Law firms can use chatbots to quickly answer questions that visitors have. TimeSolv describes chatbots as “computer programs designed to deliver an interactive customer experience without actual human interaction.” If they have hundreds of visitors a day, do they need a fleet of service reps ready to answer incoming questions? For law firms specifically, do they need experienced associates online to provide expert advice? Not exactly.Ĭhatbots are another growing use case within law firms. Instead, they want a portal to connect with client service.īut meeting this need is challenging for lawyers and their offices. They don’t want to click through a dozen pages to find their answer. Just like many businesses with websites, visitors have specific questions they want answered and they want answers fast. Language models today are powerful enough to comprehend both the intent and the substance of a message and organise it accordingly. The AI can do this by using natural language processing methods that encode conversational content, whether speech-to-text and text-to-text, and understand its meaning. This not only saves a tremendous amount of time, but also reduces the risk of manual errors. With AI, law firms can analyse large amounts of unstructured documentation notes and organise them into standardised templates. Using AI, law firms are speeding up the laborious process of manually entering data. Legal documentation, whether internal notes or transcripts of court proceedings, is often done differently depending on the person or court. Below, we outline three important ways that law firms today (and many in the future) will use AI. Now let’s turn to explore use cases for computational linguistics and conversational intelligence within law firms. Use cases for conversational intelligence in law offices TechTarget explains that the knowledge underpinning computational linguistics powers tools “like instant machine translation, speech recognition systems, text-to-speech synthesizers, interactive voice response systems, search engines, text editors and language instruction materials.” Commonly chatbots or virtual assistants, these tools pull large volumes of data and run it through machine learning and natural language processing to speak in a natural way like a human.Ĭonversational intelligence is a branch of computational linguistics, the study “of language from a computational perspective.” Simply put, it’s determining how to make it easier for humans to communicate with computers, primarily through spoken word, but also written communication. How can conversational intelligence be applied effectively?Ĭonversational intelligence refers to the tools that leverage AI to speak with users or customers. To paint a clearer picture, let’s define a key subset of AI, conversational intelligence and practical uses for it today. Saying, “our software uses AI,” is pretty vague. There is a strong demand for AI tools, but they’re still often misunderstood. And they’re leveraging it both externally in the market and internally, in their workforce. The market size is exploding, because organisations see the strong business case for AI tools. Likewise, a subset of AI, computational linguistics, is set to grow from 21 billion in 2021 to 127 billion in 2028. The market size for artificial intelligence was $87 billion (USD) in 2021. The market for AI and computational linguistics is booming
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