AI has made its way into countless software solutions, and with good reason – it can improve the selling experience for both sellers and buyers. However, AI systems traditionally require a significant number of inputs to begin to draw patterns between data points and hone recommendations. The more inputs, the better quality of outputs.
Talking AI in Denver
Patrick Welch, President and CMO of Bigtincan, discusses this concept with Gerhard Gschwandtner, Founder and CEO of Selling Power Magazine, at the Sales Enablement Society Conference in Denver.
https://youtu.be/aSicQIKa9_c
Patrick describes AI as a crawl, walk, run scenario. However, there is a lot of crawling before any walking or running can happen. Luckily, there are new approaches to AI that can reduce the crawl time, so you can get to the walking and running much quicker. One such approach is the use of ontology - learn all about ontology here.
The Power of Ontology
Unlike traditional AI systems, ontology doesn’t require tagging. Ontology draws relationships between seemingly unrelated items through “dictionaries” and “thesauruses”. Because of the lack of need for tagging and thousands of inputs, ontology can help systems be useful on day 1 of implementation.
Through ontology, systems can make the best possible recommendations when it comes to sales content. AI can even be applied to learning systems. All companies and learning paths are different, so systems that adapt to nuances in the salesperson’s learning journey are invaluable.
As we’ve dug into previously, the purpose of AI is always to assist, not replace, the seller. Just as ecommerce didn’t replace sales people, AI won’t either. It can empower sellers by decreasing the grunt work needed in meeting prep and engagement. It helps them do their job better – not do it for them. And we could all use a little help now and then, right?
