Outcomes.
Not vendor self-reports — third-party-validated market data first, then this studio's own results.
The 95/5 gap.
Three independent 2024–2025 studies — MIT NANDA, McKinsey QuantumBlack, BCG Build for the Future — converge on the same finding: roughly 5–6% of enterprises capture material EBIT impact from AI. The other 95% are running pilots that produce no measurable P&L impact.
The gap is explained by workflow redesign, vendor partnership over internal builds, and governance maturity — not model quality. The studio's work targets the 95% directly.
95%
of GenAI pilots produce no measurable P&L impact
MIT NANDA · State of AI in Business 2025
Based on 52 executive interviews, 153 surveyed leaders, 300 public deployments. Against an estimated $30–40B in enterprise GenAI investment.
39%
of organizations report any enterprise EBIT impact from AI
McKinsey QuantumBlack · State of AI 2025
Of those that report impact, most see <5%. Only ~6% attribute ≥5% of EBIT to AI.
5%
of firms are "future-built" with 80%+ AI investment in workflow transformation
BCG · Build for the Future 2025 (n=1,250)
These firms achieve 1.5× revenue growth, 1.6× shareholder returns, 1.4× ROIC vs peers over three years.
50%+
of GenAI projects abandoned after POC by end of 2024
Gartner · 2024–2025
Causes: poor data quality, inadequate risk controls, escalating costs, unclear business value. 40%+ of agentic AI projects expected to be canceled by end of 2027.
Ceiling expectations.
The most-cited, third-party-validated AI deployment outcomes from 2023–2026. Treat these as order of magnitude, not benchmarks the average engagement will reach. Each comes from a Fortune 50 or equivalent, with 12–36 month transformation timelines.
All eight are Fortune 50 or equivalent. They share three structural features: vendor partnership over internal build, workflow redesign over tool deployment, and 12–36 month operating timelines.
NBIM
Sovereign wealth · $1.8T AUM
213,000 hours / year saved
Moody's
Financial services · Credit ratings
40 hours → 2 minutes
Novo Nordisk
Pharma · Clinical operations
12 weeks → 10 minutes
Lyft
Mobility · Customer support
87% reduction in resolution time
AIG
Insurance · Underwriting
55% faster quotes, ~40% bind rate lift
CommBank
Banking · Fraud detection
20%+ reduction in fraud losses
Pfizer
Pharma · R&D + supply chain
3 months → 6 weeks (prototype to MVP)
Walmart
Retail · Conversational commerce
35% higher AOV from AI-engaged users
The governance gap.
Across the 2025 published data, governance maturity is the decisive variable in whether AI pilots scale or stall. The gap is structural. The studio's five deliverables map directly to closing it.
Each of the studio's five deliverables — AI Charter, Council Guide, 30/90/180 Roadmap, Data Risk Matrix, Standards Mapping — addresses one of these gaps directly. Outcomes are measured against these baselines.
18%
have an enterprise-wide AI council with decision authority
→ Council Guide McKinsey · State of AI in early 2024
36%
have adopted a formal governance framework (NIST / ISO / EU AI Act)
→ Standards Mapping IAPP / Credo AI · 2025 AI Governance Profession Report
99%
of large enterprises reported financial losses from AI risks in 2025
→ AI Charter + Data Risk Matrix EY · Responsible AI Pulse, n=975 C-suite, $1B+ revenue
$4.4M
average loss per organization from AI-related risk events
→ Data Risk Matrix EY · 2025 · aggregate $4.3B across the cohort
18%
of EU-based organizations are "highly prepared" for EU AI Act
→ Standards Mapping Deloitte · EU GenAI Adoption Survey (n=700+, six EU countries)
30%
of pilots reach production (typical mid-market baseline)
→ 30/90/180 Roadmap Deloitte · State of GenAI in the Enterprise, Q3 2024
From this studio.
Anonymized engagement results, calibrated against the market baselines above. Updated as quarterly cycles close. Currently building this section in public — first published cases expected in Q3 2026.
Engagement type
90-Day AX Loop
Sector
Mid-market · Global trading
Headline
[ engagement closes Q3 2026 · published Q4 2026 ]
Metrics anchored to
McKinsey 18% Council baseline · EY $4.4M risk-loss baseline · Deloitte 30% pilot-to-production baseline
Engagement type
90-Day AX Loop
Sector
Mid-market · Global trading
Headline
[ engagement closes Q3 2026 · published Q4 2026 ]
Metrics anchored to
McKinsey 18% Council baseline · EY $4.4M risk-loss baseline · Deloitte 30% pilot-to-production baseline
Engagement type
Executive AX Briefing
Sector
PE-backed SaaS
Headline
[ session pending · published Q3 2026 ]
Metrics anchored to
Gartner 50% project-abandonment baseline · BCG ~3.5 vs 6.1 use-case-focus differential
Engagement type
Executive AX Briefing
Sector
PE-backed SaaS
Headline
[ session pending · published Q3 2026 ]
Metrics anchored to
Gartner 50% project-abandonment baseline · BCG ~3.5 vs 6.1 use-case-focus differential
Engagement type
Fractional CAIO · Portfolio
Sector
PE fund · multiple portcos
Headline
[ multi-quarter engagement · published Q1 2027 ]
Metrics anchored to
BCG 5% "future-built" cohort · McKinsey workflow-redesign correlation
Engagement type
Fractional CAIO · Portfolio
Sector
PE fund · multiple portcos
Headline
[ multi-quarter engagement · published Q1 2027 ]
Metrics anchored to
BCG 5% "future-built" cohort · McKinsey workflow-redesign correlation
No vendor self-reports. No paid case studies. When an engagement closes, the numbers will be published here against the baselines above — so the comparison is always honest.
On methodology. Every engagement is bespoke to its sandbox. Market baselines reflect aggregate data from MIT Sloan / NANDA, McKinsey QuantumBlack, BCG, PwC, Deloitte, Gartner, EY, RAND, and IAPP. Ceiling cases are third-party validated (Anthropic, AWS, MongoDB, VentureBeat, customer earnings calls). Studio outcomes will be published only after engagement close, with client agreement, anonymized by mutual review. The baselines are the proof of method. The numbers are the proof of the baselines.
Page last updated · May 2026 · Next quarterly refresh · August 2026
If you want to know what this would look like in your sandbox —
Start with a 90-minute Executive AX Briefing. The Two Weights Test, your three closest patterns, and a one-page board memo in 48 hours.
Outcomes.
Not vendor self-reports — third-party-validated market data first, then this studio's own results.
The 95/5 gap.
Three independent 2024–2025 studies — MIT NANDA, McKinsey QuantumBlack, BCG Build for the Future — converge on the same finding: roughly 5–6% of enterprises capture material EBIT impact from AI. The other 95% are running pilots that produce no measurable P&L impact.
The gap is explained by workflow redesign, vendor partnership over internal builds, and governance maturity — not model quality. The studio's work targets the 95% directly.
95%
of GenAI pilots produce no measurable P&L impact
MIT NANDA · State of AI in Business 2025
Based on 52 executive interviews, 153 surveyed leaders, 300 public deployments. Against an estimated $30–40B in enterprise GenAI investment.
39%
of organizations report any enterprise EBIT impact from AI
McKinsey QuantumBlack · State of AI 2025
Of those that report impact, most see <5%. Only ~6% attribute ≥5% of EBIT to AI.
5%
of firms are "future-built" with 80%+ AI investment in workflow transformation
BCG · Build for the Future 2025 (n=1,250)
These firms achieve 1.5× revenue growth, 1.6× shareholder returns, 1.4× ROIC vs peers over three years.
50%+
of GenAI projects abandoned after POC by end of 2024
Gartner · 2024–2025
Causes: poor data quality, inadequate risk controls, escalating costs, unclear business value. 40%+ of agentic AI projects expected to be canceled by end of 2027.
Ceiling expectations.
The most-cited, third-party-validated AI deployment outcomes from 2023–2026. Treat these as order of magnitude, not benchmarks the average engagement will reach. Each comes from a Fortune 50 or equivalent, with 12–36 month transformation timelines.
All eight are Fortune 50 or equivalent. They share three structural features: vendor partnership over internal build, workflow redesign over tool deployment, and 12–36 month operating timelines.
NBIM
Sovereign wealth · $1.8T AUM
213,000 hours / year saved
Moody's
Financial services · Credit ratings
40 hours → 2 minutes
Novo Nordisk
Pharma · Clinical operations
12 weeks → 10 minutes
Lyft
Mobility · Customer support
87% reduction in resolution time
AIG
Insurance · Underwriting
55% faster quotes, ~40% bind rate lift
CommBank
Banking · Fraud detection
20%+ reduction in fraud losses
Pfizer
Pharma · R&D + supply chain
3 months → 6 weeks (prototype to MVP)
Walmart
Retail · Conversational commerce
35% higher AOV from AI-engaged users
The governance gap.
Across the 2025 published data, governance maturity is the decisive variable in whether AI pilots scale or stall. The gap is structural. The studio's five deliverables map directly to closing it.
Each of the studio's five deliverables — AI Charter, Council Guide, 30/90/180 Roadmap, Data Risk Matrix, Standards Mapping — addresses one of these gaps directly. Outcomes are measured against these baselines.
18%
have an enterprise-wide AI council with decision authority
→ Council Guide McKinsey · State of AI in early 2024
36%
have adopted a formal governance framework (NIST / ISO / EU AI Act)
→ Standards Mapping IAPP / Credo AI · 2025 AI Governance Profession Report
99%
of large enterprises reported financial losses from AI risks in 2025
→ AI Charter + Data Risk Matrix EY · Responsible AI Pulse, n=975 C-suite, $1B+ revenue
$4.4M
average loss per organization from AI-related risk events
→ Data Risk Matrix EY · 2025 · aggregate $4.3B across the cohort
18%
of EU-based organizations are "highly prepared" for EU AI Act
→ Standards Mapping Deloitte · EU GenAI Adoption Survey (n=700+, six EU countries)
30%
of pilots reach production (typical mid-market baseline)
→ 30/90/180 Roadmap Deloitte · State of GenAI in the Enterprise, Q3 2024
From this studio.
Anonymized engagement results, calibrated against the market baselines above. Updated as quarterly cycles close. Currently building this section in public — first published cases expected in Q3 2026.
Engagement type
90-Day AX Loop
Sector
Mid-market · Global trading
Headline
[ engagement closes Q3 2026 · published Q4 2026 ]
Metrics anchored to
McKinsey 18% Council baseline · EY $4.4M risk-loss baseline · Deloitte 30% pilot-to-production baseline
Engagement type
Executive AX Briefing
Sector
PE-backed SaaS
Headline
[ session pending · published Q3 2026 ]
Metrics anchored to
Gartner 50% project-abandonment baseline · BCG ~3.5 vs 6.1 use-case-focus differential
Engagement type
Fractional CAIO · Portfolio
Sector
PE fund · multiple portcos
Headline
[ multi-quarter engagement · published Q1 2027 ]
Metrics anchored to
BCG 5% "future-built" cohort · McKinsey workflow-redesign correlation
No vendor self-reports. No paid case studies. When an engagement closes, the numbers will be published here against the baselines above — so the comparison is always honest.
On methodology. Every engagement is bespoke to its sandbox. Market baselines reflect aggregate data from MIT Sloan / NANDA, McKinsey QuantumBlack, BCG, PwC, Deloitte, Gartner, EY, RAND, and IAPP. Ceiling cases are third-party validated (Anthropic, AWS, MongoDB, VentureBeat, customer earnings calls). Studio outcomes will be published only after engagement close, with client agreement, anonymized by mutual review. The baselines are the proof of method. The numbers are the proof of the baselines.
Page last updated · May 2026 · Next quarterly refresh · August 2026
If you want to know what this would look like in your sandbox —
Start with a 90-minute Executive AX Briefing. The Two Weights Test, your three closest patterns, and a one-page board memo in 48 hours.