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You could be forgiven for thinking that AI is the "fairy dust" product that instantly delivers quick and accurate results. Behind the hype there are real possibilities for its application to the delivery of legal services, but what do in-house teams – and their internal clients – need to know to bring artificial intelligence to life?
The hype around Artificial intelligence (AI) in law is all too real, but few organisations have yet to capture it to its full potential. Too many hope unrealistically that AI is a means to bypass more prosaic means of creating efficiencies or a catalyst for operational sophistication; others are prone to dismissing it all together.
The reality is that human intuition, knowledge and technical ability have to work in tandem with AI to ensure that it truly delivers. AI technology needs to be tailored to address a specific legal or business need. It is not as simple as purchasing a self-driving car that is road-ready.
Businesses - and in particular those at executive leadership level - must understand not just what AI can do but what is required to make it work. An appreciation of AI and its effect on business performance must percolate throughout the organisation for adoption to be meaningful.
AI requires lawyers to perceive work as a process rather than a work of art, it is not something that needs to be created from scratch every time. This is the sea change.
The rewards are real though. A McKinsey & Company report "Artificial intelligence: The next digital frontier" found that ‘early AI adopters that combine strong digital capability with proactive strategies have higher profit margins and expect the performance gap with other firms to widen in the next three years’.In the legal sector, in-house and private practice teams can harness AI to address business demands that have never been met before.
Some business legal risk issues are of a scale and complexity that legal teams would traditionally have found too daunting to complete on a manual basis, such as reviewing historic but live contracts for hidden risk. The technologies now available – when working in tandem with humans – make such challenges properly addressable and scalable.
This leap into a technological new age is not as daunting as many would expect. AI has in fact been around for much longer than many would think, perhaps just in a more rudimentary guise than today. Document automation, for example, speeds up the production of documents, with outputs based on the rules applied by experts, which are tailored to that situation. The rules create the output, and the rule-set created through human expert input is the most basic form of AI.What we are seeing now is the use of expert systems that apply more sophisticated rules and knowledge to a process, rather than simply an individual document. Again, the technology does not write the rules; these products will usually require input from a legal engineer or an equivalent to create rules and then apply them to the system.
The transformational aspect of this technology is that it allows lawyers to perceive work as a process rather than a work of art, it is not something that needs to be created from scratch every time. This is the sea change that is the crucial by-product and necessary precondition of successful AI implementation.
These knowledge-based processes come with obvious advantages. Everyone applies the same knowledge and in the same way. Fundamentally, it also allows legal departments to use more junior resources for tasks that previously required senior and more expensive input.
Further, AI can be used by external counsel to provide an early insight into data, enabling firms to scope out an engagement and price it accurately. Fixed price menus are now radically improved, and more senior practitioners are not burdened with repetitive work. Never has it been easier to move away from the billable hour.
For most in house counsel, however, the refrain from the boardroom remains ‘law’s not core’. In the absence of sizeable resources for R&D within legal or large enough internal accessible data-sets, progressive in-house legal teams are increasingly working with third parties – including law firms – to develop AI technology and apply lessons from day-to-day practice. There are further chances to develop shared platforms to make in-house and external legal advisers more integrated.
If AI is to become an integral component in the processing of legal matters, then how do firms and businesses deploy it successfully? There is a danger that it is treated as the magic bullet or a ‘fairy dust’ product that instantly delivers a quick and desired result.
AI users must think carefully about the problem that requires solving and then how technology might be applied to overcome that challenge. An essential foundation will be identifying the layer of data that is needed, either to report against or to be generated through the system. The technology then needs to be configured, or in the case of machine-learning trained, to a business’s ways of doing things and what is important to the organisation. And the process must be constantly reviewed, honed and improved in light of feedback from the legal and business users.
Human participation will remain integral to product implementation, but also in analysing what it delivers, understanding where the data sits and what conclusions can be drawn from the findings. Lawyers and other specialists will be essential to analysing the numbers and information to identify the true insights and any potential flaws in the data and process.
This is the kind of time, human and monetary investment that is required to optimise the performance of AI. The future of what these technologies can deliver is bright, but it should not be assumed that delivering on the promise is without challenge.
Pinsent Masons' agenda for change in the legal services market