AI Data Management Challenges in Enterprises

Control over a model is only one piece of enterprise AI. For organizations building AI into real operations, the bigger question is how to preserve the context, workflows, and governance that make AI useful in the first place. Going beyond open weights means building intelligence that stays valuable even as models evolve. Get the full story on #SplunkBlogs: https://splk.it/4x6NdPR

General-purpose AI can answer almost any question in seconds. For enterprise decisions, three gaps get in the way: no grounding in verified data, no business context, and no connection to workflows. Our Circana CTO guide explains how technology leaders can close them. Read it here: https://bit.ly/4yFS2QE

Logs, metrics, and events are more than exhaust — they’re fuel for AI. When machine data is connected and contextualized, AI shifts from promise to performance, reducing risk and driving outcomes that matter to the business. See how: https://splk.it/4qujnkE

General-purpose AI can answer almost any question in seconds. For enterprise decisions, three gaps get in the way: no grounding in verified data, no business context, and no connection to workflows. Our CTO guide explains how technology leaders can close them. Read it here: https://bit.ly/4yFS2QE

Your workflow just got an upgrade. ✨ Splunk AI Assistant 2.0 brings a true digital teammate into your day-to-day. Teams can now analyze data, solve problems, and move faster with full context from the Splunk Platform. See what’s new on #SplunkBlogs: https://splk.it/4mKXZ9N

AI potential is easy to demonstrate. Enterprise performance must be engineered. The value of AI becomes measurable when intelligence works reliably across trusted data, connected workflows, and everyday business decisions. Four engineering priorities make it sustainable: build enterprise capability, improve continuously, scale through reusable foundations, and measure business impact. At Qentelli, we combine engineering, modern AI platforms, and intelligent automation to turn promising pilots into scalable capabilities that deliver sustained business value as business needs evolve. Swipe through the four imperatives. See how intelligence scales: https://lnkd.in/dnywV4uP #AIEngineering #EnterpriseAI #IntelligentAutomation #Qentelli 

AI is reshaping business faster than most organizations can react. In the latest Perspectives by Splunk, we explore how to keep #AI your ally, not your adversary. From securing data pipelines to managing third-party risks and monitoring models, these practices turn AI into a trusted business enabler. See how AI can work for you: https://splk.it/4lYnxQF

Your AI bill shouldn't be a surprise. As agentic AI takes on more complex tasks, token usage can grow faster than expected. The key isn't using less AI. It's gaining the visibility to understand where costs come from and how to optimize them. Explore how observability can help organizations manage AI costs: https://splk.it/3Te37IV

AI may be speeding up operations, but it’s also raising the stakes when things go wrong. The Hidden Costs of Downtime report found outages are becoming more disruptive across the business, with growing financial pressure tied to cyberattacks, complexity, and digital resilience gaps. See what’s driving the shift: https://splk.it/4v9gUhu

Machines are generating more data than humans can process. By 2028, we'll reach nearly 400 zettabytes of global data, with more than half of it coming from machines talking to machines. The organizations winning in this environment aren't just managing the flood. They're using it as a signal. Kamal Hathi explains how the agentic AI era can turn data volume from a liability into an early warning system: https://splk.it/419kYkZ