P2P

82 adoption is now following suit, driven by pressure to modernize, compete, and keep up with shifting client expectations. AI's most significant disruption is not what it speeds up. It forces us to reexamine what it is. Baked into this adoption wave is a key assumption that the work itself is well-structured, the process well-designed, and the only thing holding us back is speed. What if that assumption is not accurate? If we optimize flawed workflows and business decisions based on faulty inputs, we are not scaling excellence—we are scaling inefficiency. The real question is not how fast we can go, but whether we are heading in the right direction. THE PRODUCTIVITY ILLUSION In most organizations, especially large ones, the adoption of AI is a cautious process. Client expectations, internal governance, and lengthy procurement cycles shape it. Teams are experimenting, champions are emerging, and rollout plans are forming. However, a deeper, quieter disruption is happening beneath the surface. As tools become faster and work takes less time to complete, the value model for time-based businesses begins to shift. Legal work, such as accounting and other professional services, remains tied mainly to the concept of the billable hour. What happens when that hour no longer reflects the actual effort required? Efficiency creates a paradox. On one hand, it is precisely what clients expect. On the other hand, it can erode revenue unless firms recalibrate how they define, deliver, and price value. This paradox creates a dilemma: to embrace AI and risk short-term revenue compression, or to resist it and fall behind. AI's momentum is irreversible. The advantage will belong to firms that know where it creates valid leverage and where it does not. LEVERAGING TIME'S ATOMIC UNIT FOR INSIGHT—NOT JUST INVOICING Remarkably, most industries can accurately determine their cost of production, down to the decimal point. But in knowledge work? That cost is often blurry at best and sometimes completely invisible. Why? Because our systems of record were designed to track billing, rather than effort, time entries are often self-reported, delayed, filtered, and inconsistent. They are edited before they are recorded, adjusted again before invoicing, and shaped more by perception than precision. Professionals are trying to obscure the truth. The system was simply not built for accuracy. It was built for billing. This gap has tangible consequences.

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