Industry executives and experts share their predictions for 2025. Read them in this 17th annual VMblog.com series exclusive.
By Leaders from Splunk
AI is now the cornerstone of every company’s strategy. As AI matures, organizations are strategically deploying it to bring a competitive advantage. From new data integrations to agentic AI and AI agents, the possibilities will continue to expand when business leaders think of AI use in 2025.
Moreover, the tools used to help bring these ideas to life also play a pivotal role in helping build momentum for AI. Large language models (LLMs) help streamline a multitude of processes for efficiency, but they also have the potential to cause issues, such as AI hallucinations, if used incorrectly. This will bring a variety of solutions to address these challenges.
All of this would not be possible without data. Data is the lifeblood of all things innovation, and it’s what will bring new and exciting ideas to the future. With that being said, here is how leaders at Splunk predict AI will transform in 2025:
AI exploration gives way to expectations as boards prioritize tangible outcomes
Organizations are looking to see real results coming from AI’s integration with their company, which includes seeing a more efficient execution of business processes. Tom Casey, SVP of Products and Technology at Splunk, believes that the way companies will use AI will be reflected in their business outcomes:
“There have been a lot of exploratory projects over the last year, and now we’re starting to see a shift towards much more
practical ones with real targeted returns for the business.”
One such practical AI use case is boosting the productivity of entry-level workers.
“One of the biggest problems in security is there aren’t enough skilled workers to fill SOC analyst roles. AI is going to help lower the barrier to entry and effectiveness for those who are early in their careers or making job changes.”
The biggest dividends may come from AI investments that improve operations, such as in the SOC to help set alerts or automatically generate run books. Mark Maslach, GVP, Global Technical Sales, Observability at Splunk, envisions AI driving anomaly detection and root cause analysis, as well as predicting issues and automation responses:
“One trend that will evolve next year is observability in AIOps. Specifically AI in IT operations. We’ll see an influx of automation.”
There’s no digital resilience without vendor resilience
Vulnerabilities continue to be a challenge for companies, and third-party integration is not going anywhere. Partnerships with
resilient vendors will become an even bigger priority, as Michael Fanning, Chief Information Security Officer, at Splunk, outlines:
“Next year, the focus will be on business continuity if an organization loses a third-party vendor to an outage of security failure. We’ll see more strategic planning around vendor resilience and more investments to ensure the business is not impacted.”
AI-powered risk forecasting will help companies predict security threads, service distributions, while also aiding in developing adaptive SLAs that dynamically adjust based on real-time performance data and event urgency.
Defending business continuing will become a two-way street for vendors and customers. Vendors may dictate practices to customers, such as requiring stronger security measures and certain ITOps assurance, and may also attempt to align with their customers’ resilience philosophy and execution. This could mean stronger processes for reporting incidents and outages promptly and communicating real-time updates during disruptions.
The future of large language models (LLMs) will be small
With all the excitement that comes with new LLMs, Hao Yang, VP of Artificial Intelligence at Splunk, believes that companies will look to utilize LLMs for specific use cases.
“Today’s LLMs know everything. But do you really need that all the time? If you reduce the model to a reasonable size
that fits your specific use case, you can reduce the cost significantly.”
This is why we’ll see a rise in domain-specific small language models (SLMs), which will deliver unprecedented accuracy while significantly reducing operating costs and environmental impact.
“From an environmental perspective, I look at the numbers from these data centers that use tremendous amounts of energy,” says Yang. “That will be a huge problem if everyone builds their business on AI and LLMs. We need to rethink these architectures.”
Expanded Opportunities in the Era of AI
Data is becoming more important as we go into the new year because it drives new solutions and improves business outcomes
through gained knowledge. Simon Davies, Splunk SVP and General Manager in APAC, believes that utilizing important data will lead to transformative innovations:
“Data is not only the lifeblood driving better business outcomes. It’s the seed that transforms and catalyzes innovative
solutions. Solutions like crop health monitoring, gene therapy, and wildlife preservation – all of which will revolutionize our world for the better.”
The revolutionizing aspect of data utilization carries over into AI, as companies find equitable ways to leverage the benefits of data for AI use. Petra Jenner, SVP and General Manager for EMEA at Splunk, finds AI humanizing:
“AI will make us more human again. Think about our uniquely human skills: trust, empathy, connectedness. In an AI-driven
world, these will become more relevant than ever.”
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