I am attending the 13th Annual Knowledge Management in the Legal Profession conference in NYC, hosted by Ark Group. This is a live post of the session Practical Magic: Using Advanced Technologies to Achieve Results. The speaker is J. Stephen Poor, Partner & Chair Emeritus, Seyfarth Shaw LLP. The session description appears at the end of this post.

Stephen Poor presenting at Ark KM 2017

This is a live blog post. I publish it as a session ends. So please forgive typos or any misunderstandings of meaning.


We were promised flying cars and personal robots 50 years ago. They have not yet delivered. Stephen says there have always been periods of hype in technology and that we are in one now. This is especially true with respect to artificial intelligence (AI). Many who talk about AI don’t know what they are talking about.

The hype makes it hard to define the value and the path forward. Stephen will share how Seyfarth has gotten beyond the hype.

The legal market has changed. Demand for law firms is flat. Alternative legal service providers take share from firms and provide an opportunity for clients to change the service mix.

We tend to think that everything lawyers do is practice law. That may be true in high-end, bespoke services. But increasingly, law is about delivering legal services, which is more than law practice. It invokes technology. And the need to change.

Cites Altman Weil survey that shows law firms think they are changing more than their clients do. And a big reason for this is that partners resist change. Plus, clients are not asking for the change – at least not directly. Clients ask indirectly by selecting lower cost options such as brining work in-house, using tech, or retaining alt providers.

Stephen is surprised that Altman Weil finds that only 49% of firms use tech to replace humans for improved efficiency. Expresses deep surprise the number is not 100%. He cites several barriers to adoption and change;

  1. Pricing structure (billable hour disincentive)
  2. Resistance to change (and it’s not just older lawyers, young lawyers too)
  3. Organizational challenges
  4. Lack of understanding
  5. Compensation structures


To work around these barriers, Seyfarth has tried to break down tech change to smaller, more modular concepts and smaller changes. This leads to the question of tech can do for legal. You need a strategy for the business – and tech should support it. Cool tech alone does not suffice.

To keep AI simple for lawyers, Seyfarth uses a chart with four levels of automation:

  1. Robotic process automation
  2. Machine learning
  3. Cognitive computing
  4. General AI


And the discussion of this progression is around specific tasks, not a general approach. This has led Seyfarth to develop several programs: SeyfarthLink, Quantum, RPA, RAVN, Ask Lee, Express Quest. The last one uses Neota Logic for intake.

RPA – robotic process automation – automates the actions of everyday users. It carries out repetitive processes, is configured by business users (no coding), scales to meet variable demand, and works within existing IT architecture with no integrations required.

Using BluePrism brand for RPA. In one uses case, a repetitive task was reduced from 24 minutes to one minute: matter intake. The process taps multiple existing firm systems to automate the multiple systems that require inputs and generate outputs (that may go into other systems).

Seemed like immigration lawyers, with big case loads, it seemed obvious RPA for intake would help. Nonetheless, much change management was required to get to automation.

The firm uses iManage (RAVN) Extract to deal with contracts to extract data. Also experimenting with it in a center of excellence for a broader contract management service (eg, around compliance). Goal is self-service for rapid deployment and scalability.

The firm is bundling multiple systems to solve bigger problems. Extract pulls out contract terms, SeyfarthLink looks like middleware that feeds it to Neota Logic for a summary document and to a BI system.

The firm has a workflow to prove the RPA concept. It tracks time savings at each stage. But much change management is required. The implementation process starts by defining automation strategy, then establishes a baseline of metrics, and then to system-wide implementation.

A key learning in all this: it’s not just the tech, you have to combine teams and tech. And the teams are not just lawyers – many disciplines involved.

Lessons Learned: Have a strategy. Shocking that this needs to be said, but it does. People are more important then ever. That’s because Tech can’t everything.

Practical Magic: Using Advanced Technologies to Achieve Results

It is increasingly difficult to determine what can be achieved by using the power of technology to enable productivity—as the hyperbole around robots, artificial intelligence, and automation often results in a bewildering mass of information.

This keynote segment will provide an analytical framework for the application of technology that will equip attendees to make quality decisions for their organizations as they look to deploy automation solutions. The objective is to share experience and lessons learned from Seyfarth’s journey into automation, which includes robotic process automation techniques, cognitive computing applications, client collaboration technology, and financial management tools using a variety of underlying applications.

J. Stephen Poor, Partner & Chair Emeritus, Seyfarth Shaw LLP