While applications of generative AI are relatively recent in the tech landscape, they have managed to create shockwaves in a very short period.


During the last couple of years, we have witnessed an intensified rivalry among the leading tech giants in the race of generative AI. Surprisingly, there have been several startups that have been able to disrupt the field by building on different approaches and business models that harness the power of generative AI technologies. A recent report of CBInsights highlights that during the past year, startups were able to attract more than $42.5B in funding, which showcases the massive potential that is expected from tech-driven disruption. Nevertheless, with all the hype that has surrounded generative AI, and perhaps even the inflated expectations that surround startup companies in the field, it is important to understand on what basis such disruption can be built.

The algorithmic advantage builds on novel ways of utilizing generative AI technologies to improve processes in a way that is hard to imitate.

By surveying the current state of developments in the field over the past years, some patterns begin to emerge concerning strategic archetypes that enable startups to disrupt existing markets or create new ones. Studies have highlighted that there are three main strategy archetypes which startups can leverage: the data advantage, the algorithmic advantage, and the execution advantage [1]. The data advantage requires startups to build generative AI products and services based on real-time and unique data flows. While such opportunities may be challenging in general-purpose services like general conversational agents or text-to-image models, they can be refined in domains where specialized data sources exist and models can be refined with precision. The algorithmic advantage builds on novel ways of utilizing generative AI technologies to improve processes in a way that is hard to imitate. This strategic archetype requires that generative AI applications provide demonstrated superior results compared to rival solutions. Finally, the execution advantage highlights areas where generative AI applications can be used to enable superior value propositions and focus on areas where continuous improvement can lead to increased user value and lower costs.

Already we are witnessing many startups that are building on the potential of generative AI and targeting niche markets or disrupting existing ones. There have also been significant breakthroughs of generative AI startups in the so-called creative industries, where such applications have been pivoted as augmenters to human creativity. A recent article on the potential of generative has highlighted many disruptions that generative AI technologies have introduced across different disciplines [2]. While these may be just some of the many potential use cases of generative AI, they do paint the picture of things to come in the domain, and where generative AI will have an important part in automating or enhancing existing human-led tasks. This changing landscape creates manifold startup opportunities and a path for disrupting long-established industries.


[1] Ruokonen, M., & Ritala, P. (2023). How to succeed with an AI-first strategy?. Journal of Business Strategy, (ahead-of-print).
[2] Ooi, K. B., Tan, G. W. H., Al-Emran, M., Al-Sharafi, M. A., Capatina, A., Chakraborty, A., … & Wong, L. W. (2023). The potential of Generative Artificial Intelligence across disciplines: Perspectives and future directions. Journal of Computer Information Systems, 1-32.

© 2023-2024 • SSPVC

[email protected]