AI success requires rebuilding core systems, not just adding new tools
Executives are urged to fix legacy IT, data, and workflows before scaling AI, as shiny demos alone won’t deliver business results.
While CEOs love to tout AI’s potential, most overlook the mundane challenges that block real impact. The piece likens the situation to running high-speed trains on rusted rails, emphasizing that legacy systems, siloed data, and broken processes are the true bottlenecks. A recent partnership to modernize TIAA’s 108-year-old record-keeping foundation showed that rebuilding the digital core, establishing a unified data platform, and rethinking end-to-end workflows were prerequisites for AI-driven improvements, such as reducing plan-change times and boosting participant engagement by 13%.
The author proposes five practical steps: audit and replace load-bearing platforms, ensure data is AI-ready, map and redesign workflows, keep humans in high-trust interactions, and adopt a resilient, governance-focused architecture. These disciplined, non-glamorous actions, rather than large budgets or flashy demos, differentiate companies that will sustain AI-enabled growth from those stuck in endless pilots.
Why it matters
Businesses that ignore foundational upgrades risk wasting AI investments and missing real performance gains.
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