Using AI to streamline global supply chains

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In an era where artificial intelligence is transforming industry, Robo AIThe global fintech company is leveraging AI technology to help organizations manage their supply chains.

The company's approach to spend analysis and procurement optimization has attracted the attention of large corporations looking to improve operational efficiencies and reduce costs in an increasingly complex global marketplace.

“The primary business problem we were trying to solve was getting 360-degree visibility into spend data for a large organization.” Nitin Upadhyaythe company's chief data innovation officer told PYMNTS.
“RobobAI leverages AI to rapidly consolidate, categorize and segment vast amounts of spend data, providing insights that would be difficult or impossible to obtain using traditional methods.”

As PYMNTS Previously reportedCompanies are increasingly turning to advanced technologies such as artificial intelligence (AI), automation and blockchain to transform and modernize all aspects of their supply chain processes.

AI-Driven Insights Delivers Savings

The company's AI-driven platform is delivering results for its clients: Upadhyay says that a typical organization spending $1 billion annually on goods and services can realize savings of up to $6 million to $8 million annually by adopting insights generated by the company's platform. These savings come from a variety of areas, including operational optimization, payment restructuring and contract expansion opportunities.

Upadhyay shared the example of a client who identified an opportunity to reduce order volume by 52%, realizing significant cost savings while maintaining operational excellence. He said this level of optimization can be particularly effective in industries with low margins or increasing competitive pressures.

Another client discovered the potential to move 33% of its suppliers to commercial card transactions, streamlining the payment process and improving cash flow management. Insights like this can provide a significant competitive advantage in an economic environment where cash flow is paramount.

RobobAI's platform helped one client identify $98 million worth of contract opportunities from edge suppliers — smaller vendors often overlooked in traditional spend analysis — a discovery that highlights the power of AI to uncover hidden value in areas often overlooked by human analysts.

The company also helps clients tackle the long-standing challenge of unclear spending: In one case, RobobAI's AI-powered analysis uncovered $1 billion in spending with blank invoice entries, providing the client with an opportunity to better understand spending and identify additional cost-saving measures.

Implementing AI in supply chain management is not without challenges. Upadhyay points out that data wrangling – the process of cleaning, structuring, and enriching raw data – remains the biggest barrier to successful AI adoption. “AI can struggle with inconsistent, incomplete, or inaccurate data,” he notes. Overcoming these hurdles requires sophisticated techniques and tools, especially when dealing with large, complex datasets from multiple sources.

This challenge is particularly acute in supply chain management, where data often comes from numerous systems, suppliers and geographies. RobobAI's success in this area speaks to the sophistication of the company's AI models and data processing capabilities.

Another key issue is scalability: as datasets grow in size and complexity, AI systems must be able to process and analyze data efficiently without performance degradation. To meet this challenge, RobobAI has invested heavily in developing a scalable infrastructure, enabling it to serve large, global organizations with complex, multi-tiered supply chains.

The company also has to contend with unstructured data, such as text, images, and video, which requires more advanced AI techniques to analyze effectively. By developing natural language processing and computer vision capabilities, RobobAI is expanding the types of data it can analyze and providing more comprehensive insights to its customers.

The Future of AI in Supply Chain Management

Recent geopolitical tensions, trade disputes and The conflict in Ukraine has exposed the fragility of traditional supply chain models.Extreme weather caused by climate change is making logistics operations even more complicated around the world. Companies are increasingly adopting AI-based tools to improve forecasting accuracy. and risk management.

AI has the potential to crunch massive amounts of data and identify patterns that humans might miss, which could be crucial for predicting disruptions and optimizing operations in real time. But observers say the transition to an AI-driven supply chain will be difficult.

As AI continues to evolve, RobobAI is looking to expand its offerings. The company plans to provide direct access to AI models to help customers more easily leverage their financial and procurement data. This move toward democratizing AI capabilities could accelerate the adoption of AI in supply chain management across industries.

Upadhyay also sees a trend toward more specialized, “off-the-shelf” AI models tailored to specific markets and industries. This approach could lower the barrier to entry for smaller organizations or those in niche industries, expanding the market for AI-driven supply chain solutions.

The impact of AI on the workforce is a topic of ongoing discussion across many industries. At RobobAI, the adoption of AI has created opportunities for growth and new employees.

“The new initiatives we are developing will give staff an opportunity to learn new skills and build employee sentiment,” Upadhyay said.

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