Cybersecurity at the heart of the Datavore show
The recent Datavore 2024 edition highlighted once again the growing importance of data in technological innovation. But, despite the hype around AI, can it really disrupt companies’ business and operational models?
The opening conference, which focused on investing in customer data development, was categorical: AI is not revolutionary. It is crucial to distinguish between the notions of revolution (more radical and fundamental) and innovation (more gradual and progressive). Revolution challenges existing norms and paradigms, while innovation introduces something new, incrementally. For example, aviation and the automobile revolutionized transportation, and the Internet revolutionized the transfer of information.
Sure, AI is a tool to improve business models by reducing costs through predictive analysis of large data sets. It represents a definite innovation and incremental optimization, but not a revolutionary invention. The customer case of collaboration with robots, an interaction that has existed for a long time, is a concrete example. Thus, a business strategy should focus more on market needs and productivity rather than on digital or AI. For example, Facebook connects people to monetize data, Netflix reinvents the video store, and Amazon focuses on e-commerce. These 3 leading companies have been using AI for many years now. They are to the automotive revolution what AI is to its engine.
What about cybersecurity? It must manage the opportunities related to digital strategies, while minimizing threats. AI, although not revolutionary, is a lever for growth and an incredible innovation, which nevertheless implies increased data management and security challenges. Paradoxically, data protection also requires AI, an ideal tool for analyzing human behavior and different processes. Clearly, cybersecurity needs AI, which needs cybersecurity. If the automobile embodies a revolution and AI symbolizes its engine, then cybersecurity is the technical control, watching over all the components of the whole.
It is crucial for organizations to have robust data management strategies and proper cybersecurity in place to protect their AI-driven data from potential threats. AI-driven data can also be used to proactively detect and respond to threats, automating certain security tasks and enabling faster anomaly detection.
