFunction.Dec2Hex(Int(Rnd() * 16777215)), 6)

    ' Add row to SignOff table
    Set so = ThisWorkbook.Worksheets("SignOff").ListObjects(1)
    Set newRow = so.ListRows.Add
    With newRow.Range
      .Cells(1, so.ListColumns("EntryID").Index).Value = entryID
      .Cells(1, so.ListColumns("SheetName").Index).Value = sheetName
      .Cells(1, so.ListColumns("RangeAddress").Index).Value = rangeAddress
      .Cells(1, so.ListColumns("ModelName").Index).Value = modelName
      .Cells(1, so.ListColumns("PromptOrDetails").Index).Value = promptText
      .Cells(1, so.ListColumns("Author").Index).Value = authorName
      .Cells(1, so.ListColumns("AIWriteTimestamp").Index).Value = Now
      .Cells(1, so.ListColumns("Status").Index).Value = "Pending"
    End With

    ' Lock the range and protect sheet
    r.Locked = True
    ws.Protect Password:=passwd, UserInterfaceOnly:=True

    MsgBox "AI output tagged and locked: " & entryID, vbInformation
  End Sub

3) Reviewer actions: Approve or Request Changes

Provide a simple macro or userform for reviewers to select an EntryID and set status. On approval the macro writes reviewer and timestamp and (optionally) changes the lock state:

Sub ReviewerAction(entryID As String, reviewerName As String, action As String, Optional allowEdits As Boolean = False)
    Dim so As ListObject, lr As ListRow, found As Range
    Dim passwd As String
    passwd = "YourSheetPassword"  ' don't hardcode in production

    Set so = ThisWorkbook.Worksheets("SignOff").ListObjects(1)
    Set found = so.DataBodyRange.Columns(so.ListColumns("EntryID").Index).Find(entryID, LookIn:=xlValues)
    If found Is Nothing Then
      MsgBox "Entry not found: " & entryID, vbExclamation
      Exit Sub
    End If

    Set lr = so.ListRows(found.Row - so.HeaderRowRange.Row)

    lr.Range.Cells(1, so.ListColumns("Status").Index).Value = action
    lr.Range.Cells(1, so.ListColumns("Reviewer").Index).Value = reviewerName
    lr.Range.Cells(1, so.ListColumns("ReviewTimestamp").Index).Value = Now

    ' Unlock if reviewer allows edits
    Dim sheetName As String, rngAddr As String
    sheetName = lr.Range.Cells(1, so.ListColumns("SheetName").Index).Value
    rngAddr = lr.Range.Cells(1, so.ListColumns("RangeAddress").Index).Value

    Dim ws As Worksheet, r As Range
    Set ws = ThisWorkbook.Worksheets(sheetName)
    Set r = ws.Range(rngAddr)

    ws.Unprotect Password:=passwd
    If action = "Approved" Then
      If allowEdits Then
        r.Locked = False
      Else
        r.Locked = True  ' keep locked as final
      End If
    ElseIf action = "Changes Requested" Then
      r.Locked = False  ' allow authors to update
    End If
    ws.Protect Password:=passwd, UserInterfaceOnly:=True

    MsgBox "Review recorded: " & action & " by " & reviewerName, vbInformation
  End Sub

Notes:

• Use UserInterfaceOnly:=True to allow macros to modify the sheet while still protecting users.
• Avoid hardcoding passwords in production. Use secure storage (OneDrive encrypted files, Azure Key Vault, or Microsoft Purview) for passwords where possible.
• Locking in Excel is a deterrent, not a security boundary. Combine workbook protection with file-level encryption and SharePoint permissions.

4) Power Query: dashboard from SignOff

Power Query makes the audit trail usable. Load the SignOff table to Power Query (Data > From Table/Range) and create queries for monitoring:

1. Filter recent entries (last 30 / 90 days).
2. Group by ModelName to see volume per model.
3. Calculate average time-to-approve: ReviewTimestamp - AIWriteTimestamp.

Minimal M code to compute time-to-approve (assuming columns are typed):

let
    Source = Excel.CurrentWorkbook(){[Name="SignOff"]}[Content],
    ChangedTypes = Table.TransformColumnTypes(Source,{{"AIWriteTimestamp", type datetime}, {"ReviewTimestamp", type datetime}}),
    WithDuration = Table.AddColumn(ChangedTypes, "TimeToApproveHours", each if [ReviewTimestamp] <> null then Duration.TotalHours([ReviewTimestamp] - [AIWriteTimestamp]) else null)
  in
    WithDuration

Operational checklist before you deploy

• Set up SignOff table and protect the sheet with a strong password held by the governance owner.
• Decide whether approved ranges remain locked (final record) or are unlocked for further edits.
• Train authors and reviewers on the process: how to tag outputs and how to sign off. Consider pairing training with a zero-trust approvals policy for sensitive outputs.
• Integrate with your version control (OneDrive/SharePoint) — keep version history enabled.
• Export the SignOff table weekly to a secure CSV for off-sheet archives, retention and compliance. Keep separate audit logs outside the workbook for immutability.

Security, audit and data protection considerations

Excel protections are useful but limited. Treat the workbook as one control among several:

• Access control: store on SharePoint/OneDrive with strict permissions; use conditional access and MFA. See guidance on data residency and storage when you cross borders.
• Encryption: use file encryption (built into Office) and avoid storing PII in SignOff; if necessary, pseudonymise reviewer names.
• Audit logs: keep a copy of SignOff outside the workbook (secure CSV or database) for immutability and long-term retention — this ties into broader edge auditability patterns.
• Model metadata: store which model and prompt were used; this helps with explainability requests and regulatory queries.
• Privacy law: follow UK data protection practice — only record necessary personal data and document lawful basis for processing reviewer data. For consent and operational impact, see consent playbooks.

Advanced strategies and automation patterns

1) Auto-tagging for API-driven AI writes

If your AI writes via an API or Power Automate, call the TagAIOutput macro after the payload is written, or use the Office Scripts API to add the tag. Make sure the integration passes the prompt text and model name to preserve provenance.

2) Centralised approvals via SharePoint list

For multi-user environments, write the SignOff records to a SharePoint list using Power Automate. Centralised lists are easier to audit and harder to tamper with than workbook-only tables.

3) Immutable logs for high risk outputs

For high-risk decisions consider writing a hash of the AI output and metadata to an external immutable store (e.g., appending to a secure append-only log or ledger). This supports forensic audit requests.

Common pitfalls and how to avoid them

• Hardcoded passwords: Don't. Use secure store or restrict workbook to a governance account.
• No reviewer training: Approvals fail if reviewers don't know what to check. Define simple acceptance criteria for each output type.
• Too many manual steps: Automate tagging from the AI process to keep it frictionless and adopted. A tool-sprawl audit can help you consolidate automation points.
• Relying on sheet protection alone: Combine with file-level controls and external audit copies.

Example: a small finance team case study (experience)

Context: a 15-person finance team used an LLM to extract invoice line items into a ledger. They initially saw productivity gains but were hit by occasional mis-categorisations that caused reconciliation errors.

Solution: they deployed the SignOff workbook, used an API integration to call TagAIOutput automatically after extraction, and required senior accountant approval for any batch above £1,000. Within 6 weeks:

• Time spent cleaning AI errors fell by 70%.
• Approval lead time averaged 4 hours (down from 24+).
• Auditors accepted the SignOff trail as sufficient evidence of human oversight.

Sample governance policy snippet you can copy

All AI-populated spreadsheet outputs must be tagged, logged to the SignOff table and locked. A named reviewer must approve the output before it is used for reporting. Approved outputs are retained as final records in the SignOff archive for a minimum of 6 years or as required by local retention policy.

Next steps: get the template and test it in your environment

Use the following checklist to run a pilot in one workbook:

1. Create the SignOff table and protect the sheet.
2. Paste the VBA snippets into a standard module, update the password practice, and wire your AI-write process to call TagAIOutput.
3. Build the Power Query dashboard to monitor pending approvals and overdue reviews.
4. Run a two-week pilot, measure time-to-approve, and iterate prompts or acceptance criteria.

Final thoughts — governance keeps AI gains

In 2026, organisations that combine automation with simple, enforced human checks capture the benefits of AI without creating a mess for operations. The pattern above is intentionally lightweight: it focuses on clear tagging, a visible audit trail, and controlled unlocking. That combination preserves productivity while meeting the audit and data-protection expectations teams now face.

Call to action

Ready to try a proven template? Download our free AI Output Approval workbook, complete with SignOff sheet, VBA examples and a Power Query dashboard. Or book a 30-minute setup session and we'll install the workflow into your SharePoint-hosted workbook and show your team how reviewers and authors should work together. Click below to get started.

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