Though it is challenging, having visibility into all this legal data is paramount not only for efficiency and cost-saving purposes, but more importantly, to meet regulatory demands.
We have an effective model for converting information governance requirements into a digital framework. It is called the DIRKS methodology and you’ll find it in ISO 15489 Standard for Records Management.
In one of the legal technology industry’s largest-ever funding rounds, US crowdsourced legal research platform Casetext has closed a $12m Series B funding round in order to expand the capabilities of its AI-backed automated research assistant CARA and build up its platform and business.
With the vast expanse of data streams available, Francis predicted that attorneys will be likely to start bringing new kinds of data to the table in litigation. That said, without the sophistication to do cost-effective e-discovery tools to new kinds of data, the average cost of getting through relevant data is likely to trend upward.
The right level of detail at which to analyze the potential impact of automation is that of individual activities rather than entire occupations.
Putting aside the dystopian views that sensationalize AI, bright prospects are ahead for corporations that embrace this transition to new ways of thinking. However, to make the leap, some radical adjustments in the ways of working are necessary.
The phrase “artificial intelligence” is invoked as if its meaning were self-evident, but it has always been a source of confusion and controversy.
Today, every lawyer conducting “discovery” in civil litigation needs to confront the fact that—no matter how large or small the case may be—it is insufficient to simply define the search task as being limited to finding relevant documents in traditional paper files.
In 2017, the challenge for technology providers in the legal and data discovery spaces appears to be less about defining offering requirements and validating market needs and more about developing and delivering solutions that focus on specific tasks and processes that streamline the discovery of data and the conduct of eDiscovery.
SaaS Benefit: Putting costs under operational expenses also affords companies better control of technology spending across the enterprise.