Generative artificial intelligence (GenAI) has passed its peak in Gartner’s hype cycle, but has not met expectations, analysts warned at the company’s European conference in Barcelona.
In the opening keynote at the Gartner European Symposium, Alicia Mullery, vice president of research at the analyst firm, discussed two AI races: the first is the race of technology providers; The second is to deliver AI results safely and securely. “This is your race,” she told the audience of IT executives.
One takeaway from the opening session is that it is It’s easy to waste money With Jinai. “You have to understand the bill and monitor it at all times,” warned Mullery and co-presenter Darryl Plummer, a senior research analyst at Gartner.
Plummer noted that the majority of organizations Gartner spoke to are not ready for AI. “They are not prepared for this emotionally, technically, organizationally or administratively,” he said.
To reduce failure. Gartner recommended two approaches: one for organizations primarily seeking to use AI to improve productivity; The second focused on using artificial intelligence to drive transformational change.
Data from Gartner shows that running a proof-of-concept project can cost anywhere from $300,000 to over $2 million. While IT and business leaders may appreciate the significant costs associated with training AI models on expensive GPU hardware, Plummer said the costs associated with Artificial intelligence conclusion It can get out of control quickly.
“Processing is very expensive because AI models have to use something called matrix multiplication to process all the parameters they use to arrive at the prediction. That requires GPUs, which you can buy and put in your data center, or rent from a cloud provider,” he said. “Both.” “Very expensive.”
Plummer warned that technology providers are too focused on looking at AI progress from their perspective, without taking customers on a journey to achieve the goals of these advanced AI systems. “Microsoft, Google, Amazon, Oracle, Meta and OpenAI have made a big mistake – they are showing us what we can do [but] “They don’t show us what to do,” he said.
Because many organizations are not ready to adopt the advanced AI available to them from major providers, Plummer said many find that 75% of their budget is spent on IT consulting to understand how new technology can benefit their organizations.
“Getting to the proof-of-concept stage requires more budget,” he said, adding that costs will continue to rise until IT leaders start putting enterprise AI systems into production, at which point they should be able to gain a better understanding of how to manage ongoing costs. .
Analysts explained that IT leaders need to consider the results they want to achieve. Those looking to deploy AI to drive business efficiency improvements — referred to by Gartner as “AI-hardened” organizations — will likely be running 10 or fewer pilot projects or AI initiatives. In this scenario, people could be tasked with monitoring and checking to ensure that the AI systems are working properly.
Those organizations where GenAI is viewed as an industry-transforming technology are likely to employ a greater number of pilots. Gartner classifies these organizations as “Accelerated AI.” The analyst firm does not believe it is humanly possible to manage the AI systems that AI-driven organizations are looking to deploy.
As such, he predicted the advent of dubbed technology TRiSM (Trust, Risk and Security Management)which she said will play an important role in ensuring that AI systems remain compatible.
