AI Readiness

The Operational Truth Framework™

Artificial intelligence has become the responsibility of the CEO and the CFO. Boards and investors expect leadership teams to use AI to improve business performance. Yet many organizations struggle to produce meaningful results.

The reason is simple.

AI cannot determine what is true. It can only reason over what the business agrees is true. If the underlying facts of the business are incomplete, inconsistent, or not trusted across departments, AI will produce confident answers based on flawed input.

AI readiness starts with Trusted Facts™.

The Operational Truth Framework™ explains how organizations progress from fragmented reporting toward Trusted AI through four stages:

  • Trusted Facts™

  • Truth Domains™

  • Operational Truth

  • Trusted AI™

Trusted Facts establish the certified performance measures that allow leaders, systems, and AI to operate on truth.

Why AI Reveals Organizational Maturity

Artificial intelligence does not create operational maturity.

It reveals it.

  • AI does not reconcile inconsistent definitions.

  • It does not break down departmental silos.

  • It does not establish a culture of truth and transparency.

If the measures used to describe performance are disputed between teams, incomplete, or poorly defined, AI will provide confident answers built on flawed facts. This is why AI initiatives fail to produce meaningful results. AI exposes the underlying clarity of an organization’s performance measurement, governance discipline, and cross-functional collaboration.

Organizations that have not established trusted performance drivers will struggle to use AI effectively.

AI Readiness Begins With Certified Trusted Facts™

Before decision-makers use large language models for financial or operational analysis, the underlying facts must be trusted within the agreed business context.

  • AI does not verify definitions.

  • It does not question the business rules’ logic.

  • It assumes the inputs are correct.

If measures are incomplete, disputed, or poorly defined, AI will produce confident answers built on flawed input.

Certification of Trusted Facts is governed through the Trusted Facts Certification Council™ (TFCC).

The TFCC is responsible for:

  • Approving core measure definitions

  • Confirming stewardship accountability

  • Resolving cross-functional conflicts

  • Certifying thresholds and operational guardrails

  • Authorizing AI usage against certified drivers

The CFO has final decision-making authority over cross-functional disagreements regarding business definitions and rules.

AI readiness exists only where Trusted Facts are formally certified.

The Immediate Value of Trusted Facts

The first value created by Trusted Facts is through simple visibility. When Trusted Facts are established in the right places first, clarity emerges quickly. Misalignment between departments and strategic goals becomes visible. Therefore, organizations will discover meaningful performance improvements before leveraging AI. The simple act of making trusted performance drivers visible reveals opportunities that can be addressed immediately.

Executives often assume that AI is required to unlock business improvements. In reality, organizations frequently uncover some the most significant opportunities through trusted visibility alone.

Trusted Facts is the first step toward AI readiness.

When Artificial Intelligence Becomes Valuable

Artificial intelligence becomes valuable when three conditions exist.

  • First, pattern identification requires machine-level processing due to the large number of variables that affect results.

  • Second, the underlying performance drivers are Trusted Facts that have been formally certified.

  • Third, business context and guardrails can be engineered into the AI interaction so outputs can be trusted.

Ideas for AI use cases often originate within functional departments or cross-functional planning discussions.

These ideas must be evaluated through governance that ensures the underlying data is trusted and the expected business impact is clear.

Truth Domains™

A KPI may represent either a business outcome or a driver of that outcome. Truth Domains™ represent the collection of performance drivers that produce an aggregate KPI. An aggregate KPI is a fundamental performance metric, such as revenue, margin, and operating cash cycle. While aggregate KPIs are important, effective performance management requires managing the drivers of outcomes.

For example, revenue performance may be influenced by operational drivers such as on time, in full (OTIF) delivery. If OTIF declines, revenue performance may suffer. But understanding the issue requires investigating the drivers of OTIF, including inventory availability, production constraints, logistics performance, and changes in demand.

Truth Domains provide the business context needed to understand the strengths and weaknesses of performance that drive business outcomes.

As Trusted Facts are established across these drivers, the Truth Domains provide greater clarity into operational truth.

Operational Truth

Operational Truth emerges when enough Trusted Facts and Truth Domains have been established to create a reliable understanding of forces driving business performance. Operational Truth emerges as business context is engineered into the operating environment. When Operational Truth exists, leaders across finance, sales, and operations can identify misalignment in cross-functional planning and execution and work together to improve coordination.

Cross-functional discussions no longer focus on debating what is happening. They focus on deciding what actions to take to improve results. In this environment, Finance and FP&A operate as strategic partners to the lines of business, helping guide decisions.

Operational Truth creates the conditions necessary for Trusted AI™.

Specific Uses of AI

Artificial intelligence can be applied safely when it is grounded in Trusted Facts.

An effective AI tool can be designed when three conditions exist:

  1. The organization has established Trusted Facts.

  2. The business context behind those facts is understood.

  3. The questions AI is allowed to answer are clearly defined.

When these conditions are in place, AI can be deployed within carefully designed guardrails. These guardrails define what information the AI can access, what questions it is allowed to answer, and who is authorized to ask them. Role-based security ensures that people only see insights appropriate to their responsibilities.

If the concept is new, think of these guardrails as embedding the experience that normally lives in the heads of your best people into the AI system. The prompts and rules that guide the AI are engineered to reflect how the business actually operates. When designed this way, leaders can explore insights through a conversational interface while the AI stays within the bounds of what is true and receives AI Trusted Insight. The user of AI cannot wander outside the trusted data or the approved business logic.

This approach allows organizations to begin applying AI to specific business questions while the Trusted Facts foundation continues to expand. As more facts become certified and the organization’s Truth Domains mature, the value of AI analysis increases dramatically.

AI becomes more powerful because it is grounded in a growing body of Trusted Facts and Truth Domains.

Governance for Trusted AI

Trusted AI requires disciplined governance.

Two councils support this process.

Trusted Facts Certification Council™ (TFCC)
Responsible for certifying performance drivers and resolving definition conflicts.

Operational Truth Council™ (OTC)
Responsible for evaluating cross-functional performance issues, Truth Domains, and AI initiatives. The council includes leadership representation from business, technology, security, and legal functions to ensure AI initiatives meet enterprise governance, risk, and compliance requirements.

AI initiatives advance only when the required Trusted Facts exist and the expected business impact is clearly defined.

Business and IT Team Alignment

AI initiatives require joint ownership between business leadership and technology leadership.

Every initiative must have:

Business Lead
Responsible for measurable business impact.

Technical Lead
Responsible for feasibility, architecture, and operational integration.

This partnership ensures that AI solutions are designed to solve real business problems and are technically feasible.

AI requires relentless attention to the business value and technical requirements, as well as risks before investment.

Truth Stewards

Every certified Trusted Fact™, Truth Domain™, and Trusted AI™ use case must have a Truth Steward.

Truth Stewards are responsible for maintaining the operational integrity and business relevance of the truths that guide enterprise decision-making and AI systems. Their role ensures that certified truths are clearly defined, properly governed, and consistently applied across the organization.

Truth Stewards are responsible for:

  • Maintaining definition clarity and certification integrity

  • Governing role-based access and operational use

  • Monitoring usage and measuring business impact

  • Escalating changes or issues to the Trusted Facts Certification Council™ (TFCC) or the Operational Truth Council™ (OTC)

Truth Stewards also participate in cross-functional operating cadences where performance drivers are reviewed and discussed. Their involvement ensures that Trusted Facts, Truth Domains, and Trusted AI capabilities remain aligned with how the business actually operates.

Stewardship ensures that trusted measures, domains, and AI capabilities remain reliable and useful over time.

Trusted AI requires both certification and stewardship.

The Trusted Facts AI Flywheel

Certified Trusted Facts create the foundation for Trusted AI.

As AI initiatives are developed, new insights emerge about performance drivers, workflow dependencies, operational constraints, and decision governance. These discoveries often reveal the need for additional Trusted Facts.

Each cycle strengthens both the Trusted Facts foundation and the effectiveness of AI solutions. With each sprint, teams and individuals develop a deeper understanding of performance drivers of business outcomes and begin to think about problems through an Operational Truth lens.

This creates a reinforcing cycle of clarity, learning, improvement, and business impact.

Key Takeaway

If you take away nothing else, please make it that AI readiness is a leadership discipline grounded in truth. In the Trusted Facts Playbook, Certified Trusted Facts expand and mature into Truth Domains, which lead to Operational Truth. Trusted Facts lead to Operational Truth.

Trusted Facts enable Trusted AI.