The essence of data management CIOs must embrace

CIOs must prioritize high-quality data management over AI models or tools to achieve sustainable competitive advantage, as AI performance depends on accurate, consistent, and timely data. KEPCO's data management framework emphasizes ongoing governance and cross-departmental collaboration, not just IT responsibility.

Since the advent of generative AI, the use of AI in business has shifted from something we should do to something we must do to survive. Many companies are now working to utilize AI with the aim of improving productivity and creating value. Here, I would like to pose a question to you all once again: “What is the fundamental factor that determines AI performance?” Is it the AI model? Is it the AI tool? Or is it the AI agent? Of course, I believe all of these are important. However, if we look at the long-term perspective, the competition among multiple companies to improve AI model performance will eventually level off, and we will eventually reach a point where every AI model is amazing In that context, what I believe is the most important factor influencing AI performance is the data accumulated by companies that connects to their unique strengths. For example, if asked, “What do plants need to grow?” I would say “good water and light.” Similarly, if asked, “What do people need to thrive?” I would say, “Kind words.” Finally, “What does AI need to thrive?” The answer is “good data.” I believe that the extent to which companies can genuinely understand the importance of this extremely simple principle and implement it with unwavering dedication will determine their ability to establish a competitive advantage and achieve sustainable growth. As I’m sure you’re all aware, AI is by no means a magic wand. It is an entity that learns based on the data it is given and makes inferences within that scope. In other words, AI’s output depends heavily on the quality of its input data; one could say that AI is a mirror of data. In this way, AI is not smart but rather faithful to the data. Based on this premise, it becomes clear that the essence of AI utilization lies not in which tools to use, but in what kind of high-quality data to prepare and how to utilize it. So, what exactly is good data? It goes without saying that data is useless if it is merely abundant in quantity, but on the other hand, what specific qualities must good data possess? Generally speaking, good data possesses at least the following elements. In summary, good data is data that is accurate, has few gaps, is consistent in meaning and notation, is collected at the appropriate time, is suitable for the purpose and comes from a reliable source. Only when the quality of this good data is guaranteed can AI produce valuable outputs. Conversely, introducing AI with unorganized data will not yield the expected results. Many complaints, such as “We implemented AI but it’s unusable” or “The AI’s accuracy isn’t improving stem from data issues.” The key point here is that good data does not arise naturally. On the contrary, if left unattended, data will inevitably deteriorate. These conditions are likely common in many companies. Below is an overview of our company’s data management framework https://www.kepco.co.jp/english/corporate/list/report/ . Akio Ueda Broadly speaking, it consists of data governance — covering roles and structures, risk management and evaluation — and data management, which encompasses data utilization cycle management and data utilization support services. Within this framework, data utilization cycle management involves: Data management is not a one-time effort; it is an ongoing initiative that requires continuous maintenance and improvement. The CIO must embed data management as a system within the organization and continue to implement it until it becomes firmly established. Another important point is that data management is not just the IT department’s job. Data is fundamentally generated within day-to-day operations on the front lines. Therefore: are, in essence, operational issues, business issues and management issues. The latest Digital Skills Standard ver. 2.0, published by the Ministry of Economy, Trade and Industry in April 2026, defines the following three roles within the data management category: The CIO is not merely responsible for establishing data storage and analysis infrastructure; they are also tasked with appropriately assigning personnel to these three roles within the company and establishing cross-departmental, company-wide tools and rules to connect data with management, business operations and daily tasks. On the other hand, no matter how much progress is made in staffing, infrastructure, tools and rulemaking, data will not be utilized unless there is an organizational culture that actively drives management, business and operations based on data. In such a situation, no matter how well the systems are set up, they will become mere formalities. In contrast, in organizations where data utilization is advanced: These actions occur naturally. In other words, the essence of data management ultimately lies in creating an organizational culture that assumes the effective use of data. Data management cannot be achieved overnight. That is precisely why it is important to start small and build on your successes. By repeating this cycle, the importance of data will permeate the entire organization. In the AI era, the role expected of a CIO has changed significantly. Traditionally: However, moving forward: In other words, the CIO must evolve into the person responsible for creating value from data. In the coming era, the use of AI will be a given. What will set companies apart is not whether they use AI, but what data they possess. Data is the accumulation of a company’s past strengths and the source of future value creation. And its quality is determined by daily operations and the nature of the organization. Taking this simple principle as our starting point, we must place data management at the core of our business strategy. Isn’t that the shortest route to sustainable growth in the AI era? CIOs are called upon to lead the way in making this a reality. This article is published as part of the Foundry Expert Contributor Network. Want to join?