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Enterprises must rewire legacy operating systems to adopt AI
AI adoption stalls when companies bolt new tools onto 20th-century operating systems. Marketing teams must flatten multi-layered approvals to see actual ROI.
Melissa Reeve, former VP of marketing at Scaled Agile, argues in her new book Hyperadaptive: Rewiring the Enterprise to Become AI-Native that organizations fail at AI adoption because they bolt the technology onto industrial-era operating systems. For marketing teams, this means current workflows and approval layers will stall AI pilots unless the underlying organizational structure changes.
The industrial-era operating system
Most companies still use operating models built for the 20th century. Strategy flows top-down through layers of approval, while work moves sideways through functional silos. This hierarchy slows decisions and causes handoffs to lose information. "This was the correct design for a world that valued consistency over speed," Reeve said.
Marketing leaders attempting to scale these tools must recognize that AI for Marketing requires rethinking how campaigns are approved and executed, rather than just adding new software. Simply purchasing new generative tools will not overcome structural bottlenecks.
Becoming hyperadaptive
The solution is not better technology, but a different organizational structure. Reeve defines successful companies as hyperadaptive. They are "architected to sense faster, learn continuously, and make smarter choices than any human could make alone."
When organizations attempt to force AI into rigid frameworks, pilots stall and adoption plateaus. The company gets faster at the edges, while the middle stays exactly as slow as before. This shift from rigid hierarchies to continuous learning mirrors broader trends in AI for Executives & Strategy, where leadership must redesign decision-making processes to support rapid iteration.
Why this matters for marketing professionals
Marketing teams often sit at the intersection of creative speed and corporate compliance. If your department relies on multi-layered approvals and siloed data, AI tools will only accelerate the creation of assets, not their deployment. To see actual ROI from AI, marketers must push for flattened approval workflows and cross-functional collaboration, ensuring the organization's operating system can actually run the technology.