The biggest challenges facing law firms in 2026 weren’t new. They were old operations problems that AI made impossible to ignore. Every firm felt it had to “do something” with AI, and firms that had ignored their operations for years found their problems got bigger, faster.
I’m the founder and CEO of Chops Consulting. We’ve worked with over 70 law firms across Canada and the US on technology and operations audits, practice management conversions and AI implementation. This is what I saw inside firms this year, on the business and operations side, and what the strongest firms did about it.
The short answer
The defining challenge for law firms in 2026 was AI pressure colliding with years of underinvestment in operations and technology. The other big ones: law society rules on generative AI, privacy and cross-border data obligations, shadow AI, and burnout driven by bad processes. The strongest firms fixed their workflows, data and tech stack first, wrote AI policies more specific than their regulator requires, measured AI against a baseline, and invested in change management.
What were the biggest challenges facing law firms in 2026?
2026 was the year AI pressure collided with years of underinvestment in firms’ operations and technology. Things were already breaking before AI arrived:
- Undocumented processes
- Every lawyer doing things their own way
- Data spread across systems that don’t talk to each other
- Practice management software only partly set up
80% or more of the firms I meet are only using the surface-level features of the software they already pay for.
When you add AI on top of that, you don’t get a better-run firm. You just scale the problems at an accelerated rate.
No baseline, no way to measure AI
At the Ontario Bar Association’s TECHxpo in 2026, where I spoke about measuring the return on AI, one of the questions I heard most was some version of “we spend more time running the AI than it saves us.” Another was “how do we know if it’s worth it?” Most firms hadn’t tracked any baseline before they bought, so they had nothing to measure against.
Buying the demo instead of the fit
I’ve seen a firm burn half a million dollars on a platform built for much smaller practices, because they were sold on a polished demo. Software chosen for its demo rather than its fit with your firm’s size, practice areas and workflows is one of the most expensive mistakes a firm can make.
How did the strongest law firms respond?
The strongest firms slowed down to speed up. They fixed the foundation first:
- They mapped their workflows and audited their operations and tech stack.
- They cleaned up their data and made full use of the tools they already had.
- They built a legal technology roadmap so AI and other technology went in, in a logical order, with a budget and clear measures of success.
- They invested in change management, which is where most technology projects actually succeed or fail.
A law firm technology audit is the fastest way to see where your firm’s foundation stands before you add anything new.
Which regulatory changes are having the biggest impact on law firms?
Law society guidance on generative AI
From an operations point of view, the biggest change is law society guidance on generative AI. Nearly every Canadian law society has now published it, including the Law Society of BC, the Law Society of Alberta, the Law Society of Ontario, the Barreau du Quebec and the law societies of Saskatchewan, Manitoba and Nova Scotia (the Canadian Bar Association keeps a full list). In the US, ABA Formal Opinion 512 applies the same core duties to generative AI: competence, confidentiality, client communication, supervision and reasonable fees.
Most of the discussion focuses on individual lawyers’ duties. The part that gets less attention is what the guidance means for how your firm runs day to day:
- Who approves AI tools?
- How is staff use supervised?
- Where does client information actually go?
- What has to be in place in your systems before AI can be used safely?
This is a firm-level obligation, not just a personal one. ABA Formal Opinion 512 says managerial lawyers must establish clear policies on the firm’s permitted use of generative AI and make sure lawyers and staff are trained on it. The firms handling this well treat the guidance as a starting point and write firm AI policies that are more specific than the regulator requires.
Data residency and cross-border processing
Nearly every firm I talk to wants its data to stay in Canada, but much of today’s AI, including a lot of legal-specific software, processes data outside the country. Here is what the rules actually say:
- No Canadian private-sector privacy law bans it. Under PIPEDA, transferring personal information to a service provider outside Canada for processing is allowed. Your firm stays accountable for it, must use contracts or other means to get a comparable level of protection, and must tell clients their information may be processed in another country and accessed by that country’s courts, law enforcement and national security authorities (Office of the Privacy Commissioner of Canada).
- BC: BC PIPA has no data residency requirement for private-sector organizations. The Law Society of BC cloud computing guidelines say that if your client records will be stored outside British Columbia, you should tell the client so they can decide whether to use you, ideally with their consent recorded in a written retainer. Your provider also has to let you meet the Law Society’s records and audit requirements; the Law Society of BC cloud computing checklist sets those out.
- Alberta: under PIPA, a firm that uses a service provider outside Canada must name the countries and purposes in its privacy policies and notify individuals how to get that information and who can answer their questions (Government of Alberta).
- Quebec: section 17 of the Quebec private-sector privacy act, as amended by Law 25, requires a privacy impact assessment before personal information leaves Quebec, and a written agreement with the recipient.
- United States: ABA Formal Opinion 512 requires informed client consent before client information goes into a self-learning generative AI tool, and says boilerplate language in an engagement letter is not enough.
The practical impact: your firm needs to know exactly where its data goes, update its engagement letters, and make that choice deliberately instead of guessing.
Rules firms misunderstand
A lot of the friction I see comes from rules firms misunderstand rather than the rules themselves. I still meet firms with rooms full of file boxes because they believe their law society requires paper copies of everything. It doesn’t. Law societies allow electronic records. Ontario’s By-Law 9 lets firms keep financial records electronically as long as they can produce a paper copy promptly on request, and the Law Society of BC’s cloud checklist spells out the standards electronic records must meet. Trust accounting and reporting deadlines are another area where clean processes and the right software make compliance much less painful.
How are leading law firms using AI and managing its risks?
Start with the shadow AI you already have
The first risk most firms don’t realize they have is shadow AI. I can’t tell you how many firms I’ve worked with where everyone on the team is using a different free AI tool, often on a personal account, and pasting sensitive client information into it. It’s not compliant, it’s not safe and it’s not secure.
The other extreme is firms that are so afraid that they ban it, and people use it anyway. Neither works.
Take the practical middle path
- Take an inventory of what’s already being used.
- Write a short, clear AI policy.
- Choose approved, secure AI tools and check each one’s terms, data location and retention against your obligations.
- Train people on how to use them.
- Keep a human in the loop on anything that touches a client.
- Be transparent with clients about how AI is used, and know where your data is stored.
Put AI where it removes the worst parts of the job
AI doesn’t need to replace jobs. It should replace the worst parts of people’s jobs so they can do higher-value work. The best uses are back-end and administrative: intake, reminders, document organization, first drafts and summaries.
Clients pay lawyers for their judgement and expertise, not for regurgitated AI output.
AI is still wrong a lot of the time. A Stanford study cited in ABA Formal Opinion 512 found that leading legal research AI tools hallucinated between 17% and 33% of the time. Everything AI produces needs a careful review.
Measure it
Leading firms measure it. Before they roll anything out, they capture a baseline, even if it’s just time-tracking data on how long certain tasks take, and then compare it afterwards. That’s the only way to know whether a tool is paying for itself or just adding another subscription and another headache.
Why are law firms struggling to attract and retain talent?
A lot of talent problems are really process and technology problems. Lawyers and staff burn out on administrative grind: re-entering the same information in multiple systems, chasing documents and working around clunky software.
Frontline staff often build their own workarounds that partners don’t even know exist. When systems are frustrating, people stop using them and go back to the old way, and that frustration adds up to burnout and turnover.
Culture matters more than age
There’s a generational piece, but it isn’t as simple as “young lawyers are tech-savvy.” Many newer lawyers didn’t learn practice technology in school and then joined firms that didn’t use much of it. Some firms are run by younger lawyers who want to be cutting edge. Others are more traditional, and long-time partners resist new tools even when younger associates are keen.
How leading firms keep their people
- Use technology and AI to take the worst parts of the job off people’s plates.
- Document processes so new hires get up to speed quickly and consistently.
- Train by role, so people only learn what they actually need.
- Keep training ongoing: an initial session, then follow-ups a couple of weeks and a month or two later, once people have real questions.
- Ask frontline people where the pain points are, and act on what they hear.
- Before hiring to cover a gap, check whether the gap is actually a process problem.
For the people side of an AI rollout, see organizational readiness for AI.
What sets top-performing law firms apart?
The firms that consistently perform at the highest level run their practice like a business. Lawyers are trained to be excellent at law, but running a modern firm also takes operations, technology, cybersecurity, finance and client experience. The top firms accept that and invest in it proactively, instead of waiting until everything’s on fire.
- Documented processes, so the firm doesn’t depend on one person doing things their way.
- A technology roadmap tied to their three- to five-year goals, reviewed at least once a year.
- A lean tech stack, as small as it can be while still doing everything they need, with full value taken from the tools they already have instead of chasing the next shiny thing.
- Decisions made with data, using the KPIs every law firm should track.
- Discipline on the basics that quietly drain revenue. I’ve seen firms sitting on millions of dollars in receivables simply because nobody had a process to follow up on unpaid invoices. More on that in law firm billing efficiency.
Change management is the multiplier
The best firms take change management seriously. They line up champions, train their people properly and get buy-in before a rollout, so new systems actually get used.
Technology amplifies whatever processes you already have. The top performers make sure they’re amplifying good ones.
How can law firms improve access to justice?
Access to justice isn’t separate from operational excellence. It depends on the same things that make a firm run well: clear intake, good systems and timely communication. A lot of people never get help because their first call isn’t returned or falls through the cracks of a manual intake process.
Turn efficiency into capacity
When firms use automation and AI well, for intake, document automation and administrative work, they free up capacity. That efficiency lowers the cost of delivering some services and lets firms take on more pro bono and lower-cost matters. The point is to expand the help your firm offers, not just cut the hours spent on it. Fixing client intake and onboarding is the place to start.
The human side matters as much as the systems
Firms should keep building partnerships with community organizations, clinics and nonprofits, and train lawyers and support staff in trauma-informed and cross-cultural communication. Many people seeking help face barriers that are very different from those of a typical paying client.
FAQ: challenges facing law firms
What are the biggest challenges facing law firms in 2026?
The defining challenge is AI pressure colliding with years of underinvestment in operations and technology: undocumented processes, disconnected systems and partly set up practice management software. Close behind are law society rules on generative AI, privacy and cross-border data obligations, shadow AI, and staff burnout caused by poor processes.
How is AI changing law firms?
AI is exposing weak operations. Firms that add AI to broken processes scale their problems. Firms that fix workflows and data first use AI for back-end and administrative work such as intake, reminders, document organization, first drafts and summaries, with a human reviewing anything that touches a client.
Do law societies allow lawyers to use generative AI?
Yes. Law societies across Canada, including those in BC, Alberta and Ontario, have published generative AI guidance, and in the US the ABA issued Formal Opinion 512. They allow its use subject to existing duties of competence, confidentiality, supervision, client communication and reasonable fees.
Can Canadian law firms store client data outside Canada?
Yes. No Canadian private-sector privacy law prohibits it, but the firm stays accountable. PIPEDA requires comparable protection by contract and telling clients their data may be processed abroad. Alberta’s PIPA requires notice and policies naming the countries involved, Quebec requires a privacy impact assessment and written agreement, and the Law Society of BC advises telling clients when records are stored outside BC, ideally with written consent in the retainer.
What is shadow AI in a law firm?
Shadow AI is staff using unapproved AI tools, often free tools on personal accounts, for firm work, sometimes pasting in confidential client information. It isn’t compliant or secure. The fix is an inventory of what is in use, a short AI policy, approved tools and training, not an outright ban.
How do you measure the ROI of AI in a law firm?
Capture a baseline before rollout, even if it’s just time-tracking data on how long specific tasks take, then compare the same measures afterwards. Without a baseline there is nothing to measure against, and no way to tell whether a tool is paying for itself.
Why do law firms struggle to retain staff?
Much of it is process and technology. Lawyers and staff burn out re-entering data in multiple systems, chasing documents and working around clunky software. Firms that document processes, train by role with ongoing follow-ups, and use technology to remove administrative grind keep their people longer.
What makes a law firm successful?
Top-performing firms run their practice like a business: documented processes, a technology roadmap tied to three- to five-year goals, a lean tech stack used to its full value, KPIs, discipline on receivables and billing, and serious change management.
Fix the foundation before you add AI
We’re vendor-neutral consultants who have worked with over 70 law firms on technology, operations, practice management and AI readiness, across Canada and the United States. We help your firm fix the foundation first, then bring in AI in a logical order with clear measures of success.
Ready to see where your firm stands?
Explore law firm technology audits
This article is general information, not legal advice. Rules cited are current as of October 2026.
