AI-generated summary
In the era of digitalization, artificial intelligence (AI) is rapidly transforming how companies operate, driven by three key technological trends: cloud-edge computing for vast data storage and processing power, open-source machine learning frameworks from big tech firms, and high-speed telecommunications like fiber optics and 5G enabling real-time AI execution. However, many organizations struggle to begin their AI journey, often lacking a foundational shift in corporate mindset recognizing data as a critical asset. Effective data governance—identifying, sourcing, cleaning data, designing algorithms, and interpreting results—is essential but complex, requiring evolving discipline to foster a virtuous learning cycle and drive successful AI integration.
To measure digital maturity, Reinier Van Den Biggelaar introduces the 5X10 Data-Driven Maturity Model & Assessment, evaluating ten dimensions encompassing technical and organizational capabilities. Establishing a robust data culture—where data is trusted, understood, and integral to decision-making—is crucial. This culture reflects collective behaviors valuing data use and is developed through the “9 E method”: engaging employees, educating and empowering them with tools, enabling supportive environments, encouraging experimentation, embedding data as a core value, energizing success sharing, and emphasizing continuous momentum. Ultimately, companies must align AI initiatives with their vision and business goals, recognizing AI as an enabler rather than an end, to fully embrace digital transformation.
Artificial Intelligence is an enabler for digitization and data culture within companies.
In the context of digitalization, we often talk about artificial intelligence, and optimizing data-driven decision making. AI has broken into our lives faster on the back of three technological trends, as explained by Future Trends Forum expert Reinier Van Den Biggelaar, managing partner at BastaGroup and data science and AI manager at ORTEC in his remarks during the FTF meeting about the Future of Work on digital corporate culture:
- Cloud -Edge- Computing: It provides massive data storage and all the computational and processing power needed.
- Open source or open code. This goes beyond programming language, it also includes library and solution building environments, where big tech are promoting their machine learning frameworks, such as Google’s TensorFlow, Amazon’s SageMaker Neo or Microsoft’s Azure AI.
- Speed of telecommunications. Optic fiber and 5G today enable AI executed remotely with basically no wait time and very low latency.
Many companies want to leverage AI solutions, but don’t know where to start. “We must digitalize, we must digitalize” has become a mantra out of a Dilbert cartoon one would say. Reinier explains that changing the corporate mindset is essential: data are essential assets, and we should treat them as such.
Identifying data, knowing where to source them from, clean them, design algorithms to use them, having a clear goal and knowledge to interpret the responses, being capable of creating a virtuous learning circle in the process. Easy to say and tremendously complex to execute successfully. Therefore, data governance is a new discipline, still in its infant stages, but definitely critical in a few years. It must adapt and improve over time, to be effective.
In order to assess a company’s degree of maturity in digitalization, Reiner proposes the framework The 5X10 Data-Driven Maturity Model & Assessment, to check our bearings, are we having analytical problems or are we a data-driven, innovative organization. Digital maturity is defined based on 10 dimensions—all together cover all aspects of digitalization: both technical and organizational capabilities.
Once the digitalization maturity is defined, we can start creating a prosperous data culture where you can:
- find,
- understand and
- trust data.
What is a data culture?
A culture is the mix of customs, habits, unwritten rules and symbols that govern behavioral patterns in a company. It guides the thinking, feeling and actions of employees, and therefore, it has impact on each and every decision. A data culture is the set of collective behaviors and beliefs held by people who value, practice and encourage the use of data for better decision-making. As a result, data intertwine with corporate operations, mindset and identity.
How is a data culture developed?
Reinier proposes the 9 E method:
- Engage: explain why and what for is a shift in mindset needed to engage employees.
- Educate: develop employee training, reinforce with specialist profiles. In short, increase data literacy.
- Empower: offer work tools to create dashboards, insights and solutions.
- Enable: create support and learning environments and communities.
- Experiment: start with small projects (learn by doing) with grassroots initiatives. Test, test, test, fail and test again.
- Encourage: create safe learning environments, encourage learning and experimenting.
- Embed: Data are considered essential values, they become a priority.
- Energize: Celebrate and share success.
- Emphasize: keep up the momentum with bootcamps, hackathons, newsletters, etc.
In short, there are a few basics a company must do to truly be digital: first, assess digital maturity, then, define and act based on a data culture appropriate for their activity. Everything starts with the vision and business alignment because Artificial Intelligence is not an end in and of itself, it is an enabler.
Socio director de BastaGroup
