AI Readiness Assessment: Evaluate Your Company in 5 Minutes

Introduction · 2 quick Questions

Before we get started, let’s briefly discuss your vision.

Two introductory questions will help us tailor the assessment to your situation. This is followed by the three diagnostic dimensions.
The entire process takes about 5 minutes.

Introductory question A

What is the main reason for getting involved with AI right now?

This helps us tailor the recommendations in the report to your vision.

Cut costs and reduce manual labor

Accelerate growth – achieve more with the same team

Competitive pressure – Competitors are already using AI

Improve quality and reduce the error rate

It's still unclear – we want to figure out what's possible first

Introductory question B

How ready is the company to make a decision about AI?

An honest assessment helps us recommend the right next step.

Orientation phase – we'll take a look first

There is interest, but no internal consensus has been reached yet

The decision has been made – it's time to get down to business

Ready to go – the budget and mandate are in place

Answer both questions briefly

Go on: AI-Potential →

Dimension 1 · AI-PotenTial

Where is AI making an immediate impact in your organization?

During the assessment, we categorize use cases using a three-wave approach (quick wins, scalability drivers, strategic levers), create a canvas for each quick win, and provide a platform recommendation rather than a patchwork of tools. The following questions serve as the basis for this.

Question 1.1 · Wave-1-Maturity

What percentage of your core processes are still performed manually today?

In the assessment, we identify Wave 1 quick wins (2–6 weeks to value). A high proportion of manual work = more immediate opportunities for improvement.

Over 70% – almost everything is done manually, with Excel and email dominating

40–70% – a mix of both; some processes are automated, but many are still done manually

20–40% – well-positioned, but with specific gaps

Less than 20% – highly digitized, with AI as the next step

Question 1.2 · System Landscape & Data Readiness

How is your system landscape structured and how mature is your data?

In the assessment, we distinguish between Wave 1 (platform use cases without preliminary data preparation) and Wave 3 (strategic levers with a data project in the lead-up).

Data scattered across emails, Excel files, and paper – virtually impossible to consolidate

ERP or CRM systems are in place, but there are many data silos and gaps

Central systems, regular maintenance, reports running

Clean database, APIs available, analyzable in real time

Question 1.3 · Quick-Win-Candidate

Clean database, APIs available – which area is currently taking up the most time or causing the most stress? Analyzable in real time

In the assessment, this area is assigned its own canvas: Problem, User Group, Data & Tools, Owner, Launch Date, Success Metric.

Document processing – invoices, contracts, reports, product catalogs

Email Triage and Customer Communication – Inquiries, Support, Complaints

Reporting & Analytics – Consolidating Data from Multiple Systems

Quotation Preparation & Sales Support

Meeting minutes and internal knowledge management

Multiple areas at once – prioritization is still pending

Question 1.4 · Tool-Landscape & Shadow-IT

What AI tools does your company currently use?

In our assessment, we provide a platform recommendation rather than a patchwork of tools and consolidate shadow IT with clear governance rules.

None – AI is not yet an issue internally

Shadow IT – individual employees use ChatGPT and similar tools for personal purposes without authorization

Individual tools have been officially approved (e.g., Copilot, DeepL), but are not centrally managed

Centralized platform available – tools, assistants, and governance all in one place

Question 1.5 · EU AI Act-Compliance

How far along is your company with the EU AI Act?

During the assessment, we classify your planned AI initiatives by risk level and provide a concrete compliance roadmap.

No problem – I haven't looked into it yet

Known – but no concrete steps have been taken yet

In preparation – AI inventory created or guidelines defined

Well-prepared – compliance documented, risk assessment by system

← Back Go on: Staff & Competences →

Dimension 2 · Staff & Competences

Do you have the right people and are they firmly established?

During the assessment, we define the role model (central AI leadership plus champions for each department), the steering committee structure, and provide a recommendation for each key role: develop internally or hire externally?

Question 2.1 · Champion-Candidates

How many people on your team have genuine intrinsic motivation regarding AI?

During the assessment, we identify the champions from this group within each department—the key influencers without whom AI adoption in day-to-day operations would fail.

No one is visible – the issue is barely on the team's radar

A handful of individuals with a genuine passion for AI

At least one motivated person per department

Widespread Adoption – AI Has Become Part of Many Employees' Daily Lives

Question 2.2 · Central AI-Responsibility

Is there a key person in charge of AI – someone with the time and support of the executive board?

During the assessment, we define the job description for this role and determine whether it can be filled internally or must be filled externally.

No – that matter is entirely up to management

There are interested individuals, but they lack a clear mandate and don't have the time

One person coordinates this matter on a part-time basis, without a specific mandate

A dedicated role with a mandate and a set timeframe – reporting directly to management

Question 2.3 · Hire vs. Develop

How do you currently decide: hire externally or develop internally?

That is the key question that the assessment answers for every key AI role – with a recommendation for each position, including a job description when a hire is recommended.

Reactive – we hire when someone resigns or a vacancy arises

A gut decision – we weigh the pros and cons, but without a clear method

We are reviewing both options, but not yet systematically for each role

A structured make-or-buy process with clear criteria for each key role

Question 2.4 · Control & Steering Circuit

How is AI managed in your company?

During the assessment, we define the steering committee structure: who makes decisions, who drives the process, and who implements them – ensuring alignment between the executive and implementation levels.

Not at all – AI just happens on the side, without any direction or rhythm

Ad hoc – Issues are discussed when they become urgent

Regular meetings, but without a clear division of roles between management and implementation

Steering committee established – management, AI leads, and champions meet regularly

Question 2.5 · Enablement & Visibility

How can AI expertise be developed and highlighted within a team?

In the assessment, we recommend specific formats: executive briefings, departmental workshops, and personalized learning paths tailored to each role and level of maturity.

Not at all – everyone finds out for themselves, if at all

Individual workshops or external training sessions, without a systematic approach

Structured enablement has begun – e.g., initial workshops, newsletters, learning paths

Established program – regular sessions, role-specific learning paths, tangible results

← Back Go on: Development Efficiency →

Dimension 3 · development efficiency

Does your team use agents – or do you still do everything manually?

During the assessment, we measure the DORA baseline (lead time, deployment frequency, change failure rate), evaluate the AI coding stack for systematic adoption, and ensure code quality. If you do not have an internal development team, please indicate this in the first question.

Question 3.1 · Team-size

How large is your in-house development team?

Helps scale the recommendations. For larger teams, AI-native workflows often provide the greatest impact.

Question 3.2 · Agents instead of Code

Is your team building AI agents for recurring workflows, or are they still programming every workflow by hand?

This is the key factor for 2026: Teams that build agents instead of code deliver 5–10 times faster. In our assessment, we evaluate whether the necessary conditions are in place.

Traditional – every workflow is implemented in code; no agents are used

Early experiments – individual developers are trying out agent frameworks on their own

First agents are now live – but there is still no clear architecture or standards in place

Agent-First – the team thinks in terms of agents; code is the exception

Question 3.3 · KI-Coding-Stack

To what extent have AI coding tools been systematically implemented within the development team?

GitHub Copilot, Cursor, Claude Code, and more. In our assessment, we outline the adoption path—from a trial tool to a structured stack with measurable productivity gains.

Not at all – AI coding tools aren't even on the team's radar yet

Shadow adoption – individual developers use tools privately, without adhering to standards

Licenses available – Adoption varies, impact difficult to measure

Structured implementation – onboarding, workflows, and adoption established in a measurable way

Question 3.4 · DORA-Baseline & Code-Quality

How do you measure delivery speed and code quality today?

DORA metrics (lead time, deployment frequency, change failure rate) will be standard for AI-augmented teams by 2026. During the assessment, we establish a baseline and ensure quality through AI reviews and test coverage.

Gut feeling – we don't systematically measure either delivery speed or quality

Selective metrics, e.g., story points, but no consistent metric logic

Initial DORA metrics established; code quality assessed through manual reviews

DORA Baseline Live, AI-powered code review, turnover rate as an early warning system

← Back Go on: Contact →

Last Step · Evaluation

Where should we send your evaluation?

Please provide a few details about yourself and your company—we’ll then generate a personalized report right in your browser. Required fields are marked with an *.

Person & Contact

Full name *

Your Position *

Phone

E-Mail (business) *

Company

Company *

Branche *

Number of Employees *

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