How AI and Predictive Truckload Pricing Are Impacting Shipping | Episode 16
Predictive Truckload pricing is here, and the logistics industry will never be the same!
In episode 16 of Banyan’s Tire Tracks™ podcast, Patrick Escolas sits down with Dawn Salvucci-Favier, CEO and Chief Product Officer at Greenscreens.ai, to find out how dynamic pricing can help you build a more cost-effective and efficient over-the-road (OTR) shipping operation. They discuss how Greenscreens.ai is transforming traditional Truckload pricing using artificial intelligence (AI), the difference between AI and machine learning (ML), and what you should expect from this technology in the next three to five years.
“Machine learning is about using data to learn the way that a human would learn,” said Salvucci-Favier. “It essentially simulates the intelligence of the human. It’s using data, but a lot more data than humans could ever possibly absorb, in milliseconds. While it might take that broker 20 minutes to an hour or maybe more to come up and price the lane or a few lanes, the AI is doing it in milliseconds.”
AI and Predictive Truckload Pricing Episode Key Points
- An overview of what Greenscreens.ai does and how Dawn became CEO.
- Predicting forward: the gap in the market that Greenscreens.ai was built to bridge.
- How AI and predictive pricing can meet the specific needs of your business.
- Why a lack of change management is the biggest obstacle to digital transformation.
- The competitive disadvantage that comes with refusing to embrace emerging technology.
- AI, ML, DL, and more: decoding the “alphabet soup” of artificial intelligence.
- Short- and long-term impacts that this technology will have on the marketplace.
- Why Dawn says half of Greenscreen.ai’s sales strategy is focused on education.
- How freight brokers can best leverage Greenscreen.ai’s offering.
- The importance of continued investment in the adoption of new technology.
To learn how AI and predictive Truckload pricing are impacting OTR shipping, click above to view Tire Tracks Episode 16.
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