Today marks Labor Day in the United States — a time when people relax and prepare for the upcoming fall season. As we enter the final quarter of 2025, it's an opportune moment to reflect on what has been widely predicted as "the year of AI agents."

With three quarters behind us, the AI agent landscape has indeed evolved at breakneck speed, particularly in sectors like AI coding agents (remember the Windsurf drama?). As innovators and practitioners in the AI shopping agent and agentic commerce space, we've built three LLM-based AI shopping agents and empowered numerous others throughout this transformative year.

Based on our hands-on experience and market observations, here are three predictions that will shape the future of AI shopping agents and agentic commerce.

1. Agentic ecommerce ecosystem has really come into play in 2025. AI shopping agents, Large Language Models, payment companies, commerce tools are actively collaborating to transform digital commerce. Brands and retailers should step up now, design a strategy to serve AI shopping agents well and grab agentic commerce opportunities.

The agentic ecommerce ecosystem has truly come into its own in 2025. AI shopping agents, large language models, payment companies, and commerce tools are actively collaborating to fundamentally transform digital commerce. Brands and retailers should step up now, design a strategy to serve AI shopping agents well, and grab agentic commerce opportunities. Execution is now essential.

Throughout 2025, we've partnered with numerous AI shopping agent startups, each bringing unique value propositions: including personal styling assistants, virtual shopping avatar shopping,intelligent gift recommendation systems such as Giftly, and advanced price discovery tools such as AI Price Hunter.

Some AI shopping agents provide comprehensive end-to-end shopping journeys, while others focus on specialized point solutions. We're even seeing traditional publishers and content creators integrate AI shopping agents with checkout capabilities, creating seamless experiences for their audiences.

The payment ecosystem has embraced this transformation wholeheartedly. Major players including Visa, Mastercard, and PayPal all announced significant agentic commerce initiatives in Q2, driving innovation in payment processing for AI agents. Meanwhile, LLM foundation model companies continue advancing their agentic capabilities — ChatGPT Operator being such an example.

Our CloudStore AI products exemplify this ecosystem evolution, providing AI shopping agents with comprehensive fashion and sports ecommerce capabilities including catalog management, checkout processing, logistics tracking, and visual search APIs.

Despite this progress, many brands and retailers have remained on the sidelines due to economic uncertainties and trade policy fluctuations throughout 2025. As market conditions stabilize, this hesitation represents both a risk and an opportunity.

The agentic commerce transformation will eclipse the impact of the gig economy revolution (think DoorDash, Uber, and Instacart). In the future, brands and retailers may find themselves serving AI superintelligence rather than human customers exclusively (think some retail stores or restaurants which serve gig economy apps exclusively.)

Brands and retailers has a few questions to think, and plan and execute accordingly. How should brands and retailers position themselves to work effectively with AI shopping agents or bots in general? What security and safety protocols are needed for AI agent payments? How can pre-sales and post-sales customer service adapt to serve both human and AI customers?

Brands and retailers must develop comprehensive agentic commerce strategies now to remain competitive.

2. Domain-specific AI agents will dominate over super agents for the next three years

While super agents like Manus generated significant buzz early in 2025 with promises of handling everything from presentation creation to travel booking, our experience suggests a different path forward.

Each domain requires unique workflows, optimization strategies, and performance metrics. Achieving high completion rates, high accuracy, low cost, and low latency demands deep domain-specific optimization that super agents simply cannot provide across multiple verticals simultaneously.

Based on our experience building and empowering AI shopping agents, we're confident that domain-specific AI agents—whether in shopping, coding, or other specialized areas—will deliver the most meaningful business impact over the next three years.

Specialized AI agents can optimize workflows for specific industry requirements, develop deep domain expertise and knowledge bases, integrate seamlessly with existing industry tools and platforms, and deliver measurably performance in their focus areas.

3. The Era of building impactful AI agents and generating sound unit economics has arrived.

The days of burning through venture capital while spinning compelling narratives are ending. The market is demanding AI agents that deliver measurable business impact with sustainable economics.

Over the past two years, we've witnessed impressive fundraising rounds and reports of rapid ARR growth. However, many of these success stories lack fundamental unit economics. Some companies operate with negative gross margins, relying entirely on venture funding to subsidize unsustainable business operations. Market correction is already underway. A recent MIT report revealed that "despite $30–40 billion in enterprise investment into GenAI, 95% of organizations are getting zero return" based on measurable P&L impact.

Business leaders are reevaluating their AI strategies with increased focus on tangible business outcomes. For AI agents to sustain this innovation wave, they must demonstrate clear value and maintain sound unit economics.

We should at least do the following three things and enhance your AI agents' business value iteratively:

1. Conduct Value Assessments: Regularly evaluate your AI agents' value proposition for consumers (B2C) or clients (B2B)
2. Gather Authentic Feedback: Engage with customers directly to understand real impact and areas for improvement
3. Optimize Business Models:
   
   • Consumer applications: Consider advertising (CPM/CPC), commission-based (CPA) or subscription models
   • Enterprise applications: Explore monthly fees, revenue sharing, or usage-based pricing

Looking Ahead: The Future of Agentic Commerce

As we enter the final quarter of 2025, the AI shopping agent landscape is poised for continued evolution. The companies that will thrive are those that combine domain expertise, sustainable business models, and clear value propositions.

The agentic commerce revolution is here. The question isn't whether AI shopping agents will transform digital commerce, but how quickly businesses can innovate to serve this new paradigm effectively.

For those building in this space, focus on creating specialized, valuable solutions with sound economics. For brands and retailers, the time for strategic preparation is now. The future belongs to those who embrace the agentic commerce transformation today.