The timing reflects a maturation problem. Current research shows 89% of organizations deploy AI somewhere, yet only approximately 33% have achieved meaningful scale. Most remain trapped in pilot programs that never reach production. The distinction between "uses AI" and "doesn't use AI" has become operationally irrelevant. What separates leaders from laggards is whether organizations have reimagined their core processes around intelligence as infrastructure rather than bolting AI onto legacy systems.
Attorneys should monitor this shift because it changes how AI governance, liability, and compliance frameworks apply. Embedded systems create different audit trails, accountability structures, and failure modes than user-facing tools. Organizations making this transition will face novel questions around agent autonomy, decision lineage, and human oversight that existing AI governance frameworks don't yet address. The competitive advantage will accrue to companies that solve these governance problems first—making this less a technology story than an organizational and legal one.