Sveriges mest populära poddar
The AI in Business Podcast
NäringslivTeknologi

AI for Enterprise Legal Departments - Contract Analysis and More

23 min•7 mars 2019

AI has numerous use cases in legal, from document search to compliance and contract abstraction. This week, we speak with Lars Mahler, Chief Science Officer for LegalSifter, about what's possible with AI for legal departments today and how AI applications for legal teams, such as natural language processing-based contract analysis, work. In addition, Mahler discusses how lawyers at companies and data scientists work together to train machine learning algorithms.

He provides some insight into how a company has to make its way into the legal space and the challenges of training an NLP system and collecting data for it.

Read more about AI in legal at Emerj.com

Fler avsnitt av The AI in Business Podcast

Visa alla avsnitt av The AI in Business Podcast
Connecting Forecasting and Warehouse Decisions at Scale - with Jerod Hamilton of Tyson Foods
•24 min
Decentralized Trials That Scale Globally Without Compliance Risks - with Emma Vitalini of Amgen
•30 min
Solving the Expertise Gap with AI in Manufacturing - with Antoine Bisson of Poka
•30 min
How Digital K‑1 Data Changes Tax Workflow Maturity - with Ken Powell and Neal Schneider
•30 min
Closing the Customer Service Gap: How AI Is Redefining Scale, Speed, and Satisfaction - with Philipp Heltewig of NiCE
•40 min
Creating a Single Source of Truth for Enterprise Legal Work - with Christo Siebrits of AbbVie
•21 min
What Global Tariff Uncertainty Means for Supply Chain Leaders - with Edmund Zagorin of Arkestro and Michael Shin of Trinity Rail Industries
•46 min
Managing Third-Party Risk at Scale Without Drowning in Surveys - with Carey Smith
•14 min
Why Enterprise AI Fails Without a Context Engine - with Eran Yahav of Tabnine
•31 min
From AI Experiments to Enterprise Value Driving Real Business ROI - with Dan Diasio of EY
•39 min

The AI in Business Podcast med Daniel Faggella finns tillgänglig på flera plattformar. Informationen på denna sida kommer från offentliga podd-flöden.