AI solution providers and infrastructure providers committed to spend $1T on AI-related capex over the next few years, in anticipation of high demand for and heavy use of generative AI enterprise solutions. A few years ago, similar scale investments were committed by the automotive industry toward the development and deployment of battery electric (BEV) and other new energy vehicles (NEV) anticipating strong consumer demand. However, today as a result of slower-than-expected demand, automakers are reducing their investment commitments and run the risk of ending with unused manufacturing capacity. What return on investment (ROI) does an enterprise need from each generative AI solution it deploys so that it can cross the generative AI chasm and for the huge investments in software, data, and infrastructure that have been committed to be justified?
Robotaxis and autonomoustrucks are the two autonomous vehicle use cases that receive the most attention. AI is a key enabling technology for both. To achieve the determinism required in mobility, #AV software platforms incorporated a combination of statistical and symbolic AI. A new crop of AV startups, led by Wayve and Waabi, received large financing rounds for their “end-to-end” deep neural network approaches similar to those used in generative AI. Could these approaches result in vehicles that are cheaper to produce and operate than those utilizing the approaches used to date, adhere to regulations, and be accepted by autonomous vehicle users?
Despite the noise from high-tech corporations, startups, venture investors, and analysts, we are still in a very early phase of generative AI. As a result, it is hard to assume, let alone declare, that generative AI will transform every business process driving operational efficiencies, create new revenue streams, result in massive productivity improvements, and curtail costs. However, the early signs are adequately encouraging for corporations to allocate budgets and start pilot projects.
The current AI spring is in full swing. Entrepreneurs remain extremely excited about generative AI, as manifested by the number of financing requests our firm and many other investors continue to receive but are starting to think more diligently about where the white space they can go after. Corporations are in testing and evaluation mode as they formulate, or reformulate, AI strategies and assess the impact that generative AI will have on their business. Venture investors remain upbeat about the sector but are also concerned about four issues.
Enterprises use several different technologies, including AI, to automate their processes and create value. They are currently experimenting with generative AI to determine whether it can provide significant and enduring value. Is the enterprise’s excitement about generative AI justified? Is the size of the investments being made and planned warranted? What is their strategy missing and should be in their action plan?




