The Workforce of the Future: Human Ingenuity and AI Intelligence

This guest blog was contributed by Tom Findling, CEO and Co-Founder, Conifers.ai

Artificial intelligence is reshaping the landscape, giving attackers new speed and scale while forcing defenders to rethink their operating methods. At the same time, the ongoing global shortage of skilled analysts has left security teams stretched thin and struggling to keep pace. 

Security leaders can’t hire enough people to tackle the problem. And they’ve invested a great deal in tools that seemed to hold promise but still struggle to scale. The workforce of the future will be defined not by humans or technology alone, but by how effectively the two can work together.

Agentic AI as a SOC Force Multiplier

For more than a decade, SOCs have leaned on automation to ease the load. SOAR platforms and playbook-driven workflows promised efficiency but often created new complexity. Automation assumes predictability, yet cybersecurity is anything but predictable.

Agentic AI changes this. Instead of just executing tasks that follow playbooks and deliver standard results, it learns from individual environments and incidents, giving analysts the tailored reasoning they need to act faster and smarter. By transforming alerts into context-rich stories, AI highlights what matters and reduces the noise. This is the model for the hybrid workforce: AI acts as a force multiplier. It handles triage, investigations, and other tasks autonomously and supports more complex investigations while humans focus on execution and strategy, incorporating intelligence and knowledge that machines can’t replicate.

A Shift in Cybersecurity Analyst Skills

The conversation about the cybersecurity workforce has long been framed as a shortage, but the real story is a shift in what skills matter most. Tomorrow’s analysts — who may not work in a tiered system — will need strong analysis skills, critical thinking, and the ability to connect security outcomes to business priorities. Analysts who can explain risks clearly to leadership and, in the case of MSSPs to their customers, will add greater value.

Building Trust in AI-Driven Operations

Enterprises often hesitate to rely on AI in high-stakes environments because, just like humans, AI can make mistakes. Building trust in AI takes time. If analysts can’t explain how a system reached its conclusion, they won’t use it when it matters most.

That’s why adoption has to be deliberate. A phased rollout, starting with targeted use cases and expanding gradually, lets teams validate results before scaling. This approach builds confidence and ensures that AI is seen as a partner, not a black box.

The impact is tangible. Agentic AI can reduce investigation times by as much as 87%, freeing analysts to focus on complex threats. More than efficiency, it changes how SOCs operate and allows teams to spend less time reacting and more time proactively reducing risk.

AI’s Cybersecurity Impact

With AI as a true force multiplier, SOCs can evolve from reactive alert centers into proactive engines of defense. By continuously learning from institutional knowledge and adapting to each environment, AI can surface the threats that matter most. Analysts are then free to focus on high-value decisions that strengthen their organization’s security posture and resilience. Instead of firefighting, the modern SOC becomes a driver of measurable risk reduction.

The workforce of the future will be defined by results: reduced risk, faster response, and tighter alignment with business objectives. These outcomes are only possible when humans and AI operate as trusted partners. Attackers are already exploiting AI to move faster and strike smarter, and defenders who treat AI as a secondary tool will fall behind. Those who embrace it as a true partner, one that scales expertise, accelerates investigations, and amplifies human judgment, will succeed. The future of security isn’t human or AI. It’s human with AI. The organizations that understand and embrace that balance will be the ones that stay resilient.

Tom Findling is the co-founder and CEO of Conifers.ai. He is a strategic leader with a proven go-to-market, product, and data science track record. Having served as chief customer officer at IntSights (acquired by Rapid7) and as senior director of product at Rapid7, he brings a unique blend of strategic vision and execution to the table, running large-scale operations. Additionally, he led go-to-market and product roles at VMware and SUS.