Enterprise Business Architecture Package: AI Transformation Blueprint

The Enterprise Business Architecture Package describes the enterprise around an industry's core operations, from strategy and finance to people, technology, risk and corporate affairs, with an AI layer in every part. Architecture and transformation teams at banks, insurers, asset and wealth managers and payments firms place it beneath their industry model as the enterprise view. It contains 865 Level 3 capabilities with AI profiles, 20 value streams that cross functions, a data model of 398 entities, 79 agent specifications, 119 use cases and 80 controls. The package is industry-neutral, so lending, underwriting and trading belong to the industry model.

What it is

Inside the Enterprise Business Architecture Package

The package is the enterprise capability model with the full architecture added around it. It includes the Capability Model edition unchanged, 10 Level 1 domains, 112 Level 2 groups and 865 Level 3 capabilities with an AI profile and KPIs on every Level 3, and links each Level 3 capability to the agents, data entities, use cases and value stream stages that use it.

Its 20 value streams describe work that runs between functions, for example Strategy to Execution, Order to Cash, Hire to Retire, Record to Report and Risk to Assurance. The 144 stages set current practice next to an AI-native design and name the agents, the target AI mode, the human checkpoint and the KPIs of each. One business data model sits under the streams: 30 subject areas and 398 entities, a single record for a party that plays several roles, and a sensitivity class and data-quality requirement on every entity.

The 79 agent specifications state for each agent what triggers it, which tools it may use, its guardrails, when it hands a case to a person and who owns it, and every agent runs on one platform for identity, authority limits, action logs and monitoring. The 119 use cases are business cases tied to capabilities, value streams, agents and data. Responsible AI principles and 80 controls apply one set of risk tiers to every AI use, model and agent.

One Design for the Whole Enterprise

Each value stream crosses two or more areas of the enterprise; examples are Strategy to Execution, Order to Cash, Hire to Retire, Risk to Assurance and AI Idea to AI in Operation. In the data model each business concept appears once, and a customer that is also a supplier is one party. Agents operate across functions or along the value streams and share one platform for identity, authority limits, action logs and monitoring. Every AI use, model and agent falls under one governance framework, and a named person decides each consequential outcome. About This Model describes the design and why the model has three levels.

The deliverables

What the Download Contains

Everything in the Capability Model edition is included, with the enterprise layers around it:

The model

• The complete AI-Ready Capability Model edition: 10 L1, 112 L2 and 865 L3 capabilities with definitions, an AI profile and KPIs for every Level 3 (3,369 KPIs), Level 2 rollups, prioritization, the AI heatmap and a 40-question readiness assessment
• 20 value streams across functions and 144 stages, each stage with its steps in current and AI-native form, the agents involved, the target AI mode, the human checkpoint and KPIs
• One business data model of 30 subject areas, 398 entities, 2,973 attributes and 1,805 relationships, with each entity's sensitivity and the data quality AI requires
• Each Level 3 capability cross-referenced to its agents, data entities, use cases and value stream stages

AI and governance

• 79 enterprise agent specifications, each naming its triggers, tool permissions, guardrails, escalation paths and human owner, on a single shared agent platform
• 119 use cases set out as structured business cases, grouped by wave and value driver
• 80 controls with responsible AI principles, mapped to risk tiers, agents and the platform
• An AI operating model covering governance bodies, decision rights, a RACI, an agent lifecycle, role impacts and new roles
• A roadmap in three waves

Files and terms

• The Capability Navigator: capabilities, value streams, agents and the data model in one browser page, searchable, filterable and linked
• To begin, a Welcome document; then About This Model, a leadership presentation template to adapt, the capability map and value streams decks, standalone documents for the capability definitions, KPIs, data model, agent specifications, use cases and AI governance, the Excel workbook, the implementation guide
• Bonus files included: an enterprise glossary, A Practical Guide to Business Architecture, a capability modeling overview, an AI-ready capability profile template, capability relationship mapping templates, roles in the enterprise, operating model archetypes, a transformation overview and framework, a framework-to-enablement guide, a capabilities to microservices and AI agents mapping example, and the business architecture leader's role
• Corrections free of charge, and new versions free for 180 days after purchase

Your organization's name and license ID are printed in every file. Ratings reflect a typical large enterprise; treat them as a first draft of your own.

The Problem Behind It

In a financial services firm, the functions around the core business usually meet AI one at a time. Finance trials an assistant for the close, operations automates a reconciliation, the service center adds a chatbot and procurement buys a contract tool, and each team writes its own data definitions, approval limits and controls. The firm ends up with several partial pictures of itself, agents that cannot pass work to one another, and a governance group that reviews the same questions again for every project.

The package describes those functions as one enterprise. Value streams cover the work end to end, the data model defines each concept once, the agents share one platform and one set of authority limits, and the controls use the same risk tiers everywhere. An architecture team can lay the industry model on top, compare AI proposals from every function on equal terms and decide the sequence of the program once.

Who It Is For

Heads of enterprise architecture. Adopt the package as the enterprise layer beneath the industry model, and map applications, data and change initiatives to it.

Chief AI officers and AI program leads. Staff and sequence the program from the use case portfolio, the agent specifications and the roadmap, and keep every team's agents on the shared platform and its rules.

Chief data officers and data governance leads. Set one definition and owner for each business concept, and the sensitivity and quality rules an agent must meet before reading data.

Model risk, compliance and internal audit teams. Use the principles, controls and risk tiers as one framework for AI, and test the evidence each control asks owners to keep.

Operations and shared services leaders. Use the value streams to agree on where AI changes the work first and which decisions stay with a named person at each stage.

Putting it to work

Use Cases

Placing the enterprise layer under an industry model. Combine the package with the firm's industry model, which holds core operations such as lending or underwriting. The capabilities and value streams give the industry detail a common structure to attach to, so the two models read as one architecture.

Building the AI roadmap across functions. Score the 119 use cases with your own value and data readiness ratings and sort them into the three waves. Dependencies surface early, because every use case names the capabilities, agents and data it needs.

One platform for every agent. Decide from the platform components and agent specifications what all agents share: identity, authority limits, action logs, human review and monitoring. Teams then build on one foundation instead of buying separate tools.

Redesigning a cross-functional stream. Take Order to Cash, Record to Report or Hire to Retire, set each stage today beside its AI-native design, and agree with each function where a person keeps the decision. The stage names its capabilities and agents, so the redesign stays tied to the architecture.

Preparing the data foundation. Check the 30 subject areas and 398 entities against the data you hold and the systems that hold it. Each concept recorded once, with its sensitivity and quality requirements, becomes data work scheduled ahead of the use cases that need it.

Setting up AI governance. Fit the principles, controls, governance bodies and decision rights to the committees the firm already runs. The risk tiers show which agents and use cases need the governance group's review and who approves each.

The economics

The Alternatives

A firm that wants an enterprise architecture with an AI layer has three ways to get one, and they differ in how much effort goes into structure every enterprise has in common.

• Building it from a blank slate. Architects gather capabilities and processes from each function, resolve names and overlaps, model shared data, and only then design agents, use cases and controls. Every layer depends on the previous one, and keeping them consistent across functions takes repeated rounds with each domain owner.
• Hiring consultants to build it. An outside team runs workshops and delivers the layers, often from material it already has. Much of the fee covers drafting what all enterprises share, and the links between layers are only as consistent as that team's own checks.
• Starting from this model. Work begins with the layers already linked: capabilities to stages, stages to data, agents and use cases to both, and controls to risk tiers. Workshops are spent on ratings, oversight, removing what the firm does not do, and naming who approves each decision.

Fitting the architecture to the firm and running the change still need people who know it, internal or external. A linked starting point lets that work begin at the first meeting.

Getting Started

These steps take an architecture team from the download to an approved first wave:

1. Read the Welcome document and About This Model, then the implementation guide for the order in which to use the files.
2. Open the Capability Navigator in a browser to move between capabilities, value streams, agents and the data model.
3. Set the industry model beside the package and mark where its core operations attach.
4. Review each value stream with the process owners involved and note where your stages differ.
5. Compare the data model with your data and list the gaps the first use cases rely on.
6. Score the use cases yourself, name the approver for each decision, and take the first wave, the controls and the leadership presentation to the executive team.

Public sample

A Sample Profile

The sample is 0.15% of the package and traces one thread through it: strategic environment analysis. The fields below come from the Strategic Environment Analysis (EN-1.1.1) AI profile:

• AI mode: Augment
• Oversight level: Human-in-the-loop
• Risk rating: Moderate
• Wave: Wave 1
• Fit, value, feasibility and data readiness scores: 4, 4, 4, 3 on a 1–5 scale
• Patterns of work: Analysis & insight, Knowledge retrieval
• What AI could do: Scan licensed market research, competitor announcements, analyst coverage and industry news each week and summarize the developments that touch the enterprise's markets, with a link to every source
• What people decide: The Chief Strategy Officer decides which external developments the strategy must respond to, on the environment analysis the Strategic Planning Lead prepares

Upgrading Later

Customers who bought the AI-Ready Capability Model edition within 90 days receive its full price as credit against this package. Email your order number to support@finantrix.com for a one-time checkout code.

Read before you buy

Common Questions

Which edition fits my team?

The Enterprise Capability Matrix: AI-Ready Edition gives you the capability model, an AI profile and KPIs for every Level 3 capability, prioritization, the heatmap and the readiness assessment. This package gives you the same and adds the value streams, the business data model, the agent specifications and shared agent platform, the use cases, responsible AI principles and controls, the operating model and the roadmap, a leadership presentation template, and bonus files on roles, operating model archetypes and transformation.

How does this package fit with the functional blueprints?

Its agents are enterprise agents: they work across functions or along the enterprise value streams, and an agent that works inside a single function is part of that function's package. Pair this package, as the enterprise view, with a functional blueprint wherever one function needs its full depth, for example Finance and Accounting Business Architecture Package: AI Transformation Blueprint, Technology Business Architecture Package: AI Transformation Blueprint and Governance, Risk and Compliance Business Architecture Package: AI Transformation Blueprint.

Does it go down to Level 4?

No. It runs from Level 1 to Level 3; for more detail in one function, use that function's model next to this one.

Is it built for one industry?

No. The package is industry-neutral: core operations particular to one industry, such as lending in a bank or patient care in a hospital, are outside it, and work that applies only to enterprises that make, move or service physical goods is marked.

Can our internal AI tools use the content?

Yes, inside your organization. The Enterprise license covers internal tools, including assistants and agents you run yourselves. No license permits using the content to train, fine-tune or prompt AI systems on behalf of third parties.

Does it address AI laws and regulations?

No. The content is business architecture by intent: capabilities, value streams, data and the AI layer describe what the enterprise does and where AI fits, which holds under whatever laws apply to you. The risk tiers, principles and controls are lasting practices for your compliance team to map to the jurisdictions you operate in.

What happens when the 180 days end?

The license continues with no end date, and corrections stay free for as long as you use the files. New versions released within 180 days of purchase are free, and we email a download link for each. After that nothing renews, and new versions are offered at 25% off.

Could an AI assistant write this instead?

A chat assistant can list enterprise value streams or AI use cases quickly, and that helps for orientation. An enterprise blueprint must stay consistent across its layers and its functions. In this package every link between capabilities, stages, entities, agents, use cases and controls is checked before release, IDs are stable, each concept is defined once, and each agent and use case carries a risk tier and a named decision maker. A generated answer varies with the prompt and checks none of this, and the gaps appear once risk, finance and operations leaders review the same plan.