“Sagging productivity and declining realization have combined to put a pinch on law firm profitability growth such that even the high pace of rate growth has been largely unable to remedy the situation,” wrote the authors of the 2024 Report on the State of the U.S. Legal Market (Thomson Reuters and Georgetown Law).
Like every other sector, the legal industry is undergoing transformation from global recession pressures, AI and high overhead. Firms are working to diversify and cope with competition from growing cadres of freelance lawyers.
Fortunately, there is some relief on the horizon from AI and automation, which promise to take some heat off the time spent doing undifferentiating tasks such as billing, document review and research. Legal unstructured data management is another tactic, to right-place data and deliver cost savings on data storage and backups. The global legal technology market, projected to grow at a rate of 37% over the next several years, is a sign of this growing trend.
IT and Data Challenges
Law firms and legal departments are document heavy. IT organizations report an average 20% annual growth in storage for file-related data, resulting in the need to add expensive on-premises storage capacity every year or two. To make matters worse, most firms do not delete data. After all, cases can be reopened after decades. Therefore, managing costs is difficult. In some cases, law firms are moving data to the cloud – although cost savings aren’t guaranteed there either.
Secondly, in recent years law firms have been lucrative targets for ransomware actors and other cyber criminals, given the amount of sensitive, personal data they retain. Meanwhile, law firms would like to take advantage of AI to be more efficient and reduce operational overhead. Innovation in the sector is attracting big dollars: startup Harvey announced a $100 million Series C round in July. Yet that opens another can of worms to avoid exposing sensitive client data into AI tools.
How Unstructured Data Management Helps
A strategic approach to managing file and object data can help reduce the high costs of data storage and protection while making data more useful for AI initiatives:
1. Cut costs with automated policies
By understanding data usage patterns, you can determine which data sets are no longer actively needed and could be easily archived. Better yet, by tiering data to an online archive in the cloud, legal professionals can recall that data quickly if needed to support client work. Komprise Intelligent Data Management delivers the capability to establish internal policies for different use cases, such as to tier cold data that hasn’t been touched in more than a year to secondary storage or by situation, such as when a case has been closed.
2. Avoid user disruption
Legal work can be fast-paced and urgent. IT leaders would like to avoid stressful disruptions where employees cannot find their documents after they have been moved. Because Komprise does not use stubs, agents, or other proprietary interfaces, applications and users always find their data in the same place as if it had never moved. This is valuable in an era when data is in motion more than ever before. Learn more about Komprise Transparent Move Technology (TMT). Users simply click on a Komprise Dynamic Link which seamlessly redirects to the new location.
3. Add another layer of ransomware protection
By tiering cold data to immutable cloud object storage, Komprise delivers a proactive security posture preventing ransomware actors from accessing or making any changes to data and reducing the attack surface. Also, moving data out of on-premises data centers reduces the attack surface for hackers. Learn more about ransomware cost optimization.
4. Support a safe AI journey
Komprise analysis of data across storage gives IT the insight to right-place data in the most cost-efficient storage for its current needs and easily move it to different tiers as it ages or as its value changes. This automated process can free up funds to support AI and achieve the benefit of cloud-native access to data after it has been moved –thanks to Komprise TMT. This is useful given the depth of innovation in cloud AI services, making it easier to leverage data already in the cloud. Finally, Komprise Smart Data Workflows allows IT to create automated, policy-driven processes to find, tag and move data to AI platforms and to enrich metadata tags using built-in integrations to machine learning tools such as Amazon Rekognition, Amazon Macie and Azure AI.
