Peter Evans is the CEO of Xtract One Technologies
Artificial intelligence (AI) is undoubtedly having a moment. Prompted by a flurry of product releases that seemed to gain instant popularity—OpenAI’s ChatGPT was briefly the fastest app to gain 100 million daily active users—leading technology companies, scrappy startups, forward-thinking entrepreneurs and, of course, investors are rushing to build the next big thing powered by AI.
According to Pitchbook, a research firm that tracks investment capital, investors have poured more than $15 billion into generative AI companies in the first half of 2023. Meanwhile, hundreds of AI startups have launched this year, reinvigorating whole cities (paywall) like San Francisco and reorienting the tech workforce at a time of deep disruption.
Naturally, some companies are AI-focused in name only. As one Axios headline quipped, “In tech, everything is labeled ‘AI’ now.” In this environment, where the hype is real and the potential endless, it can be difficult to differentiate speculation from innovation.
Innovation builds upon what came before it to bring consumers new value, products and services. In contrast, speculation is want-to-be innovation, leveraging the potential for innovation to attract attention, raise money and, almost inevitably, “change the world.”
Is It Innovation Or Speculation?
That’s why we need to define innovation for the age of AI, creating a rubric for determining the difference between a great idea and a truly ground-breaking product. Here are three criteria we can use to help evaluate the innovative potential of AI companies, products and services so we can best assess their efficacy and potential impact moving forward.
1. Real-World Implications
To understand if a product or service is truly groundbreaking, we should ask, “What are people actually doing with it?” Is it changing the way people perform work, connect with their communities or live their lives? When it comes to AI, we’re seeing these implications emerging.
Although large language models (LLMs) and image generators have attracted the most attention, they’re far from the only AI solutions impacting our day-to-day lives. Some prominent real-world implications include:
Security: Digital and physical security is being enhanced by AI-powered solutions that identify threats, analyze risks and empower human specialists to intervene.
Content: Although generative AI is obviously attracting a lot of attention, the technology has been influencing our social media feeds, news alerts and other information-oriented services for years.
E-Commerce: AI has changed the face of e-commerce. It’s used for personalized product recommendations, automated customer support and predictive analytics for inventory management. These innovations have transformed shopping experiences, arguably making them more convenient and efficient.
Real-world use cases don’t inherently make a product or service innovative, but it’s a necessary first step to disruptive potential.
2. Prolonged Market Impact
Truly innovative products and services make a meaningful market impact. As of today, over 40% of U.S. professionals say they’ve used ChatGPT at work. This could suggest a genuine market impact.
However, understanding a product or service’s potential requires a protracted analysis to see if it actually lasts the test of time. For example, The Washington Post (paywall) reported that ChatGPT lost users for the first time in June 2023 as web and mobile traffic fell nearly 10% month-to-month.
The lesson here is simple: It can be difficult to determine the difference between innovation and speculation in the short term. A protracted analysis provides a more comprehensive framework for evaluating a product’s or service’s efficacy.
3. Sustainable Implementation
Speculative products and services are a flash in the pan. They burn hot and quickly disappear. Often, they rely on overhyped potential or unique market forces that make them temporarily popular or highly valued.
Innovative products have a pathway to sustainable implementation, moving beyond the hype cycle and the subsequent trough of disillusionment into true and pragmatic growth, including operational efficiencies and consumer interest, which make their long-term viability more secure.
Conclusion
In this exciting AI era, identifying genuine innovation can be challenging amid the white noise of hype and speculation. Nonetheless, by applying these criteria, we can better identify ground-breaking products and services that truly have the potential to change the world.
As we move forward, it’s essential to focus our energies not just on what sounds exciting but on what can sustainably transform our societies for the better. In doing so, we’ll ensure that the age of AI isn’t just a flash in the pan but a lasting era of real and transformative innovation.
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