For a long time, retail technology was a back-office concern: the systems that kept the lights on while marketing and merchandising got the credit for competitive advantage. That’s no longer true. In 2026, the line between “the technology behind the store” and “the reason customers choose your store” has essentially disappeared.
Worldwide retail technology spending is projected to reach $388 billion this year, with AI-related investment growing nearly 25% annually. That’s not retailers chasing a trend; it’s retailers recognizing that eCommerce platforms, order management, point-of-sale, and store systems have become the actual mechanism for competitive advantage, not just the infrastructure behind it.
The gap between “it works” and “it competes”
Most retail organizations aren’t running on nothing; they’re running on something that was right for 2015 or 2018 and has been patched, extended, and worked around ever since. The eCommerce platform still processes orders. The Order Management System still routes inventory. The Point-of-Sale platform still rings up sales. None of it has technically failed. But “hasn’t failed” and “keeps pace with a customer who expects real-time inventory accuracy across five channels” are very different bars, and the gap between them is where competitors pull ahead.
A few shifts are making that gap harder to ignore:
Unified commerce is replacing “omnichannel” as the baseline expectation. Customers don’t experience “online” and “in-store” as separate systems, so increasingly retailers can’t run them that way internally either. The architectural pattern behind this, often described as MACH (microservices, API-first, cloud-native, headless), lets retailers sync inventory and customer data in real time across channels instead of reconciling siloed systems overnight or worse. Platforms and order management systems are increasingly judged on how well they support that real-time model, not just whether they process a transaction correctly.
AI in retail has moved from experimental to operational. The interesting AI work in 2026 isn’t a chatbot bolted onto a website; it’s agentic systems that manage inventory reordering on their own and demand-forecasting models that do quiet, unglamorous work in the background.
POS has stopped being just a checkout tool. Modern point-of-sale systems increasingly double as integration hubs, pulling together inventory visibility, customer data, and marketing in one place. Add computer-vision-based self-checkout and biometric payment options, and the POS terminal is doing meaningfully more work than it was three years ago, which means it needs meaningfully more integration and support than it used to.
Supply chains are being rebuilt for resilience, not just efficiency. The last several years have made clear that a supply chain optimized purely for cost is fragile. Retailers are re-architecting order management and warehouse systems to absorb disruption (multiple sourcing paths, better real-time visibility, faster rerouting) rather than assuming the smoothest path will always be available.
Where the work actually is
None of this means ripping out and replacing everything, and it shouldn’t. The retailers making real progress are the ones treating modernization as a scoped, prioritized set of projects, closing the specific gaps between what a system does today and what the business actually needs from it, rather than a single high-risk platform replacement.
That’s true across every layer of the stack: eCommerce and web platforms, order management and warehouse systems, in-store POS and kiosk technology, CRM and loyalty programs, and the business intelligence and merchandising systems tying it all together. Each of those has its own modernization path, risk profile, and timeline.
If you need support with your retail systems, ClearBridge can help!
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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