If you’re running freight, warehouse, or transportation operations and need to choose an AI in logistics vendor in the next quarter, this is for you. If you’re piloting in 30–90 days… you’re likely juggling partial data, shifting priorities, and urgent stakeholder questions; when pilots stall, it looks like work, not failure.

Decision criteria

1) integration depth

What it means in real ops: The tool connects to your TMS/WMS/ERP, EDI/API feeds, email inboxes, and document stores in a way that supports live workflows, not just exports. You can map fields, preserve IDs, and write back status updates without manual rekeying.

How it fails: It “integrates” via periodic CSV dumps and can’t update the system of record reliably.

2) exception handling

What it means in real ops: The tool identifies when something is off (rate mismatch, missing appointment, invalid NMFC, conflicting accessorials) and routes it to the right queue with context and recommended actions. It supports human-in-the-loop steps with clear handoffs.

How it fails: It only works on happy-path automation and punts exceptions to an unstructured inbox.

3) auditability

What it means in real ops: Every decision, edit, and automation has an evidence trail: source inputs, timestamps, user/role, and before/after values. You can answer “why did we do that?” for a chargeback, claim, or customer dispute.

How it fails: You can’t reconstruct decisions after the fact, or the vendor claims logs exist but can’t show them per transaction.

4) controls

What it means in real ops: You can set role-based approvals, thresholds (e.g., accessorial dollar limits), and segregation of duties so that high-risk actions require review. Controls are configurable without breaking the workflow.

How it fails: Anyone can override anything, or controls are so rigid they force workarounds.

5) ownership

What it means in real ops: There is a named operational owner on your side and a named accountable owner on the vendor side for configuration, exceptions, and continuous improvement. Ownership includes escalation paths and a cadence for changes.

How it fails: The project lives with “IT will handle it,” and no one owns outcomes when the first edge case hits.

6) data lineage

What it means in real ops: You can trace any field used in a decision back to its source (EDI 214, carrier email, POD image, WMS event) and see transformations applied. This prevents silent data drift.

How it fails: Outputs appear “correct” until you discover fields were inferred from stale or unrelated sources.

7) SLA support and escalation paths

What it means in real ops: The vendor commits to response times for incidents, provides severity definitions, and supports after-hours escalation if your operation runs nights/weekends. You know who picks up when a tender flow stops.

How it fails: Support is ticket-only with vague turnaround, and critical issues wait for business hours.

8) role-based approvals

What it means in real ops: Approvals match your org structure: dispatch, customer service, billing, claims, and management have distinct permissions. You can require dual approval for high-dollar adjustments.

How it fails: The only options are “admin” vs “user,” which forces shared logins or unsafe permissions.

9) evidence capture

What it means in real ops: The tool attaches the right artifacts (emails, rate confirmations, BOLs, PODs, accessorial proofs, appointment confirmations) to the transaction record. Evidence is searchable by shipment, invoice, and carrier.

How it fails: Evidence sits in separate places, so disputes still require manual hunting.

10) operational resilience

What it means in real ops: When data is late, systems are down, or a carrier sends nonstandard docs, the workflow degrades gracefully and keeps the operation moving with safe fallbacks. You can run in “assist mode” without losing traceability.

How it fails: A single missing field breaks the automation and creates a backlog you can’t unwind.

What to ask vendors

Security & compliance

1) Where is shipment and customer data stored, and what data is used for model training by default?

2) Show me how you segregate our data from other customers and how you handle deletion requests.

3) What happens when a user downloads documents or exports data; where is that action logged?

4) Who at your company can access our environment, under what approval process, and how is that access recorded?

5) Describe your incident response process: who notifies us, in what timeframe, and what evidence do we receive after closure?

Workflow ownership & change management

1) Who can change business rules (approval thresholds, routing logic, tolerances), and how are changes reviewed and approved?

2) Show me a rollback process: if a configuration change causes bad tenders, how do we revert in minutes, not days?

3) What is the workflow for adding a new customer SOP or carrier-specific rule, and what artifacts do you require?

4) Where do we see version history of rules and prompts, including who changed what and when?

5) When we add a new integration field, what breaks, and how do you test it before production?

Exception handling

1) Walk me through what happens when required data is missing: where is it flagged, who is notified, and what is the default safe action?

2) Show me how the system prioritizes exceptions by service risk (missed appointment, customs hold, short ship) versus administrative risk.

3) Who can override an automated decision, and what justification is required before the override is accepted?

4) What happens when two sources conflict (EDI status vs carrier email); which one wins and how is that decision recorded?

5) If the system can’t classify an accessorial, where does it route the item and what context is attached?

6) How do you prevent the same exception from bouncing between teams (billing vs operations), and where is ownership visible?

Reporting & audit logs

1) Show me where every automated action is logged per shipment, including inputs used, confidence/score if applicable, and before/after values.

2) Can we export audit logs for a date range and filter by user, carrier, customer, exception type, and action taken?

3) How do you track “touches” per shipment and distinguish human work from automated work?

4) Show me a dispute workflow: where is evidence attached, who approved the decision, and how long each step took.

5) What reports are available out of the box for backlog aging, exception categories, and SLA adherence, and what requires customization?

Demo script (text-only)

Run these 10 scenarios live

1) missing info: a tender arrives without commodity or weight; show the system’s default action, routing, and how it requests the missing fields.

2) conflicting docs: the rate confirmation shows fuel included, but the carrier invoice adds fuel; show detection, evidence capture, and resolution path.

3) after-hours quote: a spot quote request hits at 7:30 pm; show how it is handled, what is auto-sent, and what requires approval.

4) accessorial approval: a carrier requests detention; show required proof, threshold rules, who approves, and how the decision is logged.

5) tender rejection recovery: a carrier rejects a tender; show how alternates are selected, how service risk is flagged, and how customer comms are triggered.

6) duplicate shipment creation: the same order is keyed twice; show how duplicates are detected and how the correct record is preserved in the system of record.

7) appointment reschedule: the consignee moves the appointment; show how the change updates status, notifies stakeholders, and avoids missed delivery.

8) POD late: delivery is marked complete but POD is missing after an adjustable window; show escalation, collection workflow, and evidence attachment.

9) carrier no-show: a pickup is missed; show how the exception is created, how recovery actions are proposed, and how dwell risk is tracked.

10) invoice dispute evidence: an invoice includes an unexpected accessorial; show end-to-end dispute creation, evidence compilation, and approval trail.

Red flags (AI-washing)

• vague answers
• no audit trail
• “works best with perfect data”
• can’t name an owner
• black box decisions
• can’t run scenarios live
• no rollback
• no role-based controls
• exception queues are just email forwarding
• requires you to change your process to match their demo
• claims automation but only generates suggestions with no write-back
• can’t show per-shipment evidence capture for disputes

Simple scoring rubric

Use a 1–5 score for each decision criterion above.

1 means: Not proven in a live operations context; relies on manual steps, tribal knowledge, or future roadmap.

3 means: Works for standard lanes and customers with documented limitations; exceptions are manageable but still create measurable rework.

5 means: Works end-to-end with your systems of record; exceptions are routed with context; audit logs, controls, and ownership are demonstrably strong.

Instruction: Score each criterion, then total the points to compare vendors side by side.

Weighting guidance: If your current pain is chargebacks and disputes, consider giving extra weight to auditability and evidence capture; if your pain is service misses, consider weighting exception handling and operational resilience. Adjust weights to match your cost-to-serve and service priorities rather than copying someone else’s rubric.

If a vendor can’t pass scenarios, they’ll fail in week 2. Book Demo To Know More