The future of AI-driven manufacturing and B2B ecommerce

In this second article of a two-part series on how artificial intelligence is transforming manufacturing and B2B ecommerce, BigCommerce’s Lance Owide looks ahead to the emerging trends that will define the next phase of artificial intelligence (AI) adoption.

In part one, Lance Owide, General Manager of B2B at BigCommerce, discussed the current applications of AI in manufacturing—from predictive forecasting to logistics optimisation—and shared practical advice on how manufacturers can get started. 

How AI is transforming customer experiences, reshaping sales roles, and setting the stage for full automation

AI is no longer a future concept in manufacturing—it’s already embedded in everyday operations, from sales assistance to inventory optimisation. But according to Owide, we’re still only scratching the surface. In the near future, AI is expected to take on even more complex roles, reshaping how manufacturers sell, deliver and support their products—while also changing the roles of the people behind the scenes.

In part one, Owide explored the tangible, near-term benefits of AI in manufacturing. Now, he looks ahead to the transformative trends already emerging and the structural shifts that lie just over the horizon.

From static portals to dynamic buying experiences

One of the most exciting frontiers for AI, according to Owide, is in reshaping the B2B customer journey. Traditionally, B2B e-commerce portals have offered the same static experience to every buyer. But AI is enabling dynamic personalisation at scale.

“Today, a lot of manufacturers sell online through a basic portal,” Owide said. “But we’re now seeing dynamic content being generated based on who the buyer is—what region they’re in, what they typically purchase, or even what they’re searching for in real time.”

That level of personalisation is beginning to rival B2C experiences and is expected to become the norm in B2B. BigCommerce customers are already experimenting with these capabilities, allowing buyers to see different product assortments, pricing structures, and recommendations based on their unique profiles and behaviours.

Toward fully automated quote-to-cash systems

As AI technology matures, some manufacturers are already automating the entire quote-to-cash process. While these systems are still in their early stages, the foundation is being laid for a future where AI agents handle everything from quoting and negotiation to order fulfilment—without the need for human involvement.

“Some of our customers today already allow buyers to get a quote and negotiate in real time with a bot,” Owide explained. “It’s impressive—but it’s still only one side of the equation. When we see both the buyer and seller using AI agents to transact, that’s when we’ll hit full automation.”

He believes we’re just a few years away from this kind of interaction becoming mainstream—especially as the tools become more sophisticated and businesses grow more comfortable placing AI at the centre of transactional workflows.

What happens to the sales rep?

This shift inevitably raises questions about the future of traditional B2B roles—especially sales. But Owide is quick to push back against the idea that AI is a job killer.

“The biggest misconception I hear is that AI will replace jobs,” he said. “In fact, AI is going to enhance jobs—especially for sales reps.”

Rather than spending time processing orders or responding to quote requests, reps can focus on building relationships, exploring cross-sell and upsell opportunities, and delivering strategic value to customers. As AI takes over the repetitive, low-value tasks, human salespeople are freed up to become more consultative and proactive.

“It’s a return to what B2B selling should be—more human, more strategic,” Owide noted. “Salespeople should be in the field, building relationships, not stuck behind a desk chasing paperwork.”

Getting the infrastructure right

While the promise of AI is compelling, its success depends heavily on foundational readiness. According to Owide, many manufacturers still face significant obstacles in their data infrastructure.

“You can’t do any of this without clean, structured data,” he emphasised. “If your systems don’t talk to each other or if you’re using a homegrown ERP with no cloud access or APIs, then you’re simply not ready for real-time AI.”

The prerequisites for AI success include integrated, cloud-based systems, centralised data governance, and well-maintained customer and product data. Only then can manufacturers begin layering in AI tools with confidence and clarity.

Beyond the technical requirements, organisational alignment is equally important. Owide recommends that AI initiatives be aligned with clear business goals—whether that’s driving revenue, reducing costs, or improving customer satisfaction—and championed by internal stakeholders who can advocate for iterative, test-and-learn implementation.

Democratising access to AI

Another common misconception Owide encounters is the belief that AI is only for large enterprises with vast budgets and IT teams. That’s no longer true.

“With platforms like BigCommerce, AI capabilities—like product recommendations and CPQ (Configure, Price, Quote) automation—are available to businesses of all sizes,” he said. “Anyone can start using AI today. It’s not just for the big players anymore.”

Off-the-shelf tools, cloud-based applications, and no-code platforms are rapidly lowering the barriers to entry. The key is knowing where to focus efforts for the greatest business impact and making sure the foundational data and systems are in place.

A bold prediction: AI as the manufacturing orchestrator

Looking ahead to 2030, Owide envisions a world where AI does more than assist—it orchestrates. He predicts that AI systems on both the buyer and manufacturer side will communicate directly, exchanging real-time data on demand, inventory, raw materials pricing, and even labour availability.

“The gap between the manufacturer, the distributor, and the end customer is going to shrink dramatically,” he said. “Manufacturing will become dynamically responsive to real-time signals from buyers and the market.”

In this vision, manufacturers don’t wait for orders—they anticipate them. Factories adjust production schedules on the fly, based on real-time demand data flowing in from customer-facing AI systems. The result? Less inventory waste, faster fulfilment, and more efficient allocation of resources.

While Owide admits this level of orchestration may still be a few years away, he believes early adopters are already laying the groundwork—and those who embrace the shift will gain a serious competitive edge.

Conclusion: embrace the change, start small

The transformation AI is driving in manufacturing and B2B e-commerce is both exciting and complex. But for Owide, the message is clear: AI is not a luxury—it’s a necessity. And the best way to embrace it is with a deliberate, phased approach.

“Start small, align with business goals, and make sure your data is ready,” he advised. “AI isn’t going to replace your team—it’s going to make them more effective. The companies that realise that first will be the ones who win.”