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Because AI is so new, there are no established best practices or regulations for its use. This creates a critical but temporary window where every organization's choices matter more. The precedents set now by early adopters in business, government, and education will significantly influence how AI is integrated into society.

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Predict AI's enterprise rollout by modeling autonomous driving. It starts as a human-assisted tool, moves to an internal process with a human "safety copilot," and only becomes fully autonomous when society and regulations are ready, not just the tech.

AI's growing ability to perform long-horizon tasks, like building software for hours without human intervention, means leaders must proactively rethink strategy, staffing, and budgeting. A responsible approach accounts for this increasing autonomy and its impact on knowledge work.

Facing growing moral panic, the AI industry's plan appears to be moving so fast that regulation becomes impossible. By building data centers and deploying models at breakneck speed, companies aim to make their technology ubiquitous before any effective policy can form.

Formal standards development organizations (SDOs) like the ISO operate on a 12-24 month timeline. This deliberate, consensus-based process is too slow to keep pace with the rapid evolution of AI technology, creating a governance gap that requires more agile, iterative approaches.

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.

Organizations must urgently develop policies for AI agents, which take action on a user's behalf. This is not a future problem. Agents are already being integrated into common business tools like ChatGPT, Microsoft Copilot, and Salesforce, creating new risks that existing generative AI policies do not cover.

AI is the first revolutionary technology in a century not originating from government-funded defense projects. This shift means policymakers lack the built-in knowledge and control they had with nuclear or space tech, forcing them to learn from and regulate an industry they did not create.

Effective AI policies focus on establishing principles for human conduct rather than just creating technical guardrails. The central question isn't what the tool can do, but how humans should responsibly use it to benefit employees, customers, and the community.

Technological advancement, particularly in AI, moves faster than legal and social frameworks can adapt. This creates 'lawless spaces,' akin to the Wild West, where powerful new capabilities exist without clear rules or recourse for those negatively affected. This leaves individuals vulnerable to algorithmic decisions about jobs, loans, and more.

As AI models evolve, they automate more internal steps, hiding the underlying process. Early adoption is crucial for understanding how AI works, much like early media buyers understood ad platforms better than those who started with today's automated systems.