The Deals You've Been Saying No To

A legal ops leader at a major energy company mentioned two deals his team had worked on. A toll road refinancing in an emerging market. A bond transaction in a country that most transactional practices wouldn't staff for. Neither would have been economical the traditional way. Too many jurisdictions, too much overhead, too thin a margin. AI changed the math. Both got done.

Most transactional practices are still asking how AI can help them do existing work faster. The more interesting question is what deals become possible that weren't before.

The efficiency pitch has a problem

There's a question that keeps coming up in conversations with firm leadership. If AI makes lawyers faster, and faster means fewer billable hours, where does the revenue come from?

It's a fair question. Even at firms that have deployed AI across hundreds of deals, the billing question doesn't have a clean answer. Some of the most AI-forward practices in the country have reached near-total internal adoption and still can't clearly point to the bottom-line impact.

This is what happens when efficiency is the whole story. Firms adopt the tools, the work gets done faster, and nobody has connected that speed to what comes next. More capacity. New deal types. Transactions that weren't viable before.

Efficiency isn't the wrong goal. It's the incomplete one.

What new revenue actually looks like

Every transactional practice has a category of work it avoids. Not because the lawyers couldn't handle it, but because the math never worked.

• Multi-jurisdictional transactions with unfamiliar disclosure rules and local counsel coordination, where overhead eats whatever margin existed.

• Mid-market deals where a full diligence workstream would cost more than the transaction warranted. You'd scope it down or turn it away.

• Emerging growth clients who need real transactional support but can't sustain traditional billing rates. You'd refer them out and hope they came back when they were bigger.

AI doesn't change what's legally possible in any of those situations. It changes what's economically viable. The overhead compresses. The time per instrument drops. Mandates that sat just below the threshold of profitability cross it.

The same pattern plays out on the client side. Firms have been able to offer more thorough diligence on venture financing transactions that previously couldn't support a full workstream. Not because the deals became less complex, but because the cost of doing them well came down enough to make them viable.

The deals that should have been done properly now are.

What this looks like for your firm

The firms moving fastest on this aren't the ones with the biggest innovation budgets. They're the ones who have sat down and asked an honest question. What deals are we turning away, or running at thin margins, because the staffing math doesn't work?

That question looks different at a 10-lawyer transactional practice than it does at an AmLaw 100 firm. Which is exactly why it's worth asking.

Map the below-waterline work

Above the waterline are judgment, client relationships, and deal strategy. The work that justifies your rates. Below it is everything mechanical. Data room review, first drafts, closing condition tracking, and cap table reconciliation. AI belongs below the waterline. Your lawyers belong above it.

Test with a real deal

The firms making progress didn't start with a policy or a pilot programme. They picked one workflow, ran it with AI, and measured what changed. One transaction. Real numbers.

Where August fits 

Most of the firms we work with come with a specific problem. A deal type that wasn't profitable to staff. An emerging growth client segment that they kept referring out. A geography that never made financial sense to pursue.

August is built for transactional teams at mid-market and growing firms. The ones who need something that works inside their existing practice, not a platform that requires rebuilding around it. Due diligence, document review, redlines, matter knowledge, embedded in Word and Outlook, not bolted on as a separate tool. Firms using August configure it to their own standards and playbooks, so the output reflects their practice, not a generic template. Single-tenant, zero training on customer data, ISO 27001 certified.

At August, we're building AI purpose-built for transactional teams. If you're thinking about the deals sitting just outside your current economics, let's talk.