Over the past year, many of the conversations we’ve had with eCommerce leaders have come back to the same theme: AI feels full of promise but overwhelming in practice. Everyone can see what AI could do for their business, but no one’s quite sure where to actually start. Whether it’s merchandising, personalisation or operational support, brands are struggling to move from experimentation to measurable commercial outcomes.
AI is reshaping eCommerce faster than any previous technology shift. New tools are becoming available almost weekly, while platform-native AI capabilities are evolving rapidly across Adobe Commerce/Magento, Shopify, and BigCommerce. And surrounding these core platforms is an increasingly powerful ecosystem of AI-driven third-party plugins and extensions, from search and merchandising optimisation to personalised product recommendations, dynamic pricing, content automation, and AI-powered customer service tools.
The opportunity is significant, but so is the risk of moving too slowly, investing in the wrong direction, or stitching together tools that don’t deliver real commercial value.
This is where the right agency partner makes all the difference.
Our Williams Commerce team of eCommerce specialists work with AI every day , advising how and where it can drive revenue, efficiency, and experience improvements right now. We’re helping clients work out which AI tools actually solve their specific problems, and which ones are just adding complexity. Because it’s not about chasing every new tool. It’s about applying AI intelligently, inside real storefronts, real customer journeys, and real business constraints.
In this paper, we explore where AI is driving measurable impact in eCommerce today, and how businesses can adopt it sustainably and with confidence.
The Current State of AI Adoption in eCommerce
AI adoption in eCommerce is building at pace, but the ways in which eCommerce businesses are applying it differ significantly.
- Most retailers are experimenting, but fewer have fully embedded AI into core operations.
- The biggest blockers we see are: knowing where to start, choosing the right tools, and aligning AI to commercial goals.
- The brands seeing the greatest success are those applying AI to very specific parts of the customer and merchandising experience, rather than trying to “automate everything at once.”
In other words:
The gap isn’t access to AI tools, it’s knowing how to use them well.
This is why platform and integration expertise matters. AI is most impactful when it’s deployed in ways that support conversion, AOV, customer lifetime value, fulfilment efficiency, and brand experience.
“AI has become a core part of almost every conversation we’re now having with clients,” says Tanya Peasgood, Head of Consultancy at Williams Commerce. “Whether we’re speaking with long-standing partners or new prospects, there’s a genuine desire to understand where AI fits, what’s realistic, and where to begin. Our role has evolved; we’re not just advising on platforms and commerce strategy anymore; we’re helping businesses make sense of how AI can support their goals in a practical, sustainable way. Every organisation is at a different stage, and our job is to understand where they are and guide the next step forward with clarity.”
Where AI Is Delivering Real Value Today
Smarter Merchandising & On-Site Search
Many merchandising teams will recognise this picture: endless hours spent dragging products up and down category lists, trying to second-guess what customers want to see first. It’s time-consuming, often subjective, and can change daily. This is where AI is already making a noticeable difference.
A retailer with a large product catalogue was manually resorting key categories every week. Moving to AI-assisted search and automated merchandising within Adobe Commerce immediately reduced that workload, product listings began to shift dynamically based on what customers were actually browsing and buying.
For even more control, we are able to layer in specialist third-party merchandising tools (such as Athos Commerce, Bloomreach, or Algolia) to refine ranking logic around margin, seasonality, stock depth and strategic product priorities.
The result was truly real-time merchandising, relevance improved, product discovery got faster, and the trading team gained back hours previously spent on manual sorting.
Williams Commerce configures and tunes these AI models, so they support commercial priorities like margin, seasonality, and stock depth, not just popularity.
Tanya’s Guidance…
AI Needs Quality Data to Perform Well. If product data is incomplete, inconsistent, or poorly structured (e.g., missing attributes, weak descriptions), AI can only optimise so far.
What this means in practice: You may need to invest some time upfront in cleaning product data. The better the data, the smarter the AI appears
Good news for our clients: Williams Commerce has extensive experience handling data as part of onboarding, so you’re not doing it alone.
“Like any evolving technology, AI performs best when it’s guided and tuned over time. That’s where having an experienced partner makes such a difference. We help ensure AI is aligned to real business priorities and continually adjusted as trading conditions change, so it delivers meaningful results, not just novelty.”
Faster, Consistent Product Content (Shopify)
If you’ve ever watched a content or merchandising team try to keep up with a flow of new products, you’ll know the pressure. Launch days become writing days, and creativity gets replaced by speed and formatting. It’s not that the team doesn’t want to tell great product stories, they simply don’t have the time.
We’ve seen our client’s merchandising teams spending hours producing product descriptions manually. As the catalogue grew, the workload grew with it.
By using Shopify’s AI-assisted product content tools, strong, brand-aligned first draft product descriptions can be generated in seconds, giving writers something solid to refine rather than a blank page to fill.
AI didn’t replace writing, it removed the repetitive, time-consuming part
so the team could focus on:
- Product storytelling
- Customer understanding
- Brand voice consistency
And that’s where the real value is.
Williams Commerce supports clients by:
- Creating brand voice rules the AI can follow
- Designing prompt frameworks that produce consistent outputs
- Building workflows that keep the human touch where it matters
This means content scales without losing identity, and teams spend time where their expertise has the greatest impact.
Meaningful Product Personalisation
More Meaningful Product Recommendations (Adobe Commerce & Shopify)
We’ve all experienced the moment where a site shows recommended products that feel completely random; socks with furniture, hats with cookware. When recommendations miss the mark, they don’t just fail to help; they interrupt the shopping experience.
But when recommendations get it right, it feels effortless, like the store understands your taste, your needs, and where you are in your buying journey.
One lifestyle retailer we worked with had been relying on simple “bestseller” and “customers also bought” rules. This meant every customer saw roughly the same products, regardless of their preferences or history. Engagement was flat, and AOV wasn’t shifting.
After implementing behaviour-driven recommendations, powered by AI from Adobe Commerce and Shopify’s recommendation engine, the shopping experience became much more personal. Customers began seeing products that related directly to:
- What they were browsing
- What they’d purchased before
- What items paired well together
- Their price sensitivity and buying patterns
The outcome felt subtle, but powerful:
A slight increase in product relevance led to more add-to-basket actions, higher AOV, and more returning customers.
This isn’t about AI taking over merchandising.
It’s about AI spotting relationships between products and behaviours faster than a human ever could and surfacing them at just the right moment.
Williams Commerce ensures the recommendation engine is tuned to your commercial goals, such as:
- Promoting higher-margin product lines
- Supporting seasonal sell-through
- Surfacing new arrivals at the right time
- Encouraging repeat purchase behaviours
This is how AI moves from “interesting feature” to revenue-driving capability.
Reducing Customer Service Pressure with AI Assistance
Most customer service teams are stretched. They juggle order questions, stock queries, delivery delays, sizing advice, returns, exchanges, often all at once and coming from different communication channels. When volumes spike, it can quickly become overwhelming, and response times and customer service can suffer. Not because the team isn’t committed, just because the workload is relentless.
One retailer we worked with was handling hundreds of repetitive queries each week:
“Where’s my order?”
“How do I return an item?”
“Does this come in my size?”
The team was spending valuable time typing the same responses, again and again.
By introducing AI-assisted reply drafting and an AI-powered helpdesk assistant, the system now automatically suggests complete, brand-appropriate replies based on order data, product information, and previous conversations.
Most customer service teams are stretched. They juggle order questions, stock queries, delivery delays, sizing advice, returns, exchanges, often all at once and coming from different communication channels. When volumes spike, it can quickly become overwhelming, and response times and customer service can suffer. Not because the team isn’t committed, just because the workload is relentless.
One retailer we worked with was handling hundreds of repetitive queries each week:
“Where’s my order?”
“How do I return an item?”
“Does this come in my size?”
The team was spending valuable time typing the same responses, again and again.
By introducing AI-assisted reply drafting and an AI-powered helpdesk assistant, the system now automatically suggests complete, brand-appropriate replies based on order data, product information, and previous conversations.
Tanya says… “When we introduce AI into customer service, the goal isn’t to replace the team, it’s to support them. We help businesses decide where AI can genuinely make things easier and where a human touch is essential. By setting tone, escalation rules and reviewing performance over time, we make sure customer service still feels personal, just far more sustainable for the people behind it.”
How Williams Commerce Helps Clients Navigate AI, With Confidence and Clarity
1. We Start with the Commercial Goal
We identify the highest-impact use cases, conversion, AOV, loyalty, workload reduction, then match AI to the objective.
2. We Recommend Based on Evidence
Because we work hands-on across Adobe, Shopify and Big Commerce, as well as trusted AI plugin ecosystems, we know what works, and what doesn’t.
3. We Integrate AI Into Real Workflows
We configure models, train teams, build guardrails, and ensure AI becomes a sustainable capability, not a one-off project.
4. We Help You See What’s Next
We also guide early adopters toward emerging capabilities where the advantage is strongest, without unnecessary risk.
Tanya says… “There’s no one-size-fits-all path to AI. Every organisation has different goals, capabilities, pressures and ambitions. Our role is to listen first, understand what success looks like for you, and guide AI adoption in a way that feels natural, not disruptive, not overwhelming, and definitely not rushed.”
Tanya’s Guardrails for Smart, Sustainable AI Adoption in eCommerce
Before we expect AI to deliver performance gains, it needs to be introduced with clarity, structure and realistic expectations. This is where many businesses stumble, not because the technology isn’t effective, but because it needs guidance to work well inside real teams, processes and trading conditions.
To help teams take confident, informed steps, here are Tanya’s detailed guardrails:
Success Factor | What It Looks Like in Practice | How Williams Commerce Supports It |
Start where effort is highest | Begin with repetitive or time-heavy workflows (e.g., product descriptions, manual category sorting, repetitive customer queries).
| We identify high-impact, low-risk starting points that deliver fast, visible wins and build internal confidence. |
Keep humans in the loop | AI assists, but human judgment approves, refines and guides outputs, especially early on.
| We design workflows so teams stay in control and feel empowered, not replaced or sidelined. |
Apply commercial guardrails | AI is tuned to respect margin goals, stock depth, seasonality, brand guidelines and promotional plans.
| We configure AI settings to align outputs with real trading priorities, not just popularity or engagement. |
Allow time for learning | AI requires real behaviour data to improve, performance strengthens over several weeks, not instantly.
| We set expectation frameworks, monitoring dashboards and evaluation milestones so teams see progress clearly. |
Review, tune and evolve | AI effectiveness increases through continuous, light-touch adjustments responding to trends and business shifts.
| We provide ongoing optimisation, from adjusting recommendation weightings to refining tone-of-voice prompts. |
Communicate the “why” internally | Teams understand that AI is here to support them, not replace expertise or reduce roles.
| We help shape messaging and adoption strategies, so teams feel ownership, not anxiety or resistance. |
Conclusion: Moving Forward with Confidence
AI in eCommerce is no longer experimental or theoretical, it’s here, reshaping how customers browse, evaluate, and buy every day. The question for retailers is no longer “Should we use AI?” but “How do we apply it in a way that feels meaningful, strategic, and right for our business?”
The brands gaining the most value from AI right now are not the ones rushing to adopt every new feature or plug-in. They are the ones taking thoughtful, well-guided steps, starting where AI can solve real problems, reduce pressure, improve customer experience, and create space for teams to focus on what they do best.
This is where the right partner matters.
Williams Commerce helps businesses introduce AI with purpose, aligning tools to commercial goals, supporting teams through the change, and building capability in a way that strengthens the organisation rather than overwhelming it.
Final Thoughts from Tanya
“AI isn’t something you switch on and walk away from, it’s something you build into the way your business works. When it’s done well, it doesn’t replace what teams do, it enhances it. It gives people more headspace, more clarity, and more capacity to think strategically. Our role is to help clients move forward with confidence, not just adopting AI, but understanding it, shaping it, and using it to create better experiences for their teams and their customers.”
If you are exploring how AI could support your customer journey, improve merchandising efficiency, or strengthen your digital commerce strategy, we’re here to guide the conversation and help you think about the next steps for your business.
Ready to chat with our team? Email or call us today.
