Managing partners, financial partners, members of executive committees and administrators must devote more of their time today, than in the past, to planning and managing their firms' finances and those functions that improve the cash flow. Part One of this article described the first three of six aspects of law firm management and economics that the author has recommended to assist them in improving their firm's cash flow: 1) cash flow; 2) a business plan; 3) budgets for revenues, expenses and client advances. Part Two examines the remaining aspects: 4) partner compensation; 5) a recommended new business and billing committee; and 6) partners' capital and borrowing.
Joel A. RosePart Two of a Two-Part Article
Managing partners, financial partners, members of executive committees and administrators must devote more of their time today, than in the past, to planning and managing their firms' finances and those functions that improve the cash flow.
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Despite widespread investment into AI across the legal industry, just a small group of law firms are consistently realizing measurable returns in operational speed, financial visibility and revenue performance, according to a new report from Law.com and legal industry technology provider Elite.
Most firms are aiming their newest tools at the work they already do — pouring their most powerful technology into running the same tasks a little faster. But when everyone automates the same tasks at once, no one pulls ahead. That reaches the future a little faster while leaving a firm’s largest opportunity untouched — and that opportunity isn’t doing more of the existing work, but transforming how the high-value work gets done.
AI is becoming both an accelerant and a distraction for cybersecurity. In many respects, AI is acting as a stress test for existing security operations by exposing how difficult many organizations still find it to enforce basic controls consistently at scale.
Artificial intelligence is rapidly embedding itself into legal workflows, but much of the conversation treats all use cases as if they carry the same level of risk, even if they do not. The more useful question is not whether AI works, but where it can be safely applied and where it cannot.
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