Augmenting knowledge management with artificial intelligence
Hasn’t there been lots of hype around artificial intelligence lately?
It seems that every time you turn around a virtual internet-corner someone else is making a new claim about it: “solve world hunger”, “cure all diseases”, “have machines take over the world ….
We can safely say that none of these will become true any time soon – maybe never. But we can also say that, as it applies to business, artificial intelligence has a lot to offer. And one of the areas where this is most true is knowledge management and collective wisdom.
A crucial component of artificial intelligence is machine learning: applying learning to machines, so they can acquire wisdom and use knowledge to solve problems according to preset cognition rules. In business, nothing we do is closer to this mantra than knowledge management, and customer service use of it more specifically.
Following conversations between Transversal and thinkJar, we set out to find the best way to use artificial intelligence (AI) to improve knowledge management (KM) in customer service. We commingled a few dozen interviews of practitioners adopting AI for their KM solutions with research and experiences in many projects and enquiries to learn better how to build a better system.
We found a few things we want to share with you – and we will as a series of blog posts:
- The five stages of value for artificial intelligence
- How AI can enhance existing KM solutions
- The emergence of knowledge automation
- A decision framework for choosing a knowledge solution
- Seven lessons learned by those who blazed the trails.
These posts will help you plan how to embrace the two concepts: the new reality of KM in an overabundant information age, and the world of AI as it begins to encroach in the enterprise.
The biggest lesson learned in this research was that although many organizations are undertaking the initial steps towards letting AI systems improve the results of their human-assisted contact centres (and while those same systems have improved the use of KM in customer service), we are not yet at the point where self-service and automated systems can take over.
At least, not yet. Thus the concept of augmenting humans, not replacing them is what this series focuses on.