To avoid being overwhelmed by AI's rapid progress, focus on staying ahead of the "speed of adoption," which is far slower than the "speed of research." Real-world implementation is slowed by legacy systems and organizational inertia. Outpacing this slower adoption curve is a manageable career strategy.

Large enterprises navigate a critical paradox with new technology like AI. Moving too slowly cedes the market and leads to irrelevance. However, moving too quickly without clear direction or a focus on feasibility results in wasting millions of dollars on failed initiatives.

The same organizational slowness that hinders enterprise AI adoption may paradoxically benefit society. This inertia acts as a natural brake on the rate of AI-driven disruption, giving the broader economy and workforce more time to adapt to transitional chaos.

The rapid evolution of AI means a 'wait and see' approach is no longer viable for large enterprises. Companies that delay adoption while waiting for the technology to stabilize will find themselves too far behind to catch up. It is better to start now and learn through controlled, iterative experimentation.

The default assumption is that slowing innovation is inherently bad. With a technology as potent as AI, a deliberate slowdown is a feature, providing critical time to understand the systems, manage disruptions, and build governance structures before irreversible consequences occur. A true halt is not the alternative.

The constant leapfrogging between AI labs and shifting architectural paradigms makes enterprise teams hesitant. They fear backing the wrong technology and getting locked into a strategy that will soon be deprecated, leading to inaction.

While AI labs release powerful models at an astonishing pace, large organizations are notoriously slow to adopt new technologies. This bureaucratic 'human friction' might be an unintentional benefit, providing society with the necessary time to grapple with the profound changes AI will bring.

Despite fears of rapid job displacement, the slow pace of technology adoption in large corporations provides a crucial window to develop solutions. The fact that many firms are still migrating to the cloud indicates AI integration will take years, not months.

The pace of AI development is so rapid that committing to a long-term contract with any single vendor is extremely risky. A better strategy for large companies is to patiently observe the market and avoid getting locked into technology that will be outflanked tomorrow.