{"id":163141,"date":"2026-09-18T02:00:00","date_gmt":"2026-09-18T10:00:00","guid":{"rendered":"https:\/\/xira.com\/p\/2026\/09\/18\/lawyers-dont-need-more-ai-tools-they-need-better-workflow-decisions\/"},"modified":"2026-09-18T02:00:00","modified_gmt":"2026-09-18T10:00:00","slug":"lawyers-dont-need-more-ai-tools-they-need-better-workflow-decisions","status":"publish","type":"post","link":"https:\/\/xira.com\/p\/2026\/09\/18\/lawyers-dont-need-more-ai-tools-they-need-better-workflow-decisions\/","title":{"rendered":"Lawyers Don\u2019t Need More AI Tools, They Need Better Workflow Decisions"},"content":{"rendered":"

The next phase of legal innovation, says Ivy Grey, should focus on building AI-enabled workflows attorneys will actually use, with accountability baked in. A few best practices.
\nThe post Lawyers Don\u2019t Need More AI Tools, They Need Better Workflow Decisions appeared first on Articles, Tips and Tech for Law Firms and Lawyers.<\/p>\n

The legal market has spent the last two years chasing new AI products, but many lawyers still have not changed how work really happens. The next phase of legal innovation, says <\/strong><\/em>iManage<\/em><\/strong><\/a> adviser Ivy Grey, should be less about adding more tech and more about optimizing AI-enabled workflows for attorneys.<\/strong><\/em><\/p>\n

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Building Accountability Into the AI-Enabled Workflow<\/h2>\n

\u201cWorkflow\u201d is often pictured as a technical diagram filled with the steps and building blocks to be assembled into an automation. But identifying those building blocks takes you only so far. You need to get them into the proper order. And the more important part of workflow is getting the handoffs right<\/a> \u2014 understanding how work gets handed off to another lawyer, to a junior associate, to a piece of software, to an AI agent.<\/p>\n

That\u2019s the piece that needs attention now, and it\u2019s why \u201caccountability by design\u201d is essential for increasing lawyers\u2019 adoption of artificial intelligence, and actually improving how work gets done.<\/p>\n

Trusting a person or an AI agent to act on one\u2019s behalf requires a way to build accountability into the natural course of doing the work \u2014 affirming, as part of drafting or reviewing, that a fact has been checked and a citation is accurate. The more typical approach bolts accountability onto the end of the process: Do the work, then audit it, then document that the audit happened.<\/p>\n

That structure is no longer tenable in the AI era.<\/p>\n

Accountability Leads to Efficiency<\/h2>\n

Consider a litigator drafting the factual background of a brief, working from \u201cthe record\u201d \u2014 everything filed with the court, plus supporting material pulled from a document repository. Suppose the narrative states that a mortgage payment of $3,510 arrived on a specific date. In the paper era, that sentence needed little scrutiny. The underlying check existed, physically, and no one worried its amount had been invented.<\/p>\n

Once an AI system drafts that sentence, the calculus changes. The amount, the sender and the date all need confirming against the source, preferably with a link back to the document.<\/p>\n

The same discipline applies to legal requirements, not just facts. Suppose the argument is that the payment arrived after a contractual cure period expired, thus the contract was breached, and the creditor can now pursue its collection remedies. An AI tool might accurately conclude that the prerequisites have been met and that foreclosure is now proper.<\/p>\n

Confirming the analysis and application of lien law is correct<\/em> remains a professional obligation. <\/h3>\n

A junior associate, for example, should check the facts and mark them as verified by inserting their initials. A senior lawyer should never have to personally recheck that kind of foundational point. They should be able to trust that the associate has done the legwork and that they can pick up where the associate left off as the work is handed off.<\/p>\n

Without an accountability structure like the above in place, AI creates a strange inefficiency: Multiple lawyers can spend excessive time verifying every line. Time spent checking for invented case law, invented facts or other hallucinations to make sure that whoever was entrusted to do the work didn\u2019t solely rely on AI and performed the necessary verification in a way that\u2019s recorded and visible.<\/p>\n

That\u2019s a phenomenon known as the \u201cverification-value paradox<\/a>.\u201d It exemplifies how quickly the expected efficiency gains from AI disappear if accountability by design isn\u2019t part of the workflow.<\/p>\n

A Few Best Practices Go a Long Way<\/h2>\n

Workflow optimization requires taking a look at the handoff itself. <\/h3>\n

Poor handoffs are among the most common (and most avoidable) pitfalls when leveraging AI for various pieces of workflow. <\/p>\n

For instance, lawyers routinely tell a colleague or an AI tool to \u201cjust do X\u201d without mentioning the 25 steps that have to happen first. A good handoff spells out the goal, the sources typically needed, and how to make a judgment call if a question arises. That context isn\u2019t simply a courtesy. Providing context turns a vague instruction into a task someone else can successfully complete.<\/p>\n

This gets at the heart of a distinction many lawyers blur: Delegation is not assignment. <\/p>\n