AI Enablement Programs for Banks
Strategic Proposal for Fortune 500 Implementation
Prepared for The NBS Group
A comprehensive proposal for implementing AI enablement programs that recalibrate business benchmarks and unlock exponential productivity gains in the modern banking sector.
The AI Economy Reality
We now live in an AI-driven economy where traditional business metrics are being fundamentally recalibrated. The cost of knowledge work is collapsing by orders of magnitude.
New Valuation Framework
Traditional valuation methods assume business as usual, but AI enables radical improvements in cost structure, productivity, and competitive positioning.
Measurable Results
Based on thousands of documented cases, companies achieve 10x minimum productivity gains, with many reaching 100x improvements in specific workflows.
The AI Economy Narrative
Understanding the fundamental shift in business valuation
Valuing Companies in the AI Economy: Recalibrating Benchmarks with AI-Enabled Productivity
The AI Economy Has Arrived: Benchmarks Are Being Rewritten
We now live in an AI-driven economy, where every traditional business metric – cost, productivity, margins, ROI – is being fundamentally recalibrated. The reason is simple yet profound: the cost of knowledge work, which constitutes the majority of value creation in modern businesses, is collapsing by orders of magnitude thanks to advances in artificial intelligence.
In practical terms, tasks that once took days of human effort can now be accomplished in minutes with AI assistance. For the first time in history, organizations can produce the same output (or more) at a fraction of the time and cost. This seismic shift means that any credible business valuation today must account for a company's AI enablement – i.e. how thoroughly the business has integrated AI into its operations – or risk severely misjudging its true potential and competitive position.
Traditional valuation methods (whether based on EBITDA multiples, discounted cash flows, or comparables) assume business as usual. But business as usual is changing. The benchmarks that used to drive those valuations are no longer static. A company's cost of goods and services, labor efficiency, time-to-market, and even achievable profit margins can all be radically improved by pervasive AI integration.
In an economy dominated by knowledge work (design, software, finance, marketing, etc.), AI is compressing the cost of that work 10×, 50×, even 100× in many cases. Every key performance indicator – from cost per deliverable and ROI per employee to cycle time and payroll allocation – "can now be rewritten" by AI-first operations.
"AI is not just a tool. It is a recalibration of the economy itself… nearly every KPI can now be rewritten." — CEO of Repeatable AI
Investors and VCs are starting to recognize that we've reached an inflection point. Companies that fully embrace AI at all levels will dramatically outpace those that don't. A corollary is that non–AI-enabled businesses risk rapid obsolescence. In fact, analysts have begun to warn that companies ignoring AI are on track to disappear, "not melodrama... the clock is not sentimental".
In this context, a forward-looking valuation must ask: How would this business look if it were AI-first? And what is its value if it isn't?
Traditional vs. AI-First Valuation
A new lens for business evaluation
Traditional Valuation
- Historical financial performance
- Industry comparables
- Steady-state projections
- 2-3% annual efficiency gains
- Static cost structures
AI-First Valuation
- AI-enabled productivity scenarios
- Cost per deliverable analysis
- Step-change efficiency gains
- 90%+ cost reduction potential
- Dynamic margin expansion
Critical Valuation Differences
Operating Costs
Traditional: Assumes 2-3% annual cost reduction from process improvements
AI-First: Models 90%+ cost reduction on core knowledge tasks through automation and AI assistance. Tasks taking 40 hours reduced to 4 hours represent a 10× productivity gain.
Profit Margins
Traditional: Gradual margin improvement through operational excellence
AI-First: Dramatic margin expansion from freed payroll costs. Example: 10% margins can become 40% margins through AI-enabled cost reductions, representing a 113% increase in net margin.
Revenue Growth
Traditional: Linear growth projections based on historical trends
AI-First: Accelerated innovation and output enabling faster market capture. Documented cases show 3.9× revenue increases with 25× growth potential.
Time-to-Market
Traditional: Fixed product development cycles and go-to-market timelines
AI-First: Compressed development cycles through AI-assisted research, analysis, and content creation. Faster iteration means quicker revenue realization and compounding advantages.
The Harada Matrix Methodology
From Org Chart to Work Board: Mapping Deliverables and Costs
How do we actually evaluate a business through this AI-first lens? It starts by changing what we analyze. Instead of looking only at departments and line-item budgets, we break the business down into its fundamental units of work – the deliverables produced by each role in the company.
The Paradigm Shift
Think of this as moving from the traditional org chart view (positions and salaries) to a "work board" view, where each sticky note is a key deliverable or task, with a cost attached to it.
The Deliverables Matrix Framework
Corporate Controller
- Monthly Financial Statements
- Budget Forecast Reports
- Compliance Checklists
- Cash Flow Analyses
- Variance Reports
- Audit Preparations
Marketing Manager
- Weekly Social Media Content Calendar
- Campaign Performance Reports
- Product Launch Plans
- Market Research Analysis
- Brand Guidelines Documentation
- Customer Journey Maps
Cost Per Deliverable Analysis
Marketing Content Example
Before AI
- Research: 3 hours
- Drafting: 4 hours
- Editing: 3 hours
- Total: 10 hours ($500)
After AI
- AI Draft Generation: 1 minute
- Data Integration: 10 minutes
- Human Review: 50 minutes
- Total: 1 hour ($50)
Financial Analysis Example
Before AI
- Data Collection: 2 days
- Analysis: 2 days
- Report Writing: 1 day
- Total: 5 days (40 hours)
After AI
- Automated Data Pull: 1 hour
- AI-Assisted Analysis: 3 hours
- Report Review: 4 hours
- Total: 1 day (8 hours)
Productivity Gains: 10× is the New Normal
Understanding the dramatic scale of AI-driven productivity improvements
The Scale of Transformation
A 10× improvement means something that took a full workday can be done in under an hour, or a process that needed 10 people might need only 1 person now. This is not a 10% efficiency tweak – it's on the order of 1000% increase in output per worker.
It's worth underscoring just how dramatic these AI-driven productivity gains are. As noted, 10× is truly the baseline floor observed when employees across many industries adopt current AI tools effectively. When you stack multiple AI optimizations, 50× or 100× total improvement for certain deliverables is not uncommon.
Real-World Productivity Examples
Data Cleaning & Report Generation
Traditional Approach
- Manual data gathering: 4 hours
- Data cleaning & validation: 4 hours
- Report formatting: 2 hours
- Total: 10 hours
AI-Enhanced Approach
- Automated data collection: 2 minutes
- AI-powered cleaning: 3 minutes
- Human review & refinement: 5 minutes
- Total: 10 minutes
RFP Response Process
Traditional Approach
- Market research: 1 week
- Technical documentation: 2 weeks
- Legal compliance review: 1 week
- Final assembly: 3 days
- Total: 1 month
AI-Enhanced Approach
- AI research & analysis: 4 hours
- Automated documentation: 8 hours
- AI compliance checking: 2 hours
- Human review & polish: 2 days
- Total: 3-4 days
Customer Service Operations
Traditional Approach
- Manual inquiry handling
- 10 agents for routine queries
- Standard response times
- Limited scalability
AI-Enhanced Approach
- AI chatbot handles 90% instantly
- 1 agent monitors AI system
- Immediate response capability
- Infinite scalability
Evidence from the Repeatable AI Repository
World's Largest Productivity Dataset
The Repeatable AI Repository contains thousands of real entries from employees across different roles and industries, each showing measurable improvements in deliverable completion times.
Key Research Findings
Nearly every employee can hit a 10× improvement on at least some key tasks after adopting AI
100× improvements are common in workflows where AI automation chains together formerly siloed tasks
Companies implementing systematic AI training have documented 40%+ operating margin expansions
One mid-sized company projected 25× revenue growth with 40% higher margins after AI implementation
Financial Impact
Freed Payroll, Fatter Margins, and Faster Growth
From a financial perspective, the AI-first transformation can be viewed in two complementary ways: cost savings and growth enablement. Both ultimately flow to the bottom line (profit), but they do so via different paths – one by shrinking expenses, the other by expanding output and revenue.
1. Massive Cost Reduction (Freed Payroll)
By automating or accelerating deliverables, a huge number of work hours are freed up across the company. Tasks that consumed 40 hours now take 4 or even 1 hour, which means 39 out of every 40 hours can be repurposed.
Scenario Example
Smart Reallocation Strategy
"If a task drops from 40 hours to 5, congratulations: you just freed 35 paid hours. Fire the person? Cute, but wasteful — you already paid the onboarding tax. Reallocate those hours to revenue..."
The freed payroll hours can be redeployed to tackle revenue-generating initiatives: more sales outreach, enhanced customer success, product experiments, and clearing backlogs.
2. Profit Margin Expansion
Whether or not headcount changes, the effective cost per unit of output plunges with AI. This means if the company keeps its pricing the same, its gross and net margins will skyrocket.
Real Case Study Results
An AI-enabled firm might achieve in 1 year what would take a legacy firm 10 years, or might do with $1 of expense what the other needs $10 to accomplish. This compounds into market dominance over time.
3. Revenue Growth and Market Share
Freed capacity and faster cycle times often translate into accelerated revenue growth. Employees focusing on "profit work" means more effort on activities that generate sales or improve customer value.
Accelerated Innovation
AI-empowered teams can iterate faster, launch products sooner, and respond to customer needs in real-time, enabling new revenue streams with low incremental cost.
Strategic Pricing Power
Since cost per deliverable is much lower, companies can drop prices to capture customers from competitors while still increasing profit due to volume gains.
Market Expansion
AI provides scalability that enables global expansion without proportional headcount increases, opening new markets cost-effectively.
Documented Growth Results
4. Intangibles – Innovation and Agility
An AI-first company is generally a more agile and innovative company. It can respond to opportunities or threats much faster, which reduces risk and increases terminal value.
Faster Time-to-Market
Generate future cash flows sooner and stay competitive with compressed development cycles
Premium Valuation
Investors pay premiums for companies that clearly "get it" with transformative technology
Market Share Capture
Expect to grab outsized share of future market changes through superior agility
New Performance Metrics for the AI Era
We might even introduce new metrics like Return on Intelligence (RoI²) – defined as output gains from AI-enabled deliverables divided by payroll invested. This RoI² essentially measures how effectively the company turns payroll into results with AI leverage.
Traditional Company
AI-Enabled Company
A First-Principles Tool for AI-Adjusted Business Evaluation
Interactive application for systematic AI-first valuation assessment
To assist VCs and investors in making these assessments systematically, we envision an interactive application – essentially a valuation "calculator" or diagnostic tool – that implements the above analysis. This application would embody the explicit set of tools and steps needed to evaluate a business with and without AI augmentation.
Application Components & Features
Industry & Company Input
Input basic company information including industry, size, current financials, and payroll by department. Industry input tailors analysis with benchmark data for typical deliverables and productivity gains.
Role & Deliverable Breakdown
Generate deliverables matrix for each role using templates from the Repeatable repository. 8×8 matrix of core deliverables per role with effort and cost assignments.
Current State Metrics
Assign current effort required for each deliverable based on benchmarks or user input. Creates picture of current resource allocation and establishes baseline costs.
AI-Enabled State Assumptions
Apply AI productivity multipliers with default values (10× baseline, up to 100× for complex workflows). Adjustable sliders for conservative, likely, and aggressive scenarios.
Company-Wide Impact Calculation
Aggregate results showing hours saved, payroll freed, and cost reductions by department. Translates efficiency gains into concrete dollar savings and capacity increases.
Revised Financial Projections
Generate pro forma income statements for AI-enabled scenarios. Compare current vs. AI-optimized EBITDA, margins, and Return on Intelligence (RoI²) metrics.
Valuation Outputs & Reporting
Comprehensive Valuation Report
Status Quo Valuation
Current EBITDA × Industry Multiple = Traditional Value
AI-Enabled Valuation
Enhanced EBITDA × Premium Multiple = AI Value
AI Premium: +$100M Enterprise Value
Quantifies the "AI boost" factor and attributes value increases to specific improvements (cost savings, margin expansion, growth acceleration).
Executive Dashboard
Visual representations of before vs. after metrics including cost reductions, productivity gains, and financial projections. Interactive charts showing the impact across departments and deliverables.
Narrative Documentation
Plain English explanation of assumptions, department-by-department changes, and benchmark comparisons. Includes external validation from industry cases and competitive analysis.
Scenario Planning & Risk Assessment
Conservative Scenario
- 5× average productivity gain
- 50% workforce AI adoption
- 2-year implementation timeline
Likely Scenario
- 10× baseline, 50× for key tasks
- 80% workforce AI competency
- 18-month implementation
Aggressive Scenario
- 10× minimum, many at 100×
- Full AI-first transformation
- 12-month rapid deployment
Implementation & Monitoring Framework
The tool can be extended for post-investment monitoring, allowing investors to track actual AI transformation progress against projections. This creates a feedback loop for improving valuation accuracy and measuring Return on Intelligence (RoI²) in real-time.
Dynamic Valuation Updates
Track real productivity data to update valuations as AI implementation progresses
Performance Benchmarking
Compare actual results against projections and industry benchmarks
Investment Performance
Measure ROI on AI enablement initiatives and optimize future investments