Free AI Readiness Assessment | BRUKD Consultancy

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1. Business Value

We start with whether AI is tied to a real business outcome.

How clearly has your leadership team defined where AI or automation should create value?

No clear use case yet. We are still exploring broadly.We have a few ideas, but not yet ranked by business impact.We can name priority use cases and the business outcomes they should improve.

Strong AI strategy starts with a measurable problem, not a tool search.

Can you estimate the cost, time, or revenue impact of your highest-priority opportunity?

No, the ROI case is mostly qualitative right now.Partially. We have assumptions, but they are not validated.Yes, we can estimate impact and explain why it matters now.

2. Data Readiness

Reliable outcomes require reliable inputs.

How well organized is the data needed for reporting, forecasting, or AI use cases?

Data is spread across spreadsheets, inboxes, or disconnected tools.We have some structure, but quality and ownership vary by team.Core data is centralized, relatively clean, and accessible for decision-making.

Do your teams work from a shared definition of key data like customers, products, and KPIs?

No. Definitions vary and duplication is common.Some standards exist, but they are not enforced consistently.Yes. Core definitions are standardized and trusted across functions.

If definitions shift between teams, automation and AI outputs lose credibility fast.

3. Governance & Risk

Responsible adoption depends on oversight, not just experimentation.

How prepared is your organization to govern how staff use AI tools and sensitive business information?

There is no policy or guidance in place yet.We have informal expectations, but little structure or documentation.We have clear rules, review steps, and accountability for AI-related decisions.

Could you explain why an automated recommendation or model output should be trusted?

No. It would largely operate as a black box.Partially. We could explain some parts, but not consistently.Yes. Transparency, review, and auditability are part of how we would implement it.

4. Workflow & Adoption

AI works best when the underlying workflow already makes sense.

How standardized are the workflows you would want to automate or augment?

Processes vary by person, and documentation is limited.Some workflow documentation exists, but execution is uneven.Core workflows are defined, repeatable, and ready for optimization.

How ready is your team to adopt new tools, reporting routines, or AI-assisted processes?

Change resistance is high and ownership is unclear.There is some openness, but adoption would require structured support.Leaders and teams are ready to test, learn, and embed changes.

When adoption is weak, even technically sound projects struggle to produce value.

5. Technology & Measurement

Lasting readiness means tools, integration, and KPI visibility are all working together.

How modern and integration-ready is your current technology stack?

Most systems are manual, legacy, or difficult to connect.Some tools integrate, but there are still major handoffs and gaps.Core systems are modern, cloud-based, and reasonably integration-ready.

How quickly can leadership access trusted performance metrics today?

It takes days and manual effort to produce reliable numbers.Reporting exists, but trust and speed are inconsistent.Leadership can access timely, trusted KPIs with minimal manual work.

Find your BRUKD readiness stage.

1. Business Value

2. Data Readiness

3. Governance & Risk

4. Workflow & Adoption

5. Technology & Measurement