Insights

Read time: 4 minutes

Most CTOs don't think of their engineering teams as a compliance risk. They think of compliance as a legal obligation, a governance checkbox, or an audit preparation exercise separate from the world of writing code, building systems, and shipping products. But these worlds aren’t separate.

Some of the most significant compliance exposure risks organizations carry are introduced by competent engineers making reasonable decisions under time pressure. Take for example the misconfigured cloud resource that seemed fine at deployment, the hardcoded credential that never made it into the secrets manager because the sprint was ending, or the logging configuration that was set up quickly and never revisited. None of these decisions felt like compliance failures when they were made, but in aggregate, they create the kind of audit findings that are expensive, time-consuming, and entirely avoidable.

For engineering leaders, the opportunity is to reframe compliance not as something imposed on engineering from the outside, but as a natural output of how systems are designed and maintained from the inside.

Read time: 3 minutes

In most organizations, SaaS adoption happens by accumulation. A project team adopts a new task management tool. Marketing subscribes to an analytics platform. HR brings in a scheduling application. Finance approves subscriptions through expense reports. Over time, the software environment stops being something IT teams actively design and becomes something IT teams inherit.

This is SaaS sprawl, and for most growing businesses it's already well underway. According to Zylo's 2025 SaaS Management Index, organizations wasted an average of $21 million on unused SaaS licenses last year, with this number increasing 14.2% per year. For CIOs seeking executive alignment, this level of financial leakage creates a clear and compelling entry point. Every dollar recovered from unused licenses, duplicate tools, or unreviewed renewals is budget that can be redirected toward initiatives with real strategic impact.

AI adoption is accelerating the problem. According to a 2025 Zapier survey of over 500 enterprise leaders, only 35% of organizations say their AI tools go through proper approval channels. This means the majority of AI tools entering the businesses surveyed were following the same ungoverned path as the SaaS subscriptions that created the sprawl problem in the first place.

The good news is that SaaS sprawl is entirely preventable with the right governance in place. The first step to getting ahead of it is understanding exactly how it accumulates.

Multi-factor authentication (MFA) was supposed to solve the credential problem. For years, adding a second factor to the login process stopped the vast majority of attacks that relied on stolen passwords, and for most organizations, it felt like a significant step forward. That progress was real. But traditional MFA was never a complete fix, and attackers have spent the past several years learning how to work around it.

For CISOs, the authentication landscape in 2026 looks meaningfully different than it did even two years ago. The techniques used to bypass traditional MFA have matured from niche to mainstream, the regulatory and insurance pressure to adopt stronger alternatives is accelerating, and the window for treating phishing-resistant MFA as a future consideration rather than a current priority is closing faster than most security leaders realize.

Understanding what's changed, what it means for your authentication architecture, and what a realistic migration path looks like is now a near-term operational requirement.

Every COO understands what it means for operations to stop. The cost is immediate, visible, and cumulative. The longer the disruption runs, the more expensive each additional hour becomes, both in direct losses and in the downstream consequences that take weeks or months to fully resolve. 

That information is not particularly new. What's changed in recent years is how severe these disruptions tend to be. According to a 2022 report from Statista, once an attack hits the average recovery time is 24 days of disrupted operations, which is up from 15 days in 2020. SMBs should be particularly wary, as Verizon's 2025 Data Breach Investigations Report recorded that ransomware features in 88% of all SMB-related data breaches. 

For operational leaders who haven't built continuity planning into their operational framework, the question isn't whether a significant disruption will occur; it's whether the organization will be ready to respond when it does. 

The encouraging reality is that downtime, while rarely preventable in absolute terms, is very much mitigable. The difference between an organization that recovers in hours and one that recovers in weeks usually comes down to the decisions made long before the incident. 

When employees adopt AI tools on their own, it's rarely because they're being reckless. It's because they've found something useful and the organization hasn't yet provided a governed alternative. This phenomenon, commonly referred to as shadow AI, is one of the more instructive signals a CEO can receive about the gap between what employees need and what the organization has sanctioned.

Understanding why it happens, what it means for the business, and how to lead a culture that channels that energy productively is one of the more consequential conversations happening in executive leadership today.

Moving infrastructure to the cloud is one of the most consequential technology decisions a business can make. For most organizations, the case is straightforward: reduced hardware costs, greater flexibility, easier collaboration, and infrastructure that scales with the business rather than against it. The migration itself tends to get significant attention in timelines, budgets, and technical planning. What often gets less attention is what happens to security posture on the other side of it.

For CIOs, this is where a familiar problem surfaces in an unfamiliar form. For businesses that move quickly to capture the operational benefits without revisiting their security architecture, migration can create exposure that didn't exist before.

Getting the most out of cloud infrastructure means closing gaps before they become incidents.

AI adoption across small and mid-sized businesses has accelerated greatly in the past few years. Productivity tools powered by AI are now deeply embedded in customer service, and for good reason: the efficiency gains are real, the tools are accessible, and the business case is straightforward.

What's less straightforward is the compliance picture that's forming around it. As AI becomes a standard part of how businesses operate, regulators at the state, federal, and international level are catching up.

The patchwork of requirements is growing more complex by the quarter. For Chief Compliance Officers, the regulatory environment around AI is no longer theoretical. Laws are already in effect, enforcement actions are being filed, and the scope of what's covered is expanding. The good news is that CCOs who get ahead of it now have far more options than those who wait for a regulatory notice to prompt the conversation.

Most technology problems build quietly. By the time the drag they cause becomes visible, the cost of fixing it is significantly higher than the cost of planning ahead would have been. For growing businesses, IT decisions have a way of compounding over time. The choices you make today shape what's possible in the years ahead.

CIOs who treat technology as a reactive function (something to address when it breaks or when a contract expires) consistently find themselves behind, but those who treat it as a strategic one consistently find themselves with more options.

Getting ahead of your IT means understanding which decisions carry the most weight, when to make them, and what a disciplined approach to technology planning actually looks like in practice.

For years, network security operated on a simple assumption: if you were inside the perimeter, you were trusted. Employees logged into the office network, and access flowed freely from there. The model was built for a world where work happened in one place, on company-owned devices, and behind a secure firewall.

For many businesses, that world is no longer the environment they operate in. For CTOs managing distributed teams, cloud-based infrastructure, and a growing web of third-party integrations, the perimeter model creates a false sense of security that attackers have learned to exploit with precision.

Zero Trust is the architecture built for the new hybrid-and-remote-work world. Understanding what it means in practice and why it matters now is one of the more consequential decisions a technology leader can make.

While the shift to remote and hybrid work unlocked flexibility for small and mid-sized businesses, it also quietly dismantled one of the oldest assumptions in business security: that your people, your devices, and your data all live inside the same four walls.

When everyone worked in a central office, a single firewall and a locked front door handled much of your exposure. Today, your team logs in from home offices, on a mix of company-issued and personal devices, across personal networks with no IT oversight. For business leaders, that means the security perimeter you once relied on no longer exists. What replaces it has to be intentional.