Reading about the “dollar commit” Microsoft has earmarked to increase compute power in support of generative AI and their quest towards Artificial General Intelligence ("AGI") got me thinking about the speed of change.

I remember some 10 years ago, trying to engage with legal teams and the judiciary on the benefits of Technology Assisted Review ("TAR"), as a document review accelerator within eDiscovery software. For those unfamiliar with TAR, think good old fashioned machine learning. To say that the levels of interest from within the legal profession were limited, would be putting it politely.  Jump forward to the current day and TAR is now mainstream, along with a suite of other data analytics tools to assist with analysis and review of large unstructured data sets, though it did take a while to arrive at this point.

So, what to the future and how quickly will that arrive? While I do not have a crystal ball, I feel confident, especially on the back of the money being spent by Microsoft and others, that I will not have to wait 10 years for the mainstream acceptance of generative AI as a default part of the eDiscovery tool kit.  Whilst at face value this appears to be a positive thing,  I now find myself leaning towards the other side of the fence when compared to 10 years ago.  

AI has huge potential to transform eDiscovery and revolutionise how legal professionals review documents, there is however a risk that if the speed of change is too rapid then ethical considerations, and a thoughtful approach as to when generative AI should be incorporated into eDiscovery workflows, may well be overlooked by some. Therefore, while I look forward to embracing the change that is coming, I would caution that jumping in feet first may not always be the right approach.

Disclaimer: Authors own work, apart from one sentence which generative AI crafted for me.  Let me know if you can determine which one.