{"id":154154,"date":"2026-06-09T15:32:16","date_gmt":"2026-06-09T23:32:16","guid":{"rendered":"https:\/\/xira.com\/p\/2026\/06\/09\/the-legal-tech-to-english-dictionary-2-0-artificial-intelligence-in-legal-tech\/"},"modified":"2026-06-09T15:32:16","modified_gmt":"2026-06-09T23:32:16","slug":"the-legal-tech-to-english-dictionary-2-0-artificial-intelligence-in-legal-tech","status":"publish","type":"post","link":"https:\/\/xira.com\/p\/2026\/06\/09\/the-legal-tech-to-english-dictionary-2-0-artificial-intelligence-in-legal-tech\/","title":{"rendered":"The Legal Tech-To-English Dictionary (2.0): Artificial Intelligence In Legal Tech"},"content":{"rendered":"
\"\"
<\/figcaption><\/figure>\n

Auth. note<\/span><\/em>: <\/strong>Though it was certainly tempting, no artificial intelligence technology was used to create this publication. All appearing em dashes were added by the author \u2014 just as nature intended.\u00a0<\/em><\/p>\n

Welcome to the sequel to the Legal Tech-to-English Dictionary (2022)<\/em><\/a>. This edition updates a vestige of the pre-AI world to share all of the AI and practice management terminology you need to be funner at parties.\u00a0<\/p>\n

Here, we\u2019re pleased to share Chapter 2. Check out the first installment here<\/a>, and feel free to pre-register for the full eBook using the form below. <\/p>\n

Judgment Day \u2014 Artificial Intelligence in Legal Tech.<\/strong><\/p>\n

Attorneys \u2014 famously tech-averse, late adopters \u2014 are flocking to artificial intelligence.<\/p>\n

The uptick in usage across all firm types has far surpassed cloud adoption. There are lawyers out there right now, using ChatGPT and still answering emails in an AOL account \u2014 and not just because they\u2019re hipsters!\u00a0<\/p>\n

Certain forms of artificial intelligence have been available in legal technology softwares for quite a long while \u2014 largely unbeknownst to the attorney masses. However, AI in legal tech and case management is now more accessible and obvious than it\u2019s ever been.\u00a0\u00a0<\/p>\n

So what are some of the major features you should know about? Well, let\u2019s let the AI handle that for you! (Nah, I\u2019ll just tell you; I\u2019m feeling generous.)<\/p>\n

technology assisted review (TAR) <\/strong>n. <\/em>1. <\/strong>machine learning and artificial intelligence processes deployed to organize, manage, and aggregate electronic discovery materials in the legal space.<\/p>\n

Etymology<\/em><\/strong><\/p>\n

The first usage of the term \u201cTechnology Assisted Review\u201d was Geoffrey Chaucer\u2019s, in a 1398 draft of \u201cThe Knight\u2019s Tale.\u201d Nah, I\u2019m just messing with you. The term was coined in 2011, by Maura Grossman and Gordon Cormack in a law review article. (Yeah, they sound fun.) But, it was a year after that, that predictive coding was first approved by a judicial ruling, in the case of Da Silva Moore v. Publicis Groupe<\/em> from 2012. Thus, TAR, as a viable legal process, if human, would not even be old enough to drink yet.<\/p>\n

Related Words<\/em><\/strong><\/p>\n

predictive coding, continuous active learning, validation, seed set, control set, recall, linear review<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Bruce: I just got a discovery drop.<\/p>\n

Bruce: It\u2019s literally 673 million documents.<\/p>\n

Bruce: I\u2019m gonna grab a coffee, and put my head in the toilet.<\/p>\n

Lydia: Run it through our eDiscovery software.<\/p>\n

Bruce: You\u2019re a sTAR, Lydia.<\/p>\n

Lydia: I know.<\/p>\n

chat with the case <\/strong>adj. <\/em>1. <\/strong>common law practice management software feature utilizing artificial intelligence that allows users to interact with a matter, for the purpose of engaging status updates.<\/p>\n

Synonyms<\/em><\/strong><\/p>\n

knowledge assistant, internal chat tool, case messaging, data aggregator<\/p>\n

Related Words<\/em><\/strong><\/p>\n

case summarization, case view, case management software, intelligent messaging triggers<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Alex: Status update, Johnson matter.<\/p>\n

HAL 9000: Which Johnson?<\/p>\n

Alex: Harvey.<\/p>\n

HAL 9000: Harvey Johnson. Litigation.<\/p>\n

Alex: Yes, what\u2019s the status?<\/p>\n

HAL 9000: Statute of limitations missed.<\/p>\n

HAL 9000: Three days ago.<\/p>\n

Alex: Crap.\u00a0<\/p>\n

HAL 9000: As an artificial intelligence, I cannot perform this action.<\/p>\n

Alex: Off, goddamnit.<\/p>\n

Alex: OFF!<\/p>\n

HAL 9000: Contacting your local bar overseers office.<\/p>\n

Alex: What, no!?!?<\/p>\n

predictive analytics <\/strong>n. <\/em>1. <\/strong>the use of statistical data to project outcomes based on historical precedent, including via machine learning techniques.<\/p>\n

Etymology<\/em><\/strong><\/p>\n

The roots of predictive analytics begin with insurance companies. In the late 17th century world famous insurance firm Lloyd\u2019s of London began using the strategy to set insurance rates for shipping companies. Arnold Daniels created the first predictive index assessment in 1952. He first became interested in statistics when the Army high command asked to study his tactics during World War II, when (amazingly) his battalion suffered zero casualties. Now, every industry (from sports to manufacturing to finance, and more) uses predictive analytics regularly, as powered by machine learning.\u00a0<\/p>\n

Related Words<\/em><\/strong><\/p>\n

regression analysis, random forest, decision trees, cluster modeling, time series modeling<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Carnac the Magnificent: When I wear this oversized hat I can predict the future.<\/p>\n

Edward: I just asked Google Gemini about that. It says you\u2019re lying.\u00a0<\/p>\n

Edward: What the hell?!?!<\/p>\n

Carnac the Magnificent: See \u2026<\/p>\n

Carnac the Magnificent: I knew that glass of water would get knocked over onto your laptop.<\/p>\n

intelligent document processing (IDP) <\/strong>n. <\/em>1. <\/strong>artificial intelligence process that can extract and categorize document data in support of generating finalized versions of documents (or document sets) from templates or unstructured document types.<\/p>\n

Related Words<\/em><\/strong><\/p>\n

document automation, documentation generation, workflow automation, field management, document logic, version control, data integration<\/p>\n

Antonyms<\/em><\/strong><\/p>\n

Just stop using Word Perfect, OK? I don\u2019t want to have to say this again.<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Andrea: My IDP is acting up again.<\/p>\n

Andrea: I think I have to reach out to support.<\/p>\n

Noah: I think there are some probiotics in the bathroom cabinet.<\/p>\n

Andrea: [facepalms]<\/p>\n

demand drafting software <\/strong>n. <\/em>1. <\/strong>an independent artificial intelligence program (or feature) that is capable of gathering disparate datasets in service of producing a formal demand letter requesting settlement.<\/p>\n

Related Words<\/em><\/strong><\/p>\n

medical records, medical chronology, structured data groups, integrations, structured data<\/p>\n

Cf. Most frequently utilized by personal injury law firms, but not exclusively.<\/p>\n

AI billing<\/strong> n.<\/em> 1.<\/strong> invoicing technology that uses artificial intelligence to generate and send billing and\/or to automate client\/customer payments.<\/p>\n

Related Words<\/em><\/strong><\/p>\n

pre-billing, activity codes, epayments, evergreen retainer, collection, cashflow<\/p>\n

Antonyms<\/em><\/strong><\/p>\n

paper-based time tracking, paper-based invoices, sticky notes, cash, checks, the waiting is the hardest part.\u00a0<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Wanda: I designed an AI billing model in my financial software today.<\/p>\n

Wanda: It uptakes my raw time description, applies activity codes, revises my notes, and then drafts an invoice for me to approve.<\/p>\n

Wanda: Once I approve, it sends an invoice, and follows up until it\u2019s paid.<\/p>\n

Wanda: I think my collection rate is about to go through the roof.<\/p>\n

Wanda: I\u2019m excited.<\/p>\n

Lena: Put your jacket on.<\/p>\n

Lena: We\u2019re going to the Kroger.<\/p>\n

\n

CosmoLex is proud to sponsor this edition of the Legal Tech-to-English Dictionary. As an end-to-end practice management platform built specifically for small to midsize law firms, CosmoLex integrates AI directly into the workflows attorneys rely on every day \u2014 summarizing documents, filtering matters and invoices in plain language, automating intake, and streamlining firm workflows. No separate tool to learn, no AI layer dropped onto a legacy system. Practical functionality built into the platform where the work already happens, with the compliance guardrails law firms actually need.<\/em><\/p>\n

Pre-Register for the Legal Tech-to-English Dictionary \u2014 Version 2.0<\/strong><\/p>\n

Registrants will receive the eBook via email this summer. <\/em><\/p>\n

<\/div>\n
\n

Jared Correia<\/a>, a consultant and legal technology expert, is the host of \u201cAdventures in Legal Tech,\u201d the featured podcast of Above the Law\u2019s Legal Tech Center<\/em><\/strong>.<\/p>\n

The post The Legal Tech-To-English Dictionary (2.0): Artificial Intelligence In Legal Tech<\/a> appeared first on Above the Law<\/a>.<\/p>\n

\"\"
<\/figcaption><\/figure>\n

Auth. note<\/span><\/em>: <\/strong>Though it was certainly tempting, no artificial intelligence technology was used to create this publication. All appearing em dashes were added by the author \u2014 just as nature intended.\u00a0<\/em><\/p>\n

Welcome to the sequel to the Legal Tech-to-English Dictionary (2022)<\/em><\/a>. This edition updates a vestige of the pre-AI world to share all of the AI and practice management terminology you need to be funner at parties.\u00a0<\/p>\n

Here, we\u2019re pleased to share Chapter 2. Check out the first installment here<\/a>, and feel free to pre-register for the full eBook using the form below. <\/p>\n

Judgment Day \u2014 Artificial Intelligence in Legal Tech.<\/strong><\/p>\n

Attorneys \u2014 famously tech-averse, late adopters \u2014 are flocking to artificial intelligence.<\/p>\n

The uptick in usage across all firm types has far surpassed cloud adoption. There are lawyers out there right now, using ChatGPT and still answering emails in an AOL account \u2014 and not just because they\u2019re hipsters!\u00a0<\/p>\n

Certain forms of artificial intelligence have been available in legal technology softwares for quite a long while \u2014 largely unbeknownst to the attorney masses. However, AI in legal tech and case management is now more accessible and obvious than it\u2019s ever been.\u00a0\u00a0<\/p>\n

So what are some of the major features you should know about? Well, let\u2019s let the AI handle that for you! (Nah, I\u2019ll just tell you; I\u2019m feeling generous.)<\/p>\n

technology assisted review (TAR) <\/strong>n. <\/em>1. <\/strong>machine learning and artificial intelligence processes deployed to organize, manage, and aggregate electronic discovery materials in the legal space.<\/p>\n

Etymology<\/em><\/strong><\/p>\n

The first usage of the term \u201cTechnology Assisted Review\u201d was Geoffrey Chaucer\u2019s, in a 1398 draft of \u201cThe Knight\u2019s Tale.\u201d Nah, I\u2019m just messing with you. The term was coined in 2011, by Maura Grossman and Gordon Cormack in a law review article. (Yeah, they sound fun.) But, it was a year after that, that predictive coding was first approved by a judicial ruling, in the case of Da Silva Moore v. Publicis Groupe<\/em> from 2012. Thus, TAR, as a viable legal process, if human, would not even be old enough to drink yet.<\/p>\n

Related Words<\/em><\/strong><\/p>\n

predictive coding, continuous active learning, validation, seed set, control set, recall, linear review<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Bruce: I just got a discovery drop.<\/p>\n

Bruce: It\u2019s literally 673 million documents.<\/p>\n

Bruce: I\u2019m gonna grab a coffee, and put my head in the toilet.<\/p>\n

Lydia: Run it through our eDiscovery software.<\/p>\n

Bruce: You\u2019re a sTAR, Lydia.<\/p>\n

Lydia: I know.<\/p>\n

chat with the case <\/strong>adj. <\/em>1. <\/strong>common law practice management software feature utilizing artificial intelligence that allows users to interact with a matter, for the purpose of engaging status updates.<\/p>\n

Synonyms<\/em><\/strong><\/p>\n

knowledge assistant, internal chat tool, case messaging, data aggregator<\/p>\n

Related Words<\/em><\/strong><\/p>\n

case summarization, case view, case management software, intelligent messaging triggers<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Alex: Status update, Johnson matter.<\/p>\n

HAL 9000: Which Johnson?<\/p>\n

Alex: Harvey.<\/p>\n

HAL 9000: Harvey Johnson. Litigation.<\/p>\n

Alex: Yes, what\u2019s the status?<\/p>\n

HAL 9000: Statute of limitations missed.<\/p>\n

HAL 9000: Three days ago.<\/p>\n

Alex: Crap.\u00a0<\/p>\n

HAL 9000: As an artificial intelligence, I cannot perform this action.<\/p>\n

Alex: Off, goddamnit.<\/p>\n

Alex: OFF!<\/p>\n

HAL 9000: Contacting your local bar overseers office.<\/p>\n

Alex: What, no!?!?<\/p>\n

predictive analytics <\/strong>n. <\/em>1. <\/strong>the use of statistical data to project outcomes based on historical precedent, including via machine learning techniques.<\/p>\n

Etymology<\/em><\/strong><\/p>\n

The roots of predictive analytics begin with insurance companies. In the late 17th century world famous insurance firm Lloyd\u2019s of London began using the strategy to set insurance rates for shipping companies. Arnold Daniels created the first predictive index assessment in 1952. He first became interested in statistics when the Army high command asked to study his tactics during World War II, when (amazingly) his battalion suffered zero casualties. Now, every industry (from sports to manufacturing to finance, and more) uses predictive analytics regularly, as powered by machine learning.\u00a0<\/p>\n

Related Words<\/em><\/strong><\/p>\n

regression analysis, random forest, decision trees, cluster modeling, time series modeling<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Carnac the Magnificent: When I wear this oversized hat I can predict the future.<\/p>\n

Edward: I just asked Google Gemini about that. It says you\u2019re lying.\u00a0<\/p>\n

Edward: What the hell?!?!<\/p>\n

Carnac the Magnificent: See \u2026<\/p>\n

Carnac the Magnificent: I knew that glass of water would get knocked over onto your laptop.<\/p>\n

intelligent document processing (IDP) <\/strong>n. <\/em>1. <\/strong>artificial intelligence process that can extract and categorize document data in support of generating finalized versions of documents (or document sets) from templates or unstructured document types.<\/p>\n

Related Words<\/em><\/strong><\/p>\n

document automation, documentation generation, workflow automation, field management, document logic, version control, data integration<\/p>\n

Antonyms<\/em><\/strong><\/p>\n

Just stop using Word Perfect, OK? I don\u2019t want to have to say this again.<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Andrea: My IDP is acting up again.<\/p>\n

Andrea: I think I have to reach out to support.<\/p>\n

Noah: I think there are some probiotics in the bathroom cabinet.<\/p>\n

Andrea: [facepalms]<\/p>\n

demand drafting software <\/strong>n. <\/em>1. <\/strong>an independent artificial intelligence program (or feature) that is capable of gathering disparate datasets in service of producing a formal demand letter requesting settlement.<\/p>\n

Related Words<\/em><\/strong><\/p>\n

medical records, medical chronology, structured data groups, integrations, structured data<\/p>\n

Cf. Most frequently utilized by personal injury law firms, but not exclusively.<\/p>\n

AI billing<\/strong> n.<\/em> 1.<\/strong> invoicing technology that uses artificial intelligence to generate and send billing and\/or to automate client\/customer payments.<\/p>\n

Related Words<\/em><\/strong><\/p>\n

pre-billing, activity codes, epayments, evergreen retainer, collection, cashflow<\/p>\n

Antonyms<\/em><\/strong><\/p>\n

paper-based time tracking, paper-based invoices, sticky notes, cash, checks, the waiting is the hardest part.\u00a0<\/p>\n

Example Sentence<\/em><\/strong><\/p>\n

Wanda: I designed an AI billing model in my financial software today.<\/p>\n

Wanda: It uptakes my raw time description, applies activity codes, revises my notes, and then drafts an invoice for me to approve.<\/p>\n

Wanda: Once I approve, it sends an invoice, and follows up until it\u2019s paid.<\/p>\n

Wanda: I think my collection rate is about to go through the roof.<\/p>\n

Wanda: I\u2019m excited.<\/p>\n

Lena: Put your jacket on.<\/p>\n

Lena: We\u2019re going to the Kroger.<\/p>\n

\n

CosmoLex is proud to sponsor this edition of the Legal Tech-to-English Dictionary. As an end-to-end practice management platform built specifically for small to midsize law firms, CosmoLex integrates AI directly into the workflows attorneys rely on every day \u2014 summarizing documents, filtering matters and invoices in plain language, automating intake, and streamlining firm workflows. No separate tool to learn, no AI layer dropped onto a legacy system. Practical functionality built into the platform where the work already happens, with the compliance guardrails law firms actually need.<\/em><\/p>\n

Pre-Register for the Legal Tech-to-English Dictionary \u2014 Version 2.0<\/strong><\/p>\n

Registrants will receive the eBook via email this summer. <\/em><\/p>\n

<\/div>\n
\n

Jared Correia<\/a>, a consultant and legal technology expert, is the host of \u201cAdventures in Legal Tech,\u201d the featured podcast of Above the Law\u2019s Legal Tech Center<\/em><\/strong>.<\/p>\n

The post The Legal Tech-To-English Dictionary (2.0): Artificial Intelligence In Legal Tech<\/a> appeared first on Above the Law<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

Auth. note: Though it was certainly tempting, no artificial intelligence technology was used to create this publication. All appearing em dashes were added by the author \u2014 just as nature intended.\u00a0 Welcome to the sequel to the Legal Tech-to-English Dictionary (2022). This edition updates a vestige of the pre-AI world to share all of the […]<\/p>\n","protected":false},"author":3,"featured_media":154155,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[16],"tags":[],"class_list":["post-154154","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-above_the_law"],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/xira.com\/p\/wp-content\/uploads\/2026\/06\/ornaw-book-3986102-1024x683-e9dyoK.jpg?fit=1024%2C683&ssl=1","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts\/154154","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/comments?post=154154"}],"version-history":[{"count":0,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts\/154154\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/media\/154155"}],"wp:attachment":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/media?parent=154154"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/categories?post=154154"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/tags?post=154154"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}