A case for why organizations don't need a GenAI strategy

Is your business pondering the idea of a GenAI strategy? Perhaps you've been tasked with crafting one. Here's a contrarian perspective to chew on: Your business may not need a GenAI strategy for two compelling reasons: 1. it is never a good idea to center strategy around a particular technology and, 2. there is likely a lot more opportunity to drive revenue for your business via the good ol’ machine learning! Join the discussion in the comments!

Firstly, generative AI is general technology that has just become accessible to the masses via the latest developments in the field. It's generally unwise to anchor your strategy solely around a specific technology. Pinning your strategy solely on GenAI might seem a bit topsy-turvy. It would be akin to planning your housing renovation around electricity. Doesn't make sense, does it? Instead, consider a more comprehensive approach. Begin with a broad business strategy firmly grounded in understanding the unique economics of your specific industry. Then, let that cascade into a data strategy and an AI strategy, with GenAI being just one of the tools in your arsenal. While GenAI holds immense potential, it's my forecast that most businesses will primarily employ Large Language Models (LLMs) for tasks like building classification models and deciphering conversations, rather than tapping into their generative capabilities in the immediate future.

Secondly, it's crucial to recognize that the size of the GenAI opportunity might be smaller than you imagine when compared to more traditional AI methodologies, such as supervised machine learning. While GenAI is undeniably promising, Andrew Ng, a prominent figure in AI, points out that the current scope of opportunity is relatively modest (see the graphic above for current and future valuations of AI opportunities by technology). The lion's share of financial value in revenue to be harvested through AI technology over the next three years will be driven by the rapid evolution of supervised learning. In contrast, Generative AI is a captivating newcomer on the scene. According to Ng, the growth trajectory for Supervised learning, already substantial, is set to double, moving from massive to even more massive, within the next three years. GenAI, although smaller in scale at present, is poised for significant expansion due to developers and capital exploring its diverse applications. Both are versatile technologies, but there's still substantial untapped potential in supervised learning, making it a vital area to focus on.

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The smart play is to align your business strategy with your data strategy and your AI strategy. Your approach should incorporate components that leverage GenAI, not only for language generation but most often for 'comprehension' and supervised learning use cases. So, before diving headfirst into the GenAI hype, take a step back and consider the broader AI landscape. It's where the real action lies.

Tell me your thoughts in the comments below! ?? #AI #GenAI #BusinessStrategy