AI has become an organizational capability for most ecommerce teams. By automating manual work, teams can focus on more strategic, high-impact projects that require their unique skills and experience.
It’s likely not a surprise that AI is changing ecommerce jobs very quickly: 88% of organizations reported regular use of AI in 2025, up from 78% in 2024, according to Stord’s 2026 State of AI in Ecommerce Report. However, Stord’s research shows that only 7% of ecommerce organizations have a high level of AI maturity.
Having AI tools is one thing; actually knowing how to win with them is another. To get over the adoption hump and scale AI fluency, brands are realizing they can't just buy software. Instead, they have to hire for strategy.
Enter the new MVP of the digital shelf: the AI ecommerce specialist.
Whether you call it an AI ecommerce specialist or an AI ecommerce manager, this new job title is the ultimate bridge between just messing around with basic AI tools and achieving true digital shelf maturity.
Essentially, it’s the role that unlocks AI enablement for your entire team. To see exactly how this shift supercharges team productivity and fuels organizational growth, explore insights from top ecommerce strategists and tech futurists.
AI adds an automation layer across backend functions, from product information management (PIM) to inventory optimization.
Instead of getting bogged down in manual execution, this technology fundamentally changes how digital teams win on the digital shelf. In fact, there are two distinct ways where AI makes things easier.
“If technology just increases worker productivity, then that's giving a person another arm,” says futurist Byron Reese. “With AI, it's giving a person another brain. Anything that device can do, all of a sudden I can do.”
Reese says AI is making work less transactional and more relationship-based. This is something Colette Richards, director of alternative sales and distribution at Barcel USA, is seeing within her organization.
“Machine learning now can tell you what consumers want, what they're looking for, and how they're looking. Why not take advantage of that low-hanging fruit if you know how to harvest it?” she says.
Richards uses selling on Amazon as an example. Amazon has leaned on machine learning algorithms to personalize and accelerate every part of the buying experience. But for brands to really be successful on this channel, human judgment, relationships, and strategic knowledge remain critical, Richards says.
“If we don't begin having these conversations as humans selling to Amazon or learning from people who've worked there, how will all of us ever be successful? And that includes Amazon, because we're still selling to people,” she says.
Going forward, ecommerce organizations will need to embrace AI-human collaboration to make their business more resilient. They will need to embed AI into their organizational design — from data governance and creative execution to campaign activation and the customer experience.
This means rethinking traditional roles and workflows. It calls for a dedicated role to own this process and empower employees to use AI, making an AI ecommerce specialist or manager invaluable.
An AI ecommerce specialist or manager is comfortable with and already skilled in AI-related ecommerce innovations.
Brands can structure this role in different ways, but an AI ecommerce specialist or manager may completely or partly own the systems, processes, and governance that turn AI tools into a key driver of better digital shelf performance.
In an interview on the Digital Shelf Institute (DSI) podcast, “Small But Mighty Team Standing Out on the Digital Shelf,” Zack Rubin, director of ecommerce and marketplace at Zephyr, talks about essential requirements for brands to effectively compete online.
Rubin offers a three-part framework across foundational basics, enablers, and accelerants for building a digital business that could be instructive for shaping a potential AI ecommerce specialist or manager role.
Rubin calls the foundational basics “the starter elements” that you need to begin your ecommerce journey.
Foundational basics include:
Full assortment
Enablers drive customers further down the purchasing funnel, while providing them with a shopping experience that meets their expectations.
Key enablers include:
Quick shipping and fulfillment
“We call it the why behind the buy,” Rubin says of enhanced content. “It's an opportunity to bridge the gap between the experience that customers have in store when they can ask questions, and online when they're looking for just a little bit more information to get over the edge before they convert on that product,” he adds.
Rubin says that accelerants are how you can put the fuel behind the fire and drive your business to the next level.
Notable accelerants include:
“What can be challenging sometimes is that digital appears as an opportunity, but there are so many moving pieces behind the scenes,” Rubin says. “It's an educational process. It's helping folks understand along the way what are the pieces that are needed to succeed within the space.”
Rubin’s framing can help brands think through how to build an AI-enabled, digital business. This framing can also help them organize the core responsibilities of this new ecommerce AI role.
Curious what an AI ecommerce specialist would own in their day-to-day responsibilities?
The role can include data governance, AI change management and enablement, experimentation, and more.
Here are some examples.
You could align this responsibility to the foundational basics Rubin mentions, as good data governance shapes effective assortment, pricing, and inventory management.
An AI ecommerce specialist or manager could serve as the go-between internal data and ecommerce teams, ensuring product, customer, and inventory data is both accurate and relevant. They also can identify data gaps and workflow bottlenecks that prevent ecommerce teams from activating information for the PDP, marketing campaigns, and new channels.
An AI ecommerce specialist or manager can support or oversee cross-functional data and AI governance between ecommerce teams and their various internal and external partners — from internal IT teams to supply chain, retail, and marketplace partners.
Within lean organizations, this role ideally should sit within the ecommerce function and report directly to the head of ecommerce. This is one way to make AI an embedded ecommerce capability, rather than a bolted-on function.
Large global brands may consider placing an AI ecommerce specialist or manager within an AI Center of Excellence (CoE). Brands like Johnson & Johnson and Unilever have established CoEs to accelerate AI-led innovation across their operations.
“Many companies are creating AI centers of excellence that offer internal training and rethinking their organizational design to embed AI as a daily co-pilot — not an isolated capability,” according to a review of Salesforce’s 2025 Consumer Goods Industry Insights Report by Kantar, which provides industry insights on brand growth.
An AI ecommerce specialist or manager can build AI literacy across the organization, using their deep knowledge of ecommerce to create role-based training for marketers, customer service teams, and ecommerce managers. This training could involve how to write effective prompts, assess AI outputs for accuracy, and teach other methods for responsible AI use.
This role could define and shape AI-human collaboration, identifying the best internal opportunities to save staff time with AI-driven automation and when it’s critical to keep a human in the loop in the decision-making process. They could also share best practices across the organization, operationalizing how AI is integrated into daily workflows.
This role also could lead the charge in creating a test-and-learn culture.
An AI specialist or manager can identify and test new use cases, track success metrics, and develop recommendations for how a brand can adapt its AI use to improve customer engagement, growth, and profitability.
Richards says her team has set up different KPIs to track its ecommerce performance, including scorecarding its product content to improve searchability and the quality of product descriptions.
This is just one example of a metric an AI specialist or manager could track and own, comparing baseline metrics to metrics post-AI implementation to see how the technology improved performance or shortened time to market for PDP launches and updates.
Lauren Livak Gilbert, executive director of the DSI, says ecommerce organizations also should look at AI metrics from another lens.
“AI requires HR teams to take a step back and evaluate what performance metrics will drive the behavior they want inside their organizations,” Livak Gilbert says.
To Livak Gilbert’s point, organizations must define key metrics that will inform how their teams work and contribute to the business’s success. In this case, they can set KPIs to continually assess their ecommerce AI maturity.
If they truly hope to make AI an embedded capability, they must understand how ecommerce teams are using AI tools today and develop a strategy for how to grow AI adoption in ways that drive key business outcomes.
It’s always helpful to think of AI as a complement to human knowledge and ingenuity.
As Reese says, AI is essentially a productivity tool, one that will remake most work from a transactional exchange to a more strategic, outcomes-driven discipline.
"The only way to find out what these technologies are going to be is to use them,” Reese says. “Technology creates jobs at the top, destroys ones at the bottom, and we all shift up a notch.”
As AI becomes table stakes in ecommerce, more brands will need a defined AI strategy they can execute against. An AI ecommerce specialist or manager will play a pivotal role in getting ecommerce teams more comfortable with AI and empowering them to use the technology as their ultimate copilot.