What we need are new buzzwords and acronyms. How about AI?
No, not that AI (artificial intelligence)! I’m talking about another AI, which will help us get the best from “that” AI. I’m talking of the oft-overlooked actual intelligence!
Actual intelligence provides you with the ability to determine which new technologies will materially contribute to your firm’s innovation versus which will not, despite the hype and urge to jump on the proverbial bandwagon. Actual intelligence can also be referred to as common sense, which we all know is not as common as we’d like it to be!
So let’s be truly intelligent about artificial intelligence. “Artificial intelligence” has overtaken “innovation” in just about every conversation, pitch or marketing piece. At the same time, there are still those who have absolutely no idea what it actually is. Clever computers? Trained computers? Active Learning? Statistical analysis? Complex algorithms? Smart devices? Robots?
The answer is, elements of all of the above—but it depends, so there’s a requirement to be specific instead of just spouting jargon.
The AI Race is On
There is a race—or a sprint perhaps—to adopt AI technology but is the AI race to catch-up, to get ahead, or to stay ahead? Whatever stage an organization is at, a new product or concept released or published tomorrow could change everything. AI is in a huge state of flux. Therefore, law firms and corporations alike must be agile and flexible, informed of new technologies being developed, and then well-positioned to be able to accommodate, embrace and implement suitable tools when they become available.
Innovative AI technology often has multiple uses, but not all new technology will enhance your business in all areas. Ensure that any new tools and their functionality are relevant to your business needs and technical aspirations. In other words, do not implement technology for technology’s sake, but only when direct benefits will result for your end-users and clients.
Relevant innovative technology will undoubtedly make life easier. Processes will become more efficient and often accuracy will increase. For example, intelligent use of the technology can often facilitate smarter working later in the process and provide opportunities to delegate or outsource higher value work.
However, new tech is unlikely to be the silver bullet that completely obviates the need for human interaction. Actually, adoption of innovative technology will almost certainly require significant changes in the culture of those using it and those shifts must be guided by people who understand human nature and know how to navigate through it. For example, if predictive coding software can find about 95% of all the documents likely to be relevant, that’s very promising. However, if the users cannot get comfortable with the fact that the 5% might be missed and are therefore unwilling or reticent to accept the results of the software, the opportunity for the technology to successfully benefit the organization evaporates. Also, in this scenario a receiving party has to accept that any documents that were not captured were missed by the technology. The missed documents were not deliberately suppressed by a human, which is something completely different.
In the context of using AI for contract extraction, while historically the process of extracting data from volumes of contractual documentation has been a manual one, this is no longer the case. There are AI tools that can locate and collect contracts stored on hard drives, file shares, network drives and various software platforms. Once contract files are found, these tools can index them and render any text fully searchable. Then, the information important to the client must be extracted from each contract. Automated metadata extraction and categorization technology can be used to speed up this process and reduce the cost associated with the traditional manual contract review. This technology auto-triages contracts based on certain business rules (e.g., the exclusion of expired, duplicate, unsigned or immaterial contracts), groups like-contracts together and prioritizes the most critical contracts for review before automatically extracting the metadata. Having set up and implemented the technology, humans can then efficiently work with the output to conduct their review, add their valuable work product, check for errors, such as false positives, and make key decisions in a structured manner.
A better way to evaluate deployment of innovative technology is to ask whether its use will provide a valuable and significant steer in the right direction.