Data to decisions examines the enablement of data-driven decisions across organizations. Holistic, data-informed decisions require a multi-disciplinary approach that combines performance monitoring with traditional business intelligence and analytic technologies. In addition, data-driven decisions are increasingly delivered in the context of business applications rather than in separate, analytic interfaces.
The enterprise data center was supposed to be dead by now, but the reality is on-premises workloads are getting new life courtesy of AI workloads.
ServiceNow said that the purchase of Logik.ai will expand its reach into CRM. Salesforce said Logik.ai will also accelerate its efforts in sales and order management processes.
The AI Landscape's Tectonic Shift: OpenAI's dominance is crumbling under the weight of technical missteps, unsustainable economics, and intensifying competition from both established players and newcomers. With Microsoft testing rival models, Apple reconsidering partnerships, and Chinese innovations accelerating, the "simply partner with OpenAI" strategy has become dangerously outdated. The next 18 months will transform the AI ecosystem—and only organizations with flexible, sophisticated approaches will emerge as winners.
Wikimedia, the organization behind Wikipedia, said its infrastructure is being taxed by non-human traffic scraping the site for data to train AI models.
Informatica's Spring launch of its platform integrates its data management platform with the key enterprise data platforms as well as a preview of its CLAIRE Copilot for Data Integration.
OpenAI's move to raise another $40 billion at a $300 billion valuation is being funded by Softbank, which in turn is paying for its bet with a lot of leverage.
Amazon is putting its Nova family large language models (LLMs) on display for a tryout aims to spur developer interest. And if Alexa+, which is also available for early access, performs well Nova's profile will only increase.
AI agents remain the hot topic among BT150 CxOs and there’s little to no doubt multi-agent systems will be useful. However, there are doubts about vendor offerings, platform lock-in, data strategy, architecture and change management.
Cognizant is betting that it can embed agentic AI across enterprises. The strategy will be driven by the ability to design enterprise AI agents that work across systems, create industry-specific large language models and build its own platforms such as Cognizant Neuro AI, which is built on Nvidia's stack.
