The Value System View: Finding Your AI Leverage Points

The Value System View: Finding Your AI Leverage Points
How to model your business to identify the most impactful areas for AI implementation, maximising return on investment.
The Strategic Imperative for AI Implementation
The emergence of Generative AI (Gen AI) offers a profound technological shift with unprecedented opportunities to transform operations, boost productivity, and ignite innovation. However, achieving measurable return on investment (ROI) requires moving past mere experimentation. Leaders must adopt a Value System View, strategically modeling their organisations to locate the precise leverage points where AI implementation will maximise returns.
AI implementation success hinges on a value-focused approach that targets clear, measurable business objectives, aligning every initiative with the overall strategic vision. Avoiding "AI for AI's sake" is a crucial first step.
Step 1: Define Strategic Ambition and Target the Right Problems
Effective modeling begins with setting high-level goals guided by the organisation's vision, purpose, and values. Leadership must communicate a compelling change story about the purpose of AI adoption to secure buy-in.
1
Identify High-Value Use Cases
Instead of applying AI everywhere, companies must prioritise domains with the greatest potential. Look for opportunities where AI can solve well-defined tasks or problems:
Well-defined repetitive or menial tasks, such as document processing, claims handling, or code development.
Tasks involving complex policy interpretation, like risk and compliance assessments.
Areas where AI can assist with core business functions like R&D, sales, and manufacturing, as approximately 70% of potential value is concentrated here.
2
Establish a Baseline
To measure ROI effectively, organisations need a clear "before" picture for key metrics (e.g., process time, cost, quality). This rigorous upfront measurement setup is vital for tracking progress.
Step 2: Leverage the Three Strategic Plays for Value Creation
Successful AI implementation utilises three complementary strategic plays—HARNESS, TRANSFORM, and CREATE—to maximise value potential and achieve end-to-end enterprise transformation.
Organisations that capture outsized value focus on transformation and creation rather than incremental automation. Transforming (or reshaping) critical functions involves holistic and centrally coordinated effort to rethink how work gets done and who does it.
Step 3: Implement the AI-First Operating Model
Capturing value requires rewiring the firm's architecture and processes around the new technology. This necessitates an integrated, holistic focus on strategy, people, processes, technology, and data. This systemic change is often described using the 10-20-70 Rule:
10%
Algorithms
Building algorithms and the science behind them.
20%
Technology & Data
Deploying the technology stack and ensuring high-quality, trusted data feeds into the right systems. A flexible, modular architecture that supports interoperability is essential to avoid vendor lock-in and allow scaling.
70%
People & Processes
Allocating the majority of effort to change management, process redesign, and people. Most roadblocks in AI adoption are related to people, organization, and processes.
The Human Leverage Point (The 70%)
The transition to an AI-enabled company is fundamentally an organizational change.
Foster Trust and Adoption
Transparent and frequent communication from leaders about AI initiatives is crucial for employee trust and preventing resistance. Trust in AI adoption is foundational. Employees should participate in developing initiatives and be given opportunities to offer feedback and identify use cases, which radically improves outcomes.
Targeted Upskilling
Training must move beyond a one-size-fits-all approach and be tailored to teach employees how to use specific AI tools within the context of their specific roles and workflows. This approach ensures that skill development translates into measurable business outcomes.
Redirect Capacity with Intent
Individual time savings do not automatically equal enterprise value. Leaders must design new processes to redirect time freed up by AI (such as automating repetitive, low-skill tasks) toward high-value activities that require uniquely human skills, like strategic thinking and creativity, and are tied directly to business goals and KPIs.
Step 4: Measure Value Holistically
To maximize ROI, the measurement framework must go beyond simple efficiency gains. Executives, particularly the CFO and finance teams, prioritise metrics tied clearly to business outcomes, revenue impact, and ROI.
ROI Tracking Framework
ROI should be articulated by tracking:
Process Velocity (Speed to Outcome)
Quantifying how much faster core business processes are completed.
Cost Efficiency
Measuring cost per transaction or FTE hours saved.
New Capabilities (Strategic Impact)
Tracking the creation of new products, services, or hyper-personalised customer experiences that AI makes possible. AI agents, for instance, are expected to double their value by 2028, underscoring their strategic long-term impact.
Decision Quality
Measuring improvements in the accuracy and success rates of decisions.
Successfully tracking value requires rigorous measurement setups and clear, AI-driven KPIs. Companies capturing the most value are 2.6 times as likely as others to rigorously track AI value across the organization.
Conclusion: Act Strategically, Lead Holistically
The path to maximising AI ROI involves pursuing a multiyear strategic ambition, prioritizing the functional TRANSFORM play, and establishing a robust operating model.
For organisations to successfully scale AI, governance and accountability must be top-down priorities. Executives should embed AI ownership jointly between business and IT teams. Investing in AI literacy for leaders and directors is crucial for strategic decision-making, risk management, and oversight. By leading with a clear vision, focusing on rewired workflows, and dedicating significant resources to people and change management (the pivotal 70%), organisations can capture sustained competitive advantage and position themselves to win in the AI era.