This year marked a turning point for enterprise tech as spending recovered and the economy stabilized following years of rising interest rates and supply-chain disruption. While no one knows what lies ahead, here are five things we thought summed up a pivotal year.
Today: A look back at some of the most notable developments from the past year and the last Runtime Roundup of 2024.
Today: Salesforce continues its agentic AI push, Databricks secures one of the biggest funding rounds in tech history, and the rest of this week's enterprise funding.
Most enterprises are still struggling to turn their generative AI experiments into actual production applications. They've done more than 99% of the work, but the last 1% has proven much harder than anticipated, according to AWS's Swami Sivasubramanian.
This era of enterprise software is either the dawn of a new era of corporate productivity or the most hyped money pit since the metaverse. ServiceNow's Amit Zavery talks about the impact of generative AI, how SaaS companies should think about AI models, and his decision to leave Google Cloud.
Anyscale is built around Ray, an open-source project that was designed to help AI workloads scale. But in recent years, commercial pressures have forced several companies with similar open-source origin stories to put restrictions on their projects to ward off competition.
In an interview at the Data Cloud Summit, Ramaswamy described how enterprise customers are working with generative AI, outlined growth opportunities for Snowflake's future, and lamented the "insular" culture at Google that denied it the opportunity to lead the generative AI transition.
Certainly, the generative AI craze has been good for C3 AI, but according to chairman and CEO Tom Siebel, it also has the potential to go to a really dark place.
Google announced plans this week to bring its Gemini foundation model into its database strategy, giving administrators new tools to maximize uptime and generate SQL code.
"The more significant decision is, 'what is your strategy for centralizing the data?' Because these data platforms do not do that; they are the place that it gets centralized to, but they do not centralize anything."
The most important issue in AI is a lack of open models that could allow researchers — who know surprisingly little about how the generative AI craze that upended the tech industry actually works — to set the parameters of the larger discussions around AI regulation.
"When you have way too many companies chasing way too few opportunities, you go through a cycle like this and only the best will survive." McKay thinks Snyk has found a path forward.
Nishita Henry's job involves helping Deloitte's clients find opportunities and avoid problems while operating on AWS. After several years of rapid change for clients that needed a cloud computing strategy, another disorienting time has arrived thanks to the rise of generative AI.
It became clear in 2023 that the incredible growth in enterprise tech spending during the early years of the pandemic was a mirage, rather than a new baseline. Redpoint's Scott Raney isn't sure how quickly the good times will return.
AWS evolved into one of the biggest businesses enterprise tech has ever seen by taking the Home Depot approach; it offers everything companies need to build digital experiences around their businesses, but it's up to you to find it and put it together. However, the market has shifted.
