AI's Race to the Bottom: Why Rushing to Market Leaves Users Behind

AI's Race to the Bottom: Why Rushing to Market Leaves Users Behind

The AI industry is in a frenzy, racing to bring new products to market – but this urgency to launch and grow quickly is having the opposite effect, leading to disappointing business results and even more disappointing experiences for users.

Take Google’s Gemini AI as an example: it launched with incredible fanfare and high expectations but quickly ran into trouble – with some users reporting the model would generate inaccurate, biased, or even offensive images. In one such instance, the Gemini model incorrectly generated scenes with historically inaccurate images built on misinterpreted context. These issues quickly caught the public’s attention and prompted widespread criticism, forcing Google to pause Gemini’s image generation feature and focus on improving their algorithms and content moderation systems.

Humane is another example: a startup that promised a revolutionary AI device but delivered a product that was slow and largely unusable in real-world scenarios. Early reviews pointed out that the device struggled with even basic tasks, showing a clear disconnect between the ambitious vision and practical execution.

Both of these examples highlight a rapidly emerging trend in the AI sector: as firms race to capitalize on the wave of interest in AI, a gap is forming between what companies promise to create and what they ultimately deliver to users.

Much of this traces back to simple competitive pressure – the desire to be first to market and drive rapid, top-line growth as the AI landscape takes shape. But here’s the rub: speed and haste come at the expense of product readiness and the user experience. By focusing almost exclusively on launching and scaling quickly, companies have neglected a critical component of what fuels durable growth and go-to-market success: customer-centricity.

Gemini and Humane are cautionary tales. In order to drive uncommon, sustainable, top-line revenue growth, companies betting big on AI need to shift their focus from merely being “the first” to being “the best.” Real growth comes through human-centered innovation – developing a clear understanding of the most important jobs-to-be-done and creating products and services that improve people’s lives.

As the AI race heats up, remember this: companies that prioritize understanding and meeting customer needs will ultimately come out on top.


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Peter Stubbs

Strategy, Growth, Marketing, Media and Gen AI

4w

Great article Kristen Groh. It also emphasizes what I’ve been talking to companies about which is that we are really only in this first phase of AI where the real business benefits are in process automation and efficiency. The next phase will be about using AI to solve real customer problem but we are just not there yet (keep an eye on Apple though). Companies should therefore be focusing on these early opportunities not only to gain the benefits but also build their AI muscle so they are ready to then start solving real customer problems.

Heidi Therese Dangelmaier

I run an all-girl global think-tank we will lead the future of consumerism & technology & scientific intelligence, & culture- 2024 it begins

4w

Kristen Groh they are not the problem ideologies like socialism , feminism are.. they falsely assume that equality in the system instead of challenge the system is the path to progress

Kanu Priya Goel

Be humble Be kind Stay hungry Stay Calm

1mo

Interesting .. but firms will comtinue to run in the race for “being the first “ rather “being the best” .. the temptation to bring AI in every business is at its High !

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Neil Johnston

Connecting Leaders to Growth — with Strategic, Creative, and Innovative Ideas

1mo

Well said, Kristen. Innovation isn't just about being first; it's about being the best for the customers. Rather than rush to join the AI race, take the time to craft solutions that truly serve users' needs.

Well argued Kristen Groh. I do believe the market will be forgiving as long as the Googles and Humane's rapidly follow with 2.0 and 3.0 versions. Early Internet experiences were novel enough that we gave them a 2nd chance and were rewarded. The risk of early unfinished products, of course, all depends on the stakes. Fun AI image generation on Google - relatively low stakes. Using AI for disease diagnosis - higher stakes.

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