AI integration increases operational complexity
The idea that AI will simplify everything is misguided. Yes, it opens doors. But in execution, especially across a multicloud setup, it introduces more complexity than most companies are ready for. Throwing another AI tool into your already expanding tech stack without a solid governance model isn’t innovation. It’s clutter. If you’re running AI across multiple cloud platforms, expect to deal with different APIs, incompatible data formats, and a rise in cross-platform transfers. These aren’t minor issues. They compound fast.
You want performance, interoperability, and tight security. That takes intent. It also requires consolidating legacy infrastructure and managing software sprawl before it becomes a drag on innovation. Technical debt builds quietly. Without a plan to manage it, agility fades and velocity hits a wall. The upside? AI can help you fix what it breaks. If properly trained and deployed, AI tools can identify cost inefficiencies, redundant software, and integration failures. They help modernize infrastructure by providing real-time telemetry on software usage, guiding smarter decisions on what stays, what goes, and what scales.
Ignore the noise. Focus on clarity. Ensure every AI initiative is linked to measurable business outputs.
Mindy Lieberman, CIO at MongoDB, put it plainly. She states that failing to tame AI-driven sprawl leads to rising costs and deepening technical debt. But she’s also clear: AI can simplify complexity if we use it to monitor, govern, and reengineer fragmented systems. That’s where AI gives more than it takes.
Data sovereignty regulations complicate multicloud strategies
Compliance isn’t optional. And in a multicloud world, it doesn’t get easier, it gets more fragmented. If you’re operating across regions, you’re dealing with regulations like the EU’s GDPR or state laws like the California Consumer Privacy Act. These laws dictate where data is stored, processed, and accessed. If the rules say your customer data must stay in the EU, then your infrastructure needs to align with that. Put simply: you don’t get to decide where the data lives. The law does.
This adds load, architecturally and financially. Companies wind up building redundant systems just to meet compliance, which increases operating costs. It also pulls attention away from scale and innovation. But that’s the landscape now. You either build for it or face later disruptions from audits, legal risk, or reputational damage.
For leaders, the nuance is this: every new region you expand into means new compliance overhead. Without close integration between IT and legal teams, you risk compliance gaps that aren’t evident until it’s too late. You don’t want your infrastructure dictating your compliance strategy. You want compliance guiding the build.
Scott duFour, CIO at Corpay, knows this firsthand. His team had to build new EU instances just to meet GDPR. Not cheap, but necessary. Even in the U.S., where regulations are varied, his team works hand-in-hand with compliance to ensure cloud architecture supports every partner relationship, especially in stricter states like California.
Expansion should amplify performance, not multiply risk. Data governance at scale requires precision, and that starts early. Build infrastructure that respects how the world works now, not how we hoped it would.
Security risks multiply in multicloud environments
Security gets more complicated when you’re operating in multiple clouds. Each platform has its own configurations, policies, and default settings. You’re not just securing one perimeter, you’re watching over many. And if your team doesn’t have full visibility or a centralized strategy, you’ve already lost ground before a breach even happens. The attack surface expands with every new provider added to your architecture. That’s reality, not theory.
In multicloud, consistency matters more than complexity. You need a unified security framework that spans all clouds and applies identity management, threat detection, and encryption with no gaps. This isn’t about trusting your cloud vendors to handle everything. Most companies still wrap their cloud assets in additional protections with tools they control directly. That’s the right approach. Each cloud should be continuously monitored using your own standards, standards that hold up under regulatory scrutiny and real-world threats.
Executives often underestimate the operational overhead of managing different compliance and security rules across commercial and government-grade cloud environments. It’s not just inconvenient, it defines where certain types of data can legally reside and how your teams must adapt security protocols accordingly.
Scott Simari, principal at Sendero Consulting, emphasizes the need for purpose-built security models in multicloud setups. He explains that some clients, such as utility companies operating nuclear power plants, can’t store federally regulated data in commercial clouds at all. It forces organizations to adopt a tailored method for every cloud they use, even down to how they administer access and encrypt data across environments. That includes adopting least-privilege access and just-in-time permissions, critical steps to reduce exposure.
Deploy once, monitor always, and assume complexity will increase. That mindset helps prevent failure when the stakes are highest.
Flexibility and observability are critical for effective multicloud management
Running across multiple cloud providers demands flexibility not just in your contracts, but in your code. If your systems are tightly bound to a single cloud, you’re reducing your options and increasing your risk. The ability to shift workloads across providers, based on performance or price, is a basic requirement now, not a feature. Getting there means using containerization, abstracting infrastructure, and adopting orchestration tools that run across clouds without friction.
But deploying is only half the story. You also need full observability. That means a single view into system behavior across clouds, tracking performance, availability, cost, and security indicators across every platform you use. Staring at dozens of dashboards doesn’t make you smarter. Unified monitoring makes the data useful. And with scale, it’s the only thing that keeps real-time control within reach.
You can’t fix what you can’t see. Hidden inefficiencies, outages, or compliance lapses in a siloed system cost more the longer they go undetected. This is especially true when your infrastructure spans across multiple geographic regions with varying latency and service capabilities.
Bryan Wall, senior competency leader for cloud engineering at Experis, points to the importance of decoupled, portable architectures that don’t restrict workload deployment. Flexibility means you pick the right tool from the right provider when you need it. Chris Thomas, principal at Deloitte Consulting, reinforces the need for holistic observability. He highlights that issues missed in one part of your architecture can impact users globally, including compliance failures or degraded user experiences.
Leaders need to see observability and architectural flexibility as two sides of the same requirement. One lets you move, the other lets you monitor. Both are essential if you expect your infrastructure to scale predictably.
Cost management requires active, cross-functional financial governance (FinOps)
Cloud costs grow fast, especially in multicloud environments. Providers offer scale and performance, but not clarity. Without active financial governance, it’s easy to waste millions on redundant services, underused capacity, or mismatched pricing models. This problem doesn’t fix itself. You need active measurement, deliberate alignment between IT and finance, and discipline across teams. That’s where FinOps comes in. It’s not just a process, it’s a mindset where spending and performance are continuously evaluated, not just reviewed quarterly.
The basic function of FinOps is simple: help your teams understand the cost of every cloud decision, in real time. That means building accountability across teams, optimizing workloads on the right-sized infrastructure, and using pricing models that reflect actual usage, not guesswork. Without this operational rigor, your cloud budget becomes bloated fast. Especially with multicloud, where billing complexity multiplies quickly, and where teams often deploy without clear cost oversight.
For executives, the real opportunity is strategic control. When FinOps works, it enables smarter investment decisions that scale with the business. You get more out of your cloud partners, spend less on unnecessary resources, and align budget with actual outcomes. But it doesn’t happen automatically. It requires buy-in across engineering, finance, and product teams, not just a dashboard.
Scott Simari, principal at Sendero Consulting, explains that many organizations pay for far more cloud capacity than they use, simply because they aren’t tracking consumption closely enough or adjusting resource allocations month-to-month. He sees FinOps as the counterbalance to that waste, enabling regular cost-benefit analysis and proactive resource tuning.
Scott duFour, CIO at Corpay, adds another layer. His team faces the added complexity of integrating cloud environments from acquired companies, each with their own service providers and billing structures. Moving those environments into a centralized, secure footprint helps contain costs and enforce operational standards. But it takes time, and it’s not a one-off effort. With every new acquisition, that realignment cycle repeats.
If you’re expanding your cloud strategy, or your business, FinOps must scale with it. Otherwise, you’re delegating financial control to your systems instead of building it into your operations.
Key takeaways for leaders
- AI adds friction without strong governance: Leaders should ensure AI workload deployments are streamlined across cloud environments to avoid technical debt and tool sprawl. Use AI not only to execute tasks but also to monitor systems, reduce redundancy, and modernize infrastructure.
- Data laws demand architectural precision: Multicloud strategies must be designed with data sovereignty in mind, ensuring compliance with region-specific laws like GDPR and California privacy legislation. Align IT and compliance teams early to manage cost and complexity effectively.
- Security must scale with complexity: A fragmented cloud stack increases exposure. Centralize identity management, enforce least-privilege access, and build cloud-specific security protocols that meet both operational and regulatory requirements.
- Flexibility and observability aren’t optional: Architect cloud solutions to run across any provider by using containerization and orchestration tools. Invest in unified observability platforms to maintain visibility as your infrastructure scales.
- FinOps turns cost control into strategy: Cross-functional financial governance is essential to prevent multicloud cost overruns. Leaders should establish FinOps practices that tie cloud investment directly to usage, business objectives, and strategic expansion.
