Will AI flop because of bad product management?
This week, we dig into the influence of product in the AI space.
I was doom scrolling through YouTube videos this past weekend and came across a video called "Why AI Is Tech's Latest Hoax" by Modern MBA.
While tools like ChatGPT are fascinating, I often question some tech companies' practices and product decisions - mainly through the lens of being in the industry for a decade+.
As the video has some interesting takes on how AI could be the next underwhelming hype cycle, I decided it would be fun to break down the concepts in the video and highlight how product management decisions could be the reason why so many companies are struggling despite getting a ton of press with their AI/big data hype.
Let’s dig in.
The Hype Cycle in Silicon Valley
Silicon Valley often jumps on new technologies, hyping them before they prove their worth.
Companies focus more on marketing than on developing quality products. The video highlights some companies that have excited their abilities but struggled over time—Stitch Fix, Groupon, and Blue Apron come to mind.
The hype creates a cycle of a few things - many copycat companies are trying to get their share of $ for one.
Secondly, and the one I’ve seen the most in my world, even the most risk-averse companies want to give the perception that they’re revolutionizing the way they do business by also incorporating all of these flashy technologies or concepts (e.g., AI).
These companies get sold on the promise of unlocking unlimited potential instead of investing in more deeply understanding their product market fit.
They may pay a bunch of money for licenses, and then once the hard part comes - like realizing how poor their data quality and processes are - they soon find out that the benefits they thought were coming may never actually become a reality.
Focus on Growth over Profitability
Venture capitalists tend to prioritize potential growth over actual profitability with the assumption that profitability will follow.
This leads companies to focus on user acquisition rather than strong product development.
Many companies prioritize releasing MVPs to quickly capture market share, often at the expense of long-term product management.
This short-sightedness can cause major setbacks when market conditions change.
My favorite example of this highlighted in the video is Groupon.
Like many, I was all about living that “great deal” life in the mid-2010s when Groupon skyrocketed in popularity. Early on, I loved the product/platform because it really opened up such a huge amount of exposure to small businesses that I may not have seen - plus, I love saving money, so the combo was brilliant.
Despite a boom in users, I perceive that they rested on their laurels, assuming the growth would continue forever.
However, their lack of continual innovation opened the door for others to catch up, and year over year, starting in 2017 (seen below with data compiled by Modern MBA), they simultaneously saw significant drops in revenue while also seeing booms in operating cost spikes. Presumably, this was due to efforts to use cash to get people back into the same old products.
How can these companies avoid failures in the past?
Here are my three thoughts I have on how companies can really lean in on AI in a way that helps create sustainable businesses without suffering similar fates to the Groupons of the world:
Deep Understanding of Product Market Fit - Businesses should prioritize their understanding of product-market fit through thorough research and validation. This ensures that the product addresses real customer needs rather than just following trends.
Invest in Data Quality - High-quality data is essential for AI success. Focus on cleaning and organizing your data to ensure that AI technologies can deliver meaningful and accurate results. No companies REALLY want to focus on this piece because it’s not sexy. However, if they don’t fix their trash data, the results they seek may be capped because of data.
Long-Term Product Development - Companies should continue to emphasize continuous improvement and innovation. They should avoid quick fixes and invest in robust product management practices that focus on creating long-term value and sustainability.
Final Thoughts
While technological advances such as what we have been seeing with AI have potential, a company's lasting success relies on sound product management.
Although I’m all for expanding into other markets and being disruptive, I feel more companies should continue to focus on and invest in creating innovative products that help solve the problems of their current (and future) customers.
By creating a deeper understanding of their customers, they can build marketable, longer-term revenue-generating products that add value and avoid the pitfalls of hype and near-term thinking.
What are your thoughts on the future of AI in product management?
PS I have a few links and shoutouts above related to the video, but in case you haven’t seen it yet, here’s an embed:
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