“AI-first” is a term that is heard regularly in boardrooms, strategy meetings and business planning sessions across nearly every industry. It signals a shift in organizational thinking around scalability and productivity — and it’s already proving to be a competitive differentiator.
According to Gartner, organizations that adopt and sustain an artificial intelligence-first strategy are expected to achieve approximately 25% better business outcomes than competitors by 2028, underscoring the value of embedding AI at the core of operating models rather than treating it as an add-on.
The security industry is no exception. But as the concept of AI-first gains popularity, integrators are left wondering: What does it really mean in real-world security operations?
As we move into 2026, security integrators are being measured not just by what they install but by how well their solutions operate over time. Customers are facing regulatory mandates, staffing shortages and rising threat complexity simultaneously. As a result, integrators are increasingly responsible for designing security environments that scale, stay compliant, and reduce human fatigue.
In this article, we explore the key security trends likely to play out in 2026 and explain how integrators can design AI-first, regulation-ready systems that support continuous operations without increasing staffing burdens.
AI Takes on Redundant Security Functions
AI-first security does not mean replacing people with machines. It means innovating to multiply the efforts of existing staff in order to provide the security needed amidst diminishing resources. It means making sure that humans are empowered to do what only humans can do and leveraging AI as a force multiplier.
More and more, organizations are leveraging AI to help manage persistent and repetitive tasks such as screening, monitoring, alerting, and first-pass decision support. These are roles where consistency and speed matter more than subjective judgment and where fatigue can introduce risk.
Humans remain essential, but their role shifts toward supervision, escalation and response. For integrators, this changes system design priorities. The key question becomes whether a solution can operate hour after hour with consistent performance while preserving human focus for high-value decisions.
Healthcare Regulations Accelerate AI-First Adoption
One of the clearest drivers of AI-first security design is regulation, particularly in healthcare. New requirements are increasingly mandating weapons-detection capabilities at hospital entrances, often across dozens of access points within a single facility.
Staffing every entrance manually is neither operationally realistic nor financially sustainable. AI becomes essential to automating screening, identifying potential threats, generating compliance logs, and maintaining audit trails without slowing patient and visitor flow.
For security integrators, this means designing entryway architectures that balance safety, compliance, throughput, and experience. Hospitals are no longer purchasing standalone devices. They are investing in operational models that allow them to meet regulatory obligations while maintaining a welcoming environment.
The Move Toward Centralized AI Security
Labor shortages are a reality. More than 40 percent of security service providers cite staffing shortages as a top operational challenge. In response, organizations are moving away from labor-intensive staffing models and toward supervision-based models. AI handles continuous monitoring and screening, while human operators oversee multiple systems simultaneously and intervene when escalation is required.
For integrators, this shift demands new design thinking. Systems must provide centralized visibility, consistent alert logic, and clear escalation pathways. The objective is not only efficiency but reducing cognitive load so operators can perform effectively when it matters most.
AI Compliance and Auditability
As AI becomes embedded into daily security operations, expectations around transparency and accountability rise. Regulators, auditors and executive leadership increasingly want evidence that systems perform as intended.
This includes uptime data, accuracy metrics, documented procedures, and reliable audit trails. Integrators are now expected to deliver solutions that support compliance by design rather than relying on manual reporting or after-the-fact justification.
In regulated environments such as healthcare, transportation, and critical infrastructure, integrators who can clearly articulate how new AI-enabled security systems support compliance—not just detection—gain a meaningful competitive advantage.
Early AI Security Investment Separates Leaders
Perhaps the most important takeaway heading into 2026 is that AI is no longer an optional, future add-on. It is becoming a foundational layer in systems throughout business operations.
It’s likely that early-adopter clients are already seeing tangible returns. According to Boston Consulting Group, organizations that focus deeply on AI and commit to reshaping core functions around it generate approximately 2.1 times greater ROI on their AI initiatives compared to peers who spread their efforts too thin. This shows the value in helping your clients plan early and thoughtfully.
If your clients invest early, they’ll gain time to build institutional knowledge, refine human-in-the-loop workflows, and adapt processes with less friction. If they delay adoption, they risk rushed deployments driven by regulatory deadlines, staffing pressure, or incident response.
For security integrators, guiding your clients through early, thoughtful AI adoption frameworks strengthens long-term partnerships. As AI-first security becomes the industry standard, integrators who understand how to design, deploy and operate these environments will be positioned as trusted strategic advisors who can help their clients protect their people, their premises and their bottom line.
Christopher Ciabarra is the co-founder and chief technology officer of Athena Security.