AI-Powered Crisis Detection & Early Warning

Q: How are alerts routed?

Alerts follow your escalation matrix (region, line of business, severity) and integrate with Slack/Teams, email, PagerDuty, and ticketing.

Q: Can the system suggest responses?

AI drafts holding statements, Q&A, and channel guidance aligned to your runbooks and legal guardrails, with approvals captured before publishing.

Q: Is this compliant and privacy-safe?

We use publicly available or licensed data, minimize data retention, and follow your PII policies and regional regulations.

Q: How fast can we see value?

Actionable alerts in the first month; full integration with runbooks and dashboards in 6–10 weeks, with measurable reductions in time-to-detect and time-to-respond.

Executive Summary

AI crisis management continuously monitors social, news, forums, dark web sources, and owned channels to detect and classify risk in real time. Predictive models score threat severity and likely escalation, trigger targeted alerts, and provide response playbooks so teams can act before issues trend.

How Does AI Improve Crisis Detection?

AI fuses anomaly detection with NLP and network analysis to spot emerging threats early, assess credibility, and predict escalation. This enables comms, legal, and CX teams to intervene proactively with the right message, channel, and timing.

Unlike manual monitoring, AI agents ingest millions of signals per hour, de-duplicate noise, score source reliability, and surface only high-confidence incidents with recommended actions mapped to your crisis runbooks.

What Changes with AI Crisis Management?

🔴 Manual Process (45 Minutes – 2 Hours, 4 Steps)

Manual monitoring across channels (15–30m)
Threat assessment & escalation analysis (15–45m)
Internal alert coordination (10–20m)
Initial response planning (5–15m)

SLOW, REACTIVE, HIGH FALSE-NEGATIVE RISK

🟢 AI-Enhanced Process (~3 Minutes, 2 Steps)

Real-time AI threat detection & severity scoring (≈1m)
Automated alert distribution with response recommendations (≈2m)

95% TIME REDUCTION • PREDICTIVE EARLY WARNING

TPG standard practice: Calibrate models to your crisis taxonomy and risk matrix, integrate with runbooks and paging tools (e.g., Slack/Teams, email, PagerDuty), and enable human-in-the-loop approvals for tier 1 incidents.

What Metrics Matter?

Sub‑minute

Crisis Detection Speed

90%+

Early Warning Accuracy

High

Threat Assessment Precision

Likely/Unlikely

Escalation Prediction

Operational KPIs

Crisis Detection Speed: Time from first signal to alert
Early Warning Accuracy: Precision/recall for pre-viral detection
Threat Assessment Precision: Confidence-weighted severity scores
Escalation Prediction: Probability of spread across channels and geos

Which Tools Power AI Crisis Detection?

Dataminr

Real-time event detection from public data with credibility scoring and alerting

Signal AI

AI news intelligence and risk monitoring across global media

Crisp (formerly Crisp Thinking)

Brand safety monitoring with threat detection across social, messaging, and marketplaces

These platforms integrate with your marketing operations stack and incident response tools to operationalize early warning and coordinated response.

Implementation Timeline

Phase	Duration	Key Activities	Deliverables
Assessment	Week 1–2	Define risk taxonomy, critical entities, channels, and alerting matrix	Crisis monitoring blueprint
Integration	Week 3–4	Connect Dataminr/Signal AI/Crisp; configure sources, thresholds, deduping	Live ingestion & scoring pipeline
Training	Week 5–6	Calibrate severity model; map to runbooks; set routing rules	Customized risk models & playbooks
Pilot	Week 7–8	Shadow mode with manual baseline; measure precision/recall and time saved	Pilot results & acceptance criteria
Scale	Week 9–10	Roll out paging, dashboards, and auto-briefings to exec/comms/legal	Production early-warning system
Optimize	Ongoing	Expand coverage, add languages/regions, refine prediction thresholds	Continuous improvement

Frequently Asked Questions

How do we control false positives?

Use multi-signal validation (source reputation, velocity spikes, cross-channel corroboration) and require threshold consensus before paging. Tier 1 alerts always include human review.

What channels are monitored?

Global news, social platforms, forums, app stores, dark web sources (where permitted), and owned channels (support, CRM, email). Coverage is tailored to your industry and geographies.

How are alerts routed?

Alerts follow your escalation matrix (region, business line, severity). We integrate with Slack/Teams, email, PagerDuty, and ticketing to ensure the right people get context-rich notifications.

Can the system suggest responses?

Yes. AI generates first-draft holding statements, Q&A, and channel-specific guidance aligned to your runbooks and legal guardrails. Approvals are captured before publishing.

Is this compliant and privacy-safe?

We use publicly available or appropriately licensed data, apply data minimization, and retain only what’s necessary for risk detection. PII handling follows your policies and regional regulations.

How fast can we see value?

You’ll receive actionable alerts in the first month. Full integration with runbooks, paging, and dashboards typically lands in 6–10 weeks, with measurable reductions in time-to-detect and time-to-respond.