Is Generative AI is now table stakes for software businesses?

The New Frontier of Competitive Differentiation and the Data Frenzy

Generative AI features are being embedded into most of the marketing tools I use. If companies have yet to announce their plans, they are working on announcing them.

Generative AI features are also being baked into software development tools like GitHub, cloud platforms, automobiles, financial systems, and energy grids.

Today's software landscape will undeniably be transformed by the emergence of generative AI. No longer a novelty or a gimmick, generative AI has seeped into the very fabric of business, becoming a sine qua non for any software organization worth its salt.

The meteoric rise of generative AI's importance can be attributed to two simple facts: data is the new oil and oil makes machines more efficient. In today's digital world, the most successful software companies are those that have access to copious amounts of data, allowing them to leverage generative AI platforms to extract valuable insights and deliver tailored customer experiences. If data is the new oil, generative AI platforms are the drilling and processing capabilities for our software applications.

Yesterday's announcements that ChatGPT is adding support for plugs - extensions that will integrate it easier with third-party services or allow it to access up-to-date information - makes the oil that much easier to drill in new basins.

Any software business that wants to maintain a competitive edge must embrace generative AI and all that it has to offer. Companies that ignore this crucial capability in their 2023 roadmaps risk being left behind as their generative AI-enabled competitors steam ahead, equipped with more sophisticated tools for decision-making, automation, and personalization.

On the other hand, generative AI could be a race to the bottom

Let's question this prevailing narrative. Is generative AI truly the be-all and end-all for software organizations? Or are we witnessing a dangerous race to the bottom as companies blindly chase data and generative AI capabilities without fully understanding the implications?

First and foremost, not all data is created equal. The notion that "data is the new oil" glosses over the fact that collecting and storing vast quantities of information is not inherently valuable. Data quality, relevance, and context are paramount to its usefulness, and indiscriminately amassing data for generative AI-driven insights can lead to inefficient and misguided decision-making.

Moreover, the unchecked pursuit of generative AI and data can exacerbate societal issues. As more organizations join the generative AI bandwagon, the potential for biased algorithms, privacy violations, and job displacement increases. The tech industry must consider the ethical implications of its generative AI obsession, lest we find ourselves in a dystopian future where innovation and profit come at the cost of fairness, transparency, and human dignity.

Lastly, the idea that generative AI is table stakes for competitive differentiation may be overly simplistic. While AI can undoubtedly provide a significant edge, it is not a panacea. Companies must focus on their core offerings, human talent, and customer relationships to build a sustainable competitive advantage. Betting the farm on generative AI without attending to these other crucial aspects of business success is a recipe for disaster. Generative AI, after all, is a feature of a core offering for 99% of businesses not the core offering.

Generative AI's growing in the software industry is undeniable, and its potential for unlocking new opportunities and efficiencies is immense. However, as we rush headlong into this brave new world, it is crucial to remember that the race for generative AI supremacy and data acquisition has its distractions and pitfalls. A more measured and balanced approach is needed to ensure that the generative AI revolution delivers on the things we're all excitedly imagining and hoping for.