B2B and B2C companies increase AI investment as agentic commerce gains traction

Artificial intelligence is rapidly becoming a core component of both B2B and B2C enterprise ecommerce operations as companies deploy AI across customer experiences, pricing, inventory management and fulfillment while preparing for the rise of “agentic commerce,” according to new research.

Logicbroker commissioned the study, which Midsail Research and On-Call CMO conducted. The companies surveyed 600 ecommerce decision-makers at enterprises generating between $11 million and more than $1 billion in annual online revenue. The findings indicate AI has moved beyond experimentation and is now embedded across many enterprise commerce systems.

Nearly all surveyed organizations — 95. 5% — reported deploying at least one AI capability in ecommerce. The research suggests companies are increasingly integrating AI not only into digital storefronts but also into the operational systems that manage pricing, inventory and order fulfillment.

Customer-facing applications remain the most common starting point. About half of respondents said they use AI for product discovery, while 48. 5% deploy chatbots and 46. 6% use AI-powered personalization tools to recommend products or tailor digital shopping experiences. Companies are also expanding AI use into back-end commerce operations.

The survey found that 43. 5% of organizations use AI for pricing optimization, 42. 5% for inventory management and 40. 7% for demand forecasting. Another 37. 7% have deployed AI to help route orders across fulfillment networks.

News Agentic commerce faces reality check in B2B ecommerce Mark Brohan | Mar 10, 2026 AI investment spans B2B, B2C companies Researchers describe this shift as a progression from basic discovery tools toward more advanced orchestration capabilities that can manage transactions across complex supply chains.

Many enterprises expect AI to begin playing a direct role in purchasing decisions. According to the survey, 90. 7% of respondents believe AI will influence at least 20% of ecommerce orders by 2027. Meanwhile, 36. 5% expect AI to influence more than half of all transactions.

The shift reflects the rapid rise of AI-assisted product discovery and shopping behavior online. Industry data in the report shows that AI-driven traffic to U. S. ecommerce sites increased 4,700% year over year in July 2025. Researchers estimate conversational AI systems now generate about 53 million product-related shopping queries daily.

Companies are backing those expectations with significant spending plans. Almost half of the organizations surveyed, 47. 3%, said they plan to invest at least $1 million in AI commerce initiatives over the next 12 months. More than one-fifth expect to spend $5 million or more. That includes 7. 3% that anticipate investments exceeding $10 million.

Executives said those investments are primarily driven by measurable business outcomes rather than experimentation. The survey found revenue growth is the top objective, cited by 50. 2% of respondents. Next most-cited: • Improving customer experience (46%) • Reducing costs (45. 5%) • Increasing operational efficiency (44.

5%) News OpenAI shifts checkout plans in its agentic commerce strategy Brian Warmoth | Mar 6, 2026 What companies expect when it comes to ROI from AI Despite the scale of planned investments, many companies expect quick returns. About 45% of respondents said they anticipate a return on investment within 12 months. At the same time, 73.

2% expect ROI within two years. Only 4. 7% said they are uncertain about when their AI initiatives will begin producing results. The research suggests most organizations are taking a pragmatic approach to adoption. 77% of respondents describe their companies as “fast followers” or “measured adopters.”

That indicates they are pursuing AI deployments tied to operational improvements rather than experimental technology initiatives. Organizational support for AI appears strong, but many companies face significant technical challenges in expanding deployments. 42.

5% of respondents cited security and privacy concerns as a major barrier, followed by data quality issues (40. 2%) and integration complexity (36. 3%). By comparison, only 12% of respondents identified lack of executive support as a major obstacle.

The primary challenge, according to the report, is connecting multiple systems that power modern commerce operations.

Those include: • Customer relationship management platforms • Order management systems • Warehouse management software • Ecommerce platforms • Product information management systems Companies said improved integration tools, better data quality and emerging industry standards could help accelerate adoption.

Deciding which AI capabilities to prioritize As AI capabilities expand, enterprises are increasingly focused on connecting those systems into real-time order networks capable of supporting automated transactions. The survey found 67. 2% of respondents consider order-network connectivity either very or extremely important for enabling AI-driven commerce.

Such networks allow AI systems to dynamically route orders across suppliers, warehouses and fulfillment partners based on inventory availability, pricing and delivery conditions. Researchers said this capability will become critical as AI agents begin evaluating suppliers and executing transactions across multiple digital channels.

Enterprises are also adopting multi-platform strategies for the large language models (LLMs) that power many AI systems. The survey found: • 60. 3% of organizations use OpenAI or ChatGPT technologies. • 55. 3% use Google Gemini. • 54. 7% use Microsoft Copilot. • 14. 8% said they are developing proprietary LLMs internally.

The research suggests companies are deliberately avoiding dependence on a single AI provider and instead pursuing strategies that allow interoperability across multiple platforms. Adoption patterns also vary across industry segments. Hybrid organizations serving both B2B and B2C markets accounted for the largest share of respondents at 44. 8%.

That reflects the growing convergence of retail and business commerce models. Varying AI focuses among B2B and B2C companies Retail companies are prioritizing structured product data and AI-driven discovery tools that improve visibility within AI-generated search and recommendation systems.

By contrast, B2B organizations are focusing more heavily on operational capabilities such as automated order routing, supplier management and demand forecasting. Manufacturers are also expanding their use of AI as many move into direct digital sales channels alongside traditional wholesale distribution. The study found 8.

5% of respondents identified themselves as manufacturers currently engaged in direct-to-consumer commerce. For those companies, integrating production systems with ecommerce infrastructure is often a significant technical hurdle.

Connecting enterprise resource planning (ERPs) systems and manufacturing execution systems with digital commerce platforms can be difficult because of fragmented data environments. However, the research suggests manufacturers may gain an advantage by combining production data with AI-driven demand forecasting and inventory optimization tools. About 40.

7% of manufacturers reported deploying AI demand forecasting systems. Meanwhile, 42. 5% use AI inventory management technologies. Forecasting the impact of AI on ecommerce Industry forecasts suggest the impact of AI on commerce could be substantial.

Estimates cited in the report include projections that AI agents could influence $385 billion in commerce activity by 2030, while some analysts predict AI could account for a quarter of U. S. ecommerce sales within the same timeframe. Other projections suggest AI-driven transactions could contribute up to $1 trillion in U. S.

retail revenue by the end of the decade, while global agentic commerce activity could approach $5 trillion. As companies prepare for that shift, many are accelerating deployment of new AI capabilities.

The survey found more than half of organizations plan to introduce AI shopping agents, predictive inventory systems and automated order orchestration tools within the next six months.

Longer-term initiatives include AI-based supplier management systems and autonomous reordering technologies that could allow software agents to identify suppliers, negotiate terms and complete purchases automatically.

Researchers said those developments could gradually reshape how digital transactions occur across ecommerce ecosystems, shifting many purchasing decisions from human buyers to AI systems capable of navigating complex supply networks and executing transactions on their behalf. Sign up Sign up for a complimentary subscription to Digital Commerce 360 B2B News.

It covers technology and business trends in the growing B2B ecommerce industry. Contact Mark Brohan, senior vice president of B2B and Market Research, at mark@digitalcommerce360. com. Follow him on Twitter @markbrohan. Follow us on LinkedIn, X (formerly Twitter), Facebook and YouTube.

Favorite The post B2B and B2C companies increase AI investment as agentic commerce gains traction appeared first on Digital Commerce 360.