The CXO’s AI Reality Check, Part 4: Clawing Back Your Margins – Overcoming the Legacy Infrastructure Trap
By Rahul Kumar, Regional Director, Experis Europe
It is easy to get excited about deploying frontier AI models. But if your legacy infrastructure is fragile, you are effectively dropping a high-performance engine into a classic car.
It doesn’t make you go faster; it just breaks the chassis.
Data from the Experis CIO Outlook 2026 shows that keeping up with the rapid pace of change and dealing with legacy systems remain the top barriers for tech leaders globally.
If you do not modernise the core, AI-driven efficiency gains will be entirely swallowed by cloud running costs and architectural bottlenecks.
Consider how a global automotive manufacturer solved this challenge. Their legacy infrastructure was struggling to keep pace with transaction volumes, burdened by over 60 critical applications communicating through hundreds of legacy integrations.
They partnered with Experis to assemble a targeted modern engineering squad − including program managers, cloud architects and developers.
By executing a phased cloud migration and modernisation, they achieved:
- A 79% reduction in cloud infrastructure usage through containerisation.
- Doubled performance across core APIs, ensuring faster, more resilient customer services.
- Successful modernisation of all 60+ applications, creating a stable, cost-effective foundation for scaling AI.
This is the power of operational modernisation:
- Solve the legacy puzzle first: Do not build AI wrappers on top of unmapped, siloed data lakes and legacy applications.
- Containerise to protect margins: Implement microservices and containerised architectures to keep cloud consumption costs from ballooning.
- Deploy elastic, project-based squads: Build focused, specialised modernisation teams that execute quickly and dissolve when the goal is achieved.
At Experis, this is the core of our execution capability.
We work with organisations to overhaul legacy systems, optimise cloud architectures and deploy modern engineering teams. Our Project Services teams tie our delivery milestones directly to the SLA of operational adoption. Supported by our global hubs, we help you clear the technical debt holding you back, so your AI ambitions actually show up on the balance sheet.
Is your current network infrastructure ready to support the bandwidth and cost demands of enterprise-scale AI?
Contact us to discuss how Experis can help modernise your infrastructure and build a scalable foundation for AI.
References:
Experis CIO Outlook 2026
Experis Project Services
