The Rise of AI Agents and Their Impact on Retail and Commerce
Broadcaster and tech expert Jonathan McCrea explores the next evolution of AI agents and their potential effects on commerce and small businesses.
By Jonathan McCrea
In a rapidly evolving technological landscape, AI agents are emerging as the next major leap in artificial intelligence. These systems, which go beyond simple chatbots, are now capable of autonomous decision-making, tool use, and complex task execution—potentially reshaping how consumers interact with businesses.
From Chatbots to Autonomous Agents
Early AI models like ChatGPT were limited to text-based interactions. However, recent advancements—such as OpenAI’s o3 model, Deepseek, and Claude Sonnet 3.7—have enabled AI to perform tasks like image generation, data analysis, and even collaborative coding. More strikingly, some models now show their reasoning process in real time (Anthropic research).
The Genie Is Out of the Lamp
Tech giants like Anthropic and OpenAI are building infrastructures where AI agents can connect to any online service via APIs, unlocking unprecedented capabilities. For example, Manus, a Chinese AI agent in closed beta, recently organized 1,000 conference talks into a coherent program in just eight minutes—a task that would take humans hours (Manus AI report).
AI in E-Commerce: A Game-Changer
At a Google Cloud Next event, a demo showcased an AI agent that:
- Identified plants via webcam
- Recommended suitable products
- Booked a planting service
- Negotiated discounts with human managers (Watch the demo).
Meanwhile, Amazon’s Alexa+ and Visa’s partnership with OpenAI hint at a future where AI handles complex purchases and service requests autonomously.
Challenges for Small Businesses
While AI agents promise convenience for consumers, they pose significant risks for small retailers:
- Reduced visibility: Google’s AI Overview already diverts traffic from third-party sites (Search Engine Watch).
- Personalized shopping: AI agents with deep user knowledge may bypass traditional marketing.
Adapting to the AI Era
Businesses must:
- Optimize databases for AI parsing.
- Use schema markup for machine readability.
- Focus on task relevance over keyword matching.
"For agile SMEs, this shift is an opportunity to become ‘preferred suppliers’ for AI concierges," McCrea notes.
For more on AI adoption, visit Get Started with AI.
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About the Author
David Chen
AI Startup Analyst
Senior analyst focusing on AI startup ecosystem with 11 years of venture capital and startup analysis experience. Former member of Sequoia Capital AI investment team, now independent analyst writing AI startup and investment analysis articles for Forbes, Harvard Business Review and other publications.