Sun. Oct 1st, 2023

Backgrounder: AI in eDiscovery

Background Note: eDiscovery professionals and providers face a myriad of business challenges that can significantly impact their success. The growing importance of artificial intelligence (AI) in addressing these challenges cannot be overstated. With AI, professionals can unlock new opportunities to enhance their operations, streamline processes, and achieve better results in the face of increasing complexity. This article aims to provide a cursory* overview of AI opportunities and their potential to transform the eDiscovery landscape, regardless of whether a professional or provider is considering AI at a superficial, specific, or strategic level.

ComplexDiscovery Backgrounder

A Blinding Flash of the Obvious? Considering AI in eDiscovery Through the Lens of Business Impact Challenges

AI in eDiscovery

The ComplexDiscovery Winter 2023 Business Confidence Survey offers valuable insights into the key concerns and challenges faced by eDiscovery professionals and providers in today’s rapidly evolving landscape. The survey findings shed light on various factors affecting the industry, including budgetary constraints, increasing data volumes, data security, diverse data types, lack of personnel, and inadequate technology. As organizations continue to navigate this complex environment, exploring AI-driven solutions across these areas is becoming increasingly important to maintain a competitive edge and address the challenges effectively.

Considering the findings of the ComplexDiscovery Winter 2023 Business Confidence Survey, it is evident that eDiscovery professionals and providers face a multitude of challenges in the current landscape. By embracing AI-driven opportunities, these professionals, including those in cybersecurity and information governance, can tap into the transformative potential of artificial intelligence to help address their concerns. The AI-powered solutions outlined below may be helpful for idea generation, helping professionals and providers to consider top industry challenges with the element of AI technology.

Potential AI Applications for eDiscovery

The following AI application opportunities, identified across six business challenges, may help eDiscovery professionals and providers enhance their capabilities, improve efficiency, and ultimately drive better outcomes for their businesses:

Budgetary Constraints

  1. Automate repetitive tasks to reduce manual labor costs
  2. Optimize resource allocation through AI-driven project management
  3. Enhance cost prediction and budgeting with machine learning algorithms
  4. Implement AI-based process optimization for increased efficiency
  5. Utilize AI to identify cost-saving opportunities across business operations
  6. Automate invoice processing and expense tracking with AI
  7. Use AI-driven pricing models for competitive advantage
  8. Deploy AI-powered procurement and supplier management systems
  9. Optimize energy consumption and facility costs using AI-driven smart systems
  10. Leverage AI-powered predictive maintenance to reduce equipment downtime and maintenance costs

Increasing Data Volumes

  1. Implement AI-powered data processing and filtering to handle large datasets
  2. Use AI-driven data classification to prioritize relevant information
  3. Utilize machine learning algorithms to identify patterns and trends in data
  4. Employ AI-based data compression techniques to reduce storage requirements
  5. Implement AI-driven data deduplication for efficient data storage
  6. Leverage AI-powered data analytics for actionable insights
  7. Use AI to identify and eliminate redundant and obsolete data
  8. Deploy AI-driven real-time data monitoring and analysis tools
  9. Utilize AI-based data visualization tools to effectively communicate insights
  10. Implement AI-powered data governance and management systems

Data Security

  1. Enhance cybersecurity measures with AI-powered threat detection and prevention
  2. Implement AI-driven access control and encryption systems
  3. Utilize machine learning algorithms to continuously improve security policies
  4. Deploy AI-based anomaly detection to identify potential security breaches
  5. Use AI-powered risk assessment tools to prioritize security measures
  6. Implement AI-driven user behavior analytics to prevent insider threats
  7. Utilize AI-based secure data sharing and collaboration tools
  8. Employ AI-powered security awareness and training programs
  9. Implement AI-driven incident response and recovery systems
  10. Leverage AI-based security auditing and compliance solutions

Increasing Types of Data

  1. Deploy AI-driven data integration tools to handle diverse data formats
  2. Use machine learning algorithms to recognize and categorize new data types
  3. Implement AI-based data normalization and transformation techniques
  4. Utilize AI-powered semantic analysis to interpret unstructured data
  5. Employ AI-driven natural language processing to analyze textual data
  6. Implement AI-based image and video recognition tools for multimedia data
  7. Utilize AI-powered sentiment analysis for social media data
  8. Leverage AI-driven geospatial analysis for location-based data
  9. Employ AI-based time series analysis for temporal data
  10. Implement AI-powered data fusion techniques to combine heterogeneous data sources

Lack of Personnel

  1. Use AI-powered recruitment and hiring tools to identify and attract top talent
  2. Implement AI-driven onboarding and training processes to improve employee retention
  3. Utilize AI-based collaboration tools to optimize team productivity
  4. Leverage AI-driven performance management systems to motivate and retain employees
  5. Employ AI-based workforce planning and forecasting tools
  6. Implement AI-driven talent development and succession planning solutions
  7. Utilize AI-powered employee engagement and satisfaction measurement tools
  8. Deploy AI-based workload and capacity management systems
  9. Leverage AI-driven career pathing and internal mobility solutions
  10. Implement AI-powered employee retention and turnover prediction models

Inadequate Technology

  1. Leverage AI-powered technology assessment and recommendation systems
  2. Invest in AI-driven research and development to stay ahead of technological trends
  3. Implement AI-based performance monitoring and optimization solutions
  4. Utilize AI-driven technology adoption and change management tools
  5. Employ AI-powered IT service management and support systems
  6. Leverage AI-based infrastructure management and automation solutions
  7. Implement AI-driven software development and testing tools
  8. Utilize AI-powered data center and cloud management solutions
  9. Employ AI-based business process automation and integration systems
  10. Implement AI-driven system scalability and elasticity solutions for peak performance

While general in nature, the listing may help leaders, developers, and consumers involved in the creation, delivery, and consumption of eDiscovery products and services as they look to the future through the challenges of today.

A Restatement of the Obvious: Observations on Business Impact Factors

ComplexDiscovery Winter 2023 Business Confidence Survey (N=65)

  • In the winter of 2023, 32.3% of respondents viewed increasing budgetary constraints as potentially having the greatest impact on their business in the next six months. This percentage is the highest of all concerns in the winter 2023 survey. This percentage is also the fifth-highest rating in the area of budgetary constraint concerns since the inception of the survey in the winter of 2016.
  • Increasing volumes of data continued to be a reasonably consistent concern for eDiscovery professionals, with 20.0% of winter 2023 survey respondents viewing data volume challenges as potentially having a substantial impact on business in the next six months. This was a solid increase in this area from the 16.0% response rate in the fall 2022 survey.
  • Respondent’s concern for the impact of data security on eDiscovery business performance increased solidly (4.4%) during the last quarter and continues to be the top concern for 15.4% of those surveyed.
  • In the winter of 2023, 13.8% of respondents viewed increasing types of data as potentially having the greatest impact on their business in the next six months. This percentage is a significant decrease from 28.0% in this area in the fall of 2022. This is also the lowest percentage of concern for respondents in this area since the spring of 2020.
  • The percentage of respondents that viewed lack of personnel as a top business concern decreased in the last quarter from 16.0% in the fall of 2022 to 9.2% in the winter of 2023. This is a continued drop from the winter of 2022 when the percentage of respondents expressing their concern of lack of personnel as their top business performance concern was the highest in this area since the inception of the survey.
  • In the winter of 2023, the impact of inadequate technology as the top business issue increased by 5.2% from the last quarter and is now viewed as the top concern by 9.2% of survey respondents. While the lowest overall concern in the winter 2023 survey, this is also the highest concern in this specific area since the winter 2019 survey.

Chart 1: An Overview of Issues Impacting eDiscovery Business Performance in the Winter of 2023

Issues Impacting eDiscovery Business Performance - Winter 2023

Chart 2: An Aggregate Overview of Issues Impacting eDiscovery Business Performance (2016 – 2023)

Issues Impacting eDiscovery Business Performance - Aggregate - Winter 2023

A Blinding Flash of the Obvious

By leveraging AI and its myriad applications, eDiscovery professionals and providers can better adapt to the dynamic landscape and overcome these key business impact factors, ensuring continued growth and success in the industry.

*A cursory examination or review is one that is quick, brief, and superficial. It typically involves only a high-level overview or a general glance at the subject matter, without delving into details or specific aspects. Cursory assessments are often carried out when there is limited time or resources, or when a deeper understanding of the topic is not necessary at the moment. However, they may not provide an accurate or complete understanding of the subject due to their limited scope.

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