COMMAND DASHBOARD
Revenue: $53.3M/quarter (Q3 FY2026) — down 46% year-over-year; full fiscal year 2026 revenue projected at ~$300M, a 23% YoY decline
Company snapshot: ~700 employees (after 26% workforce reduction) | HQ: Redwood City, CA | Founded by: Tom Siebel (Siebel Systems)
Cash burn: $80M from operations in H1 FY2026; projected annual loss of ~$200M
Leadership: Stephen Ehikian appointed CEO (September 2025) — the company's third major leadership event in 18 months; Ehikian's mandate is explicit: restructure and reverse the revenue decline before cash position becomes critical
Root causes of the collapse: Customers delayed spending, enterprise AI budgets were reassessed industry-wide, the leadership transition disrupted execution, and AWS/Google Cloud/Microsoft Azure AI services began bundling competing capabilities into existing enterprise agreements
The competitive reality: Hyperscalers are not going away. C3.ai cannot win on price. The only viable path is selling what hyperscalers cannot: domain-specific industrial AI with pre-built applications for oil and gas, defense, utilities, and manufacturing — sectors where the bundled cloud AI approach fails on regulatory and operational complexity

C3.ai's decline is not fundamentally a product failure — Tom Siebel was selling enterprise AI to industrial companies before the market existed; the products work and have live deployments at Baker Hughes, the US Air Force, and Con Edison. The collapse is a pipeline failure: the sales motion became reactive, the leadership transition created coverage gaps, and the company lost the narrative battle to hyperscalers who moved faster with cheaper messaging. Reversing a 46% revenue decline in 12 months requires someone who can rebuild pipeline from near-zero using AI-powered outreach infrastructure, identify the 30–40 existing customers at highest churn risk and stabilize them before they defect, and execute the competitive repositioning that makes "enterprise industrial AI with 8 years of domain training data" a buying signal rather than a legacy flag.

Days 1–90Q1 — TURNAROUND
Days 91–180Q2 — STABILIZE
Days 181–270Q3 — REBUILD
Days 271–365Q4 — RECOVER
Conservative

$40M in new ARR (turnaround cadence slower than modeled; government deals push to FY2027; churn above 5%)

Target

$55M in new ARR (pipeline recovery outpaces churn; oil and gas and defense close on schedule; win-back campaigns convert at 20%)

Stretch

$75M in new ARR (government anchor deals accelerate; defense prime partnerships convert faster than modeled; sequential revenue growth becomes evident to Wall Street in Q3)

Strategic Summary

Core Opportunity

C3.ai's decline is not a product failure — the products work and have live deployments at Baker Hughes, the US Air Force, and Con Edison. The collapse is a pipeline failure: the sales motion became reactive, the leadership transition created coverage gaps, and the company lost the narrative battle to hyperscalers.

Execution Thesis

Deploy AI-powered churn detection, autonomous prospect re-engagement, competitive repositioning, and federal/utilities vertical activation to deliver $40M–$75M in new ARR — reversing a 46% revenue decline and delivering C3.ai's first sequential quarterly revenue growth since FY2025.

Production systems, not theory. Revenue captured, not demos given.