AI readiness check
Targeted use of AI - with a plan instead of a gut feeling
AI readiness check with MaibornWolff
Would you like to strategically anchor artificial intelligence in your company - but don't yet know exactly where you stand? Our AI readiness check will help you gain clarity: in a structured, efficient and interdisciplinary way.
Within two weeks, we will work with you to analyze how well your organization is prepared for the integration of AI and how we can best position it for an AI future. The result is a clear roadmap that shows how you can create real added value.
Strategic clarity
We help you to sharpen your goals, visions and strategic ambitions around AI - and put them on a resilient, long-lasting foundation.
Interdisciplinary perspective
All relevant stakeholders are involved: Management, IT, HR and specialist departments contribute their perspectives.
Structured process
Our check follows a clear, proven process: from measurement and evaluation to a prioritized roadmap.
Concrete results
You don't get theory, but tangible results: Status quo assessment, target image, action plan and certainty of action.
AI Readiness Check - your benefits with MaibornWolff
Many companies start with AI - but often without a strategy that really pays into the company's goals. The result: individual measures without effect, a lack of clarity about responsibilities, a lack of acceptance within the team or unsuitable AI tools. This is exactly where our AI readiness check comes in.
We ensure that you invest in AI in a targeted manner and have a clear basis for action instead of getting lost in too many use cases.
Transparent actual status
Companies receive a clear and comprehensive overview of their current status in the field of AI. This means you know exactly where your company stands - professionally, technologically and organizationally.
Work effectively & efficiently
The structured process only takes two weeks and creates clarity about the objectives and a structured roadmap.
Prioritize goals
We help you to formulate clear maturity goals and derive suitable measures. You receive a clear framework for targeted AI implementations.
Build up knowledge
The joint analysis creates a deep understanding of requirements, potential and concrete next steps.
Mapping perspectives
By involving various stakeholders such as management, HR and IT experts, a comprehensive picture is created.
Accompanying change
The check promotes the necessary awareness in the team - and provides managers with a tool for targeted management.
Who is the MaibornWolff AI Readiness Check intended for?
Our readiness analysis is aimed at SMEs and corporations in all industries, including the public sector. Decision-makers and various stakeholders within a company - including management, HR and IT experts - benefit significantly from our readiness check.
We build on our interdisciplinary perspective and assess each situation individually - just get in touch with us!
Employees can use TÜV NORD GROUP GPT in a variety of ways as a personal assistant, for example to work their way through extensive documents, support their own research or generate new input for product development, for example.
Our references & projects
A reference is worth more than a thousand words. Luckily, we have dozens of them. Click through a selection of our most exciting projects and see for yourself!
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To the STARTRAIFF referenceSTARTRAIFF: Business Intelligence for the sales forceCloudData/Data PlatformsAppsTo the STARTRAIFF referenceAggregation of internal customer data & external data in a single web application
To the STARTRAIFF referenceData bundling & analysis with Amazon Bedrock
To the STARTRAIFF referenceIntuitive user interface for sales, 88% reduced preparation time before customer visits
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To the NOW referenceNOW: National Organization for Change in Mobility: development of a data warehouse systemCloudData/Data PlatformsIT Consulting & StrategyTo the NOW referenceData foundation for nationwide charging infrastructure in Germany
To the NOW referenceCloud data warehouse for integration & analysis of many diverse data sources (AWS)
To the NOW referenceSolid architecture, single point of truth ensures data-based evaluation of charging station demand
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To the OroraTech referenceOroraTech - Security & Compliance SupportCloudCybersecurityIT Consulting & StrategyTo the OroraTech referenceRisk threat analyses for satellite startup
To the OroraTech referenceSecurity process definition, IT security risk register, action plan
To the OroraTech referenceFuture-proof IT security for successful growth
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To the Health.exe referenceHealth.exe: AI-supported platform creates training plans for patientsCloudData/Data PlatformsAppsTo the Health.exe referenceAI-supported service for orthopedic & sports medicine practices
To the Health.exe referenceCloud-based web application for doctors for the automated, evidence-based creation of individually tailored patient training plans
To the Health.exe referenceNew revenue source without fixed costs, higher patient retention, AI-supported & guideline-based
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See robotics referenceResearch: AI-supported robotics for employees with physical limitationsEmbedded Systems & RoboticsIndustry 4.0ManufacturingSee robotics referenceCustomized assistance robots for people with physical disabilities in production
See robotics referenceIntegration of AI for automated adaptation of robots to people's capabilities
See robotics referenceEffective empowerment of people with physical disabilities
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See Siemens referenceSiemens: AI demand prediction platform for industrial production planningCloudData/Data PlatformsIndustry 4.0See Siemens referenceMachine learning for time series forecasting
See Siemens referenceAutoML for automated adaptation of models to different data
See Siemens referenceUnified, scalable solution, optimized inventory costs, efficiency gains
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See TÜV NORD referenceTÜV NORD GPT: Development of AI assistanceAppsWeb & Portal PlatformsPublic/AdministrationSee TÜV NORD referenceSecure operation of AI in the European MS Azure cloud environment
See TÜV NORD referenceFrontend & backend via MS Azure App, "Chat with your PDF" for TÜV employees
See TÜV NORD referenceQuick implementation of new technologies (AI), strengthening knowledge management
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See Schöck Bauteile referenceSchöck components: Improvement of the requirements processIT Consulting & StrategyQuality EngineeringIT ModernizationSee Schöck Bauteile referenceImproved dimensioning software for the construction of load-bearing building components
See Schöck Bauteile referenceNew digital design approach, UX concepts, UI designs, user-centered focus
See Schöck Bauteile referenceHigher user satisfaction, better software with less effort
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See BMW Group referenceBMW Group: Replacement of a production-critical legacy systemIT Consulting & StrategyIT ModernizationManufacturingSee BMW Group referenceIT modernization, replacement of a 20-year-old legacy system
See BMW Group referenceStep-by-step migration to a modern, flexible architecture & platform
See BMW Group referenceHigh stability & reliability, long-term scalability
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See MAN referenceMAN: Secure Software Development Life CycleCybersecurityIT Consulting & StrategyQuality EngineeringSee MAN referenceProtection of digitalized vehicles against virtual attacks & digital threats
See MAN referenceSSDLC in vehicle backend systems (UNECE R155), cybersecurity management system
See MAN referenceGuidelines, methodologies & tools for independent risk identification, assessment & treatment by employees
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See Bayernwerk referenceBayernwerk: Knowledge management via teamsCloudIT Consulting & StrategyIT ModernizationSee Bayernwerk referenceTeams app for service technicians
See Bayernwerk referenceUser-centered, intuitive UX/UI design
See Bayernwerk referenceIdentification & utilization of implicit knowledge within the company
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See referencePlanning systems: Optimizing the capacity utilization of pressing plantsData/Data PlatformsIndustry 4.0ManufacturingSee referenceCentralized planning of component manufacturing for cost- & resource-optimized production capacity worldwide
See referenceConversion from local processing with fat clients to a client-server application, migration to the cloud
See referenceData-based planning & calculation of different manufacturing scenarios & site-specific production costs
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See referenceGlobal workforce planning systemCloudData/Data PlatformsPublic/AdministrationSee referenceCentralized web-based IT system to replace individual isolated solutions
See referenceEvent sourcing for planning & analytics, domain-driven design, cloud migration
See referenceEasy updates, expansion, maintenance, optimized security
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See DEKRA referenceDEKRA: Modern enterprise architecture thanks to co-creationCloudIT Consulting & StrategyIT ModernizationSee DEKRA referenceOperational & technical harmonization of the legacy IT landscape
See DEKRA referenceEnterprise architecture as co-creation by the lead architects of all IT business units
See DEKRA referenceEA community worldwide for all operational units
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See digikoo referencedigikoo: A data platform for the Azure CloudCloudData/Data PlatformsIT Consulting & StrategySee digikoo referenceData-based information for planning & implementing the climate transition for the public sector & energy providers
See digikoo referenceScalable foundation data platform on MS Azure for migrating & automating differently formatted geo-data into a structured data schema
See digikoo referenceQuality-checked data, provision in the form of the target data model, robust, scalable database & infrastructure
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To the FinOps referenceTravel information systems: 25 percent savings in cloud costs and stable operation thanks to FinOpsCloudIT Consulting & StrategyWeb & Portal PlatformsTo the FinOps referenceAlignment of the distributed travel information system with many data sources & target groups on the AWS cloud
To the FinOps referenceFinOps: cost transparency, cloud strategy, system & architecture design, usage-based operating times, early anomaly detection
To the FinOps referenceCost transparency at team level, lean operating processes, robust observability
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To the FinOps referenceSupply chain management: Reducing cloud operating costs by 50 percent with FinOpsCloudData/Data PlatformsIT Consulting & StrategyTo the FinOps referenceReduction of costs caused by over-dimensioning & manual processes, establishment of transparency
To the FinOps referenceTargeted process modernization, automation & rightsizing
To the FinOps referenceAnnual cloud operating cost reduction: 400,000 EUR, scalability, reliability
AI readiness check: procedure & content
In just two weeks, we systematically determine the current status of AI integration in your company. Once the status quo is clear, we work together with the most important stakeholders to determine how AI can be successfully implemented in your company.
The AI readiness check involves the following specific steps:
1. contact
In an initial meeting, we ask about the needs and framework conditions, such as whether there is already an AI initiative, who is driving the topic and the framework in which the AI readiness check would be embedded.
2. workshop & interview planning
We plan the implementation of the readiness check in the form of a workshop and involve various stakeholders from management, specialist departments, HR and IT. We also jointly determine the time horizon for the objectives and measures to be developed - usually a period of around 6 to 18 months.
We go through the readiness check with the client in advance. We adapt terminology to the situation, thereby increasing people's understanding in the workshop and reducing potential resistance. We also adjust and supplement individual questions as required in order to evaluate your company even better, for example if you would like to offer AI services yourself.
3. carrying out the measurement
Our AI maturity model will be applied in the workshop (and possibly in the interviews). Six central dimensions are considered from an interdisciplinary perspective, including:
- Strategy (AI as part of the strategic direction),
- Application of AI (identifying and leveraging potential),
- Talent and culture (building and distributing knowledge, AI in everyday working life),
- Technology (use of an AI platform with defined AI architecture),
- Data (preparation, access and use as well as quality optimization) and
- Change management (creating awareness for change).
The workshop participants vote together on each question of the maturity model, discuss their different points of view and agree on a qualified and quantified assessment. They then define target maturity levels and concrete steps that are necessary within the specified time horizon.
At the end, the maturity level of your company is clearly on the table - including two focus dimensions, which are at the center. The prioritized roadmap for the coming months is based on these surveys.
4. target setting
Together with the decision-makers, we set short and medium-term maturity targets for the coming weeks and months. The measures are prioritized on the basis of the evaluation results.
5. development of measures & roadmap
The status quo, maturity level and goals have been determined. Now it's time to develop the specific measures and the roadmap, based on best practices and proven formats. We create a structured plan that fits the situation and the company exactly.
6. conclusion & framework for action
You will receive a detailed PDF document with all the results of the readiness check and a presentation of the current maturity level in the dimensions mentioned. We also create a management summary for top management with clear recommendations for action, the roadmap and the specific challenges that may affect implementation.
It is now possible for you to invest in artificial intelligence in a targeted manner and take the first steps independently.
7. aftercare & follow-up
Aftercare is optional. It is used to review progress and provide further support if needed. We will follow up with you in a few months to evaluate the progress you have made and your maturity compared to the starting point in more detail.
When is a company AI-ready?
A company is AI-ready when it...
- hasclear goals and strategies for the implementation of AI,
- provides an appropriate infrastructure and technology ,
- has trained staff and a supportive corporate culture,
- usesdata effectively and
- has established a change management system that actively shapes and supports change
I can see at a glance where the gaps to the target are greatest. The presentation of the results in the form of diagrams and figures is a good basis for discussions with the other stakeholders. And provides me with orientation.
AI readiness: your tasks for a successful conclusion
The readiness check is a joint process. For the AI readiness check to be a success, it also requires your commitment - strategically, organizationally and technologically. With these four areas of responsibility, you will successfully complete the AI readiness check and develop the desired AI readiness:
1. preparation & planning
- Provide relevant information and data
- Identify suitable stakeholders (e.g. from IT, HR, management)
2. active participation
- Participation in the workshop and interviews
- Contributing your own perspectives and experiences
- Openness to feedback and collaboration in the process
3. implementation & follow-up
- Implement the recommended measures according to the roadmap
- Provide resources and time for the AI strategy
- Review progress regularly and adjust measures if necessary
4. communication & cooperation
- Communicate results and measures internally
- Collaborate across departments
- Ensure management backing (buy-in & support)
Why many companies are not (yet) AI-ready
Many companies are starting out into the AI-driven future full of expectation and hope. In practice, however, they repeatedly come up against hurdles that massively slow down the successful introduction of AI. We encounter the following stumbling blocks particularly frequently in our projects:
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Unclear goals - lack of a defined AI strategy
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Technological gaps - missing or inadequate infrastructure
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Data problems - poor access and poor data quality
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Knowledge deficits - lack of training and AI expertise in the team
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Silo thinking - AI initiatives without coordination between departments
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Cultural barriers - internal resistance and low acceptance
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No change management - lack of support for change from above
AI technologies are developing at breakneck speed - stay up to date!
With the AI workshop from MaibornWolff , you can deepen the knowledge in your organization. During the workshop, participants will learn from our experts how to evaluate AI applications themselves, apply prompt engineering and tackle minimum viable products (MVP).
Our range of AI services: ready at all levels
In addition to the AI readiness check and the workshop, we also offer holistic AI consulting for companies. Take a look at our AI use cases: 33 applications of artificial intelligence - from marketing and sales to finance, logistics, production and research.
FAQ: Frequently asked questions about the AI Readiness Check
What does AI readiness mean?
AI readiness describes how well a company is prepared organizationally, technologically and culturally for the use of artificial intelligence. It is about clear goals, suitable infrastructure, qualified teams, available data and a supportive corporate culture.
What is considered in an AI readiness check?
The check analyzes the AI maturity level in six dimensions: Strategy, AI application, talent & culture, technology, data and change management. The aim is to identify strengths and gaps and derive a clear roadmap from this.