Hi all,
I've built a real-time “Cognitive Automation Index” (CAI) to track macro impacts of AI on routine cognitive/service jobs, margin effects, and incipient service sector deflation. Would greatly value this community’s review of scoring logic, evidence, and suggestions for methodological enhancement!
Framework (Brief):
CAI = (Tier 1 × 0.40) + (Tier 2 × 0.35) + (Tier 3 × 0.25)
Interpretation:
Thanks for your thoughts—open to any level of feedback, methodological or practical, on the CAI!
I've built a real-time “Cognitive Automation Index” (CAI) to track macro impacts of AI on routine cognitive/service jobs, margin effects, and incipient service sector deflation. Would greatly value this community’s review of scoring logic, evidence, and suggestions for methodological enhancement!
Framework (Brief):
- Tier 1 (Leading, 40%):
- AI infra revenue, Corporate AI adoption, Pro services margins, Tech diffusion
- Tier 2 (Coincident, 35%):
- Service employment (risk split), Service sector pricing
- Tier 3 (Lagging, 25%):
- Productivity, Consumer price response
- Score: +2 = maximum signal, +1 = strong, 0 = neutral, -1 = contradictory
CAI = (Tier 1 × 0.40) + (Tier 2 × 0.35) + (Tier 3 × 0.25)
Interpretation:
- +1.4+: “Strong displacement, margin compression beginning”
Monthly Scoring: Full Details & Evidence (Mar 2025–Aug 2025)
[th]
Month
[/th][th]Tier 1
[/th][th]Tier 2
[/th][th]Tier 3
[/th][th]CAI
[/th][th]Comment
[/th][td]
Mar 2025
[/td][td]1.1
[/td][td]1.0
[/td][td]0.7
[/td][td]0.98
[/td][td]Early infra growth, AI adoption signals up, jobs flat, minor productivity uptick
[/td][td]
Apr 2025
[/td][td]1.3
[/td][td]1.0
[/td][td]0.7
[/td][td]1.06
[/td][td]Service margins up, infra accel, service jobs start declining
[/td][td]
May 2025
[/td][td]1.8
[/td][td]1.25
[/td][td]0.7
[/td][td]1.32
[/td][td]Big AI infra jump (Nvidia/MSFT/Salesforce QoQ >50%), >2% annualized service job drop, pro services margins +200bp vs prior yr
[/td][td]
Jun 2025
[/td][td]2.0
[/td][td]1.35
[/td][td]0.8
[/td][td]1.48
[/td][td]CAI peaks: AI mentions in >25% of large cap calls, BLS confirms >2% annualized admin/customer services decline; CPI flat
[/td][td]
Jul 2025
[/td][td]2.0
[/td][td]1.35
[/td][td]0.8
[/td][td]1.48
[/td][td]Sustained: AI infra and service software growth steady, margins/declines persist
[/td][td]
Aug 2025
[/td][td]2.0
[/td][td]1.35
[/td][td]0.8
[/td][td]1.48
[/td][td]Trends continue: No reversal across any tracked indicators
[/td]Component Scoring Evidence by Month
Tier 1: Leading Indicators
- AI Infrastructure Revenue (18%)
- May–Aug: +2 (NVIDIA/Salesforce Q2/Q3: >50% QoQ growth in AI/data center, Salesforce AI ARR up 120%)
- Mar/Apr: +1 (growth 25–40%)
- Corporate Adoption (12%)
- May–Aug: +2 (>25% of S&P 500 calls mention “AI-driven headcount optimization/productivity gains;” surge in job postings for AI ops)
- Mar/Apr: +1 (10–20% companies, rising trend)
- Professional Service Margins (10%)
- May–Aug: +2 (major consulting/call center firms show margin expansion >200bp YoY, forward guidance upbeat)
- Mar/Apr: +1 (early signals, margin expansion 100–200bp)
- Tech Diffusion (5%)
- May–Aug: +2 (Copilot/AI automation seat deployment accelerating, API call volumes up)
- Mar/Apr: +1 (steady rise, not explosive yet)
Tier 2: Coincident Indicators
- Service Sector Employment (20% High/8% Med Risk)
- May–Aug: +2 (BLS/LinkedIn: >2% annualized YoY declines in high-risk service categories; declines pronounced in admin and customer service)
- Mar/Apr: +1 (declines start to appear; <2% annualized)
- Service Sector Pricing (15%)
- Mar–Aug: +1 (CPI flat or mild disinflation for professional/financial services; no inflation acceleration)
Tier 3: Lagging Indicators
- Productivity (15%)
- Mar–Aug: +1 (Service sector productivity up 2.4–2.5% YoY)
- Consumer Price Response (10%)
- Mar–Aug: 0–+1 (CPI for services broadly stable, some mild disinflation but not universal)
Request for Feedback
- Validation: Does this weighting/scoring structure seem robust to you? Capturing key regime shifts?
- Enhancement: What quant or macro techniques would tighten this? Any adaptive scoring precedents (i.e., dynamic thresholds)?
- Bias/Risk: Other ways to guard against overfitting or confirmation bias? Worth adding an “alternative explanations index”?
- Data Sources: Any recs for higher-frequency or more granular real-time proxies (especially for employment and AI adoption)?
- Backtesting: Best practices for validating this type of composite macro indicator against actual displacement or deflation events?
Thanks for your thoughts—open to any level of feedback, methodological or practical, on the CAI!