HomeFeaturesExecutive Viewpoint 2018 Prediction: Agiloft

Executive Viewpoint 2018 Prediction: Agiloft

Security and Contract Management

“With the continued rise of data breaches this year, organizations will increase security measures in 2018, including contract management security, because all contracts are information sensitive and sometimes even the existence of the contract is confidential. The current best practice for ensuring contracts are sent and signed through secure means is digital encryption with a nonmalleable algorithm (preventing the document from being tampered with). However, encryption algorithms continue to be in an arms race with computing power, so that documents encrypted just a few years ago are now potentially hackable, and copies of the encrypted documents that have been sent through third-party servers may exist somewhere and can be retrieved and cracked after all these years. Although quantum computing will likely not advance beyond the research phase in 2018, if and when it becomes practical, it will make all currently public key encryption methods ineffective.  On the positive side, quantum computing also promises new tampering detection tools.”

Legal Firms Seek Automation Tools

“Legal departments and organizations have been using automation for some time, and that is going to increase in 2018. Governmental compliance requirements will continue to be strengthened and the costs of non-compliance will increase. The EU’s new GDPR initiative, which goes into effect in 2018, is salient example of the new security requirements, but it is just the beginning. Tools that can document and validate processes against evolving regulations and support compliance will be in demand, especially for contracts, in 2018. “

Machine Learning to Impact Contract Generation

“There is potentially a huge market for machine learning in contract generation, and it will be exciting to see how it grows in 2018. It represents a way to reduce legal costs for contract reviews and to ensure more consistency in contracts.

Companies have a lot of contracts that start similarly, using content from a template or existing contract with minor edits or adaptations. Companies with a large set of contracts to use for the learning process hold real potential for machine learning in contract generation. There will be a considerable amount of manual intervention at first as a lawyer or paralegal helps train the system, but that will taper off as the computer is able to identify “matches” between contract clauses and suggest changes.”