Overview: Seven of my recent AI-related blog posts
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Here’s the story-line of seven of my AI-related blog posts published over the last three months, along with what I intend to focus on next.
Data from PwC’s 22nd annual global CEO survey provides worth repeating.
- Five percent of US CEOs (and 10% of European CEOs) say their AI investments are either fundamental to their organization’s operations or broadly in use across the organization.
- Forty percent of US CEOs (and 39% of European CEOs) say their firms have introduced AI for limited purposes, typically pilots, prototypes, experiments or tactical applications. This feels like it’s double the level of 2017 — but that’s a qualitative judgment.
- For US CEOs, two-thirds believe the Internet is a more significant business issue than AI, at least for the next few years.
- For CEOs, the prime mover is business results that demonstrate success versus the primary business objectives that the board has approved.
- AI technology available today is (sometimes) amazing technology. It does not directly address the business objectives of CEOs.
Amazon is not the only apex internet predator but, arguably, they constitute the biggest existential threat on the Internet. There are many other apex predators including Walmart, Alibaba and Tencent.
Amazon didn’t invest in AI to advance the science of AI or build their technical reputation. They rapidly ramped up investment in AI when they saw a clear path to potential strategic business benefits. Once they did, they internally developed most of what they needed. (The list of accomplishments summarized in the post is impressive.)
In the next two posts, I chose to focus on “Amazonization” — fear of your business being devoured by Amazon — as a symbol. Many enterprises are not threatened by Amazon. But they fear others will exploit disruptive technologies like the Internet in a way for which they’re not ready. Think of the impact of Airbnb and Uber. Neither is AI-driven (although they certainly use it.) They’re major business disruptors.
- Amazon (with Alexa) and Walmart (with Google Assistant) have opened a new competitive threat — voice-based-ordering — that could negatively impact the ability of consumer packaged goods (CPG) manufacturers to maintain and enhance their brand identities. This Amazon-Walmart battle also creates an existential crisis for retailers. The open question for CPG manufacturers and merchants is what should they do about this?
Using the existential threat faced by BestBuy in 2012, the post called out six different business strategies (three nontechnical, three technical) that firms under pressure might conceptually consider. The post explored what BestBuy did between 2012 and 2018 to successfully hold off Amazon. BestBuy’s approach was business based and very focused (rather than generic.)
After recapping some earlier posts in this series, I enumerated the five leading factors reducing US CEOs’ enthusiasm for significant IT project investments.
I examined Kohl’s, Walmart’s and Trader Joe’s business cases. Like BestBuy, they’re focused on business strategies. Some are technology light, some technology-heavy, but in every case, they’re led by business strategies, not technology.
Kohl’s embraced Amazon, setting up Amazon return centers in their stores. As a result, they increased their stores’ foot traffic, net new customers and total sales.
- Walmart exploited existing logistical advantages, partnered with Google for Google Assistant technology and improved customer service with curbside delivery.
- Trader Joe’s approach is enlightening. It’s a non-technological counterpoint to much of the hype flowing in the market about the importance of making strategic investments in AI.
I closed the post with
- Key takeaways (CEOs want business results, and AI doesn’t provide genius, people do)
- Eight important action items to consider following. (This collection of seven posts all focus on the first of the eight action items.)
IBM Watson-based projects have had both successes and disappointments. I examined two disappointing outcomes from IBM’s push to drive customer investment in Watson-based projects. The disappointments were not the result of a failure of technology. They were produced by a failure to meet the inflated expectations that people had for future versions of the technology.
There are already many successful applications of AI technology. Huge numbers. And in the future, there will be many more.
Businesses need to invest (and take on risks) to achieve substantial strategic objectives.
Ignore the circus barkers who are pushing the marketing envelope by announcing partnerships to deliver results in the future.
Be skeptical. Seek out results, not press releases.
This post is a collection of three small notes. The second one, entitled “AI returns for businesses have been elusive,” fits this series and can function as a segue into my next set of posts.
The central position of this note:
“AI returns for businesses have been elusive” cites cases that MIT Technology Review collected, arguing that results cost more than expected, take longer to deliver, are harder to accomplish and produce smaller than expected outcomes.
This is generally a recurring refrain regarding new, emerging technologies. The results fall short of the expectations, at least until the technology and practices improve over time.
Next Up: Will the next AI advances disrupt AI?
In upcoming blog posts, I’m going to explore some future directions that AI research is focused on and try to provide guidance on the impact of potential future discoveries on investments in current AI technologies.
This post reflects my opinions.