How Morgan & Morgan boosted earnings by $2B with genAI document processing

The Challenge

7,000+ lawyers. More cases than any other law firm in the country. Morgan & Morgan isn’t just big — it’s a legal juggernaut. But even giants can stumble in the wake of seismic shifts.

As the digital age swept through every sector — including legal services — Morgan & Morgan faced a stark choice: innovate or suffocate. To stay competitive and scale their lines of business, they would require a fast-acting technical team that could digitally advance key components of their operations. 

Morgan & Morgan's massive size and scale — typically their trump card — threatened to hobble the technical transformation. They faced unique technological challenges around enhancing claim management systems, using accumulated case valuation data more efficiently, and upgrading their knowledge management system. 

The transformation didn’t require simple technical expertise. Morgan & Morgan also needed a level of agility that could work within their existing framework to deliver timely results. In other words, they needed to turn a legal behemoth into a nimble tech innovator.

After evaluating Morgan & Morgan’s technical infrastructure, A.Team put together a flexible, agile team of product builders to tackle the mission. Other freelancer/fractional talent platforms were “very hit and miss,” according to Yath I., Morgan & Morgan’s Head of Innovation.

But not A.Team, who struck the right balance of expertise and speed. No bloated departments or endless onboarding. No scores of ill-equipped candidates to sort through. Just elite product builders, ready to hit the ground running. 

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The Build

These A.Team product builders embedded directly under Morgan & Morgan's CTO and Head of Engineering, bringing Silicon Valley-level technical expertise to the heart of the traditional legal world. They planned to deliver the same quality and dedication as full-time staff, without any of the overhead or slow ramp ups characteristic of full-time hires. 

A.Team’s model would be Morgan & Morgan’s lean, results-oriented solution. The firm needed small operational units that could get up to speed quickly but not stay around any longer than required: “We needed small flexible teams that could go in, solve a problem, and come out,” said Yath.

Deep Learning engineers used AI to optimize the efficiency of legal case analyses by identifying similar legal matters, and using ML models to predict the potential outcomes of ongoing legal matters. That process involved the development of innovative weighting logic for each case component. 

Other ML engineers focused on the time-consuming process of manually classifying, summarizing, and extracting entities from their massive trove of legal documents. These engineers worked to build NLP models for document classification, summarization, and entity extraction, using expertise in deep learning, Python, AI, and PyTorch. 

After an initial sprint and successful product delivery, Yath realized he needed even more support. Luckily that wasn’t a problem. Morgan & Morgan scaled from four to nine A.Team builders, enhancing their powerhouse team with skilled data scientists, front-end developers, and back-end developers. 

The goal was clear: overcome technical hurdles, work within a tight deadline, and ultimately transform the firm's business processes to enable more efficient work and outcompete newer, more agile competitors. 

Outcomes

Without A.Team, Morgan & Morgan would have had difficulty recruiting the technical talent they needed. Yath admitted, “We have a hard time competing with Google and other tech giants for great teams.” With A.Team, Morgan & Morgan could sidestep the traditional hiring process and skip straight to having in-house experts.

Over the course of their project, the A.Team developed a client portal, established a machine learning model for case valuation, created a centralized knowledge platform, revamped the overall customer experience, and delivered a holistic digital-native user experience. 

Through their Deep Learning initiative, A.Team’s engineers drastically reduced document processing time. For 100 million documents over 27 different categories, they achieved a 98.7% document processing accuracy. This new efficiency meant the firm could handle more cases and drive major business growth. 

The case valuation model led to fairer outcomes for clients while optimizing the firm's resources. Attorneys could shift their focus onto cases with the highest potential return, while reducing uncertainty around the complexities of various legal matters. 

Externally, the new client portal meant clients could track their cases in real-time, which significantly reduced anxiety-inducing phone calls.

Morgan & Morgan started to feel like a legal powerhouse with the heart of a tech startup. Efficient, polished, modern, and ready for the digital age. The overall digital improvements in infrastructure slashed case processing times, allowing the firm to take on more clients without expanding staff. In other words, the makeover was critical for keeping Morgan & Morgan efficient as new Legal Services players entered the arena.

In under three years, Morgan & Morgan saw a $2B increase in earnings won for clients, from $13B to $15B. They managed 70k cases in one year, all while handling 5,000 calls per day in offices across the country.

The success of their initial A.Team was so impactful, it led Morgan & Morgan to integrate several more A.Teams, with the expectation of further collaboration on the horizon.

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