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Norton Rose Fulbright’s David Kessler, Anna Rudawski and Sam Sessler work together guiding clients through the investigation, containment, and remediation of some of the world’s most high-profile cybersecurity incident response matters. Join us as they discuss legal considerations and data and reporting challenges, while also sharing practical strategies, tools and workflows for practicing effectively in this complex area.

Legal professionals face an unprecedented volume, variety, velocity, and complexity of data. Legal AI, such as data visualization, active learning, sentiment analysis, and AI models offer tools to address these challenges - but work best in experienced and creative hands. Learn how savvy law firms are implementing innovative AI-based solutions to future-proof their practices, uncover new opportunities for revenue, and increase profitability. In this session, some of the most successful and innovative eDiscovery practice leaders discuss how with Legal AI in discovery they drive adoption, improve client results, and increase revenue.

So you implemented Microsoft 365, but have questions around how to leverage the tools to better identify risky behavior in your organization and how to work with your counterparts in IT, Info Sec, Privacy and Legal to realize these benefits.

Corporate legal teams with escalating workloads and competing business demands are increasingly looking to technology to help solve their problems. From document and e-billing to digital contracting, legaltech can help teams become more strategic and productive -- doing more with less and improving their efficiency and effectiveness across the company.

Law firms and their clients across industries are seeing a significant increase in cyber incidents. Leveraging familiar eDiscovery and Analytics tools can be an integral part of effectively responding to these incidents. However, it is imperative to understand what makes these matters unique (including scope and workflow) to ensure a strong and defensible outcome all while often under time and cost pressures.

Privacy Policies and Privacy Programs are unique to each organization. Understanding your data privacy risk and where your data is located should be the starting point to creating a Privacy Policy and Privacy Program. Learn about your data privacy risk by using various assessments and techniques, including data mapping and data privacy assessments.

Given the sheer amount of discoverable data that's out there, the ability to distinguish actual from pseudo privileged information is nearly impossible without the application of "smart" auto-extraction & sifting tools. With communication channels and data sources constantly evolving, is the tedious approach keyword search approach to privilege review still the right option? It does get the job done but with the power of data science & automation at your disposal, why not save time and money?

Technology-assisted review has come a long way since its early introduction as predictive coding. While each version has its merits and place, it is important to understand that in order to select the right approach for your discovery needs, one must truly understand the underlying process and variables such as time and cost. However, has the time come for TAR 3.0 and what does that look like for discovery professionals?