How to manage digital technology with means of a human tech organization that fosters beneficial innovation?
Digital technology and AI are creating so many expectations, some realistic, some futuristic. So, how can tech organizations deal with all this in a human way and how should CIOs set up to drive business innovation?
Imagine IT together with business experts feel like they had the right to design their own work. They were encouraged to influence and shape the tech-strategy, to define their own digitalization targets as well as use their own methods. They felt trusted to use their own judgment and to decide on IT investments and resources. They perceived themselves being on same-eyes-height with superiors and executives in the organization. As much they are being valued and appreciated as much they felt like “super-stars” in their organization who can make a difference. This is what “Human AI” is also about. Unfortunately, many IT organizations do not work like this.
What are the roots of Human AI in this sense? From a practical standpoint, lots of consultants have developed many concepts, like agile, humanocratic, antifragile or neo-hierarchical organizations. Many concepts are limited to better project management, considering the uncertainty and complexity of large-scale IT initiatives. The line organization and leadership, however, need an even better structure too. The DSI essay leverages relevant concepts and provides a proposal for tech organizations or CIOs. For example, Gary Hamel and Michele Zanini, whose concept is just being used by Bill Anderson, the new Bayer CEO, to revolutionize Bayer, being one of them.
Practical concepts can provide good execution guidelines and show cases. They are often based on academic approaches developed by scientists, sometimes correctly quoted, sometimes not. From a scientific standpoint, the past 60 years of system thinking have addressed the challenge of what good organizations look like. To name just two of them, Niklas Luhmann’s system approach is highly topical. A key feature of his approach is the idea that organizations are developed to reduce the complexity of the environment. This is particularly important for tech managers who are constantly faced with the challenge of making decisions amid uncertainty and information overload. Another scientific approach is W. Ross Ashby`s law of “requisite variety” suggesting that only complexity “eats” complexity. This is particularly relevant, given that complexity in most IT organizations has raised significantly. There DSI is summarizing key scientific approaches. Next to the practical concepts, the DSI builds on these approaches as scientific roots for a Human AI. It defines guiding principles of good technology and AI management.