Uber Freight Invests in AI for Business Growth

Colgate-Palmolive and the Rise of AI in Logistics

During the height of the pandemic, when businesses faced significant disruptions, Luciano Sieber, the chief supply chain officer at Colgate-Palmolive, initiated a comprehensive “logistics blitz.”

This undertaking provided Sieber with enhanced visibility into Colgate-Palmolive’s global product movement. However, it simultaneously presented a new challenge: an overwhelming volume of data.

Uber Freight's AI Solution

Approximately one year ago, Sieber identified a potential solution through Uber Freight. The logistics and analytics division of the ride-hailing company has been actively developing innovative methods for managing extensive datasets utilizing artificial intelligence.

Colgate-Palmolive was among the first to implement one of Uber Freight’s latest offerings, a logistics-centered Large Language Model (LLM) known as Insights AI.

Expanding AI Capabilities in Supply Chain Management

Uber Freight is now officially introducing a range of AI features to its global shipper base, integrated within its existing supply chain software.

This expansion includes a broader rollout of Insights AI, initially launched in 2023, alongside over 30 AI agents designed to automate crucial logistics processes throughout the freight lifecycle.

A Competitive Landscape

Uber Freight isn't the sole player leveraging AI to optimize supply chains. Flexport unveiled its own suite of AI tools in February, and numerous startups are emerging to assist companies with data management, inventory reduction, and improved supply and demand forecasting.

However, Uber Freight believes its AI solutions can deliver tangible financial benefits to both its major clients and the nearly 10,000 other shippers it serves.

This confidence stems from the extensive knowledge base and established relationships cultivated over the eight years since its inception, connecting long-haul truckers with shippers.

The Potential of AI in Logistics

“Supply chain management is fundamentally a data-intensive problem,” stated Uber Freight founder Lior Ron in an interview with TechCrunch. “It’s complex and nuanced, and AI has a critical role to play in transforming and accelerating it.”

AI can serve as a fundamental role in shaping and accelerating supply chain processes.

“A Long-Awaited Advancement”

Launched in 2017, Uber Freight initially operated as a conventional brokerage. However, the Uber division has progressively transformed into a comprehensive service provider for businesses involved in global goods transportation.

The integration of artificial intelligence is a key focus for many contemporary organizations, often with varying degrees of success. It’s therefore unsurprising that Uber Freight is prioritizing this technology. The company’s leader notes his early academic work, both his bachelor’s degree and master’s thesis, centered on AI – dating back to a time when it was referred to as “neural networks.”

His engagement with machine learning continued during his tenure at Google Maps, spanning from 2007 to 2016. It was during this period that he recognized “the potential for digitizing the physical world.”

He articulated a core belief, formed nine years prior, that supply chain management is fundamentally a data-driven, technology-focused challenge. He believes this challenge can be accelerated through data connectivity and, ultimately, AI. “We’ve been building towards this moment,” he stated, “since the inception of Uber Freight.”

Early Adoption and Refinement

Uber Freight has utilized machine learning since its establishment. However, the exploration of more sophisticated generative AI capabilities began approximately two years ago.

This process, according to the leader, was not without its difficulties. Initial attempts to develop a “logistics co-pilot” were hampered by inaccuracies and yielded reliable results only 60% to 70% of the time.

Following extensive testing, the technology now demonstrates a 98% accuracy rate and is “driving tangible business results.” The Insights AI model has been trained on both internal data and external information pertaining to the $20 billion in freight the company manages annually. It also incorporates multiple, currently undisclosed AI models, delivering optimal combinations of price, precision, and performance.

New Capabilities for Customers

This AI initiative unlocks new avenues for customers to interact with their supply chain data. Users can, for example, request Insights AI to identify the lowest-performing origination points for specific shipments.

Alternatively, they can request a report detailing “all shipments to CVS in 2023.” The model is capable of handling far more intricate queries and consistently adapts to evolving needs.

Insights AI is presented to users in a manner similar to other popular Large Language Model (LLM) interfaces. Like other reasoning models, it transparently displays its methodology and clearly indicates the source of all data.

This allows customers to “gain network insights significantly faster, with nearly 100% accuracy and immediacy.” This contrasts sharply with the traditional process of formulating questions, submitting them to analysts, and awaiting a two-week turnaround for a PowerPoint presentation and subsequent discussion.

“What Information Are You Seeking?”

Uber Freight collaborates with numerous Fortune 500 organizations, and Colgate-Palmolive proved to be a particularly receptive partner for testing Insights AI and its associated innovative tools. According to Sieber, the conglomerate already provides a range of AI models to its entire workforce.

Furthermore, all employees are required to complete an internally developed training program focused on AI ethics. This proactive approach fosters a positive perception of AI within the company.

Shifting the Focus to Efficiency

“I believe this is highly beneficial, as it redirects the discussion from apprehension to exploring how AI can enhance efficiency and professional development,” Sieber explained. “It encourages employees to consider how they can deliver greater value by utilizing these new technologies.”

For example, Sieber noted that his company has successfully employed Insights AI to pinpoint carriers who are accepting a reduced number of shipments compared to their contractual obligations.

This allows for investigation into the reasons for these lower volumes, leading to either a resolution to restore compliance or a decision to seek alternative carriers.

Overcoming Previous Challenges

Previously, addressing this issue in real-time presented a significant challenge, Sieber stated. Companies like Colgate-Palmolive manage relationships with thousands of carriers.

These carriers often operate with diverse systems and workflows, and the resulting data was not effectively centralized. This lack of unified information hindered timely problem-solving.

Proactive Solutions and Data Utilization

The subsequent phase in AI development, as highlighted by both Sieber and Ron, involves creating more proactive solutions. Ron emphasized that Uber Freight’s data capabilities are crucial in this area.

“We possess comprehensive knowledge of facilities, transportation lanes, and pricing structures,” he said. “What specific information are you looking for?”

Alerts and Cost Savings

These proactive integrations manifest as alerts, informing customers like Colgate-Palmolive about instances of overspending on specific routes or the availability of faster shipping options.

While each individual suggestion may yield savings of a few hundred or a few thousand dollars, the cumulative effect across an entire network can be substantial.

Positive Financial Impact

Consequently, when questioned, Sieber readily identified Colgate-Palmolive’s chief financial officer as the executive most satisfied with the benefits enabled by Uber Freight.

“He greatly appreciates the reduction in logistics costs,” Sieber added with a laugh.