Meeting White House cyber priorities requires AI-driven standardization models

At the tail end of 2025, the Office of Management and Budget published an updated President’s Management Agenda (PMA), defining core plans for the government to leverage technology to deliver faster, more secure services. The cyber implications need to be addressed quickly since agencies cannot meet PMA cyber mandates with fragmented tools and alert-only AI. The real issue is decision-making at machine speed.

One of the key pillars of the PMA calls out how federal agencies must leverage security technology solutions that will eliminate data silos and duplicative data collection and reduce wasteful processes through AI. If done with the correct tools and properly implemented, better visibility into federal data will give government agencies a tactical advantage over cyber attackers.

By harnessing AI-powered platforms that sort, organize and contextualize extensive reams of data, federal agencies will be better equipped to understand and respond to attacks as they are happening. Put more simply, the better agency security operations centers (SOC) and cyber teams can organize and gain context around data during an event, the faster and more efficient their decision-making becomes, in turn driving security mission success. 

Data, context and decision-making 

With cyber adversaries accelerating their use of supply-chain attacks, identity-based intrusions and zero-day exploits, agencies face mounting pressure to detect, investigate and respond to threats in real time.  

For federal cyber leaders to meet the cyber requirements of the PMA, they will need more maturity and context in their IT and digital systems and can no longer rely on AI that simply flags an event. Without context, AI can overwhelm teams with false positives or miss true threats hiding in plain sight.   

To combat that, agency cyber teams need to understand why the event being flagged is important. Instead of AI simply saying something looks anomalous, AI should be able to tell SOC analysts why it matters. This includes answering questions about the seriousness of the threat, whether it touches any critical systems or sensitive data and how quickly action needs to be taken. 

Context allows AI to progress into a real decision-making tool, but none of this can happen if data is siloed and inaccessible when the events are unfolding. Breaking down these walls requires a unified, AI-driven platform that reaches across agencies to collect and analyze data in real-time.

Operationalizing data for security and agency efficiency 

One way to make all these moving parts work together is by deploying a unified Security Information and Event Management (SIEM) solution that can be utilized across an agency or even across the whole civilian government. 

A SIEM helps operationalize security data by standardizing collection across organizations, enabling the kind of real-time threat detection and rapid incident response that is needed to fulfill the data and cyber requirements of the PMA. The solution has a major impact on modernization, workforce constraints and standardization, too.

This unified, scalable security and operations foundation supports government modernization by moving away from siloed, legacy monitoring tools. It shifts agencies from reactive security to a more data‑driven, proactive operation.

It plays a key role in workforce constraints, too — the automation of alert triage and response reduces analyst workload and burnout, while a unified dashboard and workflow can shorten training time for new or rotating staff. Through SIEM’s embedded threat intelligence and detection, smaller cyber teams can secure larger, complex environments more effectively.

An AI-powered SIEM platform will address another core tenet of the PMA by reducing wasteful processes and cutting through alert noise. This is done by automatically gathering related alerts and packing them in a way that highlights the bigger picture in plain language. That kind of context, driven by intuitive summaries, allows SOC analysts to focus on important next steps for remediation rather than forcing them to weed through alerts to put the picture together themselves.

SIEM has become such a powerful tool that the Cybersecurity and Infrastructure Security Agency launched a program so that agencies can integrate and collaborate on their SIEM platforms to centralize data ingestion and analytics, along with responses to events. This gives the government a unified system that provides visibility across federal civilian agencies. 

This standardization includes common data models and detection rules that enable consistent security posture across agencies. By generating compliance reporting and cross‑agency visibility, federal agencies can reduce fragmentation, audit easier and quickly adopt federal security directives.

This may all sound theoretical, but in practice, it’s easy to see how much of a difference a SIEM can make in the event of a cyberattack. 

SIEM in action

Let’s say a hypothetical threat actor gains access to an agency employee’s virtual private network (VPN) credentials through a phishing campaign. The credentials are valid, and multi-factor authentication is intermittently bypassed due to a legacy exception. Without a SIEM, this activity appears as normal authentication traffic spread across multiple systems. 

As logs stream in, the SIEM begins stitching together a broader picture. The platform recognizes that the same account authenticated from an unusual location, escalated privileges, and accessed high-value systems in a way that deviated sharply from its historical behavior.  

Within minutes, the SIEM flags the activity as high risk. The alert that reaches the SOC comes with context, including a clear timeline of events, a risk score that exceeded the agency’s threshold and recognition of attack techniques associated with compromised credentials. 

From there, an automated response playbook kicks in. The employee’s account is temporarily disabled, active sessions are terminated, and affected endpoints are isolated to prevent further movement inside the network. At the same time, all relevant logs are preserved to support the investigation and compliance requirements. By the time the analyst finished reviewing the alert, the threat had been contained.

In this kind of scenario, a federal agency could have gone weeks without realizing it was under attack. With that amount of time, cyber intruders could have found ways to gain entry into other parts of the system or even other agencies that share common systems. Instead, the agency was able to stop the intrusion before data was exfiltrated or systems were altered.

Having an AI-driven security tool like SIEM can provide the necessary federal oversight into security data, a viewpoint that is pivotal for cyber threat reporting and enterprise-wide visibility.

The PMA is clear. Security against cyber threats is a priority, and a big part of that comes from breaking down data silos and enabling better and faster decision-making. The future of federal cybersecurity rests on the government’s ability to adapt quickly to complex threats from attackers harnessing AI to do the most damage. Thankfully, agencies can also utilize AI to their advantage and face those threats more powerfully and with a more complete picture. 

An AI-enabled security platform like a SIEM can deliver on that priority by ingesting, organizing and operationalizing data in real-time, making a marked impact on federal security even in the face of threats moving at machine speed.

Bill Wright is the global head of government affairs at Elastic.