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The process of insight generation is changing due to generative AI. While the foundations of insight generation I presented ten years ago remain relevant, the methods, tools, and implications have expanded dramatically. Generative AI is reshaping how insights are derived, validated, and applied across industries.
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.
Just before the holidays, I was asked to keynote an event sponsored by the German American Chamber of Commerce. This article is an updated version of that presentation. It is even more relevant today following CES 2025 and the news streaming out of Europe. The automotive industry, especially the European automotive industry, faces even greater challenges. These challenges are not from technology startups but from more formidable forces. China has become an international competitor, and its market is no longer an opportunity for incumbents. Vehicle sales, including sales of battery electric vehicles, are slowing, leading many companies to miss their financial targets and reconsider previously announced investments relating to electric vehicles. The regulatory environment is becoming more restrictive but also less reliable in terms of long-term goals and guidance for the industry. At the same time, Software-Defined Vehicles and AI require large capital investments at a time when the industry is cutting costs and continues to show an inability to deploy capital in the areas that will matter in the future. Labor is reacting to the automakers’ actions and introducing new work-life balance demands.
The biggest venture financing rounds during 2024 involved AI companies. Reviewing the characteristics of such financing rounds, combined with the performance of our portfolio startups, and our firm’s corporate advisory AI projects (completed and ongoing), I worry that venture investors expect corporate AI adoption will be fast and large-scale. In contrast, corporate AI spending, though growing, is more measured than VCs predict.
The automotive industry’s path to new mobility has been slow and full of challenges, many created by the automakers themselves, that will not disappear in the new year or even the near future. Many of these challenges emerged in the last couple of years, while the impact of others that existed longer was only recently understood and appreciated. Geopolitics, tariffs, new regulations, labor unrest, increasing competition from Chinese automakers, and decreasing sales, including in China, make up the list.
Most of you know our firm from its investments in early-stage AI software startups and as an AI advisor to corporations. Few know about the AI systems we have been developing and how we use them with our corporate customers or in new startups we spin out. Over the past several years we have been working on a class of AI-based mobility intelligence systems that are used for understanding a population’s mobility behavior within a region, such as a neighborhood, a city, or even an entire state. We found that neurosymbolic systems that incorporate generative AI components can be extremely effective in understanding such behaviors and providing their users with mobility intelligence.
A few days ago I attended the strategy meeting of a portfolio company. Like all of our Synapse Partners portfolio companies, this one provides AI solutions to enterprise customers. Their initial success is in the medical devices industry. While reviewing the company’s sales pipeline and the progress of delivering the company’s solution to signed customers,…
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…
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…
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…
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’.
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…
Automakers are facing a complex dilemma relating to software-defined new energy vehicles. Should they proceed with aggressively investing and developing software-defined vehicles while facing a slowdown in demand for battery electric vehicles (BEVs), or continue developing Internal Combustion Engine (ICE) and hybrid vehicles (including plug-in hybrids) that are based on existing architectures and practices?
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…
Another CES is behind us. The automotive and mobility extravaganza of years past was replaced this year by an AI extravaganza. For the automakers and their suppliers that participated at CES this year was about AI and Software-Defined Vehicles (SDVs). There were lots of demos involving AI and SDVs, and even more marketing statements full…
Since the beginning of last year, the interest in AI has gone into overdrive. Enterprises tried to "out-announce" one another regarding their use of AI. Similarly, venture investors have been investing large sums at nosebleed valuations in startups developing anything that appears to involve generative AI. But, despite the corporate statements and the venture investments,…
We are still in the early phase of enterprises adopting generative AI. However, even at this early point enterprises must understand the costs associated with the use of Large Language Models (LLMs) as they embark on developing generative AI applications. These costs can become significant. The goal of this post is to identify the cost…
As with every previous AI era, the benefits promised to the enterprise from the application of generative AI will likely be lower than those that will be achieved. To succeed, enterprises must avoid the pitfalls of the previous AI eras. Over my 40-year career in enterprise AI, I understood the types of and reasons for…
Automakers want to capture a larger percentage of their customers’ lifetime value than they do today. To achieve their goal, OEMs must establish direct relationships with their customers, create new customer experiences, capitalize on the capabilities of their Software-Defined Vehicles, and utilize AI to better understand their customers’ behavior so that they can match their…
During the last six months, we spent time with our firm’s corporate partners to assess whether the enterprise is ready for generative AI and updated our investment theses accordingly. Our work convinced us that Large Language Models (LLMs)/Foundation Models and applications that incorporate them will open the door to the development of a new class…
Last week I attended Ford's Capital Markets Day. Ford held the CMD to report on the progress of its three divisions and the goals they will be measured against. This piece focuses on the goals relating to software development and customer experience and their impact on the recurring monetization of the company's customers because these…
AI has three roles in new mobility. It is an enabler, a differentiator, or a monetizer. The recent explosion of interest in generative AI begs the question: could generative AI contribute to new mobility and if so, in which of the three roles? This post attempts to answer this question by presenting a few ideas…
AI is viewed by many exclusively as a prediction technology. The availability of large, diverse, and information-rich data sets combined with the power of neural networks, and more recently with the addition of Foundation Models and Large Language Models, has been responsible for achieving incredible results even in complex, multi-faceted situations. Every aspect of new…
Automakers must address two questions because of the environment they are currently facing. First, will they be able to make the announced Software-Defined Vehicle investments in the timeline they were projecting, or will they need to slow down their investment pace? Second, will they face any negative implications if they delay their plans to roll…
Automation, combined with digitalization and process engineering, will enable organizations to broadly utilize telework, address talent scarcity, and lower production costs. Onboarding new employees to a telework-centric organization is emerging globally as a major challenge. We break the onboarding challenge of teleworking employees into three parts: addressing the mundane tasks, providing training on the necessary…
One of the main theses developed in Transportation Transformation is that, though still young, the app-based on-demand mobility services companies will need to further transform before they can fully capture the opportunity afforded by new urban mobility. The book presents the decisions such companies must make and a framework that prescribes specific transformations consistent with…
During the last twenty-five years, the automotive customer journey has become more complex as incumbent automakers tried to establish direct customer relations and improve the customer experience. Software-Defined Vehicles will enable a richer and more personalizable experience. When designed properly such an experience will lead to better customer relations, recurring post-sale customer monetization, and decreasing…
To broadly and successfully employ telework during and after the pandemic we must understand the considerations and objectives that employers and employees want to achieve and the dimensions they will use to assess progress and ultimate attainment. On some of these dimensions employers and employees may be aligned, and on some may not. In this…
Several megatrends will necessitate the transformation of urban mobility from one that is centered around the privately owned vehicle to one that is offered as a service, combines multiple modalities, and promotes sharing. The pandemic forced many of us to work from home and have goods delivered there, in the process causing us to rethink…
Software-Defined Vehicles greatly facilitate the vehicle’s electrification, optimization and personalization, as well as the attainment of higher levels of driving automation. More broadly, these vehicles change how the industry designs, makes, sells, and services vehicles, and in the process enable a new customer experience.
Telework has been broadly adopted globally during the pandemic. It will also become a key component of the post-pandemic work environment, providing benefits to both employees and employers. To the employee, it will give flexibility, offer a better work experience, but also comfort related to the new safety norms being established as part of the…
During the automotive industry’s current boom phase OEMs are announcing big, multi-year investments in new vehicle platforms that combine electrification with increasing driving automation. Because under new mobility data and loyalty will become central forms of value, OEMs must also consider deploying the loyalty-enhancing data-driven services these platforms enable. The services they introduce and the…
There is no question that the pandemic is having a big impact on new mobility. Passenger transportation is down as reported by the dramatic decreases in public transportation ridership and mobility services rides. At the same time, goods delivery services are growing fast as more households are adopting Ecommerce. With these changes as a backdrop…