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4 essential insights to get the most out of AI in litigation

| Written by Altlaw

AI in litigation is completely transforming how legal professionals approach the review process. However, for all its capabilities, misconceptions and false expectations of the technology are still widespread.

Like many other industries, legal professionals fear that AI is a potential threat to their job role. The truth, however, is quite different. AI is a powerful solution, but only when given the proper foundation and support from a qualified team.

In this blog post, we'll explore AI in litigation and four essential tips to ensure your firm uses AI safely and effectively.

 

1. Know when to use the right tool

Getting the most out of an AI solution means knowing it inside out. For example, you might have a tool that can identify the relationships between words and phrases but can't decipher information from images or media-based formats.

Understanding that using this tool wouldn't be wise for a batch of images or scanned documents is how to make your eDiscovery processes more efficient.

One of the most simple but crucial ways to get the most out of your AI in litigation is to know what the different tools in your inventory do and prepare your datasets accordingly.

Doing so maximises the speed and accuracy of AI-driven reviews, as you'll be playing to the strengths of your available tools. Plus, you'll minimise the chance of sticking points or errors when using your tools.


 

2. Cut your time, not your team

AI innovations can enable businesses to be more efficient than ever before. Many paralegals and attorneys still worry about AI's progression in eDiscovery as technology advances and becomes more prevalent in the industry. AI allows firms to carry out dozens of complex, logic-based calculations at great speed.

With this in mind, however, we're still far from AI replacing humans altogether. Looking at AI in litigation, it can be easy to overestimate its capabilities, with immediate thoughts of slashing budgets or reducing your internal headcount.

Despite its capabilities, AI still requires a strong, capable, and well-sized team for its implementation and ongoing management—both for quality control purposes and to assess how to get more out of the available tools.

If you want to maximise your strategic investment in AI, aim to do more in less time rather than do more with fewer people.

 

3. Preserve your previous workflows

Another common misconception in the legal industry is that adopting advanced AI tools will render previous workflows and operating models obsolete. In fact, this is far from the truth.

If you're well-versed in using more 'dated' technology — such as predictive coding — you can leverage AI to enhance your established workflows rather than completely replacing them. 

However, the efficiencies offered by more up-to-date tools may warrant adjustments to old workflows. For example, if your new AI solution can conduct two different processes simultaneously, you'll want to shorten and condense your processes accordingly.

Overall, the real metric is improved results. Using your established workflows with upgraded AI capabilities is a cost-effective way to improve the speed, efficiency and accuracy of your document review projects.


 

4. Commit to quality

With AI in eDiscovery, you often get out what you put in — particularly when using advanced AI tools. Utilising powerful systems that can make many decisions in seconds has its benefits but also severe drawbacks.

One problem with AI and its potential for scale and volume is the number of mistakes you can make during setup or configuration. One simple mistake could leave you with hundreds of inaccuracies to undo, adding valuable time to your busy schedule.

The key takeaway is to be diligent. Clean your datasets, formalise your quality control practices and ensure you always have an extra pair of eyes to double-check every stage of your process.

With these measures in place, you'll spend more time getting results and less time sifting through errors caused by poor setup.

 

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