AI: Slow Slog in the Enterprise
...more signs AI in Enterprise takes longer, for now
More evidence continues to accumulate on a point I’ve discussed at length before. That AI adoption in the Enterprise may take longer than discounted in both the public and private markets.
There are a variety of reasons for this, not the least of it being that Foundation LLM AI models are in their earliest stage in this AI Tech Wave cycle. And truly useful applications in businesses large and small will need far more specialized ‘Extractive Data’ sources than those for the internet as a whole. And it’ll take time for enterprises to tune them for optimal results, AND get users both within their companies, ecosystems, as well as customers to truly understand how to use these add-on and native AI applications platforms & services.
The Information delves into this in “Amazon, Google Quietly Tamp Down Generative AI Expectations”:
“In the past year, major technology firms have championed generative artificial intelligence as the next big thing, boosting the stock market to new highs. But behind the scenes, representatives of major cloud providers and other firms that sell the technology are tempering expectations with their salespeople, saying the hype about the technology has gotten ahead of what it can actually do for customers at a reasonable price.”
“Several executives, product managers and salespeople at the major cloud providers, such as Microsoft, Amazon Web Services and Google, also privately said most of their customers are being cautious or “deliberate” about increasing spending on new AI services, given the high price of running the software, its shortcomings in terms of accuracy and the difficulty of determining how much value they’ll get out of it.”
This is true for Microsoft and OpenAI as well, as both are laser focused on the enterprise as well for cloud data center services. Not to mention Nvidia and others as well.
As the Information continues:
“Big cloud providers collectively spent tens of billions of dollars last year purchasing AI server chips from Nvidia to produce revenue-generating AI services. While Microsoft has said AI has accelerated its growth, Google and AWS have little to show for their recent investments so far. And some of their customers have encountered problems with the tech as they tried to release it to thousands of their employees or customers—even if the features worked well for a small number of users during earlier trials, some of the cloud provider employees said.”
“I think people got overexcited last year” about implementing ChatGPT-like technologies in their businesses, said Ali Ghodsi, CEO of Databricks, which sells software that helps large companies develop AI.”
“Customers of such software are “struggling with [questions of,] is it providing value? How do you know if it’s giving good answers? How do you evaluate how it’s doing?” he said. “Generative AI is in the first inning.”
“AWS, the biggest seller of cloud servers, recently gave its salespeople a reality check on the technology. Chirag Dekate, an analyst from research firm Gartner, told AWS’s sales staff during an annual kickoff event two weeks ago that the industry is at the peak of the “hype cycle” around large language models and other generative AI. He anticipates the hype could veer into a “trough of disillusionment” in the coming year as customers realize the technology’s limitations, according to an employee who saw the presentation. Eventually, though, he expects customers to widely adopt it.”
“Separately, AWS sales chief Matt Garman urged salespeople at the event to proactively schedule meetings with customers to talk about and sell AWS’s generative AI services and increase their own knowledge of the technology, according to two attendees. Amazon CEO Andy Jassy has told investors several times in the past few months that AWS could rake in tens of billions of dollars in revenue from generative AI over the next several years, but during an earnings call in February he said that near-term revenue is “relatively small."
All this also means a potentially broader tempering of AI adoption expectations, as Stephanie Palazzolo of the Information points out in a separate piece:
“For all the hype around generative AI, we have yet to see much evidence that this new technology is lifting the top lines of customers who are spending money on it. That’s left many buyers to wonder: When will we see those long-touted returns from AI?”
“My colleagues and I tackled that question in this story today, which reported that customers of cloud providers are being cautious about spending too much on new AI services, given its high price, shortcomings in accuracy and difficulty in figuring out its value.”
“Microsoft may have had the most success in using OpenAI’s state of the art models to power its products. But even Microsoft’s new offerings have left much to be desired, according to Todd Lohr, a principal at consulting firm KPMG which advises multinational companies on automation and resells Microsoft’s products.”
“Word is okay, Powerpoint isn’t particularly useful unless you train it on specific [instructions] because it only creates a Powerpoint that’s very basic,” he told my colleague Aaron Holmes.”
“Excel is not there yet—you have to spend a ton of time [crafting instructions] prompt-engineering to get it to do anything for you, which takes way longer than just writing the Excel formulas yourself.” (You know things are bad when someone reselling a product doesn’t even have many good things to say about it.)”
Again, this too is a timely point I underlined a while ago, for Microsoft especially, whose market cap has appreciated almost a trillion dollars for its AI Copilot led initiatives for enterprises around the world.
Tech adoption takes time, especially in the early stages when customers of all stripes are trying to figure out the ‘product-market-fit’ and pricing for themselves, as well as the best way for their users and customers to actually interface and experience these new AI technologies.
So as I stressed yesterday broadly for mainstream AI apps and services in general, we will need to continue to “Wait for it” all, both for consumers and businesses. Stay tuned.
(NOTE: The discussions here are for information purposes only, and not meant as investment advice at any time. Thanks for joining us here)