A maturity model for AI

AI maturity model

Determining the position of your company in its AI journeyJannik KlaukeJust now·6 min read📸 — StatworxAs digitization is becoming the norm in most organizations, the next era of transformation, namely the integration of AI into the day-to-day business has arrived.In a survey of more than 1800 executives in 2019, 30% have already implemented an AI strategy that aligns with their corporate goals. 63% of respondents reported revenue increases yielding from AI adoption.[1]To achieve a successful AI adaptation, a first thing to do is to determine the current level of AI maturity in the company. Only if you know where you currently stand, and what is possible, you can derive what actions you have to take to go there, and which steps and phases to pass along the way. Thereby, questions are answered such as:· What is the position of the company in the application of intelligent technologies and AI capabilities?· How will the application of AI be useful in the future? (short, medium and long term)· Which products, services and internal processes are affected by AI?· And most importantly, how do we need to start to determine the degree of maturity?To answer the last question, we have developed the following model to help determine the level of AI maturity in a company. It can also be applied on a more granular basis within the company such as on a departmental or divisional level. AI maturity is classified into five distinct maturity levels: aware, ad-hoc, opportunistic, integrated, or transformative. To achieve that, we have identified six dimensions that will help managers derive concrete measures to determine their AI maturity level before increasing it and successfully lead the AI front of tomorrow.Six maturity dimensionssix dimensions of AI maturity — image by authorDimension 1: DataData is the foundation for the successful application and scaling of AI technology in a company. Due to many common issues, such as overwhelming data accumulation, data quality and frequency of data input, data is the most significant operational challenge for many organizations instead of being considered as an important strategic asset. Access and quality of organizational data is required to realize the full potential of AI solutions. During AI maturity identification, a holistic view on the organizational data is essential.Dimension 2: Use CasesThe ability to identify and develop potential value-adding use cases for artificial intelligence is crucial. In order to do that, it is important to be aware of the limitations and possibilities of AI and transfer that knowledge to practical business problems. Processes for identifying and prioritizing AI use cases based on feasibility and success criteria are important in the scaling phases when various departments are utilizing AI for their business problems.Dimension 3: Team and SkillsA successful build-up of AI capabilities in a company is highly dependent on internal AI know-how and related skills. It is thus important to have the appropriate AI talents available before implementing AI. Building maturity in this dimension is vast and can range from meaningful job advertisements to suitable training concepts for upskilling internal employees.Dimension 4: InfrastructureIT infrastructure forms the technical foundation for the development of AI applications. AI experts need to have the right tools to develop their applications and the ability to make them accessible throughout the organization. Cloud technology adaptation is also becoming an important indicator in determining the level of AI maturity. AI projects can not only be deployed in the cloud, many large cloud providers also offer AI services that can be leveraged.Dimension 5: GovernanceVarious factors play a role in the process of undergoing comprehensive governance in AI projects.Risks involving AI must be identified and compliance to regulations as well as internal policies must be monitored in the solutions. After KPIs and metrics have been agreed upon, frequent reports should be made to ensure successful steering of AI initiatives. Other factors that are important in this context are AI ethics and explainability of AI.Dimension 6: OrganizationThe benefits that AI teams generate depend often on how well they are integrated at the organizational level and if the organizational conditions are adapted to it. The adaptation of internal processes to an agile, AI-oriented approach and the change in the mindset of the culture also contributes to the initiative’s success.Solution: AI MaturityWe at STATWORX GmbH have developed a model to capture the current status of AI maturity in a company or department. Based on practice experience and current research we defined five levels of AI maturity:five levels of AI maturity in a company — image by authorLevel 0: AwarenessCompanies in the state of awareness, have not implemented AI yet. The company is aware of the existence of AI and potentials might are known. Nonetheless, the touching points with AI go no further than that. Analysis is done manually without any intelligent tools and data storing methods at all.Level 1: Ad-hocIn this stage, AI adoption is inactive and not considered in the corporate strategy. Knowledge and AI awareness of AI technology are scarce, and data is mainly stored in fragmented systems. Planning and decision making are rarely data-based along with simple training initiatives. Many organizations are at this level or transitioning to the next level of AI maturity.Level 2: OpportunisticIn the second state of the AI maturity model, companies have identified that AI is an important future topic and have taken the first steps to explore the potential of AI. A central platform for AI in the organization does not exist at this stage. Tools and know-how are only available at an operational level to a certain extent. A few stakeholders push for AI initiatives and in some cases, AI models have made it to near production stages at a departmental level.Level 3: IntegrationIn this level, AI is applied in most areas of the company and has been integrated into existing products, services or processes. AI has become a standard technology within the organization and rules for governance of AI models are defined and followed. AI also serves as a basis for decision-making and is centrally managed.Level 4: TransformativeIn the last stage of AI maturity, AI is part of the business model and is firmly embedded into the organization and corporate strategy. At this stage, own products based on AI may be marketed and AI initiatives have been successfully implemented and interconnected within most divisions. AI competencies and training are widespread and have been systematically built up and cultivated. Data is given a high priority and is seen as both raw material and product. AI is also fully exploited in compliance to regulatory and ethical standards. Teams have central access to data and AI solutions are managed in the organization’s own AI platform.Increasing AI MaturityOnce the organization’s AI maturity level has been identified, the next important question arises: How to increase the AI maturity? Take the following three steps and implement the outcome to boost your AI maturity.increasing AI maturity — image by authorConclusionAn AI strategy sets the stage for a systematic implementation of AI within the organization. All measures to increase the level of AI maturity are pointed towards the dimensions of the organization’s holistic AI strategy and have to be aligned with the general strategic direction of the organization to avoid conflict of interest. By formulating an AI strategy, the increase of the maturity level can be accelerated significantly.You should use this model t determine your level of AI maturity both for the entire organization or individual departments. When increasing AI maturity level, steps should be taken to reduce AI weaknesses and concrete defined action steps should serve as an action plan.Next StepsI hope that this brief introduction to the fundamental dimensions of an AI strategy was helpful to you. Let me know your thoughts and ideas!If you want to learn more about the five levels of maturity and how to advance in your AI journey, you can find our whitepaper on the topic here.References:[1]: https://www.mckinsey.com/featured-insights/artificial-intelligence/global-ai-survey-ai-proves-its-worth-but-few-scale-impact#

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