2026 Predictions: The Future of Investigation is Dynamic, Visual, and AI-Powered

The loudest story around AI has been what it will automate, which tasks it will "take over", and which roles it threatens. But that framing misses the deeper, more nuanced value.

The real change in 2026 won't be that machines do the job instead of cybersecurity teams. It'll be that AI rewires the way practitioners interact with the job. As generative UI capabilities emerge and mature, organizations will access tailored, dynamic visualizations that adapt to users' needs in the moment.

While dashboards will remain essential as reference points for monitoring overall business health, the real evolution is in simplifying complex investigations. Managers still need consistent visuals to check the health of operations, but teams will increasingly move from dense tables or raw logs to on-the-fly representations that reveal patterns and anomalies immediately. In this new era, interfaces do more of the heavy lifting, helping people at every level make smarter, faster decisions with less effort.

Looking further ahead, SOC teams will see a new breed of analyst emerge over the next five to ten years. These future professionals will work in environments where generative UI provides a seamless, intuitive interface for composing and customizing investigative runbooks, while AI takes on the task of writing those runbooks. This shift will allow analysts to focus on higher-value work like interpreting insights in business context, understanding operational impact, orchestrating responses, and driving collaboration, rather than reacting to an overwhelming number of signals from raw data or getting bogged down in manual data management and process creation.

From dashboards to dynamic visualizations in sec ops

If a picture is worth a thousand words, can the infamous “single pane of glass” tell a whole story? For years, well-designed dashboards have helped stakeholders at all levels understand problems and take action more quickly (and more enjoyably) than trawling through logs ever could. But dashboards need creating manually, ongoing tuning, and (despite fresh data) remain relatively static in design. They provide updates and metrics at a glance but weren’t designed to guide analysts through an investigation journey.

Did you miss that? Here comes another tool in your visual arsenal: generative UI. Instead of painstakingly building dashboards for every challenge, generative UI dynamically generates visual result cards, adapting to the problem you’re investigating. This is more than a UI refresh; it’s a reimagining of how the analyst of the future will view, and do, their work.

How AI and generative UI are changing analyst experience

Today, analysts are very close to data. They’re typing searches, reviewing logs, and manually building SOC artefacts like detections and playbooks, often under time pressure that leaves little room for strategic work, automation, or understanding the business context behind the signals. AI is breaking this cycle by lowering the skill barrier and helping analysts get to the core of an investigation quicker, with less effort. Generative UI will further reduce tool lift and fatigue, allowing analysts to focus on the heart of the investigation instead of shuffling data between spreadsheets.

Early adopters already use AI assistants to help create artefacts, generate alerts, and draft complex queries. This marks a shift from traditional searching to prompting, much like moving from search engines to natural language prompts. As a result, analysts are moving away from raw data and instead interacting with dynamic visual ‘cards’ generated on-the-fly in a single investigative scratch pad. While they can always drill down if needed, the default experience is far more visual and accessible.

Sharing is also becoming seamless. Generative UI embeds easy, one-click sharing and real-time collaboration into investigation tools. Instead of emailing static screenshots or spreadsheets, teams will be able to share live, interactive investigation trails and results—ensuring everyone is literally on the same page and eliminating “version 19 final FINAL” files.

Looking even further ahead, analysts may see not just these cards, but also the outcomes and recommendations of autonomous agents working on their behalf. The analyst’s role will increasingly become that of a decision-maker and orchestrator—guiding agents at crucial moments, while automation handles much of the investigative process. This evolution in human-machine interaction is on the horizon; we’re not there yet, but it’s coming.

How generative UI enables faster, smarter security investigations

Imagine the investigation journey in the not-so-distant future. An alert signals something unusual. As the analyst steps in, AI has already written and run the initial search, presenting the results as clear, relevant graphs in a dynamic investigative scratch pad. This delivers an instant head start instead of starting from zero.

From there, new lines of inquiry are prompted, not manually typed. AI executes searches and fetches supporting details, with generative UI automatically sizing and highlighting the visuals that matter most. The analyst can easily share this evolving investigation for escalation, peer review, or collaboration, with teammates seeing updates in real time on the same interactive canvas.

Traditional dashboards and reports still play a role when a consistent, high-level view is needed. However, AI and generative UI now handle much of the heavy lifting of investigation and communication. When it’s time to document, AI assembles a comprehensive incident report by pulling together the sequence, key artefacts, and analyst actions, turning what once took hours into minutes.

The future of security talent in an AI-driven SOC

Analyst roles are fundamentally shifting, demanding new skills and a change in how leaders hire and build teams. As new generations enter the workforce, they are more accustomed to prompting and interpreting AI, and less focused on manual data wrangling or writing queries. Leaders must adapt their strategies to attract and retain this talent by focusing less on experience with specific tools and more on the ability to reason, communicate clearly, and ask the right questions. These skills enable analysts to work effectively with AI and generative systems.

This evolution from doing, to designing, to managing mirrors shifts in technology, from assembly language to high-level languages and now to AI-powered tools. Just as software development changed how teams are built, operational leaders must rethink their approach.

AI and generative UI are transforming security operations and how analysts work. Visualisations are expanding from static dashboards to dynamic narratives, shifting analysts from direct data interaction to prompting AI, interpreting results, and guiding autonomous agents.

Explore more from Splunk’s 2026 Predictions series, where we look ahead at what’s next for security, observability, and AI. In this series, we also the business value of smart risk-taking, the convergence of NOC and SOC operations, how unified observability will give you better business results, and the rise of adaptive AI. For more executive insights and strategic perspectives delivered monthly, subscribe to the Perspectives by Splunk newsletter.