ILTACON 2025: The Wild, Wild West of legal tech — from abajournal.com by Nicole Black

On the surface, ILTACON 2025, the International Legal Technology Association’s largest annual legal technology event, had all the makings of a great conference. But despite the thought-provoking sessions and keynotes, networking opportunities and PR fanfare, I couldn’t shake the sense that we were in the midst of a seismic shift in legal tech, surrounded by the restless energy of a boomtown.

The gold rush
It wasn’t ILTACON that bothered me; it was the heady, gold-rushed, “anything goes and whatever sticks works” environment that was unsettling. While this year’s conference was pirate-themed, it felt more like the Wild West to me.

This attitude permeated the conference, driven largely by the frenzied, frontier-style artificial intelligence revolution. The AI train is hurtling forward at lightning speed, destination unknown, and everyone is trying to cash in before it derails.

Two themes emerged from my discussions. First, no matter who you spoke to, “agentic AI,” meaning AI that autonomously takes purposeful actions, was a buzzword that cropped up often, whether during press briefings or over drinks. Another key trend was the race to become the generative AI home base for legal professionals.

— Nicole Black

“We are at the start of the biggest disruption to the legal profession in its history.”

— Steve Hasker, Thomson Reuters president and CEO

 

Also see:

Fresh Voices on Legal Tech with Bridget McCormack — from legaltalknetwork.com

Is AI the technology that will finally force lawyer tech competence? With rapid advances and the ability to address numerous problems and pain points in our legal systems, AI simply can’t be ignored. Dennis & Tom welcome Bridget McCormack to discuss her perspectives on current AI trends and other exciting new tech applications in legal…

Top Legal Tech Jobs on the Rise: Who Employers Are Looking For in 2025 — from lawyer-monthly.com

For professionals, this means one thing: dozens of new career paths are appearing on the horizon that did not exist five years ago.

 
 

Thomson Reuters CEO: Legal Profession Faces “Biggest Disruption in Its History”from AI  — from lawnext.com by Bob Ambrogi

Thomson Reuters President and CEO Steve Hasker believes the legal profession is experiencing “the biggest disruption … in its history” due to generative and agentic artificial intelligence, fundamentally rewriting how legal work products are created for the first time in more than 300 years.

Speaking to legal technology reporters during ILTACON, the International Legal Technology Association’s annual conference, Hasker outlined his company’s ambitious goal to become “the most innovative company” in the legal tech sector while navigating what he described as unprecedented technological change affecting a profession that has remained largely unchanged since its origins in London tea houses centuries ago.


Legal tech hackathon challenges students to rethink access to justice — from the Centre for Innovation and Entrepreneurship, Auckland Law School
In a 24-hour sprint, student teams designed innovative tools to make legal and social support more accessible.

The winning team comprised of students of computer science, law, psychology and physics. They developed a privacy-first legal assistant powered by AI that helps people understand their legal rights without needing to navigate dense legal language. 


Teaching How To ‘Think Like a Lawyer’ Revisited — from abovethelaw.com by Stephen Embry
GenAI gives the concept of training law students to think like a lawyer a whole new meaning.

Law Schools
These insights have particular urgency for legal education. Indeed, most of Cowen’s criticisms and suggested changes need to be front and center for law school leaders. It’s naïve to think that law student and lawyers aren’t going to use GenAI tools in virtually every aspect of their professional and personal lives. Rather than avoiding the subject or worse yet trying to stop use of these tools, law schools should make GenAI tools a fundamental part of research, writing and drafting training.

They need to focus not on memorization but on the critical thinking skills beginning lawyers used to get in the on-the-job training guild type system. As I discussed, that training came from repetitive and often tedious work that developed experienced lawyers who could recognize patterns and solutions based on the exposure to similar situations. But much of that repetitive and tedious work may go away in a GenAI world.

The Role of Adjunct Professors
But to do this, law schools need to better partner with actual practicing lawyers who can serve as adjunct professors. Law schools need to do away with the notion that adjuncts are second-class teachers.


It’s a New Dawn In Legal Tech: From Woodstock to ILTACON (And Beyond) — from lawnext.com by Bob Ambrogi

As someone who has covered legal tech for 30 years, I cannot remember there ever being a time such as this, when the energy and excitement are raging, driven by generative AI and a new era of innovation and new ideas of the possible.

But this year was different. Wandering the exhibit hall, getting product briefings from vendors, talking with attendees, it was impossible to ignore the fundamental shift happening in legal technology. Gen AI isn’t just creating new products – it is spawning entirely new categories of products that truly are reshaping how legal work gets done.

Agentic AI is the buzzword of 2025 and agentic systems were everywhere at ILTACON, promising to streamline workflows across all areas of legal practice. But, perhaps more importantly, these tools are also beginning to address the business side of running a law practice – from client intake and billing to marketing and practice management. The scope of transformation is now beginning to extend beyond the practice of law into the business of law.

Largely missing from this gathering were solo practitioners, small firm lawyers, legal aid organizations, and access-to-justice advocates – the very people who stand to benefit most from the democratizing potential of AI.

However, now more than ever, the innovations we are seeing in legal tech have the power to level the playing field, to give smaller practitioners access to tools and capabilities that were once prohibitively expensive. If these technologies remain priced for and marketed primarily to Big Law, we will have succeeded only in widening the justice gap rather than closing it.


How AI is Transforming Deposition Review: A LegalTech Q&A — from jdsupra.com

Thanks to breakthroughs in artificial intelligence – particularly in semantic search, multimodal models, and natural language processing – new legaltech solutions are emerging to streamline and accelerate deposition review. What once took hours or days of manual analysis now can be accomplished in minutes, with greater accuracy and efficiency than possible with manual review.


From Skepticism to Trust: A Playbook for AI Change Management in Law Firms — from jdsupra.com by Scott Cohen

Historically, lawyers have been slow adopters of emerging technologies, and with good reason. Legal work is high stakes, deeply rooted in precedent, and built on individual judgment. AI, especially the new generation of agentic AI (systems that not only generate output but initiate tasks, make decisions, and operate semi-autonomously), represents a fundamental shift in how legal work gets done. This shift naturally leads to caution as it challenges long-held assumptions about lawyer workflows and several aspects of their role in the legal process.

The path forward is not to push harder or faster, but smarter. Firms need to take a structured approach that builds trust through transparency, context, training, and measurement of success. This article provides a five-part playbook for law firm leaders navigating AI change management, especially in environments where skepticism is high and reputational risk is even higher.


ILTACON 2025: The vendor briefings – Agents, ecosystems and the next stage of maturity — from legaltechnology.com by Caroline Hill

This year’s ILTACON in Washington was heavy on AI, but the conversation with vendors has shifted. Legal IT Insider’s briefings weren’t about potential use cases or speculative roadmaps. Instead, they focused on how AI is now being embedded into the tools lawyers use every day — and, crucially, how those tools are starting to talk to each other.

Taken together, they point to an inflection point, where agentic workflows, data integration, and open ecosystems define the agenda. But it’s important amidst the latest buzzwords to remember that agents are only as good as the tools they have to work with, and AI only as good as its underlying data. Also, as we talk about autonomous AI, end users are still struggling with cloud implementations and infrastructure challenges, and need vendors to be business partners that help them to make progress at speed.

Harvey’s roadmap is all about expanding its surface area — connecting to systems like iManage, LexisNexis, and more recently publishing giant Wolters Kluwer — so that a lawyer can issue a single query and get synthesised, contextualised answers directly within their workflow. Weinberg said: “What we’re trying to do is get all of the surface area of all of the context that a lawyer needs to complete a task and we’re expanding the product surface so you can enter a search, search all resources, and apply that to the document automatically.” 

The common thread: no one is talking about AI in isolation anymore. It’s about orchestration — pulling together multiple data sources into a workflow that actually reflects how lawyers practice. 


5 Pitfalls Of Delaying Automation In High-Volume Litigation And Claims — from jdsupra.com

Why You Can’t Afford to Wait to Adopt AI Tools that have Plaintiffs Moving Faster than Ever
Just as photocopiers shifted law firm operations in the early 1970s and cloud computing transformed legal document management in the early 2000s, AI automation tools are altering the current legal landscape—enabling litigation teams to instantly structure unstructured data, zero in on key arguments in seconds, and save hundreds (if not thousands) of hours of manual work.


Your Firm’s AI Policy Probably Sucks: Why Law Firms Need Education, Not Rules — from jdsupra.com

The Floor, Not the Ceiling
Smart firms need to flip their entire approach. Instead of dictating which AI tools lawyers must use, leadership should set a floor for acceptable use and then get out of the way.

The floor is simple: no free versions for client work. Free tools are free because users are the product. Client data becomes training data. Confidentiality gets compromised. The firm loses any ability to audit or control how information flows. This isn’t about control; it’s about professional responsibility.

But setting the floor is only the first step. Firms must provide paid, enterprise versions of AI tools that lawyers actually want to use. Not some expensive legal tech platform that promises AI features but delivers complicated workflows. Real AI tools. The same ones lawyers are already using secretly, but with enterprise security, data protection, and proper access controls.

Education must be practical and continuous. Single training sessions don’t work. AI tools evolve weekly. New capabilities emerge constantly. Lawyers need ongoing support to experiment, learn, and share discoveries. This means regular workshops, internal forums for sharing prompts and techniques, and recognition for innovative uses.

The education investment pays off immediately. Lawyers who understand AI use it more effectively. They catch its mistakes. They know when to verify outputs. They develop specialized prompts for legal work. They become force multipliers, not just for themselves but for their entire teams.

 

What next for EDI? Protecting equality of opportunity in HE — from timeshighereducation.com by Laura Duckett
As equity, diversity and inclusion practices face mounting political and cultural challenges, this guide includes strategies from academics around the world on preserving fair access and opportunity for all

As many in this guide explain, hostility to efforts to create fairer, inclusive and diverse institutions of higher education runs a lot deeper than the latest US presidential agenda and it cannot be ignored and rejected as a momentary political spike. Yet the continued need for EDI (or DEI as it is called in America) work to address historic and systemic injustice is clear from the data. In the US, Black, Hispanic, Latino, Native American and Pacific Islander people are under-represented in university student and staff populations. Students from these groups also have worse academic outcomes.

In the UK, only 1 per cent of professors are Black, women remain under-represented on the higher rungs of the academic ladder and the attainment gap between students from minoritised backgrounds and their white counterparts remains stubbornly evident across the higher education sector.

While not all EDI work has proved successful, significant progress has been made on widening participation in higher education and building more inclusive universities in which students and academics can thrive.

This guide shares lessons from academics on navigating increasingly choppy waters relating to EDI, addressing misconceptions about the work and its core ambitions, strategies for allyship, anti-racism and inclusion and how to champion EDI through your teaching and institutional culture.

 

BREAKING: Google introduces Guided Learning — from aieducation.substack.com by Claire Zau
Some thoughts on what could make Google’s AI tutor stand out

Another major AI lab just launched “education mode.”

Google introduced Guided Learning in Gemini, transforming it into a personalized learning companion designed to help you move from quick answers to real understanding.

Instead of immediately spitting out solutions, it:

  • Asks probing, open-ended questions
  • Walks learners through step-by-step reasoning
  • Adapts explanations to the learner’s level
  • Uses visuals, videos, diagrams, and quizzes to reinforce concepts

This Socratic style tutor rollout follows closely behind similar announcements like OpenAI’s Study Mode (last week) and Anthropic’s Claude for Education (April 2025).


How Sci-Fi Taught Me to Embrace AI in My Classroom — from edsurge.com by Dan Clark

I’m not too naive to understand that, no matter how we present it, some students will always be tempted by “the dark side” of AI. What I also believe is that the future of AI in education is not decided. It will be decided by how we, as educators, embrace or demonize it in our classrooms.

My argument is that setting guidelines and talking to our students honestly about the pitfalls and amazing benefits that AI offers us as researchers and learners will define it for the coming generations.

Can AI be the next calculator? Something that, yes, changes the way we teach and learn, but not necessarily for the worse? If we want it to be, yes.

How it is used, and more importantly, how AI is perceived by our students, can be influenced by educators. We have to first learn how AI can be used as a force for good. If we continue to let the dominant voice be that AI is the Terminator of education and critical thinking, then that will be the fate we have made for ourselves.


AI Tools for Strategy and Research – GT #32 — from goodtools.substack.com by Robin Good
Getting expert advice, how to do deep research with AI, prompt strategy, comparing different AIs side-by-side, creating mini-apps and an AI Agent that can critically analyze any social media channel

In this issue, discover AI tools for:

  • Getting Expert Advice
  • Doing Deep Research with AI
  • Improving Your AI Prompt Strategy
  • Comparing Results from Different AIs
  • Creating an AI Agent for Social Media Analysis
  • Summarizing YouTube Videos
  • Creating Mini-Apps with AI
  • Tasting an Award-Winning AI Short Film

GPT-Building, Agentic Workflow Design & Intelligent Content Curation — from drphilippahardman.substack.com by Dr. Philippa Hardman
What 3 recent job ads reveal about the changing nature of Instructional Design

In this week’s blog post, I’ll share my take on how the instructional design role is evolving and discuss what this means for our day-to-day work and the key skills it requires.

With this in mind, I’ve been keeping a close eye on open instructional design roles and, in the last 3 months, have noticed the emergence of a new flavour of instructional designer: the so-called “Generative AI Instructional Designer.”

Let’s deep dive into three explicitly AI-focused instructional design positions that have popped up in the last quarter. Each one illuminates a different aspect of how the role is changing—and together, they paint a picture of where our profession is likely heading.

Designers who evolve into prompt engineers, agent builders, and strategic AI advisors will capture the new premium. Those who cling to traditional tool-centric roles may find themselves increasingly sidelined—or automated out of relevance.


Google to Spend $1B on AI Training in Higher Ed — from insidehighered.com by Katherine Knott

Google’s parent company announced Wednesday (8/6/25) that it’s planning to spend $1 billion over the next three years to help colleges teach and train students about artificial intelligence.

Google is joining other AI companies, including OpenAI and Anthropic, in investing in AI training in higher education. All three companies have rolled out new tools aimed at supporting “deeper learning” among students and made their AI platforms available to certain students for free.


5 Predictions for How AI Will Impact Community Colleges — from pistis4edu.substack.com by Feng Hou

Based on current technology capabilities, adoption patterns, and the mission of community colleges, here are five well-supported predictions for AI’s impact in the coming years.

  1. Universal AI Tutor Access
  2. AI as Active Teacher
  3. Personalized Learning Pathways
  4. Interactive Multimodal Learning
  5. Value-Centric Education in an AI-Abundant World

 

One-size-fits-all learning is about to become completely obsolete. — from linkedin.com by Allie Miller


AI in the University: From Generative Assistant to Autonomous Agent This Fall — from insidehighered.com by
This fall we are moving into the agentic generation of artificial intelligence.

“Where generative AI creates, agentic AI acts.” That’s how my trusted assistant, Gemini 2.5 Pro deep research, describes the difference.

Agents, unlike generative tools, create and perform multistep goals with minimal human supervision. The essential difference is found in its proactive nature. Rather than waiting for a specific, step-by-step command, agentic systems take a high-level objective and independently create and execute a plan to achieve that goal. This triggers a continuous, iterative workflow that is much like a cognitive loop. The typical agentic process involves six key steps, as described by Nvidia:


AI in Education Podcast — from aipodcast.education by Dan Bowen and Ray Fleming


The State of AI in Education 2025 Key Findings from a National Survey — from Carnegie Learning

Our 2025 national survey of over 650 respondents across 49 states and Puerto Rico reveals both encouraging trends and important challenges. While AI adoption and optimism are growing, concerns about cheating, privacy, and the need for training persist.

Despite these challenges, I’m inspired by the resilience and adaptability of educators. You are the true game-changers in your students’ growth, and we’re honored to support this vital work.

This report reflects both where we are today and where we’re headed with AI. More importantly, it reflects your experiences, insights, and leadership in shaping the future of education.


Instructure and OpenAI Announce Global Partnership to Embed AI Learning Experiences within Canvas — from instructure.com

This groundbreaking collaboration represents a transformative step forward in education technology and will begin with, but is not limited to, an effort between Instructure and OpenAI to enhance the Canvas experience by embedding OpenAI’s next-generation AI technology into the platform.

IgniteAI announced earlier today, establishes Instructure’s future-ready, open ecosystem with agentic support as the AI landscape continues to evolve. This partnership with OpenAI exemplifies this bold vision for AI in education. Instructure’s strategic approach to AI emphasizes the enhancement of connections within an educational ecosystem comprising over 1,100 edtech partners and leading LLM providers.

“We’re committed to delivering next-generation LMS technologies designed with an open ecosystem that empowers educators and learners to adapt and thrive in a rapidly changing world,” said Steve Daly, CEO of Instructure. “This collaboration with OpenAI showcases our ambitious vision: creating a future-ready ecosystem that fosters meaningful learning and achievement at every stage of education. This is a significant step forward for the education community as we continuously amplify the learning experience and improve student outcomes.”


Faculty Latest Targets of Big Tech’s AI-ification of Higher Ed — from insidehighered.com by Kathryn Palmer
A new partnership between OpenAI and Instructure will embed generative AI in Canvas. It may make grading easier, but faculty are skeptical it will enhance teaching and learning.

The two companies, which have not disclosed the value of the deal, are also working together to embed large language models into Canvas through a feature called IgniteAI. It will work with an institution’s existing enterprise subscription to LLMs such as Anthropic’s Claude or OpenAI’s ChatGPT, allowing instructors to create custom LLM-enabled assignments. They’ll be able to tell the model how to interact with students—and even evaluate those interactions—and what it should look for to assess student learning. According to Instructure, any student information submitted through Canvas will remain private and won’t be shared with OpenAI.

Faculty Unsurprised, Skeptical
Few faculty were surprised by the Canvas-OpenAI partnership announcement, though many are reserving judgment until they see how the first year of using it works in practice.


 

Is the Legal Profession Ready to Win the AI Race? America’s AI Action Plan Has Fired the Starting Gun — from denniskennedy.com by Dennis Kennedy
The Starting Gun for Legal AI Has Fired. Who in Our Profession is on the Starting Line?

The legal profession’s “wait and see” approach to artificial intelligence is now officially obsolete.

This isn’t hyperbole. This is a direct consequence of the White House’s new Winning the Race: America’s AI Action Plan. …This is the starting gun for a race that will define the next fifty years of our profession, and I’m concerned that most of us aren’t even in the stadium, let alone in the starting blocks.

If the Socratic Method truly means anything, isn’t it time we applied its rigorous questioning to ourselves? We must question our foundational assumptions about the billable hour, the partnership track, our resistance to new forms of legal service delivery, and the very definition of what it means to be “practice-ready” in the 21st century. What do our clients, our students, and users of the legal system need?

The AI Action Plan forces a fundamental re-imagining of our industry’s core jobs.

The New Job of Legal Education: Producing AI-Capable Counsel
The plan’s focus on a “worker-centric approach” is a direct challenge to legal academia. The new job of legal education is no longer just to teach students how to think like a lawyer, but how to perform as an AI-augmented one. This means producing graduates who are not only familiar with the law but are also capable of leveraging AI tools to deliver legal services more efficiently, ethically, and effectively. Even more importnat, it means we must develop lawyers who can give the advice needed to individuals and companies already at work trying to win the AI race.

 

Recurring Themes In Bob Ambrogi’s 30 Years of Legal Tech Reporting (A Guest Post By ChatGPT) — from lawnext.com by ChatGPT
#legaltech #innovation #law #legal #innovation #vendors #lawyers #lawfirms #legaloperations

  • Evolution of Legal Technology: From Early Web to AI Revolution
  • Challenges in Legal Innovation and Adoption
  • Law Firm Innovation vs. Corporate Legal Demand: Shifting Dynamics
  • Tracking Key Technologies and Players in Legal Tech
  • Access to Justice, Ethics, and Regulatory Reform

Also re: legaltech, see:

How LegalTech is Changing the Client Experience in 2025 — from techbullion.com by Uzair Hasan

A Digital Shift in Law
In 2025, LegalTech isn’t a trend—it’s a standard. Tools like client dashboards, e-signatures, AI legal assistants, and automated case tracking are making law firms more efficient and more transparent. These systems also help reduce errors and save time. For clients, it means less confusion and more control.

For example, immigration law—a field known for paperwork and long processing times—is being transformed through tech. Clients now track their case status online, receive instant updates, and even upload key documents from their phones. Lawyers, meanwhile, use AI tools to spot issues faster, prepare filings quicker, and manage growing caseloads without dropping the ball.

Loren Locke, Founder of Locke Immigration Law, explains how tech helps simplify high-stress cases:
“As a former consular officer, I know how overwhelming the visa process can feel. Now, we use digital tools to break down each step for our clients—timelines, checklists, updates—all in one place. One client recently told me it was the first time they didn’t feel lost during their visa process. That’s why I built my firm this way: to give people clarity when they need it most.”


While not so much legaltech this time, Jordan’s article below is an excellent, highly relevant posting for what we are going through — at least in the United States:

What are lawyers for? — from jordanfurlong.substack.com by Jordan Furlong
We all know lawyers’ commercial role, to be professional guides for human affairs. But we also need lawyers to bring the law’s guarantees to life for people and in society. And we need it right now.

The question “What are lawyers for?” raises another, prior and more foundational question: “What is the law for?”

But there’s more. The law also exists to regulate power in a society: to structure its distribution, create processes for its implementation, and place limits on its application. In a healthy society, power flows through the law, not around it. Certainly, we need to closely examine and evaluate those laws — the exercise of power through a biased or corrupted system will be illegitimate even if it’s “lawful.” But as a general rule, the law is available as a check on the arbitrary exercise of power, whether by a state authority or a private entity.

And above these two aspects of law’s societal role, I believe there’s also a third: to serve as a kind of “moral architecture” of society.

 

Osgoode’s new simulation-based learning tool aims to merge ethical and practical legal skills — from canadianlawyermag.com by Tim Wilbur
The designer speaks about his vision for redefining legal education through an innovative platform

The disconnection between legal education and the real world starkly contrasted with what he expected law school to be. “I thought rather naively…this would be a really interesting experience…linked to lawyers and what lawyers are doing in society…Far from it. It was solidly academic, so uninteresting, and I thought it’s got to be better than this.”

These frustrations inspired his work on simulation-based education, which seeks to produce “client-ready” lawyers and professionals who reflect deeply on their future roles. Maharg recently worked as a consultant with Osgoode Professional Development at Osgoode Hall Law School to design a platform that eschews many of the assumptions about legal education to deliver practical skills with real-world scenarios.

Osgoode’s SIMPLE platform – short for “simulated professional learning environment” – integrates case management systems and simulation engines to immerse students in practical scenarios.

“It’s actually to get them thinking hard about what they do when they act as lawyers and what they will do when they become lawyers…putting it into values and an ethical framework, as well as making it highly intensively practical,” Maharg says.


And speaking of legal training, also see:

AI in law firms should be a training tool, not a threat, for young lawyers — from canadianlawyermag.com by Tim Wilbur
Tech should free associates for deeper learning, not remove them from the process

AI is rapidly transforming legal practice. Today, tools handle document review and legal research at a pace unimaginable just a few years ago. As recent Canadian Lawyer reporting shows, legal AI adoption is outpacing expectations, especially among in-house teams, and is fundamentally reshaping how legal services are delivered.

Crucially, though, AI should not replace associates. Instead, it should relieve them of repetitive tasks and allow them to focus on developing judgment, client management, and strategic thinking. As I’ve previously discussed regarding the risks of banning AI in court, the future of law depends on blending technological fluency with the human skills clients value most.


Also, the following relates to legaltech as well:

Agentic AI in Legaltech: Proceed with Supervision! — from directory.lawnext.com by Ken Crutchfield
Semi-Autonomous agents can transform work if leaders maintain oversight

The term autonomous agents should raise some concern. I believe semi-autonomous agents is a better term. Do we really want fully autonomous agents that learn and interact independently, to find ways to accomplish tasks?

We live in a world full of cybersecurity risks. Bad actors will think of ways to use agents. Even well-intentioned systems could mishandle a task without proper guardrails.

Legal professionals will want to thoughtfully equip their agent technology with controlled access to the right services. Agents must be supervised, and training must be required for those using or benefiting from agents. Legal professionals will also want to expand the scope of AI Governance to include the oversight of agents.

Agentic AI will require supervision. Human review of Generative AI output is essential. Stating the obvious may be necessary, especially with agents. Controls, human review, and human monitoring must be part of the design and the requirements for any project. Leadership should not leave this to the IT department alone.

 

Fresh Voices on Legal Tech with Mathew Kerbis — from legaltalknetwork.com by Mathew Kerbis, Dennis Kennedy, and Tom Mighell

New approaches to legal service delivery are propelling us into the future. Don’t get left behind! AI and automations are making alternative service delivery easier and more efficient than ever. Dennis & Tom welcome Mathew Kerbis to learn more about his expertise in subscription-based legal services.


The Business Case For Legal Tech — from lexology.com

What a strong business case includes
A credible business case has three core elements: a clear problem statement, a defined solution, and a robust analysis of expected impact. It should also demonstrate that legal has done its homework and thought beyond implementation.

  1. Problem definition
  2. Current state analysis
  3. Solution overview
  4. Impact assessment
  5. Implementation plan
  6. Cost summary and ROI
  7. Strategic alignment

How AI is Revolutionizing Legal Technology in 2025 — from itmunch.com by Gaurav Uttamchandani

Table of Contents

  • What is AI in Legal Technology?
  • Key Use Cases of AI in the Legal Industry
    • 1. Contract Review & Management
    • 2. Legal Research & Case Analysis
    • 3. Litigation Prediction & Risk Assessment
    • 4. E-Discovery
    • 5. Legal Chatbots & Virtual Assistants
  • Benefits of AI in Legal Tech
  • Real-World Example: AI in Action
  • Implementing AI in Your Law Firm: Step-by-Step
  • Addressing Concerns Around AI in Law
  • LegalTech Trends to Watch in 2025
  • Final Thoughts
  • Call-to-Action (CTA)

 

In A Mega Deal, Clio Buys vLex for $1 Billion, Merging AI, Research and Practice Management — from lawnext.com by Bob Ambrogi

In a landmark deal that will undoubtedly reshape the legal tech landscape, law practice management company Clio has signed a definitive agreement to acquire the AI and legal research company vLex for $1 billion in cash and stock.

The companies say that the acquisition will “establish a new category of intelligent legal technology at the intersection of the business and practice of law, empowering legal professionals to seamlessly manage, research, and execute legal work within a unified system.”

 

The EU’s Legal Tech Tipping Point – AI Regulation, Data Sovereignty, and eDiscovery in 2025 — from jdsupra.com by Melina Efstathiou

The Good, the Braver and the Curious.
As we navigate through 2025, the European legal landscape is undergoing a significant transformation, particularly in the realms of artificial intelligence (AI) regulation and data sovereignty. These changes are reshaping how legal departments and more specifically eDiscovery professionals operate, compelling them to adapt to new compliance requirements and technological advancements.

Following on from our blog post on Navigating eDisclosure in the UK and Practice Direction 57AD, we are now moving on to explore AI regulation in the greater European spectrum, taking a contrasting glance towards the UK and the US as well, at the close of this post.


LegalTech’s Lingering Hurdles: How AI is Finally Unlocking Efficiency in the Legal Sector — from techbullion.co by Abdul Basit

However, as we stand in mid-2025, a new paradigm is emerging. Artificial Intelligence, once a buzzword, is now demonstrably addressing many of the core issues that have historically plagued LegalTech adoption and effectiveness, ushering in an era of unprecedented efficiency. Legal tech specialists like LegalEase are leading the way with some of these newer solutions, such as Ai powered NDA drafting.

Here’s how AI is making profound efficiencies:

    • Automated Document Review and Analysis:
    • Intelligent Contract Lifecycle Management (CLM):
    • Enhanced Legal Research:
    • Predictive Analytics for Litigation and Risk:
    • Streamlined Practice Management and Workflow Automation:
    • Personalized Legal Education and Training:
    • Improved Client Experience:

The AI Strategy Potluck: Law Firms Showing Up Empty-Handed, Hungry, And Weirdly Proud Of It — from abovethelaw.com by Joe Patrice
There’s a $32 billion buffet of time and money on the table, and the legal industry brought napkins.

The Thomson Reuters “Future of Professionals” report(Opens in a new window) just dropped and one stat standing out among its insights is that organizations with a visible AI strategy are not only twice as likely to report growth, they’re also 3.5 times more likely to see actual, tangible benefits from AI adoption.

AI Adoption Strategies


Speaking of legal-related items as well as tech, also see:

  • Landmark AI ruling is a blow to authors and artists — from popular.info by Judd Legum
    This week, a federal judge, William Alsup, rejected Anthropic’s effort to dismiss the case and found that stealing books from the internet is likely a copyright violation. A trial will be scheduled in the future. If Anthropic loses, each violation could come with a fine of $750 or more, potentially exposing the company to billions in damages. Other AI companies that use stolen work to train their models — and most do — could also face significant liability.
 

Agentic AI use cases in the legal industry — from legal.thomsonreuters.com
What legal professionals need to know now with the rise of agentic AI

While GenAI can create documents or answer questions, agentic AI takes intelligence a step further by planning how to get multi-step work done, including tasks such as consuming information, applying logic, crafting arguments, and then completing them.? This leaves legal teams more time for nuanced decision-making, creative strategy, and relationship-building with clients—work that machines can’t do.


The AI Legal Landscape in 2025: Beyond the Hype — from akerman.com by Melissa C. Koch

What we’re witnessing is a profession in transition where specific tasks are being augmented or automated while new skills and roles emerge.

The data tells an interesting story: approximately 79% of law firms have integrated AI tools into their workflows, yet only a fraction have truly transformed their operations. Most implementations focus on pattern recognition tasks such as document review, legal research, contract analysis. These implementations aren’t replacing lawyers; they’re redirecting attention to higher-value work.

This technological shift doesn’t happen in isolation. It’s occurring amid client pressure for efficiency, competition from alternative providers, and the expectations of a new generation of lawyers who have never known a world without AI assistance.


LexisNexis and Harvey team up to revolutionize legal research with artificial intelligence — from abajournal.com by Danielle Braff

Lawyers using the Harvey artificial intelligence platform will soon be able to tap into LexisNexis’ vast legal research capabilities.

Thanks to a new partnership announced Wednesday, Harvey users will be able to ask legal questions and receive fast, citation-backed answers powered by LexisNexis case law, statutes and Shepard’s Citations, streamlining everything from basic research to complex motions. According to a press release, generated responses to user queries will be grounded in LexisNexis’ proprietary knowledge graphs and citation tools—making them more trustworthy for use in court or client work.


10 Legal Tech Companies to Know — from builtin.com
These companies are using AI, automation and analytics to transform how legal work gets done.
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Four months after a $3B valuation, Harvey AI grows to $5B — from techcrunch.com by Marina Temkin

Harvey AI, a startup that provides automation for legal work, has raised $300 million in Series E funding at a $5 billion valuation, the company told Fortune. The round was co-led by Kleiner Perkins and Coatue, with participation from existing investors, including Conviction, Elad Gil, OpenAI Startup Fund, and Sequoia.


The billable time revolution — from jordanfurlong.substack.com by Jordan Furlong
Gen AI will bring an end to the era when lawyers’ value hinged on performing billable work. Grab the coming opportunity to re-prioritize your daily activities and redefine your professional purpose.

Because of Generative AI, lawyers will perform fewer “billable” tasks in future; but why is that a bad thing? Why not devote that incoming “freed-up” time to operating, upgrading, and flourishing your law practice? Because this is what you do now: You run a legal business. You deliver good outcomes, good experiences, and good relationships to clients. Humans do some of the work and machines do some of the work and the distinction that matters is not billable/non-billable, it’s which type of work is best suited to which type of performer.


 

 

“Using AI Right Now: A Quick Guide” [Molnick] + other items re: AI in our learning ecosystems

Thoughts on thinking — from dcurt.is by Dustin Curtis

Intellectual rigor comes from the journey: the dead ends, the uncertainty, and the internal debate. Skip that, and you might still get the insight–but you’ll have lost the infrastructure for meaningful understanding. Learning by reading LLM output is cheap. Real exercise for your mind comes from building the output yourself.

The irony is that I now know more than I ever would have before AI. But I feel slightly dumber. A bit more dull. LLMs give me finished thoughts, polished and convincing, but none of the intellectual growth that comes from developing them myself. 


Using AI Right Now: A Quick Guide — from oneusefulthing.org by Ethan Mollick
Which AIs to use, and how to use them

Every few months I put together a guide on which AI system to use. Since I last wrote my guide, however, there has been a subtle but important shift in how the major AI products work. Increasingly, it isn’t about the best model, it is about the best overall system for most people. The good news is that picking an AI is easier than ever and you have three excellent choices. The challenge is that these systems are getting really complex to understand. I am going to try and help a bit with both.

First, the easy stuff.

Which AI to Use
For most people who want to use AI seriously, you should pick one of three systems: Claude from Anthropic, Google’s Gemini, and OpenAI’s ChatGPT.

Also see:


Student Voice, Socratic AI, and the Art of Weaving a Quote — from elmartinsen.substack.com by Eric Lars Martinsen
How a custom bot helps students turn source quotes into personal insight—and share it with others

This summer, I tried something new in my fully online, asynchronous college writing course. These classes have no Zoom sessions. No in-person check-ins. Just students, Canvas, and a lot of thoughtful design behind the scenes.

One activity I created was called QuoteWeaver—a PlayLab bot that helps students do more than just insert a quote into their writing.

Try it here

It’s a structured, reflective activity that mimics something closer to an in-person 1:1 conference or a small group quote workshop—but in an asynchronous format, available anytime. In other words, it’s using AI not to speed students up, but to slow them down.

The bot begins with a single quote that the student has found through their own research. From there, it acts like a patient writing coach, asking open-ended, Socratic questions such as:

What made this quote stand out to you?
How would you explain it in your own words?
What assumptions or values does the author seem to hold?
How does this quote deepen your understanding of your topic?
It doesn’t move on too quickly. In fact, it often rephrases and repeats, nudging the student to go a layer deeper.


The Disappearance of the Unclear Question — from jeppestricker.substack.com Jeppe Klitgaard Stricker
New Piece for UNESCO Education Futures

On [6/13/25], UNESCO published a piece I co-authored with Victoria Livingstone at Johns Hopkins University Press. It’s called The Disappearance of the Unclear Question, and it’s part of the ongoing UNESCO Education Futures series – an initiative I appreciate for its thoughtfulness and depth on questions of generative AI and the future of learning.

Our piece raises a small but important red flag. Generative AI is changing how students approach academic questions, and one unexpected side effect is that unclear questions – for centuries a trademark of deep thinking – may be beginning to disappear. Not because they lack value, but because they don’t always work well with generative AI. Quietly and unintentionally, students (and teachers) may find themselves gradually avoiding them altogether.

Of course, that would be a mistake.

We’re not arguing against using generative AI in education. Quite the opposite. But we do propose that higher education needs a two-phase mindset when working with this technology: one that recognizes what AI is good at, and one that insists on preserving the ambiguity and friction that learning actually requires to be successful.




Leveraging GenAI to Transform a Traditional Instructional Video into Engaging Short Video Lectures — from er.educause.edu by Hua Zheng

By leveraging generative artificial intelligence to convert lengthy instructional videos into micro-lectures, educators can enhance efficiency while delivering more engaging and personalized learning experiences.


This AI Model Never Stops Learning — from link.wired.com by Will Knight

Researchers at Massachusetts Institute of Technology (MIT) have now devised a way for LLMs to keep improving by tweaking their own parameters in response to useful new information.

The work is a step toward building artificial intelligence models that learn continually—a long-standing goal of the field and something that will be crucial if machines are to ever more faithfully mimic human intelligence. In the meantime, it could give us chatbots and other AI tools that are better able to incorporate new information including a user’s interests and preferences.

The MIT scheme, called Self Adapting Language Models (SEAL), involves having an LLM learn to generate its own synthetic training data and update procedure based on the input it receives.


Edu-Snippets — from scienceoflearning.substack.com by Nidhi Sachdeva and Jim Hewitt
Why knowledge matters in the age of AI; What happens to learners’ neural activity with prolonged use of LLMs for writing

Highlights:

  • Offloading knowledge to Artificial Intelligence (AI) weakens memory, disrupts memory formation, and erodes the deep thinking our brains need to learn.
  • Prolonged use of ChatGPT in writing lowers neural engagement, impairs memory recall, and accumulates cognitive debt that isn’t easily reversed.
 
 
© 2025 | Daniel Christian