Fishing for scale in the sea of GenAI applications

The push for progress

Discussions and insights on GenAI were particularly impressive, highlighting the progress made in integrating cutting-edge technology into the automobiles today and in the future to come. I observed that GenAI PoCs or MVPs are already implemented almost everywhere. However, discussions on scaling these GenAI applications were rather a rarity.

This is particularly interesting, as general consumer trust in GenAI is already high nowadays. So why does enterprise trust remain a question mark?

Applications are the talk of the town. People working with them, not so much…

Again: various GenAI use cases are under development in our industry, including AI-powered virtual assistants, sensor fusion to enable higher autonomous driving levels, GenAI-powered navigation to improve charging experiences, to name a few. However, there appears to be very little emphasis yet on operating models around those use cases.

Now to create actual commercial value, scaling these applications successfully is key. So, they must be designed in tandem with corresponding workflows and toolchains, ensuring robust and trustworthy operations.

Put very simple: people need to be able to work with GenAI applications in a familiar environment (in terms of tools they use, the processes they already follow, etc.), while not worrying about complying with legal obligations or any other sort of risk exposure for the business.

No ethics, no scale.

This is very much about what AI SHOULD do and less about what it CAN do. Responsible AI implementation follows three essential key factors:

• AI Ethics: With 80% of executives believing business leaders should be primarily accountable for AI ethics, CEOs must lead the conversation and ensure their organizations are ethical and trustworthy.
• Trust: Customers and employees judge organizations’ AI decisions. Being a socially responsible organization that excels in data ethics, transparency, and accountability can help differentiate your brand and retain talent.
• Compliance: Leaders must incorporate ethics and regulatory considerations into AI and data investments, using communication, documentation, and preparation to navigate the uncertainty of regulation.

Everything is coming together

The automotive industry is witnessing a convergence of increasing demands towards Customer Experience, powered by GenAI and enabled by Software Defined Vehicles. Carmakers that can bring these elements together will not only stand out but also stay ahead of their competition. Consumers will increasingly demand more context-sensitive and immersive experiences.

GenAI can indeed provide this context, but carmakers must keep up with the required innovation pace and rapidly changing customer demands (that on top, vary across geographies). This is where the role of the Software Defined Vehicle comes into play. Choosing and designing the right architecture that allows the so much needed flexibility to implement and adapt new experiences is the last key ingredient in the success formula.

Obviously, no single company can achieve this transformation alone. At IBM Consulting, we believe in radical collaboration: bring your business or technology challenge – and we bring the skills, the passion and the best practices.

We are also lucky to have a big research and technology company behind us, who have long-term experience in building responsible AI solutions at scale. IBM watsonx offers a holistic AI & data platform that ensures AI is used in a way that benefits everyone. Let’s talk and continue pushing boundaries to drive innovation in the automotive industry together!

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