American Marketing Association CIO Charts a Cost-Effective Course for Strategic Modernization

For years, leaders have treated legacy technology as a sunk cost that's easier to maintain than to replace. Today, this view is becoming dangerously outdated, with the cost of inaction compounding daily. More than just maintenance fees, legacy tools create a self-imposed business tax by slowing agility, increasing risk, and blocking innovation. Now, decommissioning old systems is a modern strategic imperative as a result.

Charles Wiggins, most recently the Vice President of Technology and Chief Information Officer at the American Marketing Association, explains how technology leaders can reframe this conversation. A self-described "battle-tested partner," Wiggins has a long history of driving platform consolidation transformations that help organizations reduce costs and modernize at scale. In his experience, before technology leaders can overcome organizational inertia, they must become business storytellers first.

"Legacy tech is not just a sunk cost. It's an innovation tax. Every outdated server, application, or integration you keep alive drains resources, slows agility, and exposes your organization to risks related to competitiveness, security, and innovation. There's a true cost to inaction. It just takes some digging and storytelling to surface it," Wiggins says.

To pay down this innovation tax, CIOs and CTOs must become cross-functional business drivers, Wiggins explains.

• Show me the money: The goal is to translate the hidden costs of inaction into a language the entire C-suite can understand, Wiggins continues. "Decommissioning legacy infrastructure is no longer just a technical cleanup exercise. It is a strategic imperative. The focus should be on agility, security, cost efficiency, and innovation readiness."

For Wiggins, nowhere is the cost of the "innovation tax" more apparent than in the race to adopt AI. While organizations clamor for revenue and efficiency, many find themselves blocked by the very legacy systems they have failed to address. Here, the struggle highlights a fundamental misunderstanding of what it takes to succeed.

• AI's real challenge: "AI is not a tech problem. It is a translation, trust, and adoption problem. The hype is that AI should do everything we want—grow revenue, deliver operational efficiency, create new products, and make our lives easier. The business reality is that delivering operational efficiency is far easier than delivering revenue impact. And without correct, high-integrity data, any AI initiative will fail."

But, even with perfect data and technology, Wiggins says, an AI initiative can still fail. In his experience, the biggest hurdles are human, not technical. "Sometimes the problem is not data, it is politics," he explains. The challenge of data silos, for instance, is frequently rooted in organizational politics where controlling information is a source of power. "You have the political reality of a leader saying, 'No, this is my data, and I don't want to give anyone else access to it.' As a result, you cannot deliver what is asked. The failure is not because the technology cannot do it, but because of business operations or a regulatory framework."

Modern technology executives have a unique opportunity to tell a story of transformation, Wiggins says. But it also requires a deeply collaborative and empathetic approach. Instead of a grand vision, the process begins with a single, tangible problem, he concludes. "Find one challenge for a C-suite peer and dive deep on it. Solving that problem is your entry point. You earn buy-in from the teams because you are solving a problem that speeds up processes and automates work. From there, build a roadmap, treat it as a transformation journey, and tie business metrics to it to quantify the impact."