Generative AI Costs in Ediscovery
A Practical Guide to Pricing, ROI, and More
The legal landscape is continually evolving, with technology playing an increasingly significant role in shaping legal processes. Among the most impactful advancements is generative artificial intelligence (GenAI), which holds immense potential to transform various aspects of legal work, particularly in the realm of ediscovery.
The ediscovery process has historically been a labor-intensive and costly endeavor. However, the integration of new technology like GenAI promises to alleviate some of these burdens, offering new avenues for efficiency and cost reduction.
It has the potential to influence ediscovery costs and offer new insights for legal professionals who are looking to leverage this AI technology. It can also transform the legal practice itself by driving down expenses, from accelerating document review to optimizing data processing.
As the legal profession’s relationship with GenAI continues to evolve and it becomes more integrated into everyday tasks, the cost of these services will likely stabilize.
To fully grasp the transformative power of GenAI in ediscovery, a comprehensive understanding of its underlying mechanisms, advantages, disadvantages, and the financial considerations involved is essential for legal professionals navigating this evolving technological frontier.
GenAI in Ediscovery
GenAI distinguishes itself from traditional machine learning by its ability to create new content and information, rather than just classifying or analyzing existing data. In ediscovery, this translates into capabilities that can significantly streamline workflows and reduce manual effort.
GenAI can accelerate the document review process by producing thorough summaries of legal documents, making it easier for lawyers to quickly grasp key information from large volumes of data. This capability allows legal professionals to identify key data points and relevant information more efficiently, enabling them to focus on the most critical aspects of a case.
Beyond summarization, AI tools can also assist with drafting various legal documents, such as statements of facts or deposition summaries, often complete with citations to supporting documents. It can even help with creating case narratives, providing a concise overview of facts and issues for trial preparation.
Despite GenAI’s potential to help transform the legal industry, many organizations are still hesitant to fully embrace it because they view it as cost-prohibitive. There’s still an open question about how much GenAI costs, and how cost-effective it might be. While these are valid concerns, teams that wait to adopt GenAI run the risk of falling behind the competition.
How Much Can You Expect to Pay for GenAI?
Legal technology providers offering generative AI solutions often employ various pricing models to accommodate diverse client needs and usage patterns. Understanding these models is key to predicting and managing ediscovery costs.
Usage-Based Models
This is a pay-as-you-go approach where costs are directly tied to the actual consumption of AI services. This could be based on the number of documents summarized, the volume of data processed by AI features (e.g., per GB), the number of AI-generated drafts, or even the duration of AI processing time. This model is flexible for varying workloads but requires careful monitoring to prevent unexpected costs.
As a subset of the usage-based model, there’s also a credit-based model in which clients purchase "credits" that are consumed as they use specific GenAI features. Credits are charged for each task that’s carried out, with different tasks requiring different numbers of credits. For example, generating a document summary might cost 20 credits, while coding a set of documents might cost 50 credits. This model offers predictability as clients can pre-purchase credits based on anticipated usage.
Hybrid Models
Many providers combine elements of the above. For instance, a base subscription might include core ediscovery features and some basic AI usage, with additional, more advanced GenAI functionalities available through a credit or usage-based add-on. This allows for flexibility and scalability.
Tiered or Subscription Models
Some providers offer different subscription tiers, each providing access to a specific set of GenAI features and a certain level of usage allowance for a fixed monthly or annual fee. Higher tiers typically include more advanced features or higher usage limits. Costs increase only if a client moves to a higher tier or exceeds included allowances, potentially incurring overage fees.
A subset of the tiered model is the per-user licensing model. While less common for the AI itself, some platforms might combine AI feature access with traditional per-user licensing for the overall platform. This means a base cost per user, with AI usage potentially layered on top via a credit or usage-based system.
Advantages of GenAI Costs in Ediscovery
The integration of GenAI into ediscovery offers several compelling advantages and use cases that directly translate into cost savings and improved financial efficiency.
Accelerated Document Review and Reduced Labor Costs
GenAI can significantly speed up the document review process by automatically summarizing documents and highlighting key information. This drastically reduces the time legal professionals spend manually sifting through large volumes of ESI, leading to substantial reductions in labor costs associated with extensive human review.
Lower Litigation Costs
By automating time-consuming manual tasks, GenAI can lead to significant overall cost savings for both law firms and clients. Lowering litigation costs, particularly during the ediscovery phase, can also increase access for smaller firms that might otherwise be priced out due to high expenses during discovery.
Efficient Data Handling and Processing
GenAI's ability to process and analyze a wider array of data types, including complex and unconventional formats like videos, audio files, and various messaging platforms, can prevent the need for specialized, often costly, tools or manual workarounds for different data sources. This comprehensive approach can streamline data processing costs.
Reduced Administrative Overheads
GenAI can automate various administrative tasks associated with ediscovery, such as generating privilege logs or organizing documents. This automation reduces the administrative overhead and associated labor costs that typically accompany these processes.
Optimized Resource Allocation
By handling routine and high-volume tasks, GenAI allows legal professionals to focus on higher-value activities that require human judgment and strategic thinking. This optimizes the allocation of expensive legal talent, ensuring resources are deployed where they can have the most impact, rather than on tedious review tasks.
Pricing Factors for GenAI
The cost of GenAI for ediscovery services is not a one-size-fits-all figure, as it depends on a multitude of factors, similar to traditional ediscovery pricing models. However, it's important to understand that while the initial investment might seem significant, the long-term cost savings through increased efficiency can be substantial.
Generally, GenAI ediscovery costs are influenced by the volume and complexity of the data, the specific features and functionalities required, and the service provider's pricing model. Unlike traditional ediscovery, where costs are heavily tied to manual labor hours for review, GenAI can significantly reduce these per-hour review costs by automating large portions of the process.
Data Volume and Type
The sheer amount of data (in gigabytes or terabytes) to be processed is a primary cost driver. The complexity of data types (e.g. structured vs. unstructured, common vs. esoteric file formats, multimedia) can also impact pricing, as more complex data may require more sophisticated processing and AI models.
Features and Functionality
The range of GenAI features utilized will affect the cost. Basic functionalities like document summarization might be less expensive than advanced capabilities such as automated drafting, complex query generation, or multi-language processing. Providers may offer different tiers of service based on the depth of AI functionality.
Hosting and Storage
Like traditional ediscovery, the cost of securely hosting and storing ESI over the lifecycle of a case is a significant factor. Cloud-based solutions may offer scalable storage and the ability to manage data in-house but also come with associated hosting fees. Generally, on-prem ediscovery software is less compatible with GenAI systems than cloud-based, so there are also limiting factors in that regard.
User Licenses
Many GenAI ediscovery platforms operate on a per-user license model, where the cost increases with the number of legal professionals accessing and utilizing the system.
This can have both positive and negative impacts depending on how the GenAI system is utilized. For example, if a large majority of your organization is constantly using GenAI tools for a variety of tasks, the user license model might be more cost-effective.
However, if your organization is leveraging GenAI in a specialized way for specific use cases, the user license arrangement might not be the most financially efficient.
Training and Support
The level of training and ongoing support provided by the vendor can also influence pricing. Comprehensive training to ensure effective adoption and readily available technical support are crucial for maximizing the value of the AI investment.
Cost Recovery
Cost recovery is an important mechanism for understanding how legal organizations can help cover the expenses associated with their GenAI tools.
For example, law firms have the ability to pass on the expenses associated with advanced GenAI tools to clients depending on things like retainer agreements, fee structures, and the specific jurisdiction's rules regarding billable technology. Demonstrating how GenAI implementation leads to a more efficient and ultimately more affordable discovery process than traditional methods despite the specialized technology fees is crucial to reconciling the costs of these tools with clients.
For in-house legal departments, cost recovery often translates to demonstrating a positive return on investment (ROI) to their internal stakeholders. This involves tracking the savings generated by GenAI in terms of reduced external vendor spend, fewer hours dedicated by internal legal teams to manual tasks, and faster resolution of matters.
A Continuing Investment
GenAI stands poised to reshape the landscape of ediscovery, offering unprecedented opportunities for efficiency and cost reduction. By automating laborious tasks like document review, summarizing complex information, and assisting with drafting, it can significantly streamline legal workflows. While challenges such as the need for human oversight and evolving court acceptance remain, the advantages in terms of accelerated processes, enhanced accuracy, and the ability to handle diverse data types are compelling.
This investment, though it may require an initial outlay, is designed to yield a significant return on investment by dramatically reducing the traditionally high labor costs associated with ediscovery, accelerating case timelines, and freeing up highly compensated legal professionals for more strategic work. Ultimately, leveraging GenAI can lead to greater cost efficiency, faster decision-making, and more impactful legal outcomes.
As the technology continues to mature and gain broader acceptance, GenAI will undoubtedly become an indispensable tool in the modern legal practice.
Frequently Asked Questions
Here are some frequently asked questions regarding ediscovery costs associated with GenAI, and how it might impact your organization.
1. How does GenAI reduce ediscovery costs?
GenAI reduces ediscovery costs primarily by automating labor-intensive tasks that are part of traditional ediscovery workflows, like document review and summarization, which significantly cuts down on human review hours and associated legal fees. It also enhances efficiency, leading to faster case resolution and lower overall litigation expenses.
2. What are the main factors driving GenAI ediscovery costs?
The main factors driving GenAI ediscovery costs include the volume and complexity of data processed, the specific AI features utilized (e.g., summarization, drafting), hosting and storage fees, user licensing, and any required customization or integration services.
3. Is GenAI more expensive than traditional ediscovery methods?
While GenAI may involve an initial investment in technology and training, its long-term cost-effectiveness often surpasses traditional ediscovery methods by significantly reducing manual labor hours and improving efficiency, leading to lower overall project costs.
4. What pricing models are common for GenAI in legal tech?
Common pricing models for GenAI in legal tech include credit-based models (where you purchase credits for specific AI actions), usage-based models (pay-as-you-go based on consumption), tiered or subscription models (fixed fees for feature sets), and hybrid models that combine these approaches.
5. Can GenAI help with legal spend management in ediscovery?
Yes, GenAI can significantly aid in legal spend management by providing more predictable costs through automated processes, reducing reliance on expensive human hours for routine tasks, and offering clearer insights into data processing expenses.
6. How does data volume impact GenAI ediscovery pricing?
Data volume directly impacts GenAI ediscovery pricing as most providers base costs on the amount of data (e.g., gigabytes or terabytes) processed, hosted, or analyzed by the AI, making larger data sets more expensive.
7. Are there hidden costs associated with GenAI in ediscovery?
Potential hidden costs with GenAI in ediscovery can include expenses for thorough human oversight and validation to mitigate so-called hallucinations or inaccuracies, as well as costs for integrating the AI solution with existing systems, and ongoing training for legal teams to effectively utilize the technology.
8. How does GenAI help control litigation costs for boutique firms?
GenAI helps control litigation costs for boutique firms by democratizing access to advanced ediscovery capabilities, reducing the need for extensive manual review, and offering more affordable solutions compared to outsourcing all discovery tasks, thereby increasing access to litigation itself.
9. What is the ROI for using GenAI in ediscovery?
The ROI for using GenAI in ediscovery stems from significant reductions in labor costs, accelerated document review times, more efficient data processing, and faster case resolution, all of which contribute to substantial long-term savings and improved resource allocation.
10. Do ediscovery platforms offer GenAI features as add-ons or integrated solutions?
Many ediscovery platforms are now integrating GenAI features directly into their core offerings as comprehensive solutions, while some may also provide certain advanced functionalities as optional add-ons, depending on the provider and their service model.
