Security buyers want fewer dashboards and faster decisions

The buying question has changed

Security teams are no longer asking vendors to prove that a dashboard can show more alerts. They are asking whether a tool helps an analyst make a correct decision faster. That change matters because the modern security operations center is already carrying too many consoles, too much duplicated telemetry, and too many handoffs between products that were bought for good reasons but never fully joined into one working process.

The evidence is now visible across current security research. Splunk's State of Security 2025 report, released in May 2025 after research with Oxford Economics, surveyed 2,058 security leaders and analysts across markets including the United States, United Kingdom, Germany, France, India, Singapore, Japan, Australia, and New Zealand. Its findings show why buyers are impatient: 78% said their security tools are dispersed and disconnected, 69% said that disconnected tooling creates moderate to significant challenges, and 59% named tool maintenance as the main source of inefficiency.

That is not a branding problem. It is an operating problem. When a product forces analysts to move from one console to another, rebuild context, translate severity labels, copy evidence into a case record, and then ask a different tool for the next step, the dashboard has become part of the workload. Buyers are noticing. The better sales conversation in 2026 is not about how much data a product can ingest. It is about how much work it removes between signal and action.

Tool sprawl is now a response-time risk

The old argument for buying more security products was simple: each new threat class seemed to justify a specialist control. Endpoint detection, email security, identity monitoring, cloud posture, vulnerability management, data security, SIEM, SOAR, attack surface management, exposure management, fraud signals, and threat intelligence all had a reasonable claim on budget. The problem is what happens after those tools arrive.

Splunk's report says 57% of respondents lose investigation time to data management gaps. It also says 59% have too many alerts and 55% have too many false positives. Those numbers explain why security leaders have shifted from tool-count debates to workflow debates. A team can own excellent products and still respond slowly if the tools do not share context at the point where an analyst has to decide what matters.

The 2025 Pulse of the AI SOC report from Cybersecurity Insiders and Gurucul makes the same point from a SOC pressure angle. In that survey, 76% of respondents cited alert fatigue as a top challenge, 73% cited analyst burnout and staffing shortages, 64% pointed to manual investigations, and 59% cited tool sprawl and complexity as a major drag on SOC efficiency. The report also said 88% had seen alert volume increase, with 46% reporting a rise of more than 25% over the prior 12 to 24 months.

The conclusion for buyers is uncomfortable but practical. More tools can improve coverage while still making decisions slower. A detection product that adds signal but does not improve prioritization may raise the team's total cognitive burden. A dashboard that shows a queue but does not explain why one case outranks another leaves the analyst to do the expensive work. The next buying cycle is therefore centered on response time, not console count.

Disconnected tools make analysts the integration layer

The most expensive part of tool sprawl is often hidden inside routine analyst behavior. A suspicious login appears in one product. The endpoint history sits in another. The email trace is somewhere else. Cloud audit evidence requires a different query. The case record lives in a ticketing or SOAR product. If the analyst has to connect those facts manually, the organization has not really bought a security platform. It has bought a collection of evidence stores.

Torq's 2026 AI SOC Leadership Report, based on a survey of 450 CISOs and security leaders, gives that hidden cost sharper edges. Torq reported that 80% of SOC teams rely on disconnected point solutions and that 36% cite a patchwork of multiple tools as a functional gap. It also found that analysts spend an average of 8.6 hours a week validating AI outputs across tools. That is a useful warning for buyers who assume AI will erase fragmentation by itself.

The AI layer can make a fragmented environment faster, but it can also make the fragmentation more confusing. Different products use different confidence scores, severity labels, enrichment methods, and evidence formats. If the AI result from one console conflicts with the risk score from another, the analyst still has to resolve the contradiction. In that moment the human is not using AI as a decision aid. The human is auditing the stack.

That is why buyers are asking for fewer dashboards, not fewer controls. They still need endpoint, identity, cloud, network, email, vulnerability, and data signals. What they want is one investigation path where those signals arrive with enough context to support a defensible decision. A vendor that cannot show how an alert becomes a case, how evidence is gathered, how ownership is assigned, and how response steps are recorded is leaving the hard part to the customer.

XDR raised the bar for analyst experience

The extended detection and response market helped make analyst experience a formal buying criterion. In its Q2 2024 XDR Wave announcement, Forrester wrote that gathering endpoint telemetry is not enough; the vendor also has to visualize and explain that telemetry in a way that makes it actionable. Forrester also warned that taking in too much data can hurt detection quality when normalization and prioritization are weak.

That point has become more relevant as buyers test broader platforms. A product that promises to ingest everything can still fail if it cannot explain relationships, suppress low-value repetition, and preserve detection quality across third-party telemetry. Security leaders are learning to ask which sources improve the investigation and which ones merely expand the data lake.

Forrester also described XDR as a market with potential to reduce SIEM costs, enhance detection, and improve analyst experience. Those three goals are now tied together. Reducing SIEM cost without improving the investigation path is just a budget cut. Improving detection without lowering noise can increase stress. Improving analyst experience without enough evidence can produce fast but weak decisions.

The useful XDR discussion is therefore not whether XDR replaces SIEM in every environment. Many enterprises will keep SIEM, data lake, case management, endpoint, identity, cloud, and detection products together for years. The more important question is whether the analyst can move through that environment without repeating the same work. Buyers want fewer places to click because every extra handoff creates delay, uncertainty, and room for error.

Platformization is not the same as blind consolidation

Security platformization gained a louder voice at RSAC 2026, but the trend is not as simple as buying everything from one vendor. SiliconANGLE's March 25, 2026 coverage of theCUBE's RSAC analysis described platformization as a real enterprise buying shift as organizations pull back from expanding already crowded security stacks. The same coverage cited Enterprise Technology Research discussion showing the best-of-breed argument for adding more suppliers at a two-year low, while only 5% of respondents planned to decrease security spending.

That pairing is important. Buyers are not necessarily spending less on security. They are questioning whether another supplier will make the team safer or only add another surface to manage. The pressure is strongest where AI risk, cloud exposure, and identity abuse all intersect with existing SOC limits.

The RSAC discussion also pointed to a governance gap around AI agents. Erik Bradley of Enterprise Technology Research said 37% of organizations had AI agents deployed or in active testing, up 10 percentage points from the prior year, while 20% admitted they had no agent-specific security controls and only 3% said they had broad controls. That matters for platform decisions because agent activity creates new questions about identity, permissions, data access, audit trails, and response ownership.

Blind consolidation can still be dangerous. A single platform that lacks depth in a critical area may weaken coverage. A single vendor that makes data hard to export can create lock-in. A single console that hides poor detection behind attractive workflow screens can mislead leaders. The mature buying approach is narrower: reduce unnecessary handoffs, demand open evidence, keep the controls that materially improve detection, and retire tools that duplicate work without adding decision value.

The new demo test is the investigation path

Security demos used to center on breadth. Vendors showed dashboards, alert queues, ingestion connectors, topology maps, compliance views, and AI summaries. Buyers now need a harder test: start from a real alert and make the vendor show every step from triage to containment recommendation.

A good demo should answer practical questions. What evidence appears first? Why is the alert ranked this way? Which identity, endpoint, cloud, email, or network facts are connected automatically? Which facts require a manual query? Can the analyst see the source record behind an AI summary? Does the product show confidence and uncertainty? Can the case be assigned, escalated, and closed without rebuilding context in another tool? Does the product preserve a clear record of who made each decision?

This investigation-path test separates useful consolidation from cosmetic consolidation. A vendor may have one portal but still force the analyst through disconnected modules. Another vendor may integrate with several third-party products and provide a smoother path than a suite that looks unified only on a slide.

The key metric is not the number of panels on the screen. It is time to confident action. If a tier-one analyst can identify a false positive faster, escalate a real case with stronger evidence, or trigger a containment step with less manual copy work, the platform has value. If the tool only changes the color of the queue, the buyer has not solved the problem.

AI makes transparency more important, not less

AI is a major reason security buyers are revisiting their operations stack, but it is not a shortcut around evidence. Splunk's State of Security 2025 report said 59% of organizations had moderately or significantly boosted efficiency with AI and 56% had prioritized applying AI to security workflows during the year. It also said 63% agreed that domain-specific AI significantly or extremely enhances security operations.

Those findings support AI investment, but they do not support hands-off automation. Splunk's own framing kept human oversight central to effective cybersecurity. That matches what many SOC leaders are seeing in practice. AI can summarize alerts, correlate evidence, suggest queries, draft response notes, and speed up threat intelligence review. But when the model cannot show its sources or explain why one signal matters, the analyst inherits a new validation burden.

The Torq findings show that burden clearly. Analysts are spending hours validating AI outputs, and disconnected tools make that validation harder. If one product says the alert is likely benign and another assigns high severity, the buyer needs a clear explanation path. Otherwise the AI layer becomes another dashboard that must be checked.

For buyers, the standard should be evidence-linked AI. Summaries should point to source events. Recommendations should show assumptions. Confidence scores should be understandable. Playbooks should be reviewable. The goal is not to remove analysts from judgment. The goal is to remove repetitive collection and formatting work so the analyst can spend more time on judgment.

Logging still has to be boring and reliable

Platform consolidation does not remove the need for basic logging discipline. Google Cloud's M-Trends 2025 report said global median dwell time rose to 11 days in 2024, up from 10 days in 2023. It also said stolen credentials became the second most common initial infection vector in Mandiant investigations, at 16%, while exploits remained the most common at 33%. Those numbers are a reminder that defenders still need strong telemetry, identity visibility, and the ability to reconstruct attacker movement.

M-Trends also recommended improving logging and monitoring practices to identify suspicious activity and reduce dwell time. That advice sits awkwardly beside the push for fewer dashboards, but it is not a contradiction. Buyers do not want less evidence. They want evidence organized in a way that helps people act.

A consolidated workflow that drops critical logs is a bad trade. A platform that cannot preserve raw evidence, support threat hunting, or export records for incident response will frustrate mature teams. The right target is fewer operator handoffs with stronger evidence retention. Security leaders should ask whether the product improves visibility across identity, endpoint, cloud, email, and key application activity without hiding the underlying data from investigators.

The same logic applies to incident response readiness. During an incident, teams need timelines, affected assets, identities used, control actions taken, and decision records. A smooth dashboard is useful only if it keeps those facts intact. The buyer's question should be direct: when the board, regulator, insurer, or legal team asks what happened, can this tool help prove the answer?

What buyers should ask vendors now

The strongest vendor conversations now start with workflow evidence. Buyers should ask vendors to map a full investigation, not just display a queue. The vendor should show the first alert, the enrichment path, related identity and endpoint context, affected cloud or SaaS activity, recommended containment options, approval steps, and the audit record that remains after action.

Buyers should also ask how the product handles third-party data. A platform that performs well only with native telemetry may still be useful, but the customer needs to know the boundary. If third-party logs lose detail, arrive late, or receive weaker detection logic, the platform may create a false sense of coverage. Forrester's warning about detection quality across additional surfaces is worth turning into a procurement question: which sources improve the analyst experience, and which ones are supported only because the connector exists?

Another useful question is how the product reduces maintenance. Splunk found that tool maintenance was the main inefficiency for 59% of respondents. That means buyers should ask about connector upkeep, parser changes, API limits, version changes, playbook ownership, and what happens when a data source breaks. If the vendor's answer is that the customer can script around it, the maintenance burden has not disappeared.

Finally, buyers should ask how AI decisions are reviewed. Does the product show source events behind a summary? Can an analyst correct the model output? Are those corrections tracked? Does the product separate AI-generated confidence from rules-based severity and human disposition? A platform that cannot answer those questions may speed up the wrong work.

What security teams should retire first

Not every redundant tool should be removed at once. The better first step is to identify tools that create work without improving decisions. A product is a candidate for retirement if it raises alerts that are already covered elsewhere, requires constant parser upkeep, cannot feed the main investigation queue, or produces reports that leadership reads but analysts do not use.

Another retirement candidate is the dashboard that exists only for a narrow audience but forces daily work on the SOC. Some tools look useful during quarterly reviews but add little during live investigations. If the evidence from that tool cannot be tied to cases, severity, response, or risk reduction, the team should question whether it belongs in the active operations path.

Security leaders should also be careful with shadow consolidation. Sometimes teams stop using a tool long before contracts end. That creates a budget and coverage problem: leaders believe a capability exists because it is licensed, while analysts route around it because it slows them down. A usage review should compare procurement records with actual case activity, query logs, response actions, and analyst feedback.

The best retirement plan is evidence based. Keep tools that improve detection, preserve critical telemetry, or support required controls. Remove tools that duplicate signal, require constant care, or leave analysts to reconcile conflicting outputs. The goal is not a smaller stack for its own sake. The goal is a stack that makes the next correct action easier.

What this means for 2026 budgets

Security budgets in 2026 are likely to keep favoring platforms, identity controls, AI security, cloud detection, and exposure management. But the winning budget requests will be framed around operational outcomes. Leaders will need to show how a purchase reduces investigation time, lowers false-positive drag, improves coverage for high-risk assets, or strengthens the evidence trail for response.

That creates a harder standard for vendors and a healthier standard for buyers. A new product should not win budget only because it adds a category label to the stack. It should win because it changes what happens during a real incident. Does it reduce the time between first signal and triage? Does it help a smaller team handle more cases without hiding risk? Does it improve analyst confidence? Does it make response steps repeatable without removing human review from serious decisions?

The same budget lens should be applied to AI. AI that summarizes noise is not enough. AI that helps connect identity, endpoint, cloud, and business context into a reviewable case can matter. AI that explains its evidence and supports consistent escalation can matter even more. But AI that arrives as another disconnected product may simply add one more surface to validate.

The practical buyer position is clear: fewer dashboards, better evidence, faster decisions. That does not mean one vendor for everything. It means no tool gets a free pass if it adds work at the moment analysts are under the most pressure.