Editor's note: The following is the second half of our coverage of 'Best Practices in Law Firm Marketing', a recent audio conference sponsored by the Institute for Office Management (IOMA).
So, based on the advice given last month, you've developed a strategic, firm-wide plan and coupled it with strong research efforts. Your firm has adopted approaches that will help differentiate it, not merely through expertise, but also through client service, and you've placed attorney training and coaching at the top of your 'must-do' list. Now it's time to tackle some nagging concerns ' globalization and a flagging economy ' and to consider implementing new tactics (and adapting existing ones) to improve your client acquisition and retention efforts.
Editor's note: The following is the second half of our coverage of 'Best Practices in Law Firm Marketing', a recent audio conference sponsored by the Institute for Office Management (IOMA).
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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.