AI Trends for 2024: What’s Old is New Again

There’s a lot of shock and awe in the AI space these days. And lots of money on the table. But through the sturm und drang, some trends are emerging. To level-set, I went back and reread our last published article together, Moving Forward in 2020: Technology Investment in ML, AI, and Big Data (William F Jolitz & Lynne G Jolitz, Cutter Business Journal, 7 April 2020).

Four years ago, AI was at a crossroads. When we looked a traditional value propositions in technology, where one went from a specific technology to a target customer in a high value sector to a broadened sector and use, AI was doing miserably. 70% of companies said their AI projects provided little to no benefit to their company. Only 40% of companies said they had made a significant investment in AI. The frustration lay with “products sold with ill-defined benefits” which led to “unsustainable revenue that plummets when customers become disillusioned from a tactical lack of sales focus”. We stated the key problem was “the startup’s sales focus no longer aligns with the customer’s strategic focus”.  In tech speak, they couldn’t figure out what to do with it and got disappointed.

We suggested what we called an “axiomatic” approach: “Instead of moving from technology to key customers with an abstracted TAM (Total Available Market), we must instead quantify AI and ML benefits where they specifically fit within business strategies across segment industries”. We then highlighted three areas to watch: surveillance, entertainment, and whitespace, while also discussing the issues with ad hoc architectures which potentially disrupt the cloud services costs and security. In terms of architectures, there is now more focus on data ownership and control, as well as reducing costs in the cloud. But it’s still very much the same as four years ago for most customers.

But the key prediction where we were literally “on the money” was our analysis of chaotic disruption of the market forwarded and funded by “super angels”. This was how companies like OpenAI spawned and spurred tremendous disruption in a very short timeframe: 

“Venture capital (VC) investments in ML/AI fixate on a startup’s ability to obtain go-to-market sales by disintermediating other vendors and to lock-up highly profitable (yet elusive) opportunities. The VC’s intent is startup validation and gauging threats to other vendors’ uncompetitive businesses that will drive the startup’s ability to gain partnerships and revenue shares. However, sometimes, the result is not what VCs would wholly desire but rather more like paralysis with no clear “win” — because the startup only partially engages the customers and does not succeed in displacing other vendors. To force the win, tactical deconstructing/reconstructing of AI/ML solutions around existing layers of edge and cloud platforms as an investment category is akin to desperately reshuffling poker chips on the poker table. This is best avoided. Industry disruption is inherently unstable. Like an ouroboros, it can abruptly turn from obvious low-hanging fruit targets to feeding off earlier successful targets undergoing a state of change.  

The potential for radically greater opportunities is more interesting than patiently maintaining course or  re-navigating the rough waters to see existing ventures through to a reasonable conclusion. This potential is the realm of super angels, self-funders, and leading edge “winners.” These individuals and groups see no disadvantage to riding a chaotic wave because they’ve gotten accustomed to being so out in front of theirthe self-competition within their newly chosen, ever-shifting “whitespace path.” 

However, the traditional VC process is disadvantaged by these groups because venture capitalists’ gut instincts based on the feel of the deal get whipsawed by the loss of bragging rights to ROI, limiting them from getting too far out beyond their headlights. Thus, chaotic disruption is a no-go zone for most. For those who decide to enter these perilous waters, the tendency to share risk across many partners leads to a kind of groupthink at odds with the fast moves and flexibility required of the super angels. 

As open source investments demonstrated, it’s a risky business consuming your own potential customers. In the AI chaotic disruption, all potential customers are considered targets: media, artists, writers, businesses.

In consuming the “long tail” of literature, art, whitepapers, business databases, and personal information and opinion on the Internet and then regurgitating it as facsimiles stripped of authorship and authority, companies like OpenAI and Google whipsawed established players. As we have seen, the rush of businesses and consumers to magnify this effect was phenomenal — and dangerous.

The intent was to rapidly drive paniced companies to sign exclusive agreements and become the dominant company in AI for the next half century. If it sound unbelievable, note we now have only a few companies which dominate search, content, and connection due to brand recognition and addictive use. It takes a lot of money to maintain an addition, or establish a new one. 

As the investment space is still suppressed due to poor conditions despite all the dry powder, there are a few bright spots. Battery investments continue to spark interest. Climate change companies surge and storm. Crypto was actually legalized by the SEC, because you can’t play with GameStop forever — so it’s time to jump into the big scams, kids. Space investments are, well, vast. AI plays a role in all of these.

But because of the chaotic disruption strategy that our billionaires strategized in Silicon Valley, AI now has the attention of everyone, from governments and military and NGOs to plain ordinary users. It doesn’t matter if AI is “lazy”. Even the IMF is jumping in.

Will AI benefit humanity? That’s out of my paygrade. William and I saw it had unique potential in many areas in 2020. That’s still true in 2024. I hope the chaotic disruption doesn’t prevent us from seeing some real benefits for the better.