AI-Powered Unified Commerce: Transforming Retail with Vertical AI Agents
Key Takeaways:
- Agentic AI can enable unified, hyper-personalized commerce
- Customer experience can be transformed with personal service and insights
- As agentic AI use expands, its business value will grow exponentially
- Retail-specific expertise can put agentic AI deployments on the right track
It has now been five years since the onset of the COVID-19 pandemic, and the acceleration in online retail driven by people staying at home continues to be sustained. Forrester research suggests that by the end of the decade, nearly 30% of purchases by American consumers will be made online, and the online U.S. retail market will be worth $1.8 trillion a year - similar to the entire current GDP of Mexico.
Artificial intelligence is playing an increasing part in this growth, with nearly 40% of retail directors stating that they already use AI for some operations. And ultimately, agentic AI will enable unified commerce which brings physical and digital retail together like never before..png?width=1200&height=470&name=Key%20takeaways%20(1).png)
However, to realize the potential of unified commerce, retailers have to address pain points like siloed data, legacy systems and labor shortages that are hindering adoption. This blog explores the future of unified commerce and AI in retail, along with actionable strategies for making it happen.
Why Agentic AI is the Cornerstone of Unified Commerce
So far, agentic AI has been developed and deployed in more general terms, where agents work across a large range of tasks in different fields. This is because they’ve been developed to imitate human capabilities, and handle just about any challenge that is thrown at them.
But where agentic AI becomes more relevant to retail and eCommerce is by moving away from general use cases and towards more vertical-specific AI. This is where systems are designed to serve specialized tasks within an industry; in retail, this can include personalized customer experiences, inventory management, price optimization and customer service support.
Many organizations in retail and other industries are starting to recognize the scale of vertical AI agents’ potential. According to Aim Research, the global vertical AI market was worth $5.1 billion in 2024, but this is projected to reach $47 billion by 2030 and as much as $100 billion by 2032.
Overcoming Barriers to Technology Adoption
All this sounds great in principle, but many retailers are finding that putting agentic AI into practice for unified commerce is easier said than done. Two main barriers stand in their way:
Integrating Siloed Data
Fragmented data systems often develop over the years, which lead to data silos that prevent insights being generated and shared in real time. Breaking these down needs a concerted effort across an entire retail organization, with everyone working towards full data integration and centralization. That way, everyone can work with accurate, current information and contribute to a unified strategy.
Change Management in the Workforce
Human beings can be naturally resistant to change, and that often applies to digital transformation in the workplace, where the prevailing attitude can be “if it ain’t broke, why fix it?”. This is why change management is so important, as it enables a phased approach to implementing technology, with full training and well-defined metrics allowing employees the chance to adjust gradually. Agentic AI can also be used for education and guidance along the way.
AI in Travel Retail Technology: A Blueprint for Success
The travel industry has already started to adopt agentic AI on a wide scale, and provides a great example of how the technology can be applied to retail more widely.
AI agents have been able to hyper-personalize travel experiences, by analyzing customer preferences and purchase histories to understand what individual customers would prefer. Being able to act autonomously, these agents can then create tailored itineraries and make all the required bookings, without the need for any staff or customer intervention.
The same technology can also be used to:
Future-Proofing Retail with AI Agentic Networks
The growth of agentic AI can be observed from the perspective of Metcalfe’s Law, which states that the value of a communications network is proportional to the square of the number of connected users within it. This means that as more users join a network, the value of it increases exponentially, not only in pure financial terms, but in the context of the business and customer experience value that it drives.
In the context of AI in retail, the more customers using a platform and contributing data, the more data agentic AI algorithms can learn from and the greater the performance that it can deliver. This becomes a virtuous circle, where customers gain from ever-increasing levels of customer support, insights and AI-driven personalization; word gets round about the quality of the service provided; and even more customers are attracted to it as a result.
In Summary: Actionable Strategies for Agentic AI in Retail
Making a success of agentic AI in retail will be critical, as more and more retail organizations explore and adopt the technology. But this success won’t happen overnight: it needs careful planning and well-chosen adoption of the technology in the right areas.
Nevertheless, now is the time to start on the agentic AI journey if your organization hasn’t done already, by exploring the following:
Pilot Vertical AI Agents:
Start with highly focused use cases that can deliver immediate and quantifiable improvements. Explore A/B testing to measure agentic AI performance against traditional approaches, and track progress with continuous monitoring.
Measure ROI:Partner with Experts on AI in Retail:
Track a range of metrics, including tangible figures like revenue growth and margin improvement, and softer measures like employee productivity and customer satisfaction.
Partner with Experts on AI in Retail:
Work with a retail AI expert like Ciklum, that can leverage retail-specific large language models for applications such as pricing automation and competitor monitoring, while navigating industry terminology, regulations and business logic.
To find out more about the potential of agentic AI in retail, get in touch with the Ciklum team today to discuss your specifics.
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