Contact centers have spent the last year moving past the AI pilot phase and into full deployment. Budgets have followed: data/IT infrastructure and AI/automation now top the list of contact center investment priorities for the year ahead, with personnel and staffing ranked dead last. The logic seems sound: automate more, staff less, resolve faster.
The results tell a more complicated story. Despite the surge in investment, 61% of contact center leaders report that customer conversations have actually become more challenging, and half of consumers still say chatbot interactions leave them frustrated.
The gap isn’t the AI. It’s what’s underneath it
Industry analysts tracking this trend point to a consistent root cause: Gartner predicts that through 2026, organizations will abandon 60% of AI projects unsupported by AI-ready data. Deploying a large language model on top of fragmented knowledge bases, conflicting documentation, and unclustered customer scenarios doesn’t produce a smarter contact center; it produces a faster way to give customers inconsistent answers.
At the same time, the platform layer itself is shifting under everyone’s feet. Contact Center as a Service (CCaaS) has become the baseline architecture rather than the finish line, with the market moving from roughly $8 billion in 2025 toward double that by 2030. That’s a lot of organizations mid-migration off legacy on-prem systems at the exact moment they’re also trying to layer agentic AI, systems capable of authenticating a customer, updating a billing record, and issuing a refund without a human in the loop, on top of infrastructure that, in many cases, isn’t fully modernized yet.
Governance is now the differentiator, not the technology
Gartner predicts agentic AI will eventually resolve most common service issues autonomously. That’s the direction the industry is heading. But the contact centers actually seeing results in 2026 aren’t the ones that deployed AI fastest; they’re the ones that did the unglamorous groundwork first: reconciling knowledge articles, defining clear escalation paths, and building governance boundaries around what AI is and isn’t allowed to do on its own before turning it loose on live customers.
Where ClearBridge fits
ClearBridge’s Contact Center Solutions practice exists precisely because the technology decision (which CCaaS platform, which AI vendor) is rarely where these projects actually go wrong. We support the full lifecycle of contact center technology: planning, design, configuration, implementation, and ongoing support across both on-premise and cloud environments. That includes the parts that don’t show up in a vendor demo, such as data readiness work, integration between CCaaS platforms and existing CRM and workforce management systems, and the resources to execute a migration or AI rollout without disrupting live customer operations.
If your organization is one of the 91% of service leaders under executive pressure to implement AI, the fastest path to results isn’t skipping the foundational work; it’s having the right people to do it in parallel with the deployment instead of after it fails.
Migrating to CCaaS, rolling out agentic AI, or both at once? Let’s talk about what your environment actually needs to get it right.
According to IBM’s Cost of Data Breach Report, healthcare organizations incur the highest cost for data breaches of any industry, averaging $9.8 million per incident, more than 1.5 times the financial services industry’s $6.1 million. There is also a notable shift in attacker motivation, with espionage-driven attacks (actors after intellectual property and patient research data rather than a ransom payout) accounting for a much larger share of incidents than in prior years. Those actors are harder to catch because they aren’t trying to draw attention to themselves.
Healthcare IT leaders are heading into the back half of 2026 facing a collision of pressures: a looming overhaul of HIPAA’s Security Rule, breach costs that keep setting records, and a workforce gap that most organizations openly admit they can’t close on their own.
The compliance clock is ticking
The Office for Civil Rights is moving toward finalizing long-anticipated updates to the HIPAA Security Rule this year. The direction is clear: system-level, continuous risk analysis is becoming the baseline expectation, not a once-a-year checkbox exercise. Organizations that treat their last risk assessment as “done” are exactly where regulators are expected to look first.
That’s a meaningful operational shift for provider organizations that have historically run security reviews as an annual project rather than a standing discipline.
The cost of getting it wrong keeps climbing
Many government agencies canat’s where VMware Cloud Foundation comes in.
VMware Cloud Foundation Makes AI a Native Capability
VMware Cloud Foundation transforms the private cloud into an AI-ready platform by integrating virtualization, Kubernetes, networking, storage, security, automation, and lifecycle management into a unified operating environment.
Rather than treating AI as a separate project, VCF enables agencies to incorporate AI directly into their existing infrastructure.
With VMware Private AI technologies, agencies can bring advanced language models to their data. This approach allows organizations to:
- Keep sensitive information within secure environments
- Reduce the risks associated with moving data externally
- Improve AI performance by leveraging local infrastructure
- Accelerate deployment of generative AI applications
- Maintain governance and compliance requirements
The result is a secure foundation for adopting AI without compromising operational control.
Automation is Essential for Scaling AI
As agencies deploy more AI workloads, manual infrastructure management quickly becomes a bottleneck. Platform engineering and automation are critical to delivering AI services consistently and securely.
Using technologies such as:
- VMware Aria Automation
- Infrastructure as Code (IaC)
- Terraform
- GitOps
- Kubernetes
- CI/CD pipelines
organizations can automate infrastructure provisioning, policy enforcement, application deployment, and lifecycle management. Automation enables IT teams to spend less time managing infrastructure and more time delivering mission capabilities.
Security Must Be Embedded From the Start
Government AI initiatives require security at every layer of the infrastructure stack. VMware Cloud Foundation supports this through:
- Integrated Zero Trust networking
- Microsegmentation with VMware NSX
- Identity-based access controls
- Infrastructure lifecycle management
- Continuous monitoring
- Policy-driven automation
- Built-in compliance capabilities
Rather than adding security after deployment, agencies can build secure-by-design AI platforms from day one.
Observability Keeps AI Operations Running
AI environments generate significant infrastructure demands. Maintaining visibility across compute, storage, networking, Kubernetes clusters, and applications is essential for operational success. Modern observability platforms provide insights into:
- Infrastructure health
- Resource utilization
- AI workload performance
- Capacity planning
- Security events
- System availability
With proactive monitoring and analytics, agencies can identify issues before they affect mission-critical operations.
How ClearBridge Helps Government Organizations Prepare for AI
Successfully implementing an AI-ready private cloud requires expertise across infrastructure, automation, security, networking, and cloud operations. ClearBridge helps federal agencies modernize their environments with consultants experienced in:
- VMware Cloud Foundation design and implementation
- Private cloud modernization
- Kubernetes platform engineering
- VMware NSX and Zero Trust architectures
- VMware Aria Automation
- Infrastructure as Code using Terraform
- Platform engineering and GitOps
- AI-ready infrastructure planning
- Observability and operations
- Secure cloud migrations
Whether agencies are modernizing existing VMware environments, preparing for AI initiatives, or building scalable private cloud platforms, ClearBridge provides the technical expertise needed to accelerate deployment while reducing implementation risk.
Preparing for the Next Phase of Government AI
America’s AI Action Plan signals a clear direction: AI will become an increasingly important part of government operations. The agencies that succeed won’t simply deploy AI applications; they’ll build secure, scalable platforms that support AI for years to come. A private cloud powered by VMware Cloud Foundation provides a practical path forward, enabling agencies to harness advanced AI capabilities while maintaining security, governance, and operational control of their missions demand.
Partner with ClearBridge
As a VMware by Broadcom premier strategic partner with deep expertise in VMware Cloud Foundation, private cloud modernization, automation, and platform engineering, ClearBridge helps government organizations build the AI-ready infrastructure needed to support tomorrow’s mission-critical workloads.
Ready to prepare your infrastructure for the next generation of AI? Contact ClearBridge to learn how our VMware experts can help you build a secure, scalable, AI-ready private cloud.
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