Will MongoDB provide a specific quantification of AI workload revenue contribution by Q2 FY2027 earnings?

The Myth Meter's DIVERGING-to-DISCONNECTED assessment places AI revenue materiality 12-18 months out from the Feb 2026 analysis date, meaning roughly Aug 2027 to Feb 2028. The resolution window closes Sep 2026 — well before AI workloads are expected to become material enough to warrant quantification. Management explicitly stated AI is 'not material' in Q2 FY2026. The asymmetric disclosure argument is compelling: if AI revenue were growing fast enough to quantify, the new CEO — who named AI-native companies as a strategic pillar — would have every incentive to share that number. Three reporting periods remain (Q4 FY2026, Q1 FY2027, Q2 FY2027), and each provides an opportunity, but the Voyage AI acquisition was only Feb 2025 and enterprise AI adoption is described as 'still early' with 'few agents in production at scale.' The most likely scenario is continued qualitative progress narratives without specific numerical disclosure.

Three earnings calls remain before resolution (Q4 FY2026 in Mar, Q1 FY2027 in Jun, Q2 FY2027 in Sep). Each is an opportunity for disclosure. The new CEO has clear incentive to establish AI credibility, and the Voyage AI acquisition provides an obvious vehicle for an 'AI customer cohort' metric. However, the analysis facts are decisive: management explicitly called AI 'not material' and the Myth Meter rates the narrative as ahead of reality. The key question is whether CJ Desai, wanting to differentiate his tenure, accelerates disclosure of even modest AI metrics. Some software companies have disclosed AI revenue at very small percentages (e.g., Salesforce, ServiceNow) as a way to anchor investor expectations. There is perhaps a 30-35% chance MongoDB follows this playbook, particularly at an Investor Day or if analyst pressure mounts. But the base case is that management avoids quantification because a small number would be more damaging than helpful to the AI narrative supporting their valuation.

The analysis context provides a clear, high-confidence assessment that AI workloads are not material. The resolution criteria are strict: qualitative statements like 'early traction' or 'growing interest' do not qualify. This significantly narrows the probability space. Management must provide a specific percentage, dollar amount, or ARR figure. Companies typically only quantify a revenue category when it is either (a) large enough to be a positive catalyst, or (b) required by SEC disclosure rules due to materiality. AI workloads are neither at MongoDB currently. The Myth Meter's 12-18 month timeline means we are asking whether an event expected in roughly H2 2027 will happen by Sep 2026. The 3 remaining earnings calls provide opportunities, but the resolution criteria's requirement for 'specific quantitative disclosure' makes vague AI metrics insufficient. Even application modernization — the other AI-adjacent category — is only 'expected to contribute from FY2027 onwards,' meaning it too is pre-revenue during most of the resolution window.

This is a straightforward probability assessment. The CEO said AI is not material. The Myth Meter says the narrative is 12-18 months ahead of reality. The resolution requires specific numbers, not qualitative commentary. Three earnings calls remain, but the most informative signal is the asymmetric disclosure incentive: if MongoDB had impressive AI numbers, they would already be sharing them. The Voyage AI acquisition gives them vector search capabilities but revenue from AI-native workloads takes time to ramp. The probability is anchored around 25% — primarily driven by the nonzero chance that CJ Desai uses an Investor Day or earnings call to proactively frame an AI revenue metric, even a modest one, to anchor the narrative.

I weigh two competing dynamics. Against disclosure: AI workloads are explicitly not material, quantifying a small number could hurt more than help, and the Myth Meter's 12-18 month timeline pushes materiality past the resolution window. For disclosure: the new CEO named AI-native companies as a strategic pillar (creating a self-imposed expectation to show progress), the competitive landscape is increasingly requiring AI metrics (Databricks, Snowflake are quantifying), and analysts will press for specifics. The resolution allows 'any earnings call, investor day, SEC filing, or official press release' through Q2 FY2027 — that is a fairly wide net. But the specific quantification bar is high. I settle at 30%, primarily because of sell-side pressure on new CEOs to quantify strategic pillars, while acknowledging the majority scenario is continued qualitative-only commentary.

The analysis facts leave little room for a different conclusion. The AI narrative is rated DIVERGING-to-DISCONNECTED by the Myth Meter, which is the most bearish possible assessment of narrative-reality alignment. Management's own words ('not material') confirm the gap. The resolution criteria explicitly exclude qualitative statements. Even if MongoDB holds an Investor Day — which is not confirmed — the odds of specific quantification when the number would likely be embarrassingly small relative to valuation expectations are low. The disclosure incentive analysis in the prediction context (finding #3) is particularly persuasive: companies disclose favorable metrics and withhold unfavorable ones. The absence of AI revenue quantification IS the signal. I estimate 23%.

CEO said AI not material. Myth Meter says 12-18 months ahead of reality. Resolution needs specific numbers. Three earnings calls remain but management has no incentive to quantify a small number. Probability around 27% — the nonzero component comes from competitive pressure and new CEO wanting to show progress on his AI pillar.

Strong evidence against disclosure: AI not material, narrative ahead of reality, asymmetric incentives to withhold small numbers. The resolution criteria bar is high — qualitative doesn't count. Most likely outcome is 2-3 more earnings calls with 'growing momentum' language but no specific figures. 20% probability accounts for small chance of Investor Day surprise or competitive pressure forcing early disclosure.

Three chances to disclose (Q4 FY2026, Q1 FY2027, Q2 FY2027 earnings calls). But CEO already set expectations low by saying AI is not material. Voyage AI acquisition is too recent to generate meaningful disclosed revenue. Resolution criteria are strict. Probability is 24%, reflecting that while 3 reporting periods provide opportunities, the fundamental precondition — material AI revenue worth disclosing — is unlikely to be met within the window.