Although artificial intelligence has been a familiar concept to most of us for at least a decade or more, there hasn’t been a day since November 2022 that I haven’t seen a news article or social media post about it.
Of course, November 2022 was when ChatGPT was released, and it promised to change everything. We are approaching 18 months since that date, and it’s safe to say that the world hasn’t changed much, apart from AI-mania still being at an all-time high.
In the days and weeks following ChatGPT’s release, there was an instant response by internet side hustlers selling ChatGPT courses and changing their LinkedIn status to “AI Expert” or “Prompt Engineer”. On the surface there isn’t much wrong with this, but the marketing behind these courses is usually some form of overzealous promise on how this is going to benefit your career or ill-mannered scaremongering of how you will lose your job if you don’t buy it.
But come on, let’s be serious. Talking to ChatGPT or any other AI Chatbot isn’t exactly rocket science. For those who have grown up with the internet, it’s almost like being good at using Google.
Although I am bought into AI-mania as much as the next technology professional, the hype and language used by some of these side hustlers has been an early warning signal for me that we are in an ai bubble, not too dissimilar to a canary in a coal mine.
Are We in an AI Bubble?
It’s inherently human to get excited by the next big thing and throw all your energy into it. We’ve had it with crypto, NFTs, the metaverse, and now artificial intelligence. Whilst a few of us have been burned on buying digital art, a virtual racehorse, or some land in the metaverse (my friends and I have been burned on all three), artificial intelligence felt very different. This is mainly due to the fact there was an instant practical application of ChatGPT that went way beyond what we were used to with search engines.
But fast forward 18 months and we’re being told by many that it’s not AI that will be taking our jobs, but someone who is using AI. So where exactly are we?
One of the biggest differences from 18 months ago is tech stock prices. Nvidia is leading the charge at over 400% increase since Nov 2022, AMD is at 112%, Microsoft and Google are both sitting pretty at around 60% increases, and Salesforce has grown a whopping 84%.
Now, when I question whether we are in an AI bubble, I am talking not only about the financial markets, but also the hype that is being pushed to us daily by those who have something to sell.
Recently, there have been a number of articles discussing the AI bubble theory. Whilst ChatGPT has a huge amount of practical application, are the current valuations and hype justified?
In an interesting article by John Naughton, From boom to burst, the AI bubble is only heading in one direction, ChatGPT is asked about the stages of the bubble: displacement, boom, euphoria, profit-taking, and panic. It states that we are currently in the euphoria stage, moving into the profit-taking phase – but there is little profit to be had unless you are selling hardware like Nvidia.
On the other hand, Quartz argues against the theory that the AI boom is anything like the dot-com era: “today, AI is capable of generating substantially greater revenues than the internet was in the 1990s and early 2000s”.
Whilst I largely agree with this statement, AI doesn’t come without faults – hallucinations being the big one. The ChatGPT style language has also led to a new name being coined by Alex Hern at the Guardian: “AI-ese”. Whilst text generated by ChatGPT is grammatically correct and easy to read, there is a lot of waffle, and it uses certain words so often that it’s become very easy to spot when text has been AI-generated: words such as “’explore’, ‘tapestry’, ‘testament’ and ‘leverage’ all appear far more frequently in the system’s output than they do in the internet at large”.
Moreover, has the hype cycle put pressure on companies to dive into GenAI now, even if they aren’t ready? In a recent study conducted by Slack, they found that “nearly all executives feel pressure to integrate AI tools into their organization, with half of all executives saying they feel a high degree of urgency to incorporate AI tools”.
So it comes as no surprise Gartner predicts that by 2025, 90% of enterprise deployments of GenAI will slow, as costs exceed value, and 30% of those projects will be abandoned after proof of concept (POC) due to poor data quality, inadequate risk controls, escalating costs, or unclear business value. Accenture is one company reaping the rewards of this hype, with over $1 billion in AI bookings in six months.
How Does the AI Bubble Impact Salesforce?
Our beloved Salesforce is a fantastic case study for many of the points I’ve outlined here. They have caught on early to the fact that data, and huge amounts of it, is the only way to power the next generation of artificial intelligence applications. It’s not enough to use the most generic LLM possible (GPT3/4); you need to use specific LLMs for specific purposes and use information that is specific to your business.
This is why Salesforce has rebranded its platform “Einstein 1”, combining artificial intelligence in the form of Einstein, as well as their Data Cloud. Salesforce were looking to further bolster their data product armory with the acquisition of Informatica, but talks have since fallen through.
Salesforce are also a great case study for another point – their GPT products have only been generally available for a couple of months now. It took Salesforce exactly a year from announcing their GPT products at TrailblazerDX 2023 to then release them at TrailblazerDX 2024. Whilst this is an impressive feat, this shows that doing things properly takes time.
As Salesforce have only just released their GPT products to the world, it’s going to take time for customers to evaluate, implement, and integrate these products into their existing business processes – especially since AI is still in its infancy, and has very obvious issues when it comes to hallucinations and trust. It’s also going to take time to translate to dramatic revenue growth for Salesforce, as well as productivity boosts for its customers.
There are a few companies that are profiting in real terms, such as Nvidia, ARM, Amazon, Microsoft and Palantir. But these companies are the exception, not the rule. With so much VC money flowing into startups, Futurism quotes that the real losers will be those “who are raising money on the promise of selling their services for $20/user/month”.
Why Does a Bubble Matter?
Bubbles are defined as an economic cycle, characterized by the rapid escalation and subsequent decline of asset values such as the stock market. So unless you are investing in financial markets, why does it matter?
Well, bubbles also create hype, and hype can massively impact the decisions you are making for your business or your career.
It took 48 years for electricity to reach 100% of American households, and it took half the time for the internet to go from 10% to 88% adoption in the states. ChatGPT racked up a record 100 million users in only a couple of months, becoming the fastest-used technology in history.
Whilst it’s only logical that AI is going to be adopted faster than the internet due to the fact that technologies and ideas can now spread faster than ever, strong foundations still have to be laid out. If AI is adopted without a proper understanding of use cases, and LLMs that aren’t fit for purpose are being used, at best, you could be throwing money down the drain. And at worst, you could put company data or processes at risk.
Even Salesforce, who have been some of the biggest ‘hypemen’ around for AI, have started to cool their jets. At the Amsterdam World Tour on April 18, Ed Thompson, an Ex-Gartner analyst who now works for Salesforce, suggested that we could be heading past the hype.
In the classic Gartner Hype Cycle that observes how new exciting technologies enter the market, the stereotype is for the hype to get out of control, before falling back down to earth, slowly reaching a level of maturity. Thompson suggested with the use of some headlines such as Amazon’s AI chatbot leaking data, and chatbots being vulnerable to indirect prompt injection attacks, that we are entering the trough of disillusionment.
Summary
As much as some individuals and companies would like to tell you that AI is growing at a high speed (unless you pay X money or buy Y product), the truth is that whilst the implementation of AI is moving faster than it took people to adopt the internet, or for cars to become ubiquitous, it’s only natural that the implementation of groundbreaking new technologies will take time.
Just as infrastructure and security protocols had to be built to accommodate the internet and cars, the foundations now have to be laid for AI to be useful for companies going forward. We need systems integrated, data organized, and AI use cases to be fleshed out and experimented with. The whole world is only just getting started on this journey.
Should you ignore AI? Of course not! As many have said, this is potentially bigger than the internet itself, and a new revolution is underway. But is buying a single course on prompt engineering for hundreds of dollars going to help you? I doubt it.
Anyone who called themselves an AI expert after messing around on ChatGPT for a bit probably isn’t going to teach you much. There are plenty of free resources available from Salesforce, Amazon, Google, and Learn Prompting.
See you on the other side!