IBM's Recent Earnings Call Makes One Thing Clear: Hybrid Cloud Is the Future

The power of choice is at the center of GenAI implementation; hybrid cloud deployment gives you that choice.

If you needed a sign that hybrid cloud isn't just a trend, but the actual direction enterprise tech is heading, IBM's recent earnings report is it.

The tech giant's latest numbers don't just show growth; they show where smart investments are going as AI deployment becomes business critical.  

And the headline? Hybrid cloud is eating the world.

The Numbers Don't Lie

"Enterprises are prioritizing technology investments that drive productivity, resilience, and flexibility, particularly in hybrid cloud, AI, and mission-critical infrastructure," said CEO Arvind Krishna on last night’s call.  

This isn't corporate speak. As clients modernize systems, redesign workflows, and try to extract value from ever-growing mountains of data, "expectations for integration, security, and performance continue to rise. These trends are structural."

Structural. As in: not going away. As in: this is how we're doing business now.

And the results speak for themselves. IBM's infrastructure revenue grew 17% this quarter. But here's the kicker: Hybrid Infrastructure jumped 24%, delivering its highest fourth-quarter revenue in over two decades. We're talking 61% year-over-year growth.

That's not incremental adoption. That's a sea change.

Why Everyone's Talking About Hybrid

So what's driving this shift? Simple: organizations are realizing that the "cloud vs. on-prem" debate was always a false choice.

As Reveal CEO Eric Harmon recently laid out in Forbes, legal and enterprise teams aren't just shuffling documents around. They're managing evidence, privileged communications, trade secrets, and records that fall under increasingly complex regulatory frameworks. According to the American Bar Association's 2024 cybersecurity report, 29% of law firms reported a breach, and that’s likely undercounting the real number.  

While public cloud platforms like AWS and Azure have become security gold standards, some organizations need that extra layer of control. Maybe it's keeping encryption keys in-house. Maybe it's data sovereignty requirements for GDPR compliance. Maybe it's maintaining forensic chain of custody for high-stakes litigation.

The point is: different workloads have different needs.

The Great Cloud Repatriation

Here's where it gets interesting. According to a 2025 Private Cloud Outlook survey of 1,800 global IT leaders, 69% are considering moving workloads from public cloud back to private cloud environments. Not because the cloud is bad, but because they're optimizing for cost predictability, performance consistency, and regulatory alignment.

Other surveys report this move is already happening. G2 research found that 73% of companies have already adopted hybrid cloud, with 70% of IT leaders believing they won't realize the full potential of digital transformation without a solid hybrid cloud strategy.

It’s about security and its about economics. Because when you're processing terabytes of data—which has become routine in eDiscovery alone—volume-based pricing, à la carte processing charges, and unpredictable support costs add up fast. Organizations are doing the math and realizing that hybrid deployment often makes more financial sense, especially for large, recurring workloads.

It's Not Cloud vs. On-Prem—It's Both

Let's be clear: this isn't an argument against public cloud. The cloud is fantastic for agility, reducing capital expenditures, and scaling AI deployments rapidly. Most of the early momentum behind generative AI came from cloud-based platforms offering shared access to cutting-edge models.

Public cloud is ideal for testing, piloting, and spinning up services quickly. But as AI moves from experimentation to mission-critical functions—when you're infusing foundation models with proprietary legal data or running vector databases for retrieval-augmented generation (RAG)—the infrastructure calculus changes.

Some workloads demand the speed and global reach of public cloud. Others require the security, sovereignty, and lower latency of private deployment. And most organizations? They need both.

As Krishna puts it, a hybrid approach "enables clients to use the best option for each use case" while helping organizations "optimize operations, automate workflows, build resiliency, secure and govern data, and drive cost efficiency."

Where AI Fits In

Here's the thing about AI: it's not one-size-fits-all technology. The infrastructure you need to test a foundation model in the cloud is completely different from what you need to run a secure, fine-tuned model in production.

With hybrid models, you can prototype AI tools in the cloud where it's fast and cheap, then shift to private deployment for production when security, latency, or compliance demands increase. Some models—smaller LLMs or sector-specific algorithms—are performant enough to run entirely in-house.

Harmon notes that infrastructure must keep pace with AI innovation. As legal operations become data operations, firms need deployment flexibility that matches the sophistication of their AI strategy.

Reveal's RPD: Built for Hybrid Reality

This is exactly why Reveal is making RPD (Reveal Private Deployment) available to organizations that prefer private and hybrid deployments.

Whether you're managing eDiscovery workloads across borders, navigating HIPAA or GDPR compliance, processing terabytes of sensitive legal data, or integrating AI-powered document review into mission-critical workflows, Reveal gives you the infrastructure flexibility to deploy where it makes sense for your security, regulatory, and performance needs.

Want to run standard litigation review in the cloud for speed and collaboration? Great. Need to process regulated healthcare data in a private environment with full encryption key control? Done. Have a complex matter that requires both? Hybrid deployment lets you optimize each piece.

The Bottom Line

IBM's earnings are a wake-up call: hybrid cloud isn't emerging technology anymore. It's the foundation of enterprise AI strategy.

The legal industry is only getting more complex. Data volumes are exploding. AI is becoming embedded in daily workflows. Regulations are tightening globally. In that environment, flexibility isn't nice to have—it's essential.

The future isn't just cloud. It's not just on-prem. It's the power to choose the right infrastructure for the right task at the right time.

And that future? It's already here.