Cloud providers are shifting priorities from robust security to AI innovation
Cloud infrastructure earned its status in enterprise technology by offering world-class security, scale, and operational efficiency. That promise played a big role in helping public cloud platforms win over businesses that were reluctant to leave their on-premise systems behind. But what made cloud trustworthy is being set aside. Today, the energy, talent, and capital that once powered security innovation are now being funneled into artificial intelligence.
AI is exciting. It can automate workflows, optimize decisions, and open new revenue channels. But that doesn’t excuse ignoring security. A system that’s fundamentally insecure is a system you can’t trust, no matter how advanced the AI layer on top may be. Right now, many cloud providers are making real gains in AI functionality, especially in generative AI and machine learning platforms. But they’re doing it while putting less into the foundational controls that gave them their edge in the first place.
According to the Cloud Security Alliance and Tenable’s “State of Cloud and AI Security 2025” report, 55% of companies are actively running AI workloads. That’s a big number. And if providers are designing their platforms around AI growth while putting less into security operations, then the net result is an infrastructure that’s more powerful, and significantly more exposed.
The conclusion is simple: cloud security doesn’t scale automatically with platform innovation. It takes deliberate reinvestment. If cloud vendors continue to deprioritize this, they risk losing the trust that made them viable for enterprise workloads at scale.
The growing prevalence of hybrid and multicloud environments
We’re no longer in a world where companies use a single cloud provider. Today’s environment is hybrid and multicloud, 82% of companies are mixing on-premise systems with public cloud, and 63% are working across multiple providers. That means the average enterprise is managing about 2.7 distinct cloud environments.
This trend makes sense. Different clouds offer different strengths, and enterprises want agility. But with that choice comes complexity. These systems don’t integrate easily. Controls differ. Visibility drops. And when things break, you don’t have a single dashboard to understand what went wrong.
From a leadership perspective, what matters is that your surface area for risk is bigger now. Traditional security tools weren’t designed to protect this kind of fragmented setup. Most are built around centralized models, not environments spread across three clouds and a bunch of legacy data centers. So unless you invest in coordinated cloud-native security, and make sure your teams know how to operate across cloud systems, you’ll keep running into blind spots. And blind spots cost you.
The research confirms the challenge. IAM failures are widespread in these setups, with teams struggling to manage access and identities consistently across platforms. That means more unmanaged permissions, more misconfigurations, more leak potential.
So while hybrid and multicloud bring you flexibility, they also demand a smarter security investment framework. Ignore that, and complexity will erode any advantage you thought you gained.
Failures in identity and access management (IAM) are the weakest links
Access control is the foundation of your enterprise security. Without it, every other security layer becomes weaker. And right now, identity and access management, what most call IAM, is a failing point across modern cloud infrastructures.
According to the latest Cloud Security Alliance and Tenable report, 59% of organizations identify insecure identities and risky access permissions as their top cloud security concern. These aren’t trivial missteps. We’re talking about excessive permissions, poor enforcement of least-privilege frameworks, and inconsistent policies across cloud platforms.
This isn’t due to lack of awareness. Most teams understand IAM’s importance. The issue is operational. In hybrid and multicloud setups, IAM responsibilities get split across teams, security, DevOps, and platform operations. This leads to misalignment in policy enforcement and visibility. Metrics that actually matter, like privilege misuse, dormant accounts, or real-time access anomalies, aren’t tracked consistently. As a result, identity sprawl grows faster than it can be contained.
Executives should treat IAM not as a checklist, but as a control imperative. It’s not exciting, but it moves risk drastically if done right. The key is operational consistency, clear roles, tightly enforced permissions, and centralized monitoring. If you get that right, the rest of your security posture becomes more effective. Get it wrong, and you’re handing attackers a direct path to your data.
Current reactive security postures are insufficient for modern cloud threats
Most enterprise cloud security today is reactive. Companies review logs after an incident. They track breach frequency and impact, and report on them after the damage is already done. That needs to change.
The research backs it up. Organizations reported an average of two cloud-related security breaches within 18 months. The most common root causes? Misconfigured systems and excessive permissions. These aren’t sophisticated attacks. They’re simple oversights, and that’s the issue.
Security metrics heavily lean on reporting incident severity rather than reducing exposure. That won’t cut it in a perimeter-less, API-driven environment. Modern cloud threats move fast, and attackers target known weak points, credentials, access paths, and mismanaged assets. If your response begins after a breach alert, you’re already late.
Executives need to push for proactive security strategies. That means using data to harden infrastructure before something fails. It means investing in tooling that gives you real-time visibility into abuse patterns or unapproved configurations. And it means removing the assumption that platform defaults are good enough. They’re not.
Put simply, prevention is cheaper than response. If your security strategy is still report-driven instead of posture-driven, change that.
AI implementations introduce new vulnerabilities
Artificial intelligence is growing rapidly inside enterprise systems. From automation and analytics to generative content and advanced modeling, AI is being deployed faster than most teams can secure it. That’s the problem.
AI workloads don’t exist in a vacuum. They have software dependencies, infrastructure pipelines, and unique data profiles. When these are poorly configured, or not secured at all, they introduce new entry points for attackers. The recent Cloud Security Alliance and Tenable report shows that 34% of organizations adopting AI have already experienced AI-related breaches. These aren’t theoretical risks. They’re active faults, ranging from insider threats to misconfigured APIs and flawed model deployments.
The issue is in the priorities. Most organizations are pouring effort into developing AI-based capabilities while neglecting fundamental AI security practices, such as encrypting data used in training, validating permissions in ML pipelines, or testing the integrity of models during deployment. These gaps leave space for exploitation, manipulation, and corruption of outcomes.
C-suite leaders should treat AI workloads like high-value assets, because that’s what they are. If their infrastructure is vulnerable or their output can be manipulated, it compromises trust across business units and customer channels. Securing AI requires both technical investment and policy enforcement. Don’t expect innovation to succeed while sleeping on the risks baked into the platforms that power it.
Strategic misalignment between cloud providers and enterprise needs is amplifying cyber risks
Cloud security failure isn’t just about poor tooling, it’s about poor alignment. Enterprises and cloud providers are not operating with the same priorities, and it shows.
According to the CSA and Tenable research, only 20% of enterprises are prioritizing unified risk assessments across their environments; just 13% are consolidating tools. That means most organizations are running fragmented strategies across hybrid and multicloud setups. Meanwhile, cloud vendors continue to push capabilities focused on scaling AI and delivering platform-specific services, not on helping customers implement fully secure, cohesive architectures.
Many enterprises have over-relied on default security tools provided by cloud vendors, assuming they’re sufficient for protection at scale. That assumption is no longer valid. The complexity of today’s architecture creates more blind spots, and those won’t be covered by generic or static controls. Add to this the fact that 31% of organizations believe their leadership lacks clarity on how cloud security actually works, and the risk becomes more apparent.
Executives should take ownership of aligning risk appetite, operating models, and oversight protocols with the evolving cloud ecosystem. That requires stepping beyond provider defaults and building security frameworks that match the real-world configurations they’re running. The more alignment between business operations and security architecture, the smaller the space becomes for gaps that cause damage. Put simply, closing the distance between business priorities and technical reality is what builds resilience in the enterprise.
Main highlights
- Cloud security is losing priority to AI growth: Cloud providers are investing heavily in AI while letting core security functions stagnate. Leaders should push vendors to maintain infrastructure security as a first principle, not an afterthought.
- Hybrid and multicloud complexity is increasing vulnerability: With most enterprises managing multiple cloud environments, traditional tools aren’t enough. Executives should invest in integrated security frameworks that span cloud and on-premise systems.
- Identity and access mismanagement is a critical risk: Poor IAM enforcement and excessive permissions are top breach drivers in cloud environments. Leadership should demand strict access governance, unified policies, and real-time monitoring.
- Reactive security is failing against modern cloud threats: Tracking incidents after the fact keeps organizations in a cycle of avoidable breaches. Leaders should shift to proactive security investments that reduce exposure before an incident occurs.
- AI systems are being deployed faster than they’re being secured: Over one-third of organizations using AI have already experienced related breaches. Decision-makers must pair AI adoption with specific controls like encrypted datasets and secure ML operations.
- Cloud customers and vendors are misaligned on security: Most enterprises rely too heavily on native tools, while providers prioritize AI over risk management. Leadership should align internal teams on security priorities and demand clearer accountability from cloud vendors.
