For many B2B organizations, the promise of digital transformation still feels just out of reach. Companies have invested heavily in eCommerce capabilities, expecting modern platforms to streamline operations and strengthen customer relationships. Yet the reality on the ground tells a different story: one where digital investments often create as many challenges as they solve.
The numbers tell a paradoxical story. According to Sana Commerce research, 73% of B2B buyers strongly prefer buying online, yet 92% of B2B leaders have at least one frustration with their own eCommerce tool. Even more concerning, Shopify’s B2B research reveals that 74% of B2B buyers globally would switch suppliers for a better online experience.
The problem isn’t a lack of technology. Quite the contrary: it’s too much of it. Shopify found that companies often rely on as many as eight disconnected applications, creating inefficiencies that frustrate teams and customers alike. More platforms haven’t solved the problem; they’ve become the problem.
Gartner predicts that 80% of all transactions will take place online by 2025, and, because of that, companies need a fundamentally different approach. They need autonomous systems that orchestrate complexity rather than multiply it and use AI agents to make decisions rather than just collect data. Simply put, they need to put process control at the center.
Platforms like Emporix’s Autonomous Commerce Execution (ACE) represent this paradigm. Instead of adding another tool to the stack, autonomous commerce platforms provide the orchestration layer that makes existing investments work together intelligently.
Key takeaways
In a nutshell, in B2B commerce, adding more platforms creates complexity. Adding orchestration creates capability.
The critical insights
1. Orchestration over accumulation: 72% of US retailers have adopted composable commerce, but face orchestration overhead. Autonomous commerce platforms provide centralized coordination that manages the platforms you already have.
2. AI agents execute rather than just assist: True autonomous agents make decisions and take actions without human intervention. The AI agents market in eCommerce will grow from $7.7 billion in 2024 to $282.6 billion by 2034.
3. B2B complexity is a feature: Custom pricing, approval workflows, contract terms, and buyer hierarchies require orchestration rather than simplification. Autonomous platforms embrace this through semantic data layers and value stream orchestration.
4. Speed through autonomy: Organizations achieve 60-70% faster time-to-market through no-code process control and business-led optimization. Changes that historically took quarters now happen in days.
5. It’s happening now: ChatGPT alone processes 53 million shopping queries daily. Traffic from GenAI browsers increased 4,700% year-over-year. Payment networks are building agent transaction infrastructure.
6. Market momentum: Gartner predicts that 80% of B2B sales will occur online by 2025. Meanwhile, 74% of B2B buyers would switch suppliers for better digital experiences. Organizations that master orchestration now will lead their markets.
The deep dive: why platform sprawl is killing B2B commerce
B2B organizations have been solving complexity by adding specialized tools for each function. According to a Zaelab case study, one global electrical manufacturer relied on eight disconnected applications. Managing these systems was time-consuming, and inconsistent experiences damaged customer relationships.
Tony’s Chocolonely put it bluntly: “We were spending more on maintenance and bug fixing than on new features for customers.” Each integration creates failure points and introduces maintenance burden, which in turn requires specialized knowledge. As the result, development teams spend more time maintaining integrations than building new features.
The composable commerce movement recognized the monolithic platform problem. By March 2023, 72% of US retailers had already implemented composable solutions. But composable commerce introduced a new challenge: orchestration complexity. Who manages the interactions between your PIM, CMS, search engine, payment processor, and ERP? Who maintains the business logic spanning multiple services?
The answer is usually custom code. Lots of it. The flexibility gains from composable architecture get consumed by integration overhead. This is particularly problematic for B2B commerce, where business logic is complex and constantly evolving. Aspects like:
- custom pricing matrices,
- multi-level buyer hierarchies,
- approval workflows,
- contract-based purchasing
don’t fit neatly into disconnected services.
The Sana Commerce research found that 40% of B2B buyers experience frustration with lack of web store information on basic data like stock, pricing, and delivery dates. Companies do have this data, but it lives in multiple systems that don’t communicate effectively.
What is autonomous commerce execution?
Autonomous commerce execution combines three foundational elements that traditional platforms miss:
Commerce orchestration provides centralized control of business processes through value streams. Instead of hard-coding process logic into individual services, you define processes centrally and let the orchestration engine coordinate service interactions. Business teams can continuously modify and optimize processes without IT delays.
Agentic commerce intelligence uses AI agents to make autonomous decisions that accelerate processes without human intervention. These aren’t simple chatbots. They’re intelligent agents that monitor conditions and execute actions based on their judgement. McKinsey research indicates that agentic commerce could move even faster than prior web and mobile revolutions because agents can traverse the same digital paths as humans.
Embedded integration connects enterprise resource planning (ERP), product information management (PIM), and third-party systems through an integration platform as a service (iPaaS) layer, which eliminates complex interface projects. Rather than building custom integrations for each service connection, you use pre-built connectors.
The AI agents market in eCommerce is expected to surge from $7.7 billion in 2024 to $282.6 billion by 2034, growing at a compound annual growth rate (CAGR) of 54.7%. This reflects real business value from autonomous decision-making at scale.
Real-world AI agents in B2B commerce include:
- dynamic pricing agents that adjust based on inventory and demand.
- approval routing agents that determine appropriate chains based on transaction characteristics.
- inventory optimization agents that predict stockouts.
- customer segmentation agents that analyze behavior patterns.
How autonomous commerce solves real B2B problems
1. It eliminates tool sprawl through orchestration
Autonomous commerce platforms solve fragmentation by providing an orchestration layer above individual services. Your ERP software remains your system of record. Your CRM system manages customer relationships. Your PIM system holds product data. However, now a single orchestration engine manages how these systems interact.
When a customer places an order, the orchestration engine:
- validates product availability in your ERP.
- checks customer credit terms in your CRM
- applies contract pricing from your agreement management system.
- routes approval requests based on order characteristics
- reserves inventory.
- creates the order.
- initiates fulfillment.
- updates all systems consistently.
It all happens through automated workflows rather than custom integration code.
Tony’s Chocolonely achieved 2.5x faster site performance after implementing unified commerce and supported both B2B and direct-to-customer (DTC) across six global markets while spending less on maintenance.
2. It makes complexity manageable
B2B commerce complexity is infinite by nature. Products can be sold by weight, dimension, volume, pallet, or any other measure. Pricing varies by customer segment, contract terms, and volume thresholds. On top of that, approval chains differ based on order value and product category, or customer status.
Autonomous commerce platforms make this manageable through three mechanisms:
Semantic data layer provides a unified database that connects systems, processes, and teams. Rather than dealing with different data models in each system, you work with a semantic layer that maintains consistent meaning across platforms.
Value streams for complex processes let you define parallel processes visually with conditional logic. When business rules change, you update the value stream definition rather than modifying code in multiple places.
Native B2B capabilities include support for scenarios that are edge cases in B2C but core requirements in B2B. For instance, product catalogs handle items sold by weight without custom development. Pricing engines, on the other hand, support customer-specific rates and discounts and contract pricing simultaneously.
3. It speeds up without dumbing down
Salesforce research found that 63% of business buyers say most customer experiences fall short of what they know is possible. Companies can’t move fast enough to meet evolving expectations while maintaining the sophistication their business requires.
Autonomous commerce breaks this tradeoff through no-code process modeling that lets business teams create and modify processes without IT support. Pre-built value stream libraries provide templates for common commerce processes, while AI-assisted process generation creates templates from natural language descriptions.
As a result, traditional implementations that used to be measured in quarters shrink to weeks or days. The same platform that enables rapid deployment supports intricate business rules through orchestration and configuration rather than custom development.
4. It enables true autonomous operations
The ultimate goal autonomous commerce is operations that run intelligently without constant human intervention. Consider a typical B2B scenario: a customer’s regular order is placed through an API integration. This kicks off an entire automated chain of events:
- Autonomous commerce enables the inventory agent to check availability and reserve stock at the optimal fulfillment center.
- A pricing agent applies contract pricing and promotions,
- A credit agent verifies credit terms.
- An approval routing agent determines if no manual approval is needed, based on customer history.
- A fulfillment agent initiates picking.
- A communication agent sends confirmation.
This all happens within seconds without human intervention.
Cisco research projects that 68% of all support interactions with technology vendors will be handled by AI agents by 2028. Research shows that AI-powered systems can handle up to 90% of repetitive queries, operating 24/7 without fatigue.
The business case for efficiency over expansion
Traditional growth strategies follow a predictable pattern: add capacity to handle increased volume. More transactions mean more staff, while more customers mean more support team members. As commerce grows exponentially, this linear scaling model becomes unsustainable.
Autonomous commerce offers a different path: optimize existing resources rather than expanding capacity. If autonomous systems handle even 70% of routine decisions, the remaining 30% requiring human attention can be managed by specialized teams focused on exceptions.
BCG research found that traffic to US retail sites from GenAI browsers and chat services increased 4,700% year-over-year in July 2025, and these users spend 32% more time on sites, browse 10% more pages, and have a 27% lower bounce rate. Organizations using autonomous commerce platforms can adapt to these new behaviors quickly.
The benefits are quantifiable. Tony’s Chocolonely’s experience illustrates the total cost of ownership improvement: they’re spending less on maintenance and more on customer features while achieving 2.5x faster performance. Autonomous systems execute business rules consistently, reducing revenue leakage from pricing errors and ensuring contract terms are applied correctly.
Beyond operational benefits, autonomous commerce creates strategic advantages. When competitors change pricing, you can adjust rules and workflows immediately. Likewise, when customer segments emerge with unique requirements, you can create customized processes in days. The B2B commerce market reached $18.8 trillion globally, eclipsing B2C eCommerce. Organizations with flexible, orchestrated architectures can adapt to market evolution without platform migrations.
The future is already here
The shift to autonomous commerce isn’t a future possibility; it’s happening right now. According to eCommerce pioneer Scot Wingo, ChatGPT fields 2.5 billion prompts per day, with about 2.1% being shopping-related. This amounts to a whopping 53 million shopping queries daily. Even at conservative 5% conversion rates, this could generate between $73 billion and $292 billion in annual gross merchandise volume.
BCG reports that more than half of consumers anticipate using AI assistants for shopping by the end of 2025. Major platforms are embedding comprehensive commerce functionalities. For instance, OpenAI launched “Buy it in ChatGPT,” while Google announced “AI mode shopping.” Mastercard, on the other hand, announced Agent Pay technology, which allows verified AI agents to make transactions on behalf of consumers and businesses.
Consumer trends inevitably bleed into B2B expectations. Shopify research found that 67% of online business buyers have switched suppliers in search of a more consumer-like experience. As AI assistants become routine in personal shopping, B2B buyers will demand similar experiences.
The implications extend to agent-to-agent transactions, where buyer’s AI agents negotiate with seller’s AI agents. Such protocols, for instance, Anthropic’s Model Context Protocol, Agent-to-Agent Protocol, Agent Payments Protocol, and Agentic Commerce Protocol, are already emerging to enable agent interactions.
As agents proliferate, orchestration becomes critical.
- Who defines acceptable pricing ranges?
- Who enforces contract terms?
- Who ensures regulatory compliance?
The orchestration layer plays a large part in answering those questions. It maintains business logic centrally, provides governance and auditability, enables continuous optimization, and manages exceptions requiring human review.
Implementation: start smart and scale fast
Before implementation, assess readiness across several dimensions.
- Does your infrastructure support API-first integration?
- Are your processes well-documented?
- Will teams accept AI agents making routine decisions?
Understanding your integration landscape helps scope implementation effort.
Research indicates that 81% of B2B companies already invest in AI technology, with 79% committed to ramping up investment. That said, successful implementations rarely involve complete platform replacement overnight.
Start with your highest-pain process. For instance, if quote approvals are your biggest bottleneck, implement orchestration there first. In other words, prove value in a contained scope before expanding.
Next, add an orchestration layer without replacing everything. Your existing platform continues handling transactions while the orchestration layer manages complex workflows. This will expand value stream by value stream, delivering incremental business value.
Next steps
As your first step toward autonomous commerce, you should audit your current commerce stack. How many systems, how many integrations, how much maintenance overhead is there? Map your highest-friction processes to prioritize where autonomous commerce delivers fastest ROI.
Next, assess AI readiness around data and process quality and infrastructure capabilities. Explore autonomous commerce platforms like Emporix ACE and other MACH-compliant solutions. Finally, partner with implementation experts who understand process change management, and technical integration.
The autonomous commerce transformation is underway. Organizations that master orchestration and autonomy now will lead their markets. Those that continue adding platforms without orchestration will struggle under mounting complexity. The choice isn’t whether to adopt autonomous commerce anymore. Now, it’s whether to lead the transformation or react to it after competitors have captured advantage. The technology is ready, and the market is moving. Is your organization ready to operate smarter, not bigger?
Ready to make your commerce operations autonomous? Our digital commerce experts can assess your readiness, map your highest-priority processes, and design a phased implementation roadmap that delivers measurable ROI. Get in touch with our experts, and let’s talk about the best way forward for your business.