Using Machine Learning to Identify & Manage Supply Chain Risks [Webinar Recording]
A technology long thought as something only seen in Sci-Fi films is now penetrating our every day, within our personal & business applications.
Machine Learning, Predictive Analytics, NLP, and Cognitive Intelligence are some terms you may have heard thrown around before when hearing of AI’s application within business solutions.
But, how will procurement, sourcing & supply chain professionals move past theory, and truly begin to leverage the value of this technology?
Adoption level & plans for adopting AI solutions are generally low in procurement, as a function. Deloitte’s CPO Survey in 2018 found that AI is only fully deployed in 2% of procurement organizations, and is far from making any real impact at scale within the digital ecosystems procurement teams are so eagerly trying to build. There’s only 27% percent of procurement leaders considering AI/Cognitive technology, and the cherry on top… 55% haven’t considered it at all (Deloitte 2018).
Skepticism exists at scale within global procurement organizations about the application of AI technology, but can you blame them? Without proof of real application within the procurement function, AI solutions remain hypotheses.
But, could it be that digital procurement solution providers and procurement practitioners overcomplicating the application of AI Technology?
Join Meltwater & Kodiak Rating on February 20th at 15:00 CET during our live webinar where we’ll investigate the application of AI in procurement & sourcing, debunk the myths, and offer up an application of AI technology to manage supply chain risk, that isn’t so sci-fi!
What can you expect from this Webinar?
- Introduction of Kodiak Rating & Meltwater
- Background of Digital Complexities facing Procurement in 2020
- Procurement Intelligence 2.0
- Fairhair.ai & Meltwater delve into the potential application of supply chain signals.
- Demonstration of Meltwater x Kodiak Rating ML application for identifying and managing supply chain risk w/ the use of Machine Learning.