A Six-Lawyer Firm Replaced an Associate With AI. Costs Dropped 27%. Profits Rose. Here Is the Playbook. A Six-Lawyer Firm Replaced an Associate With AI. Costs Dropped 27%. Profits Rose. Here Is the Playbook.

Two weeks ago, we wrote about Baker McKenzie cutting 700+ staff and calling it an AI strategy. We argued that swapping headcount for software licenses is not legal engineering. It is cost-cutting in innovation clothing.

This week, Above the Law published a story that shows what the alternative actually looks like in practice, and the numbers are hard to argue with.

Ad Astra Law Group is a six-lawyer litigation firm in San Francisco. When an eighth-year associate left for another opportunity, managing partner Katy Young faced a decision every small firm leader knows well: absorb the cost and risk of recruiting, hiring, and training a replacement, or find another way to keep the team performing at the same level. Ad Astra chose the second path. They leaned into AI-assisted workflows, partnering with litigation drafting platform Legion to augment their remaining team's capacity.

The results were striking. Staffing costs dropped 27 percent. Profits increased. And perhaps most counterintuitively, the firm billed fewer hours while producing better work product.

The Counterintuitive Economics of AI-Augmented Practice

The billing math is the part that trips people up, so it is worth walking through.

Young described the shift in concrete terms: a complaint that previously took two full days to draft now takes roughly two and a half hours. On a pure hours-billed basis, that looks like a revenue loss. You are billing two and a half hours instead of eight.

But that analysis misses the full picture. When you remove a six-figure associate salary from your cost structure and replace it with an AI tool subscription, the margin on those fewer hours is dramatically higher. Meanwhile, the attorneys freed from grinding through first drafts can redirect their time toward higher-value activities: strategy, client development, and taking on additional matters the firm previously lacked bandwidth to handle.

This is the economic model we have been describing as legal engineering. Not technology for technology's sake, but the deliberate redesign of how legal services are delivered so that efficiency gains translate into better outcomes for both the firm and its clients.

Better Work, Not Just Faster Work

The quality dimension of Ad Astra's experience is arguably more significant than the cost savings.

Young reported that the time savings translate directly into more thorough filings produced under tight deadlines. When a 45-page complaint can be produced in hours rather than days, it changes the strategic calculus of pre-litigation positioning. Opposing counsel receives a filing that signals serious investment and preparation from day one, improving early settlement leverage and case outcomes.

This point cannot be overstated. The value proposition of AI in legal practice is not "the same work, cheaper." It is "better work, delivered faster, at a sustainable cost." That distinction matters enormously for small firms competing against larger shops with deeper benches.

Why This Matters More for Small Firms Than BigLaw

The Above the Law piece rightly notes that most legal AI coverage focuses on BigLaw, where firms have the resources to build expensive internal AI capabilities and the headcount-heavy models that are most visibly disrupted. But the Ad Astra story illustrates something we have been saying for over a year: AI creates the most transformative opportunity for boutique and midsize firms.

Consider the structural dynamics. A global firm with 5,000 lawyers faces an enormous change management challenge when integrating AI into workflows. There are practice group politics, partnership compensation models built around billable hours, and institutional inertia that can stall adoption for years.

A six-lawyer firm can make a decision over lunch and implement it by Friday.

The 2026 Thomson Reuters/Georgetown State of the Legal Market report confirmed this advantage quantitatively. Midsize firms surged to nearly 5 percent demand growth in the second half of 2025 while the Am Law 100 struggled to break 2 percent. Rate increases at the top are pushing work downstream, and firms that can deliver partner-level attention with AI-enhanced capability at competitive rates are capturing that mobile demand.

The Right Mindset: AI as a Junior Associate, Not a Magic Wand

The Above the Law article offered one of the more practical frameworks for thinking about AI adoption we have seen. The legal profession has spent years stuck in a binary debate: will AI completely replace lawyers, or is it useless? The answer is obviously neither.

The most effective approach treats AI the way a senior attorney would treat a junior associate. You would never hand a second-year a complex motion and walk away for a week. You give clear direction, review the output carefully, provide substantive edits, and iterate. AI works the same way. It solves what practitioners call "the blank page problem," producing a workable first draft that an experienced attorney can then refine with professional judgment and strategic thinking.

Firms that approach AI with that disciplined supervision mindset discover a powerful productivity tool. Firms that treat it as an autopilot end up with the kind of sanctionable work product that makes headlines for the wrong reasons.

The Playbook for Small Firm Leaders

Ad Astra's experience distills into a practical framework that any small or midsize firm can adapt.

Start with attrition, not layoffs. Ad Astra did not fire anyone. An associate left, and rather than reflexively replacing the position, they asked whether AI could help the remaining team absorb the work. That is a fundamentally different approach from Baker McKenzie's 700-person headcount reduction, and it produced a fundamentally different outcome.

Choose tools that solve specific workflow problems. Ad Astra's partnership with Legion targeted litigation drafting, specifically the time-intensive first-draft stage where AI provides the highest ROI. They did not try to automate everything at once. They identified their biggest bottleneck and addressed it.

Measure what matters. Costs down 27 percent and profits up is a clean story because Ad Astra tracked the right metrics. Firms considering AI integration should establish baselines for time-per-task, cost-per-matter, and client outcomes before adoption so they can quantify the impact.

Rethink pricing around efficiency. If your AI investments make you faster but you are still billing hourly with no adjustment, you are either padding hours or leaving money on the table. Fixed-fee and value-based pricing models align the firm's efficiency gains with client expectations and turn AI productivity into a genuine competitive advantage.

Invest in governance. With ABA Formal Opinion 512 establishing ethical requirements for AI competency, the EU AI Act taking full effect for high-risk systems later this year, and state-level regulations expanding, AI governance is a compliance obligation. Small firms that build governance frameworks now will avoid scrambling when regulatory scrutiny intensifies.

Key Takeaways

• A six-lawyer San Francisco firm cut staffing costs 27% and increased profits by using AI to absorb a departing associate's workload rather than hiring a replacement.
• The economic model works because margin improvement outweighs reduced billings. Fewer hours billed at dramatically lower overhead produces stronger profitability, especially when attorneys redirect freed capacity to higher-value work.
• Quality improved alongside efficiency. AI-assisted drafting produced more thorough filings under tight deadlines, improving strategic positioning in pre-litigation negotiations.
• Small firms have structural advantages in AI adoption over BigLaw: faster decision-making, fewer institutional barriers, and business models that can more readily absorb the shift from volume to value.
• The right mindset treats AI like a junior associate, not an autopilot. Disciplined supervision and professional judgment remain non-negotiable.

The Bottom Line

The Baker McKenzie story and the Ad Astra story arrived two weeks apart, and together they tell the complete narrative of where legal practice is heading. One shows what happens when a megafirm uses AI as a blunt instrument to reduce headcount. The other shows what happens when a small firm uses AI as a precision tool to amplify the team it already has.

We know which model we are building at FinTech Law. An AI-native practice where technology is not bolted onto legacy workflows but designed into the foundation. Fixed-fee pricing that passes efficiency gains through to clients. A service model where every attorney is supported by AI infrastructure purpose-built for the work we do.

The firms that will define this next era are not the biggest. They are the ones that understood, early enough, that legal engineering is about people and process first, technology second.

If your firm is exploring how AI can strengthen your practice without sacrificing quality or professional responsibility, we would welcome that conversation.