Alex Smith, Global AI Product Lead for iManage talks about the ways in which AI can help businesses with knowledge curation to enhance their information environment
Since the onset of the pandemic, knowledge workers in enterprises have been under significant pressure to help their organisations protect business, surmount commercial challenges, and drive positive outcomes – all whilst wading through unchartered waters, confusion, and uncertainty.
As might be expected of these knowledge workers – whose ranks include lawyers, accountants, financial experts, compliance and risk specialists, and other professionals who ‘think for a living’ – they have created high value work products and knowledge assets to help meet time and cost pressures and to address client demands, employee needs, regulatory requirements, and other concerns.
This is where things get tricky, however, because there are a lot of these knowledge outputs.
Knowledge, Knowledge Everywhere…
These items run the gamut from highly bespoke contracts, subject matter expertise, patents, and copyrights, to activity templates, process maps, checklists, and business advisories. These new versions of knowledge assets will to a large extent form the basis of future business activity, reflecting enterprises’ current/latest way of conducting business operation in a globally transformed sociopolitical and economic environment, alongside flexible and hybrid workforce models.
New, informal sources of knowledge have emerged too. There are recorded and transcribed Zoom meetings, learning presentations, and team sessions, as well as WhatsApp, Slack, and Teams chats that are largely substituting for the impromptu hallway knowledge exchanges that used to routinely take place when everyone was in the same physical office. Much of the information in this category is presently unstructured, which makes it hard to effectively tap into.
Enterprises need to find a way of curating all this knowledge into ‘reusable’ business know-how, so that there is brand consistency and standardised adoption of best practice and corporate policy across business operation. This is also important for mitigating business risk.
The challenge becomes finding the best way to make this curation actually happen – but fortunately, AI can lend a hand.
Technologies like machine learning are ideally positioned to help enterprises curate knowledge so that organisations can facilitate intuitive information sharing and collaboration in today’s altered business world.
The application of AI for curation isn’t a new concept – think of Spotify, Google, Amazon, or Netflix. They’re able to classify and categorise myriad items and understand the connections between them to suggest “People who liked item X will also be interested in item Y.”
Take this same concept and apply it to the world of the knowledge worker. Those highly bespoke contracts we mentioned earlier? AI can figure out, for instance, which of the contracts that center around European real estate transactions has been downloaded most often from the firm’s document management system (DMS) and used as a template or starting point by other lawyers.
Wondering what specific wording or language to include in that patent or copyright? A quick search will enable knowledge workers to find pro forma and best practice clauses from knowledge content and create unified best practices specific to clause type, thanks to AI having understood the content of the documents and how they should be classified.
Need to deliver highly valuable subject matter expertise?
AI can ‘connect the dots’ between practice management systems, billing systems, the DMS, and other business systems to identify where expertise lies within the organisation.For example, someone who has billed a large number of hours around Asian mergers & acquisitions and has drafted a number of related share purchase agreements that have been downloaded multiple times by other members of the firm is likely to be an expert in that area and someone who can be tapped for expertise.
Meanwhile, checklists, when surfaced by AI, can serve a valuable curation role of their own. More than just guiding matter teams on the right steps, they can ‘signpost’ the way to key resources for each particular stage and task in a matter. (e.g., ‘If you’re in this particular stage, make sure to check out knowledge resource X for useful tips and best practices.’)
Meanwhile, as Zoom and Slack data becomes structured, it becomes searchable.
The use of tagging and knowledge curation efforts means the useful information contained within these threads doesn’t disappear within an instant messaging black hole, and instead becomes assets that can be ‘found’ by AI and thus used to enrich the variety of content available within knowledge systems.
Throughout all of these activities, recommendations have a powerful role to play. In the same way that the Netflix and Amazons of the world use recommendations to help you find what you’re looking for when you ‘don’t know what you’re looking for, but you’ll know it when you see it,’ a similar process occurs for knowledge workers. AI comes up with recommendations that help knowledge workers find relevant and contextual information based on the workspaces they have access to, the people they work with, and what they search for – making it easy to stay current and access the content that can help them get their job done faster.
Maintaining High Performance Made Easier You can’t unring a bell, and it’s likely that the alteration in the business environment that was first occasioned by the pandemic will persist for some time. Fortunately, effective knowledge curation can ensure that knowledge workers can continue to operate effectively and perform their jobs at the highest level, and AI will play a critical role in ensuring the continuing flow of the knowledge that feeds that performance.