The Difference Between Doing and Managing Marketing
In the early, primitive days of marketing professional services, there weren't enough people doing marketing for law, accounting and consulting firms to think much about departmental management.
The Difference Between Doing And Managing Marketing In the early, primitive days of marketing professional services, there weren't enough people doing marketing for law, accounting, and consulting firms to think much about departmental management. The exceptions, of course, were the larger firms, particularly those for whom, in the beginning, having more people on staff was often equated to better marketing. Marketing, at the beginning, was invariably assigned to a partner, who had only a vague'
The Difference Between Doing and Managing Marketing
In the early, primitive days of marketing professional services, there weren't enough people doing marketing for law, accounting and consulting firms to think much about departmental management.
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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.