ZenAI Change Impact Planner

What else needs to change when you introduce AI? Explore dependencies, responsibilities and evidence for one initiative.

Describe one initiative. Get a structured worksheet of questions, suggested evidence and a scenario to test. Your inputs describe your context; suggested dependencies still require investigation.

Use non-confidential information. Inputs stay in this page and are not submitted to ZenAI. Privacy notice · Method and research foundations

1. What business outcome should improve?

Use a short, non-confidential description, for example: Help employees find current policy guidance.

2. What will AI primarily help people do?

Choose the main function within this initiative.

3. Which work or decisions could be affected?

Choose the context with the most significant consequences in your scope.

4. What is the main information or system dependency?

This identifies where to start investigating. Other dependencies may still apply.

5. How will people control the use of AI output?

Choose the intended arrangement, even if it is not implemented yet.

6. What supporting evidence is available today?

Consider the outcome baseline, test findings and operating controls together.

0 of 6 inputs completed

Method and research foundations

Connected enterprise context for a defined change

This contemporary ZenAI tool draws on the idea that a proposed change needs examination across business outcomes, work, information, systems and decision responsibilities. It is a lightweight planning aid, not the complete CCMM assessment or a connected enterprise repository.

Research provenance

Sunil Mysore Kempegowda, Enterprise Architecture Driven Approach for Digital Transformation of Modern Organization, UTS PhD (2018). Section 4.4.4 discusses CCMM across architecture phases. Section 4.5 discusses enterprise tools and connected information for impact analysis and decision support. These concepts inform topic selection here, not validation of this planner's rules.
ArchiMate + OWL/RDF: The Practical Path to an Enterprise Digital Twin (2026). The article develops a connected view of strategy, processes, information, applications and infrastructure. This worksheet does not implement a knowledge graph, live synchronisation or an enterprise digital twin.

How suggestions are selected

Each context choice selects one relevant review action. Every worksheet includes outcome and baseline guidance. The AI function selects one illustrative test scenario. Each suggestion shows the answer that caused it to appear. The order follows the worksheet topics and is not a calculated priority ranking.

There are no scores, risk weights, forecasts or automated approval decisions. Evidence described as available is self-reported. An unknown answer produces a scope or evidence clarification action. The planner does not inspect enterprise systems or verify the relationships you describe.

Human–AI interaction review

The worksheet also offers an optional, expandable review of how people understand, inspect, correct and control AI output. ZenAI wrote the review prompts, evidence suggestions and tests. They apply selected themes from Microsoft Guidelines for Human-AI Interaction. The Microsoft HAX Design Library provides the original guidelines and examples.

Scope and reliability relate to G1/G2; context and affected users to G4/G5/G6; explanation and uncertainty to G10/G11; correction to G8/G9; consequences and controls to G16/G17; and behaviour changes to G14/G18. These are topic mappings, not equivalent tests of the complete guidelines. The six original inputs remain unchanged.

Scope, evidence, correction and authority checks appear in every worksheet. A context check also appears for customer-facing, consequential or unclear work. A change-management check appears for document, record or connected-system dependencies, reviewed evidence, or action-performing functions. Unshown checks may still be relevant and should be considered during a comprehensive review. This is not a compliance score, certification or endorsement by Microsoft. The original guidance does not validate ZenAI's selection rules or tests.

Scope and interpretation

The initial scenario library covers question answering, summarisation, recommendations and bounded system actions. It is not exhaustive. Suggested acceptance criteria need tailoring and approval by the relevant owners before testing. Carry out system-action tests in a safe test environment.

The current questions, rule mappings and examples are original ZenAI content. The 2018 research does not establish validation of this 2026 AI planning tool. No third-party endorsement or standards conformance is implied.