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Choose an incident-response tabletop platform for AI workflows by testing five things in a live demonstration: whether it can represent your AI system and dependencies, bring the right technical and business roles into one decision process, let a facilitator change injects as events unfold, produce an owned after-action record, and protect the sensitive plans you provide. A polished scenario library is not proof of security or effectiveness.
AI exercises must go beyond model containment. They should test information sharing, escalation, legal and communications decisions, third-party coordination, and recovery of the business process that depends on the model. Use the same realistic scenario with every supplier, compare the results with your incident-response plan, and verify data handling and contract terms before uploading confidential material.
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What an AI incident-response tabletop platform is supposed to do
NIST defines a tabletop exercise as: “A discussion-based exercise where personnel with roles and responsibilities in a particular IT plan meet in a classroom setting or in breakout groups to validate the content of the plan by discussing their roles during an emergency and their responses to a particular emergency situation. A facilitator initiates the discussion by presenting a scenario and asking questions based on the scenario.” The platform is therefore a means to structure discussion and capture decisions, not a substitute for an incident-response plan or a technical test.
For an AI workflow, the discussion must include more than a model endpoint. Map the complete service that creates business value: the model or model provider, prompts and retrieval data, vector stores, plug-ins and tools, cloud identities, orchestration code, monitoring, human reviewers, downstream systems, and outside suppliers. Then ask what happens when one part is compromised, unavailable, manipulated, or legally restricted.
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How an AI incident differs from a conventional IT scenario
- Data can be both input and evidence. A prompt, training set, retrieval index, or conversation log may contain personal, confidential, or regulated information. Participants need to decide what can be preserved, shared, redacted, or deleted.
- Behavior may change without a conventional breach. Prompt injection, poisoned retrieval content, unsafe tool instructions, model drift, or a malicious fine-tune can produce harmful output even when perimeter controls appear normal.
- Dependencies are distributed. A hosted model, identity provider, cloud storage service, plug-in, or outsourced operations team may control a crucial part of containment and recovery.
- Impact is operational and reputational. The immediate question may be whether to disable an assistant that supports customer service, coding, fraud review, or clinical administration, and how to keep the business operating while it is offline.
- Evidence is difficult to interpret. Teams may need model versions, prompts, tool-call logs, retrieval documents, configuration changes, and human approvals to determine what happened.
A useful platform lets the facilitator expose these dependencies and lets each participant see the information appropriate to their role. A game that simply displays a generic ransomware narrative will not validate an AI operating model.
Set the exercise outcome before comparing products
Write a one-page exercise brief before speaking to vendors. State the AI-enabled business workflow, the systems and suppliers involved, the people who can authorize action, the information that cannot leave your environment, and the decisions you want to test. This prevents a supplier from steering the conversation toward features that do not matter to your plan.
Use CISA’s AI exercise objectives as a baseline
The Cybersecurity and Infrastructure Security Agency’s Joint Cyber Defense Collaborative (JCDC) AI Cyber Tabletop Exercise materials provide a useful public baseline. The 2024 exercise focused on significant incidents that jeopardize AI systems or systems enabled or created by them. Its four stated objectives were to examine information-sharing opportunities, response procedures for multistage incidents, gaps in existing plans, and operational collaboration around AI-enabled systems. Lessons were intended to inform an AI Security Incident Collaboration Playbook. These are exercise objectives, not measurements of a product’s effectiveness.
Translate those objectives into observable outcomes for your organization:
- Participants can identify who receives the first report, who validates it, and who may declare an incident.
- The group can exchange technical, business, legal, and communications information without exposing data to people who do not need it.
- The plan covers a sequence of related events, such as an initial prompt-injection report followed by credential misuse, data exposure, and a supplier outage.
- Every unresolved gap has an owner, a due date, and a way to verify completion.
Map the AI workflow that the scenario must represent
| Workflow element | Questions the platform should let you test |
|---|---|
| Model and version | Can the exercise identify which model, configuration, fine-tune, or safety policy is affected? Can the team roll back or disable it? |
| Prompts, retrieval and training data | Can participants discuss provenance, exposure, poisoning, retention, and evidence preservation without putting the actual data into the platform? |
| Tools and connected services | Can injects show a tool call, API token, plug-in, cloud identity, or downstream application being abused? |
| Human controls | Can the exercise assign reviewers, approvers, investigators, communications staff, and business owners distinct responsibilities? |
| Suppliers and partners | Can the facilitator introduce a provider notification, service-level constraint, conflicting advice, or delayed evidence? |
| Business process | Can the team decide how to continue, degrade, or stop the AI-assisted process while preserving safety and customer trust? |
Evaluation criteria that matter in an AI workflow
1. Scenario and dependency coverage
Ask whether you can build a multistage incident around your actual workflow rather than selecting a generic label. The scenario editor should accommodate model and tool dependencies, data flows, operational consequences, and decisions that are not purely technical. Request an example in which the first symptom is ambiguous and later injects change the containment decision.
Check whether you can import or reference architecture diagrams without uploading sensitive originals, branch the scenario when participants choose different actions, and add a supplier or regulator response. A fixed script may be easy to run but will not reveal whether your plan works when events do not follow the expected path.
2. Cross-functional decision practice
AI incidents cross organizational boundaries. Include security operations, engineering or data science, the business owner, privacy or legal counsel, risk, communications, executive leadership, and relevant suppliers. The platform should support separate role instructions, private information, shared discussion, escalation, and a clear record of who made each decision.
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During a demonstration, ask a facilitator to deliver one fact only to engineering, another only to legal, and then require the group to reconcile the information. If every participant sees the same dashboard and can act as every role, you are testing discussion convenience rather than your real authority and handoff model.
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3. Facilitation and role design
A facilitator needs to pause, accelerate, skip, repeat, or replace an inject when the discussion takes an unexpected path. Look for a visible timeline, controlled release of information, participant status, notes, and a way to record a decision while preserving the context that led to it. Confirm that role-specific views do not prevent a participant from seeing information that the incident commander needs to make a safe decision.
Ask how the platform handles absent participants, late joiners, accessibility needs, time-zone differences, and a degraded connection. A technically impressive exercise can still fail if people cannot enter the room, understand the interface, or obtain the information required for their role.
4. After-action quality
Require more than a participation score. The final record should show the scenario timeline, decisions, assumptions, information requests, unresolved questions, plan gaps, action owners, due dates, and evidence of closure. Ask to see an actual web and PDF report, if both are advertised, and determine whether observations can be exported to the system where your organization tracks improvements.
Separate exercise performance from operational readiness. A team may reach a decision quickly because the facilitator supplied information that would not exist in a real incident. The report should preserve those assumptions so that leaders do not mistake a smooth exercise for proof that controls work.
5. Handling of sensitive inputs
Some services invite you to upload incident-response plans, playbooks, policies, network diagrams, or other internal material. Before doing so, establish where files and participant messages are processed and stored, which personnel or subprocessors can access them, whether they are used to train a model, how long they are retained, and how you can delete or export them. Determine whether backups, logs, and support tickets follow the same retention rules.
Ask for contractual language covering confidentiality, breach notification, data location, subprocessors, deletion, and return of data at termination. Verify any compliance, privilege, or work-product representation with your own counsel; a vendor’s label does not create a legal protection by itself. Use redacted or synthetic documents until the review is complete.
6. Fit with your operating model
Confirm participant licensing and access requirements, identity integration, exercise scheduling, deployment options, accessibility, audit logging, and support. A platform designed for one security team may not suit a company that runs exercises across several business units or includes external partners. Ask whether you can export scenarios and reports in a durable format if you change providers.
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Options identified for comparison
The following approaches are not ranked. The product descriptions are first-party claims, and no independent side-by-side test, audited security comparison, or comparative outcome data was established.
| Approach | What its published description says | What you must verify |
|---|---|---|
| TableTop Sim | Role-specific incident injects, facilitator controls, AI tailoring to a client environment, and web and PDF after-action reports. Advertised scenarios include ransomware, business email compromise, malicious insider, third-party compromise, cloud identity takeover, and data extortion. | Demonstrate the AI workflow you supplied, test role separation and branching, inspect a real report, and verify processing, storage, access, retention, deletion, export, and contract terms. |
| ORNA | AI cyber-crisis simulations, generated after-action review reports, and customization using uploaded incident-response plans, playbooks, policies, and network diagrams. Its page describes an integrated cloud platform. | Establish exactly how uploaded documents and generated content are protected and retained. The published description does not independently establish security controls or effectiveness. |
| Tabletop.ai | Live exercises with role-specific participation, control mapping, generated after-action reports, and scorecards. | The product page was not independently opened for this assessment, so treat these as lower-confidence, search-result claims and verify every capability directly. |
| Do-it-yourself with CISA materials | A no-cost starting point for organizations able to tailor and facilitate an exercise. CISA materials provide objectives, scenario material, and discussion questions. | The cited program page is sector-specific. Confirm that the package fits your organization, adapt it for your AI workflow, and provide your own collaboration, evidence capture, and action-tracking process. |
When a commercial platform is not necessary
A document, video meeting, shared notes, and a disciplined facilitator can run a valuable exercise. The trade-off is that your team must build role controls, inject timing, evidence capture, report generation, and action tracking. DIY is attractive when sensitive material cannot leave your environment or when you need to learn the plan before committing to a product. It becomes harder to operate consistently when many business units require repeatable exercises and comparable records.
Run the same vendor demonstration for every candidate
Do not evaluate products with a generic slideshow. Give each supplier the same short brief and require a live, unedited walkthrough. A fair brief can use a fictionalized version of your workflow so that no confidential architecture or customer data leaves your control.
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitches- Describe the service. State the business process, model role, connected tools, key data classes, suppliers, participants, and the impact of taking the AI function offline.
- Introduce a multistage incident. Begin with an ambiguous report, then add evidence of prompt injection or poisoned retrieval content, suspicious tool use, possible data exposure, and a supplier response. Tell the vendor that the branch depends on participant decisions.
- Test scenario adaptation. Ask the vendor to show how it represents the model, data, identity, tool, and business dependencies, and how it prevents the exercise from becoming a generic ransomware script.
- Test information sharing. Have the facilitator send role-specific facts, request an escalation, and show what is visible in the shared record. Confirm that private notes and privileged material are not automatically exposed.
- Test facilitator control. Change the order of injects, pause the clock, add an external partner, and follow a participant decision that was not in the original script.
- Inspect the output. Require the complete exercise record, not a marketing screenshot. Look for timestamps, decisions, owners, due dates, assumptions, evidence requests, and export formats.
- Interrogate data handling. Ask what the platform receives, where it is processed and stored, who can access it, whether it is used for model training, how it is deleted, and how you retrieve your records at termination.
- Compare against your plan. Record each answer beside the corresponding requirement, then have security, legal, procurement, and the business owner approve the unresolved risks.
Use the same observers and a written question set for each demonstration. Score an answer as “demonstrated,” “documented but not demonstrated,” or “not established,” rather than giving credit for an untested feature statement.
Design and run an AI-specific tabletop
Step 1: Set authority and boundaries
Name the incident commander, technical lead, business owner, legal or privacy adviser, communications lead, executive decision-maker, and supplier contacts. State who may disable the AI workflow, rotate credentials, notify customers, contact a provider, or approve a workaround. Mark which documents and data are synthetic for the exercise.
Step 2: Build a scenario with decision points
For example, an internal support assistant uses retrieval from a confidential knowledge base and can open tickets through an API. A reviewer notices that the assistant cites an unfamiliar document and proposes an unsafe action. Later injects reveal a compromised service account, a batch of exposed conversation logs, and a model provider that cannot immediately explain its telemetry. Participants must decide whether to disable retrieval, revoke the account, preserve evidence, notify affected parties, and continue support manually.
This example is useful because it requires technical containment, evidence preservation, privacy analysis, customer communications, supplier coordination, and business continuity. Replace the components with your own workflow; do not copy the example into a plan without validating its assumptions.
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- Give engineering telemetry and configuration details, but not the legal assessment.
- Give legal or privacy staff the data classification and jurisdictional facts they need to advise on notification.
- Give communications staff a customer report and a deadline without revealing unverified technical speculation.
- Give the business owner the service-level impact and manual-workaround capacity.
- Give the supplier contact a provider statement that may conflict with internal evidence.
Each inject should have a purpose: expose a missing authority, test an information handoff, force a containment trade-off, or reveal a dependency. Avoid adding events merely to make the scenario dramatic.
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Step 4: Brief participants without giving away the answer
Explain the objectives, roles, confidentiality rules, timebox, and how to request information. Do not rehearse the correct response. Tell participants when the exercise is fictional, which facts are intentionally unknown, and how to report a safety concern about the exercise itself.
Step 5: Facilitate decisions, not performances
Ask who is accountable, what evidence is needed, which action is reversible, and what harm could result from waiting. When the group reaches a decision, record the owner, time, assumptions, dependencies, and trigger for revisiting it. If participants jump to a solution, ask what would falsify it and who can obtain that evidence.
Step 6: Debrief while context is fresh
Separate observations from judgments. Capture where a participant lacked authority, where information arrived too late, where a control was assumed rather than verified, and where the business workaround was unrealistic. Ask each role which handoff was hardest and which document or control would have changed the decision.
Step 7: Turn observations into owned improvements
Convert every material gap into an action with one accountable owner, a target date, a dependency, and a test of completion. Examples include documenting who can disable a model tool, adding retrieval-data provenance to evidence collection, creating a supplier escalation path, or rehearsing a manual customer-support process. Schedule a focused retest for high-risk items instead of waiting for the next annual exercise.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What a useful after-action record contains
Whether it is generated by a platform or assembled by your facilitator, the record should be understandable to someone who did not attend. Include:
- Exercise purpose, scope, date, participants, roles, and scenario assumptions.
- Timeline of injects, information requests, decisions, and changes in direction.
- System, model, data, identity, supplier, and business dependencies discussed.
- What participants knew at each decision point and what remained uncertain.
- Plan strengths, ambiguities, missing procedures, and controls that were assumed but not demonstrated.
- Action owner, priority, due date, dependency, acceptance evidence, and status.
- Restrictions on distribution and the retention or deletion decision for the exercise record.
A scorecard can help identify trends across exercises, but a score is not a benchmark of real-world resilience. Do not compare teams or suppliers using numbers whose scoring method, assumptions, and evidence are not transparent.
Procurement and security checklist
Use this checklist before granting a platform access to internal material:
- Can the supplier explain every category of data collected from participants, uploads, logs, support cases, and integrations?
- Are processing and storage locations, subprocessors, administrator access, and support access documented?
- Can you disable model-training use, set retention periods, delete backups where contractually possible, and export your records?
- Are tenant boundaries, encryption, identity controls, multifactor authentication, audit logs, and role permissions described in contract or security documentation?
- What happens if the supplier suffers an incident, changes ownership, discontinues the service, or cannot provide an export?
- Can the product operate with redacted documents or inside your controlled environment?
- Do accessibility, browser, network, and identity requirements work for every participant and external partner?
- Can legal and privacy teams review the terms before a privileged or regulated document is uploaded?
If an answer is not documented or demonstrated, mark it as an open procurement risk. Do not infer security from a feature page, a cloud label, or an assertion that a simulation is AI-powered.
Common selection mistakes and how to avoid them
Buying the most polished scenario library
Visual quality and a large catalog do not show whether the platform represents your model, data, tools, or authority. Require the supplier to build and run your scenario.
Uploading the real playbook too early
Start with synthetic or redacted material. Complete data-flow, retention, access, deletion, and contract reviews before providing sensitive plans or diagrams.
Inviting only security staff
An AI incident often turns on business continuity, privacy, communications, supplier management, and executive authority. Include those roles or document why a role is out of scope.
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Writing a single dramatic failure
A one-step breach rarely tests coordination. Use a sequence in which new evidence changes the decision and a supplier or business constraint limits the available response.
Confusing a fast answer with a correct plan
Record assumptions and evidence requests. A quick decision made with information that would not exist in production is not proof that the process is ready.
Ending with a report nobody owns
Assign each gap to a named owner and track completion in the system your organization already uses. Schedule a retest for actions that affect containment, notification, or continuity.
A practical decision rule
Select a platform only when it passes all of these gates:
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- It lets the required technical and nontechnical roles receive, protect, and share information appropriately.
- A facilitator can alter timing and injects without losing the decision record.
- The after-action output identifies gaps and assigns improvements in an exportable form.
- Security, privacy, legal, procurement, and contract reviews accept the way the service handles your data.
- The access, integration, accessibility, deployment, and support model fits how your organization actually runs exercises.
If a product fails a gate, a well-facilitated DIY exercise using CISA materials may be safer and more informative than purchasing it. If it passes, keep the demonstration record and contract commitments with your exercise documentation so that future teams can verify that the service still meets the requirement.
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