Enterprises are shifting to add AI capabilities to existing applications rather than modernize first, but 72% have barely modernized their app portfolios—creating pressure for infrastructure that can run both traditional and AI workloads in parallel.

What happened: A Broadcom survey found that 57% of enterprise IT teams cite adding AI capabilities to existing applications as their top modernization approach—the most-selected response. This represents a significant shift in how enterprises view modernization in the age of AI, with 80% of enterprises now having a dedicated platform engineering team and another 15% planning to establish one within 18 months.

Why it matters: The challenge is that 72% of enterprises have modernized less than half their application portfolio, meaning seven in ten IT organizations are trying to add AI to a largely unmodernized foundation. The old sequential model—modernization first, then AI—no longer fits the reality most IT teams face. Enterprises now need infrastructure that supports both traditional and AI-enhanced workloads in parallel as a current operational requirement, not a future goal.

What to watch: Private cloud has matured for this moment: 93% of enterprise IT leaders agree it delivers the reliability business-critical applications demand, and 92% say it provides the financial transparency and predictable costs needed to govern AI infrastructure spend. The key challenge ahead is formalizing collaboration between platform engineering and infrastructure teams—only 12% have made that collaboration formal, even though most organizations know they need shared governance for AI workload placement decisions.