Agentic commerce is creating a hiring gap most Shopify agencies and brands have not even named yet
Over the last few months I have had a familiar set of conversations with Shopify agencies and Shopify merchants.
They are not really about tooling. They are about capability.
The question underneath most of them is this. If the buying journey is increasingly shaped by AI, and if more of the purchase flow starts to happen inside conversational interfaces, do we have the people in place who know how to build, run, and improve that world.
Most teams do not. Most agencies do not. And that gap is already showing up in hiring.
In the next 6 to 12 months, I think the winners will be the ones who treat this as a people and operating model shift, not a feature update.
The context, quickly, why this is happening
Google’s Universal Commerce Protocol, developed with partners including Shopify, is part of a broader move toward agentic commerce. In plain English, it points to a world where customers express intent in an AI interface, and the purchase can be completed reliably without the same old loop of tabs, product pages and checkout friction.
That will not replace websites overnight, but it does change the centre of gravity. Discovery, decisioning, and even conversion can start to happen in places brands and agencies do not fully control today.
If that is true, then the most valuable work shifts upstream. Less time spent purely on building pages, more time spent on making product data, commercial logic, experience, and operations machine readable, consistent and optimised for intent based journeys.
That is why the talent problem matters more than the protocol itself.
The early signal we are already seeing in the market
This is not hypothetical for the Shopify ecosystem.
A UK agency and a Finnish agency, both Shopify focused, have told us they are struggling to find enough strong solutions consultants and lead consultants. These are the people who can translate client needs into platform decisions and delivery reality, and they are already in short supply.
A Shopify agency in the Netherlands has reached out asking how to build out an engineering team that is more AI savvy, more prompt focused, and capable of what they described as book ending AI, meaning engineers who can work effectively with AI tools while still owning quality, maintainability and outcomes.
On the merchant side, a UK Shopify agency asked for support hiring around AI strategy focused on CX and the customer front end, because their clients are asking the questions but nobody internally owns the answers.
All of that is a talent signal. The market is trying to staff for a shift that has not yet been formalised into neat job titles.
Gentian Shero, Co-Founder and CSO at Shero Commerce, put it well:
The biggest mistake I see right now is treating AI readiness as a technology problem. It is an operations and people problem. The merchants with clean data, clear ownership, and someone accountable for how AI fits into their commercial model will be ready when agentic commerce scales. Everyone else will be scrambling. For agencies, the question is simple: if your client’s customer never visits a website, where does your value sit? The ones building around data strategy, AI enablement, and commercial operations have a future. The ones still selling builds as the whole offer will have a problem.
The four role shapes that will matter most
These are not the only roles that will evolve, but if you are an agency founder, a delivery leader, or a merchant running a Shopify programme, these four shapes are the ones that stop this becoming a collection of disconnected experiments.
1. Agentic Commerce Lead, sometimes called AI Strategy Lead
What they do day to day They own the roadmap and the decisions. They decide what is being tested, why it matters commercially, and how it gets rolled out without breaking customer experience or operations. They align product, engineering, CX, and commercial teams so AI does not become everybody’s side project and nobody’s priority.
What backgrounds translate well You rarely find this person with a perfect title. They tend to come from digital product leadership, eCommerce leadership, strategy and consulting, platform partnerships, or strong solution consulting backgrounds where they have operated at the intersection of commercial goals and technology reality.
What a good job description actually focuses on Ownership, governance, prioritisation, and commercial outcomes. Not prompt engineering. Not an AI evangelist. Someone who can make decisions and bring people with them.
2. Product and Data Architect with an AI focus
What they do day to day They make the catalogue and commerce data usable for machines, not just humans. That includes product attributes, taxonomy, variants, availability, pricing logic, promotions, and the operational rules that sit behind the scenes. They also tend to be the person who stops AI initiatives failing because the underlying data is messy or inconsistent.
What backgrounds translate well PIM and MDM specialists, feed management, merchandising operations, ecommerce architecture, data product roles, CMS and DXP data heavy environments, and sometimes very strong platform engineers with a data leaning mindset.
What a good job description focuses on Structured data, catalogue health, commercial rules, integration awareness, and the ability to work with merchandisers and engineers equally well.
3. AI Experience and Conversation Designer
What they do day to day They shape how a brand appears inside AI driven journeys. They think about how customers ask questions, how products are surfaced, what the decision flow looks like, and how trust is built when the interface is not a traditional website. They also work closely with CX to make sure the experience is coherent from discovery through to support.
What backgrounds translate well UX content, service design, CRO leadership, lifecycle and CRM journey specialists, customer experience design, and anyone who has built guided selling experiences, quizzes, configurators, or complex assisted journeys.
What a good job description focuses on Decision journeys, clarity, trust signals, information design, and collaboration with CX and product.
4. Commercial Operations and Enablement Lead
What they do day to day They connect the strategy to reality. They make sure fulfilment, returns, customer service, and commercial reporting can cope with new buying behaviours. They also help answer the awkward questions about margin, performance measurement, and what success looks like when the old signals become less reliable.
What backgrounds translate well Trading and merchandising leads, revenue operations, commercial analytics, fulfilment operations leadership, customer operations, and people who have owned performance across multi channel commerce.
What a good job description focuses on Commercial ownership, operational coordination, performance measurement, and the ability to turn theory into repeatable execution.
The important point is that not every business needs to hire four net new people tomorrow. Plenty of organisations will evolve existing roles. The risk is simply having no clear ownership at all.
Where you actually find these people, because the titles do not exist yet
This is the part nobody talks about, but it is the practical blocker.
If you search for agentic commerce lead in most markets, you will not get a clean set of candidates. The way to hire for this is to recruit from adjacent backgrounds and hire for capability, then shape the role.
At Simply Commerce, we sit across Europe, the UK and the US with both contract and permanent talent pools, covering commerce, POS, CMS, PIM, and the wider DXP layer. We see where the transferable skills actually live because we are speaking to these people every day, not reading about them.
In practice, the best hires often come from solution consulting, product leadership, digital strategy, data heavy commerce and DXP roles, and commercial operations leadership. The mistake we see agencies make is hiring someone who can talk about AI, but cannot run a programme, influence stakeholders, or tie decisions back to commercial outcomes.
Another common mistake is assuming your engineering team will just absorb this naturally. Some engineers will, especially those already using AI tools responsibly. Many will not. You need a deliberate plan for capability building, not a hope based strategy.
What to do in the next 6 to 12 months
If you are a Shopify agency, I would focus on three things.
- First, decide whether you want to lead on this with clients or react when they ask. That decision shapes your service roadmap and your hiring plan.
- Second, build a readiness assessment offer. Something simple and repeatable that looks at data quality, commercial rules, operational constraints, and where AI driven journeys could realistically add value for your client base.
- Third, invest in one or two of these role shapes early, even if you start with a fractional hire or a senior consultant. Waiting until clients demand it usually means you are hiring in a panic, and that is when you overpay and underhire.
If you are a merchant, the biggest win is clarity. Decide who owns this internally, clean up the basics, and make sure your partners can talk about more than storefronts and build projects. If your organisation cannot name who is accountable for AI commerce decisions, then you are not yet taking it seriously, even if you are running experiments.
Closing thoughts
UCP and agentic commerce will keep evolving, and nobody should pretend they can predict the exact timeline. What we can say with confidence is that the talent market is already moving, and agencies and merchants are already feeling the gaps.
The organisations that do well in the next 6 to 12 months will not be the ones who collect the most AI tools. They will be the ones who build the clearest ownership, hire for the right capabilities, and create teams that can turn a shift in interface into a shift in commercial performance.
Tim Roedel | Managing Director | Simply Commerce
With input from Gentian Shero at Shero Commerce: If you want to compare notes on what you are seeing, feel free to message Gentian or myself on LinkedIn
