#enterprise-ai

#enterprise-ai

For many, enterprise AI adoption depends on the availability of high-quality open-weights models. Exposing sensitive customer data or hard-fought intellectual property to APIs so you can use closed models like ChatGPT is a non-starter. Outside of Chinese AI labs, the few open-weights models available today don't compare favorably to the proprietary models from the likes of OpenAI or Anthropic. This isn't just a problem for enterprise adoption; it's a roadblock to Nvidia's agentic AI vision that the GPU giant is keen to clear.

It is becoming increasingly difficult to separate the signal from the noise in the world of artificial intelligence. Every day brings a new benchmark, a new "state-of-the-art" model, or a new claim that yesterday's architecture is obsolete. For developers tasked with building their first AI application, particularly within a larger enterprise, the sheer volume of announcements creates a paralysis of choice.

They know all too well how Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla have delivered more than half of the S&P 500's gains in recent years, setting a high bar for everyone else to clear. But things change: One minute, Alphabet is behind the curve on AI and then Google's latest Gemini launch sparked a 'Code Red' from ChatGPT's Sam Altman.

"What's driving all of this is the awareness from CEOs and executives that this is the time to invest in AI," Jain said in an exclusive interview before the conference. "Everybody has been looking for a safe, secure, more appropriate version of ChatGPT for their employees. And we bring the capabilities that ChatGPT brings to consumers to business users, and in the context of their company."

OpenAI released new data Monday showing enterprise usage of its AI tools has surged dramatically over the past year, with ChatGPT message volume growing 8x since November 2024 and workers reporting they're saving up to an hour daily. The findings arrive a week after CEO Sam Altman sent an internal "code red" memo about the competitive threat of Google.

The launch comes as Mistral, which develops open-weight language models and a Europe-focused AI chatbot Le Chat, has appeared to be playing catch up with some of Silicon Valley's closed source frontier models. The two-year-old startup, founded by former DeepMind and Meta researchers, has raised roughly $2.7 billion to date at a $13.7 billion valuation - peanuts compared to the numbers competitors like OpenAI ($57 billion raised at a $500 billion valuation) and Anthropic ($45 billion raised at a $350 billion valuation) are pulling.

In this comprehensive interview at SAP Connect in Las Vegas, Stephan de Barse, President of Global Business Suite at SAP, makes the case for why best-of-breed enterprise software is being replaced by best-of-suite approaches, driven by the commoditization of the application layer through AI. De Barse, who previously spent seven years at o9 Solutions, a best-of-breed supply chain vendor, brings a unique perspective to the debate.

Enterprises can move from small pilots to full deployments without violating their jurisdiction's rules on where data should live. The reality is that, earlier, most security and compliance teams weren't rejecting GenAI because of model design; they were rejecting it because storing data in the US or EU pushed them into conflict with GDPR, India's incoming DPDPA norms, UAE's federal rules, or sector-specific mandates like PCI-DSS,

"You have to pay them a lot because there's not a lot of these people for the world," Gomez said. "And so there's tons of demand for these people, but there's not enough of those people to do the work the world needs. And it turns out that these models are best at the types of things those people do."

Everybody would say yes, but we kept moving the goalposts," Ghodsi said in the discussion, which was published Tuesday.

"The customer can set up their own tagging system or we can dynamically create that for them,"

Without really knowing how work is done, it is really hard to know where to improve it, where to automate it, where agents can help.

PromptQL is an enterprise platform that aims to automate some of the work of a typical consultant, like surfacing insights and generating reports. It helps clients build custom AI analysts by integrating their internal data with the foundation models they already use. Once deployed, these AI analysts can perform tasks typically handled by data scientists or engineers - and continuously learn and adapt to their environments over time.

In the UK, artificial intelligence (AI) is no longer a buzzword reserved for tech conferences and research labs - it's an engine driving tangible transformation across industries. Healthcare, in particular, stands at the forefront of this change. From automating administrative tasks to accelerating medical research, AI is creating opportunities for both the public and private sectors to work smarter and more efficiently. A new era of intelligent healthcare solutions

ServiceNow CEO Bill McDermott does not see artificial intelligence as a threat to business software, but rather as an opportunity to increase the value of enterprise platforms. According to him, the future lies not in autonomous AI systems that render traditional software obsolete, but in close collaboration between AI models, hyperscalers, and integrated business solutions. In an interview with CNBC, McDermott explained that ServiceNow has aligned its strategy with collaboration with the three largest hyperscalers.

Dreamforce 2025 is imminent, with 50,000 people due to descend on the Moscone Center to hear about the latest advancements across its cloud, data, collaboration, and AI offerings. In the past few years, Salesforce has gone from strength to strength, with sustained growth and an exploding customer base for its offerings. The CRM giant has gone all in on enterprise AI in moves to meet customer demand, recording 120% revenue growth across its Data Cloud & AI segments in FY25.