In March 2026, Aderant launched AI-powered employee performance reviews, sentiment analysis, and auto-summarization inside its viEval and viAllocate products — the first client-facing AI features in the vi by Aderant people-management line. If your firm runs reviews on vi by Aderant, or is weighing it against other options, this guide explains what the new tools actually do in plain terms, where they help most, and the practical questions worth asking before assuming AI changes your review process. The aim is to help you evaluate the technology clearly — not to oversell it or dismiss it.
A Quick Primer: The Two Kinds of Reviews This Affects
Before looking at the features, it helps to separate the two directions feedback flows in a law firm, because AI affects them very differently.
- Downward reviews — a partner evaluating an associate. This is the familiar, top-down review most firms already run.
- Upward reviews — associates giving feedback on the partners who supervise them. These are confidential by design, because the person giving feedback is commenting on someone who controls their assignments, bonus, and path to partnership.
Keep both in mind as you read. Most of vi by Aderant's new AI features are aimed at the first kind. The second kind has a different bottleneck, which we'll come back to.
What vi by Aderant Actually Launched in 2026
According to Aderant's official announcement on March 18, 2026, the update adds three AI capabilities to the vi by Aderant evaluation suite. Here's what each one does, in practical terms:
1. AI-powered performance evaluations. The AI helps reviewers write and review evaluations that meet the firm's standards, and surfaces structured insights from the feedback. In everyday terms: it helps partners produce more consistent, complete evaluations across a review cycle, rather than quality varying widely from one reviewer to the next.
2. Real-time sentiment analysis. As an evaluator types, the AI reads the tone and wording and flags anything that looks unclear, inconsistent, or mismatched (for example, harsh language paired with a high rating). Think of it as a spell-checker, but for the balance and clarity of feedback — nudging the reviewer to fix issues before the review is finalized.
3. Auto-summarization. The AI produces short summaries of evaluations so firm leaders can quickly grasp the main themes without reading every full review. For a practice group leader working through dozens of evaluations, that's a meaningful time saving.
Aderant describes these as the first client-facing AI features in this product line, built directly into the existing viEval and viAllocate workflows. The common thread is efficiency and consistency: less time spent drafting and revising, and more uniform evaluations across the firm.
Why Performance Reviews Are Under the Spotlight in 2026
To understand why a feature update like this matters, it helps to see the pressure firms are under. The cost of losing talent has risen sharply, and reviews are one of the few tools a firm directly controls to address it.
BigHand's 2025 "Navigating the Million Dollar Problem" report, based on responses from more than 800 senior law firm leaders, found that firm-wide lawyer attrition reached 27%, and that replacing a single third-year associate now costs more than $1 million once lost billable revenue, recruitment, and training are added up.
The timing of departures is the part that should catch a firm's attention. The NALP Foundation's Update on Associate Attrition for 2025, released in April 2026 and covering 141 US and Canadian firms, found that 83% of associates who left in 2025 did so within five years of being hired — a record high, up from 80% the year before. Overall associate attrition was 19%, rising to 24% at firms with 100 or fewer attorneys.
In short, most attrition happens early — in the exact group a firm has spent the most to recruit and train. Good review data — feedback that's specific, honest, and acted on — is one of the clearest ways to spot and address the causes while there's still time. That's a useful lens for any new review feature: does it help the feedback become more useful, and more honest?
Curious how a review program built only for US law firms compares to general software? Survey Research Associates (SRA) designs and runs performance reviews exclusively for law firms. → srahq.com/services
What AI Helps With — and What It Can't Change on Its Own
This is the most useful distinction to understand, so it's worth slowing down on. AI in performance reviews is genuinely good at some things and, by its nature, unable to fix others.
Where AI clearly helps: the work of writing and digesting reviews
For downward reviews, the new tools address real, everyday frustrations. Writing thoughtful evaluations takes partners hours they don't have. Quality varies from one reviewer to the next. Leaders drown in long documents at calibration time. AI writing support, consistency checks, and summaries ease all three. If your firm's pain point is the administrative load of reviews, this is a sensible, helpful upgrade.
Where AI runs into a limit: getting people to be honest
Here's the part that's easy to miss. AI can draft, score, and summarize feedback — but it can only work with the feedback that's actually written down. It can't make someone more candid than they chose to be.
This matters most for upward reviews. When associates give feedback on partners, the thing that determines the value of the data isn't tone or formatting — it's whether the associate felt safe enough to be honest. And that sense of safety comes from one thing above all: where the raw responses are stored, and who can see them.
Picture it from the associate's side. If the upward-review data sits inside a system the firm runs, a reasonable associate assumes someone at the firm could, in principle, trace a comment back to them. So they soften it. The feedback comes out diplomatic and vague. AI sentiment analysis will then analyze that softened feedback perfectly well — and produce a tidy, confident summary of what is, underneath, a guarded answer. The output looks polished; the honesty was already lost before the AI ever saw it.
💡 Key Insight: AI improves how feedback is written, scored, and summarized. It doesn't change whether people feel safe enough to be honest in the first place. For upward reviews especially, candor depends on where the raw data is held — which is a question of how the program is set up, not which AI features it has.
A Practical Way to Evaluate Any AI Review Feature
If your firm is weighing vi by Aderant's AI tools — or any AI-assisted review feature — these four questions help separate what the technology can and can't do for you:
- What problem are you actually solving? If it's the time and effort of writing reviews, AI helps a lot. If it's getting honest upward feedback, the setup of the program matters more than the AI.
- Where does each type of data live? Downward reviews can sit in firm systems with little downside. Upward reviews need stronger confidentiality if you want them to be truthful.
- What's the participation rate? This is a useful honesty signal. As a rough guide, below 60% participation at a law firm suggests associates don't fully trust the process; above 75% suggests they do. Ask any vendor for their real numbers.
- Are youmeasuring efficiency or accuracy? AI reliably improves efficiency and consistency. Improving the accuracy of feedback that was guarded to begin with is a separate problem.
Working through these is genuinely useful no matter which tools you choose — because AI features and program design solve different problems, and the clearest-eyed firms evaluate them separately.
How This Fits the Bigger Picture of Legal Performance Management
vi by Aderant's update is part of a broader shift: AI is being woven into nearly every legal software category, and performance management is no exception. A calm way to read these announcements is neither hype nor dismissal, but a simple sorting question — is this making a task faster, or is it changing what's actually possible?
vi by Aderant's 2026 features mostly do the former, and do it well: they make writing and digesting reviews faster and more consistent. The thing they don't change — because no AI feature can — is whether associates trust the process enough to tell the truth in upward reviews. That comes down to how the program is designed and where the data is kept.
This is also the line between a software model and a managed-service model. vi by Aderant is legal-built software your firm configures and runs, now with AI assistance layered in. Survey Research Associates (SRA) takes a different approach: it's a managed service that designs and runs the reviews for the firm and holds the raw upward-review responses externally, never inside the firm's systems — the setup that tends to produce more honest answers. The two models suit different needs, and many firms find it helpful to understand both before deciding. For a side-by-side look, see SRA vs vi by Aderant: Which Fits Your US Law Firm? (2026).
Want upward reviews your associates will actually answer honestly? Survey Research Associates (SRA) has designed confidential upward reviews exclusively for US law firms since 1987. → Talk to SRA: srahq.com/contact | Upward Reviews: srahq.com/services#upward
Frequently Asked Questions
What AI features did vi by Aderant launch in 2026?
In March 2026, vi by Aderant added AI-powered employee performance evaluations, real-time sentiment analysis, and auto-summarization within viEval and viAllocate, according to Aderant's announcement. Aderant describes these as the first client-facing AI features in its people-management product line, all focused on making attorney evaluations more consistent, clearer, and faster to digest.
Can AI sentiment analysis improve law firm performance reviews?
Yes, in a specific way: it can flag unclear, harsh, or inconsistent language as a reviewer writes, and help summarize tone across many reviews. What it can't do is make someone more honest than they chose to be. Sentiment analysis reads the feedback that's actually written, so if an associate softened their upward feedback because the data lives in firm systems, the analysis will reflect that softened version — neatly summarized, but no more candid.
Does AI fix the upward feedback problem at US law firms?
Not on its own. The main challenge with upward feedback is candor — whether associates trust that their comments about supervising partners are truly confidential. That trust depends on how the program is set up and where the raw data is held, not on the AI features. AI improves how feedback is processed; it doesn't determine whether the feedback was honest to begin with.
Is vi by Aderant's AI worth it for a law firm?
For firms that want legal-built evaluation software and feel the administrative strain of writing and synthesizing reviews, the 2026 AI features are a genuine, practical upgrade — especially for downward reviews. For confidential upward feedback specifically, the more important factor is the program model: software your firm runs versus a managed service that holds data externally. A good rule of thumb is to evaluate the AI for efficiency and the model for honesty, separately.
What's the difference between performance software and a managed review service?
Performance software is a platform your HR or talent team configures, runs, and analyzes — you control it, and the data lives in your systems. A managed service designs, runs, and analyzes the reviews for you and holds the raw data externally. Software offers control and is well suited to downward reviews; a managed service is often chosen when confidential upward feedback and higher participation are the priority.
How much does associate attrition cost a US law firm?
BigHand's 2025 research estimates that replacing a third-year associate now exceeds $1 million once lost billable revenue, recruitment, and training are included. Because most departures happen early — 83% within five years of hire, per the NALP Foundation's 2025 data — the cost falls hardest on the group a firm has invested the most in developing.
Survey Research Associates (SRA) has designed and run confidential performance reviews exclusively for US law firms since 1987 — upward reviews, 360-degree feedback, engagement surveys, and exit surveys, with all raw data held externally.
→ See our services: srahq.com/services | Start a conversation: srahq.com/contact
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