Embedded AI Could Reshape Commerce With Practical Solutions, Experts Say

Forget robot cashiers and drone deliveries. The real artificial intelligence (AI) revolution in retail and logistics is happening behind the scenes, and it’s all about making shopping smoother and shipping brighter.

From predicting what customers want before they click “buy” to slashing paperwork at customs, AI is quietly transforming how businesses operate. These aren’t futuristic concepts — they’re tools being deployed right now, saving time and money for companies big and small.

“We’re on the cusp of seeing AI truly embedded in core business processes,” Scott Dylan, founder of NexaTech Ventures, an AI venture capital fund, told PYMNTS. “These shifts are not hypothetical; they are already underway, and their impact will only grow.”

The retail sector, which accounts for trillions in global economic activity, has been under pressure to innovate in recent years. Ecommerce giants have set new standards for convenience and personalization, while brick-and-mortar stores need help changing consumer habits. Logistics companies, meanwhile, face increasing demands for faster, more efficient deliveries in an era of global supply chains.

AI’s next big practical application in industries like retail and logistics will likely focus on streamlining operations through better data management and automation, Emeka Nwosu, SVP solutions engineer at VTEX, told PYMNTS. 

“While AI has already shown potential, a major challenge remains: much of the data sources that companies pull from — websites, customer interactions, supply chains — often come in different formats with inconsistencies and are messy and unstructured,” Nwosu said. “Without properly formatted and reliable data, even the smartest AI tools struggle to deliver useful insights, making it hard for companies to unlock AI’s potential fully.”

The integration of AI in supply chain management and inventory optimization marks a shift in retail operations. Advanced algorithms now analyze vast amounts of data from multiple sources to predict demand more accurately.

“By analyzing purchasing trends, seasonality, and external factors like market conditions, AI ensures that inventory levels are optimized in real time, improving cash flow and reducing waste,” Dylan said.

This capability addresses a longstanding challenge in retail: balancing inventory to avoid stock-outs and overstock situations. Traditionally, retailers relied on historical data and human intuition to make inventory decisions. AI systems can process various variables, from social media trends to weather forecasts, potentially leading to more accurate predictions.

Document processing in logistics has emerged as another area of innovation. Max Vermeir, senior director of AI strategy at intelligent automation company ABBYY, told PYMNTS, “In transport and logistics, the most impactful utilization of AI capabilities lies with access and understanding of data, which in most cases is trapped in paper and manual processes.”

Vermeir points to brewery giant Carlsberg as a case study. The company implemented AI-powered intelligent document processing to read and process purchase orders automatically. “In Sweden alone, the company saved 140 hours a month, with 92% of orders needing no human intervention,” Vermeir said.

Alex Saric, a procurement expert and CMO at Ivalua, told PYMNTS that companies can stay agile and better analyze vast amounts of data to improve efficiency and decision-making by leveraging AI. 

For example, he noted that GenAI slashes the time required to perform manual tasks such as content creation, contract reviews, and supplier research. 

“Automating these processes will make procurement more effective while also allowing teams to focus on more crucial tasks like mitigating risk, improving sustainability, and ensuring regulatory compliance with AI’s data-driven support,” he added.

AI is also reshaping customer interactions. Dylan explained that AI-driven tools can handle routine customer queries 24/7, allowing human staff to focus on more complex issues. “This enhances the customer experience and significantly reduces response times and operational costs,” he added. 

The global chatbot market is expected to grow quickly in the coming years, with some industry reports projecting a compound annual growth rate of over 20%. This growth reflects the sophistication of AI language models, which can now handle more nuanced conversations and even detect customer sentiment.

In marketing, AI enables more precise personalization. Machine learning algorithms analyze customer behavior across multiple touchpoints, facilitating highly targeted campaigns and product recommendations.

The technology is advancing rapidly. Dylan envisioned AI tools autonomously managing end-to-end digital campaigns “from audience segmentation and ad creation to placement and real-time performance adjustments — without requiring constant human oversight.”

This level of automation represents a shift in digital marketing. Traditional approaches often involve manual campaign optimization, a time-consuming process that can struggle to keep pace with changing consumer behavior. AI-driven systems can potentially respond to market shifts in real time, adjusting strategies on the fly.

This personalization extends throughout the customer journey. “Automation ensures the right messages are sent to the right people at the right time, whether through targeted emails, social media ads, or personalized website experiences,” Dylan said.

The biggest near-term changes in commerce are expected to come from practical AI applications that address real business problems. From supply chain streamlining to personalized customer experiences, AI is redefining core operations in retail and logistics.

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