AI, generative or otherwise, holds immense promise for enterprises looking to improve efficiency, enhance decision-making, and unlock new business opportunities. Yet, despite the enthusiasm, many companies struggle to transition from pilot projects to large-scale AI deployments. The path to effective AI adoption is not as straightforward as acquiring technology or hiring data scientists. Enterprises must navigate challenges from defining the right problems to preparing their data infrastructure, fostering a culture that embraces AI, establishing governance frameworks, and understanding the true costs of scaling AI solutions.
AI’s allure is undeniable, and businesses invest heavily in its promise. Companies today invest significant amounts into generative AI initiatives. This pursuit is fueled by AI’s potential to improve productivity, cut costs, and unlock new opportunities that may create new revenue streams. However, many companies find the path to successful AI challenging because of fundamental mistakes in their approach.
The road to new mobility will not be a straight line. The twists and turns we encounter and will continue to encounter, will come as the result of economics, business models, industrial policy, politics, national security, but also culture. Mobility is impacted by at least three cultures: the automakers’, the dealers’, and the customers’.
Culture defines every company regardless of whether it is an early stage startup or a global enterprise. It influences behavior,…



