For most of the last decade, the compliance function has carried a reputation it didn't entirely deserve: a necessary tax on doing business, a resource drain with no strategic upside, a team that existed to check boxes and stay out of trouble.
That framing is increasingly wrong, and the data is catching up with what forward-thinking security leaders already know.
Frost & Sullivan recently brought together compliance and risk leaders for a cybersecurity growth webinar on the future of compliance automation. CyberSaint CPO Matt Alderman joined the panel to explore how intelligent automation is transforming the compliance function from a regulatory burden into a genuine competitive advantage. The Frost & Sullivan research behind the session makes the urgency of that shift clear.
Here's what the discussion surfaced.
There's a reason the spreadsheet survived every wave of GRC automation over the last decade: the platforms that tried to replace it weren't built for the scale the job actually requires.
"Legacy GRC systems can't scale to consume tens of millions of data points," Matt noted during the panel. "We never accounted for this type of scale when we built those platforms almost 20 years ago. Back then, we thought automation was workflow automation."
That gap between what traditional GRC platforms were designed to do and what modern compliance programs actually require is the central problem compliance automation exists to solve. The volume of control data, telemetry signals, vendor inputs, and regulatory requirements facing today's enterprise security program has grown by orders of magnitude. Manual processes and legacy workflow tools simply can't keep pace.
The result is a compliance function that spends most of its time on low-value, high-effort work: chasing down evidence, manually populating assessments, re-answering vendor questionnaires, and preparing for audits that were already underway before preparation began.
The research Frost & Sullivan shared in the session underscores just how quickly the market is moving.
62% of organizations now view AI and machine learning as vital to achieving their business priorities - not a nice-to-have, but central to how they operate. And 74% already use or plan to use AI in risk and compliance within the next two years.
The driver isn't a novelty. It's a necessity. The compliance challenges CISOs report most frequently — overlapping regulations across jurisdictions, manual audit preparation, fragmented evidence collection, understaffed teams, and tightening budgets- are structural problems that traditional approaches can't solve by working harder. They require a different category of tooling entirely.
One of the most persistent objections to compliance automation is that it works great in theory, but real enterprise environments are messy. Not everything lives in the cloud. Not everything has an API. Many organizations run significant workloads on infrastructure that was never designed for machine-to-machine data exchange.
At CyberSaint, the approach to this problem has been to stop treating it as a single technical challenge and start treating it as a set of techniques that can be applied in combination.
"It's not just one technique anymore," Matt explained. "It's multiple techniques, API telemetry, documents and reports, screenshot data, that allow you to get more and more coverage in your automation story."
That means a standardized data schema that accepts inputs regardless of source. It means evidence collection bots that can log in to systems, capture screenshots, and parse visual data to automate control scoring. It means document ingestion that can extract and reason over report data when no API exists. The specific technique matters less than the outcome: getting compliance-relevant data out of wherever it lives and into a format the platform can work with.
The practical implication for security teams is that the hybrid environment is not a blocker. It's an engineering problem, and it's a solved one.
The question the panel kept returning to wasn't whether AI belongs in compliance. It was how to deploy it in a way that security and risk leaders can actually stand behind.
The answer, at least at CyberSaint, is transparency.
"The systems we use reason responses actually and drop those responses in as they answer the assessment," Matt described. "But then a human has to review that response. We give them the ability to review it and override it."
That design philosophy, AI as a highly capable first pass, human judgment as the final authority, isn't a concession to organizational caution. It's how trust actually gets built. The more a practitioner can see what the system did and why, the faster they develop confidence in the outputs. The faster confidence develops, the more a human can let automation run without checking every step.
CyberSaint built a livestream viewer that lets clients watch evidence collection bots in real time, precisely because visibility into what the system is doing enables teams to eventually delegate more of it.
The efficiency trajectory Matt described: 50–60% reduction in manual compliance effort today, moving toward 85–90% as automation matures and trust compounds.
The most underappreciated opportunity in this shift isn't operational efficiency. It's revenue.
Most enterprise security teams receive hundreds of vendor security questionnaires every month. Each one has to be answered - accurately, completely, and quickly enough that it doesn't slow the deal. When that process is manual, it drains compliance team capacity, delays responses, and creates friction in the sales cycle at exactly the wrong moment.
Automation changes the calculus entirely.
"If we can use automation to help them speed up the answering of those questions, guess what you're doing?" Matt said. "You're speeding up sales. You're not a cost center anymore. You're actually a business enabler."
The same logic extends to market entry. Organizations that can consistently demonstrate compliance with specific frameworks, such as SOC 2, ISO 27001, HIPAA, and sector-specific international standards, can enter new markets faster and with greater confidence. Compliance becomes an enabler of expansion, not a precondition that needs to be negotiated market by market.
Perhaps the most consequential argument for compliance automation isn't efficiency or revenue. It's decision quality.
When compliance operates in a silo, leadership makes budget and prioritization decisions with incomplete information. The connection between control posture and risk exposure exists in theory but rarely in practice because the data has never been synthesized in real time.
"Controls and compensating controls are driving my risk posture," Matt explained. "If we're not taking that compliance data and tying it into our risk postures, we actually don't have the information we need to do prioritization."
Compliance automation, done correctly, makes that connection continuous rather than periodic. Instead of a point-in-time snapshot from last quarter's assessment, leadership has a current view of where risk actually sits. That's what enables meaningful conversations with boards and CFOs, not about compliance status, but about business risk and where investment should flow.
Prioritize time-to-value over feature breadth. The number of integrations or connectors a platform claims to support is not the metric that matters. What matters is whether those integrations work and whether they deliver value quickly. "If you can't get value out of these systems in 30, 60, 90 days… run away," Matt said. "You really need to see how quickly you can get value before you get locked into multi-year deals."
Quality over quantity in integrations. Not every connector moves the needle equally. The highest-value integrations in a compliance automation story are those that surface configuration and policy data at scale, cloud security posture management (CSPM), endpoint configuration, and security configuration management tools. Those are where the automation ROI actually lives.
Think in platforms, not point solutions. The risk categories that will matter most in three years don't all exist yet. AI governance, agentic system risk, and expanded third-party exposure, the compliance program of 2027 will need to address challenges that are only now coming into focus. The platform built for today's problem set and nothing else will require rebuilding sooner than expected.
Compliance automation isn't a bet on a technology trend. It's a response to a structural reality: the volume, velocity, and complexity of what modern compliance programs are being asked to manage have outgrown what manual processes and legacy platforms can handle.
The teams that recognize this early and build on platforms designed for the scale and integration requirements the problem actually demands won't just be more efficient. They'll be faster to market, more responsive to boards, and better positioned to use compliance as the competitive differentiator it's always had the potential to be.
Watch the full Frost & Sullivan webinar with Matt Alderman and leaders from Thoropass and Centraleyes.
To see how CyberSaint's CyberStrong platform is making this real for enterprise security and risk programs, visit cybersaint.io.