As organizations shift from vulnerability management (VM) to exposure management (EM), the role of the VM analyst must evolve or become outmoded.
This necessary transition forces analysts to move beyond the job description of scanning and patching and into more strategic, business-aligned roles. AI has necessitated this change in many areas of security, from SOCs to CISOs, and now vulnerability analysts are feeling the shift.
It’s an opportunity. By leaning into exposure management and all that AI enables within it, VM professionals can do more than continuously clear out backlogs. They can provide more value to the business by:
- Communicating real-world attack paths
- Prioritizing the most business-relevant risks
- Translating technical findings into insights
By adopting exposure management and leveraging AI-driven risk forecasting, VM professionals can:
- Understand real-world attack paths
- Prioritize risk based on business impact
- Translate technical findings into things the C-suite cares about
Transitioning into an exposure management role opens up more doors at much higher levels than patching CVEs alone ever could. One keeps you down in the weeds; the other puts you in front of the board.
Why exposure management unlocks career progression
VM was vital when vulnerabilities presented the biggest source of risk; they don’t anymore. Now, cybersecurity leaders are relied upon to communicate risks at every level and of every type, from cloud misconfigurations to excessive permissions to shadow AI. This leaves those with VM-exclusive skillsets and roles at a critical disadvantage.
Adaptation is needed to extend the longevity of a VM professional’s career.
Exposure management takes these fundamental skills – identifying weaknesses and gaps, prioritizing what to remediate first, ensuring the proper cadence – and applies them to a bigger arena.
Gartner asserts that “Creating prioritized lists of security vulnerabilities isn’t enough to cover all exposures or find actionable solutions,” arguing instead that “security operations managers should go beyond vulnerability management and build a continuous threat exposure management program.”
As security teams adopt EM, the move from technical execution to business-centric security strategy becomes natural for VM experts. New elements of the job include breaking down silos between tools, collaborating across previously distanced teams, and acting as the point-person for all things exposure across the enterprise.
Exposure Management allows analysts to translate vulnerabilities into business impact, bringing VM-level analysis (what’s wrong, how can we fix it) to the next level: what’s wrong, how does that impact the company, and what should we fix first to support business priorities?
It means mapping exposures to revenue risk, operational disruption, and compliance pitfalls beforehand, not fixing the security problem in a vacuum and leaving the rest of the executive board to handle the rest.
The job transitions from a laborer to a key strategist, making the role more valuable and whoever inhabits it harder to replace. AI is a major part of making this happen.
AI: increasing the need for EM experts in the hierarchy
In an exposure management program, AI may do the legwork – ingesting telemetry, correlating asset inventories, mapping attack paths, normalizing CVEs – but someone still needs to present it with authority. C-suite executives and other business leaders need a human interface so they can challenge assumptions and understand how the findings relate to business risk.
They need a person with technical authority to trust with communicating remediation priorities, and someone who can assemble the teams to do it. They need a person to take point, and shoulder the responsibility both in board meetings and after, with teams.
Most importantly, they need someone with the technical prowess and experience to apply intuition to the task, rather than another person reading another report generated by AI.
Modern EM platforms deliver security insights, and many even orchestrate responses. But humans are still needed to give the go-ahead on which projects are worth pursuing, and to tie those remediations into the overarching security – and company – strategy.
This is where AI alone falls short, and only a trained EM professional can deliver.
From fixer to forecaster
However, combined, AI and exposure management leaders bring a unique value to the SOC, and by extension to their entire organizations: predictive risk modelling and forecasting.
It’s one thing to be able to see all exposures across the enterprise and prioritize them based on severity and impact. But it’s another to be able to determine which is most likely to be exploited and add that component into the mix when determining priorities (predictive risk modelling).
AI models not only which exposures exist, but which attack paths are most plausible in context and therefore most risky. It also helps determine who is likely to be targeted next.
EM analysts use AI to understand how campaigns unfold over time, enabling them to predict things like:
- How quickly a campaign might propagate
- Where controls might fail
- Who is likely to be targeted next
AI models generate probabilistic forecasts only, meaning that a human analyst still has to vet their work. But that’s beside the point: AI helps analysts anticipate threat exposure rather than react to it, and that’s the key difference.
This shift supports the move we see paralleled across all roles of security right now: from reactive firefighting to proactive preparation. McKinsey cyber-resilience expert Justin Greis states that “The next level of maturity is proactive security, where the cybersecurity function leads the way and can point out issues to the business…”
As organizations seek out that ‘next level of maturity’, finding seasoned security experts who can helm it will be a top priority, regardless of existing AI investments.
Building a future-proof security career
With EM and CTEM becoming foundational to modern security programs, analysts who upskill will keep their jobs: even though that job might fundamentally change.
VM specialists who develop skills now in risk-based prioritization, business alignment, and communication will be better positioned for senior and strategic roles. And as more technical roles get absorbed by AI, those positions will increasingly be the only ones left.
As Carl Manion, Managing Vice President at Gartner, recently stated: “Preemptive cybersecurity will soon be the new gold standard for every entity operating on, in, or through the various interconnected layers of the global attack surface grid (GASG).”
The careers that will hold will be the ones that align with this new, proactive reality.
An ardent believer in personal data privacy and the technology behind it, Katrina Thompson is a freelance writer leaning into encryption, data privacy legislation, and the intersection of information technology and human rights. She has written for Bora, Venafi, Tripwire, and many other sites.
The opinions expressed in this post belong to the individual contributors and do not necessarily reflect the views of Information Security Buzz.