Retail has always been a people business. But the people it needs are changing faster than most organizations have been able to respond.
The store associate, the buyer, the distribution center manager these roles are not disappearing. But sitting alongside them now is a workforce profile that would have been unrecognizable in a retail context a decade ago: machine learning engineers building demand forecasting models, cloud architects designing omnichannel infrastructure, computer vision specialists programming loss prevention systems, and data engineers maintaining the pipelines that feed AI-powered personalization at scale.
Retail is becoming a technology company that sells things. The talent strategy has not kept pace with that transformation.
Ninety-one percent of retail IT leaders say AI is their top technology priority for 2026, according to Gartner. Yet more than half of retailers surveyed by the National Retail Federation cite workforce expertise gaps as the primary constraint on scaling AI in practice.
The ambition is there. The talent infrastructure to deliver on it is not.
This is not a problem that resolves itself. The roles retail needs most are in the highest demand globally, and the organizations that have historically dominated tech hiring – the hyperscalers, the software platforms, the financial services firms are not standing still. Retailers that treat technology talent acquisition as an extension of their existing hiring model will fall further behind.
Those that build a deliberate, differentiated strategy for attracting, developing, and retaining technical talent will find themselves with a meaningful and compounding competitive advantage.
The scale of the technology investment driving the demand
To understand the talent challenge, it helps to understand the scale of the technology transformation retail organizations are funding.
Deloitte’s 2026 Retail Industry Global Outlook found that 30% of retailers are already using AI for supply chain visibility, with 41% expecting to do so within the next year. Fifty-nine percent of retail executives anticipate a positive return on AI-driven supply chain investments within twelve months, but only if they can build the technical capability to execute.
Meanwhile, Gartner forecasts global AI spending will exceed $2 trillion in 2026, growing nearly 37% from 2025. Retailers are a meaningful and growing share of that investment.
The retail cloud market is on a parallel trajectory. Valued at $11.89 billion in 2018, it is projected to reach $39.63 billion in 2026, representing a compound annual growth rate of 16.3%. Target, Walmart, and Best Buy have each made significant investments in cloud platforms for AI-powered inventory tracking, predictive analytics, and marketing optimization respectively.
The infrastructure build-out is real and ongoing. The question for HR and talent leaders is: who is going to operate it?
The NRF is direct on the answer: as retailers invest in AI and robotics to streamline operations, they are changing the nature of numerous jobs across the organization, and the industry will need to invest in its people to succeed in that new reality.
What that investment looks like in practice, and how talent acquisition functions need to be redesigned to support it, is where most retail organizations still lack a clear answer.
The roles retail technology teams need most
The profile of the retail technology workforce is diversifying rapidly. The roles emerging from retail’s digital transformation fall into several distinct categories, each with its own talent market dynamics and hiring challenges.
AI and machine learning engineers are the most acutely scarce. LinkedIn’s 2026 Jobs on the Rise report ranked AI Engineer as the single fastest-growing job title in the United States, with postings rising 143% year over year. Demand for AI and ML roles reached 49,200 US postings in 2025, up 163% from 2024. In retail specifically, these roles are focused on demand forecasting, dynamic pricing, personalization engines, and supply chain optimization. The challenge for retail employers is that 78% of AI and ML engineering job postings target professionals with five or more years of experience, at a median salary of $187,500. Technology firms currently account for 46% of total AI/ML hiring, absorbing the largest share of available talent.
Data engineers and platform architects underpin every AI investment a retailer makes. Without robust, well-governed data infrastructure, AI models cannot be trained, deployed, or trusted at scale. The Bureau of Labor Statistics projects 34% growth in data science careers over the next decade, among the fastest of any occupation, and retail’s appetite for data engineers is growing in parallel with its ambition to build AI-driven decision systems. These professionals are increasingly cross-functional, expected to understand not just data architecture but the retail use cases the infrastructure is designed to serve: loyalty analytics, inventory visibility, and customer segmentation.
Cybersecurity architects and engineers are a hiring priority driven by necessity rather than transformation alone. Retail handles enormous volumes of payment, personal, and behavioral data, making it a persistent target. Cybersecurity roles reached 66,800 postings in 2025, up 124% year over year according to Robert Half, and cybersecurity engineers alone accounted for 20,000 new roles. Forty-three percent of IT managers cite cybersecurity as the most difficult technical skill to recruit for. For retailers, the stakes are particularly high: a breach does not just carry financial cost; it carries brand cost in an industry where consumer trust is a core commercial asset.
Cloud and DevOps engineers are the operational backbone of the modern retail technology stack. As retailers migrate from legacy on-premise systems to cloud-native infrastructure, demand for professionals who can build, manage, and secure cloud environments is growing at a rate that outstrips the available supply. Cloud computing is identified by 41% of IT leaders as the top skill required for digital transformation, yet the talent pool with production-grade cloud experience in a retail context remains thin.
AI product managers sit at the intersection of technology capability and retail business context defining what the AI systems retailers build should actually do, for whom, and measured against what outcomes. This is one of the most structurally underfilled roles in retail technology: organizations hire engineers to build systems they cannot always connect to business value, while the professionals who can bridge that gap are in short supply across every industry simultaneously.
Why retail’s hiring model is not built for this
Most retail organizations built their talent acquisition infrastructure around high-volume frontline hiring. They are exceptionally good at moving fast, processing large candidate pools, and filling roles at scale. That capability is genuinely valuable and hard-won.
But technology hiring requires a fundamentally different approach. The candidate pools are small. The skills are specialized and more often self-taught rather than credentialed. The competitive landscape is global – cybersecurity engineer in Ohio is evaluating offers from healthcare systems, financial institutions, software companies, and remote-first tech employers simultaneously.
Speed matters acutely: firms that fail to adjust their offer timelines lose candidates within 48 hours of an offer according to specialist research, and 60% of companies saw their overall time-to-hire increase in 2025.
The assessment challenge is different too. Evaluating whether a candidate can run a high-volume retail floor is a solvable problem with structured assessment. Evaluating whether an ML engineer can architect a production-grade demand forecasting system for a retailer operating 2,000 stores requires technical depth that most retail HR functions do not have in-house and need partners to support this capability.
The compensation reality is confronting. Average AI engineer pay reached $206,000 in 2025 a $50,000 increase year over year and specialists in generative AI and large language model fine-tuning command premiums of 40% to 60% above baseline ML salaries.
For organizations accustomed to setting retail compensation against industry benchmarks, this represents a structural recalibration. IDC estimates the global IT skills shortage will cost $5.5 trillion in losses by 2026.
Retailers competing with one hand tied behind their back on compensation will simply not be in the game for the most consequential roles.
The employer brand problem hiding inside the hiring problem
Compensation matters. But research consistently shows that for technical talent, it is not the only variable, and often not the deciding one.
Sixty-one percent of technology organizations now place career development at the heart of their employer value proposition messaging. Tech professionals evaluate employers on learning velocity, the complexity and scale of the problems they will get to work on, the quality of the engineering culture, and the credibility of the technical leadership they will work alongside.
Thirty-three percent of US employees feel disengaged in their work, and the primary driver of that disengagement for technical talent is the absence of visible, credible career development pathways.
This is where retail has an argument it has not yet learned to make well.
The technology problems inside a large retailer are genuinely interesting. Personalizing the shopping experience for tens of millions of customers at scale. Optimizing inventory across thousands of store and fulfillment locations in real time.
Building fraud detection systems that operate at the speed of payment processing. Predicting demand through supply chain disruption using incomplete data. These are hard problems that require serious engineering and they exist at a scope and complexity that most technology companies cannot replicate.
The challenge is that retail organizations have not historically thought of themselves as technology employers and have not built the EVP narrative, the technical community infrastructure, or the career architecture to make that argument convincingly.
The candidates who could most benefit from what retail genuinely offers (scale, scope, domain complexity) are not receiving that message, because retail has not yet found its voice consistently in the technology talent market.
Fifty-five percent of tech professionals already work outside traditional tech companies, according to research from Mojotrek.
The shift is underway. Retail’s task is to compete more deliberately for its share.
Three pillars of a retail tech talent strategy that works
1) Separate the hiring model for technical roles
The single most important structural change most retail talent acquisition functions can make is to stop trying to hire technology professionals through the same processes, pipelines, and timelines built for frontline or corporate support roles.
Technical hiring requires dedicated capacity specialist recruiters who understand what MLOps means and can evaluate a candidate’s GitHub portfolio, structured technical assessment processes that test real capability rather than credential proxies, and hiring timelines that reflect the pace of a candidate-driven market rather than corporate approval cycles.
Organizations that have made this separation treating technical hiring as a distinct capability within the TA function see measurably better outcomes on quality of hire, offer acceptance rates, and time-to-fill for the roles that matter most to the technology roadmap.
Skills-based hiring is a particularly important lever for retail tech. The dominant credential model, which requires computer science degrees for AI and data roles, filters out a large proportion of the most capable practitioners. The most rigorous analysis of AI and ML engineering postings found that just 6% of roles require certifications; the market has largely moved to demonstrated capability as the evaluation standard.
Retailers that adopt the same approach access a materially broader candidate pool, often with stronger practical experience in the specific systems and domains they need.
2) Build the employer brand case for retail technology specifically
The employer brand investment that matters for technical talent is not a careers website refresh. It is building authentic, credible evidence that retail is a genuinely compelling place to do serious technology work.
That means technical leadership being visible: publishing, speaking at engineering conferences, contributing to open source, sharing the specifics of the problems the organization is solving.
It means structuring early careers programs for software engineers and data scientists that give early-career talent real responsibility and clear development pathways rather than rotation programs that obscure what working at the organization actually involves.
And it means being explicit about the scale and complexity of the problems on offer the fact that a retailer’s recommendation engine serves more daily users than most enterprise software products will ever reach is a genuine differentiator that remains largely unmade in most retail employer brand narratives.
The WEF’s Future of Jobs Report 2025 is unambiguous: 77% of employers globally plan upskilling as their primary workforce response to AI transformation. For technical talent evaluating where to build their careers, the organizations that are investing in development not just deploying AI, but building the capability to lead it are the ones that will attract and hold the professionals who can shape what that transformation delivers.
3) Invest in internal technical capability as a strategic asset
External hiring cannot fully close the technical skills gap retail is facing. The supply simply does not exist at the scale the demand requires.
Only 31% of organizations are actively investing in reskilling and upskilling their workforce, according to Fuel50’s 2026 State of Skills-Based Work research yet 93% of tech leaders report their teams lack the skills required to deliver on priority initiatives.
The organizations closing that gap are treating internal capability development as a strategic investment rather than a training line item, building structured pathways for analysts to develop data engineering skills, for operations managers to build AI literacy, and for technology generalists to develop specialist depth in the domains where retail most urgently needs it.
The math is compelling. Forty-eight percent of organizations rank strengthening internal career development among the most effective approaches to addressing skills gaps ranking it higher than salary increases and reliance on contractors.
For retail, where institutional knowledge of business context is itself a valuable input into technology work, the internal talent pipeline is not just a cost-efficient alternative to external hiring.
It is often the faster route to the capability the business actually needs.
The compounding advantage of moving first
The talent market for technology professionals in retail is not yet fully competitive. Most retail organizations are still approaching it with frameworks built for a different hiring challenge. That is a disadvantage for those that remain in that position and an opportunity for those that move deliberately now.
The retailers building dedicated technical hiring capability, investing in employer brand for technology talent, and developing structured internal pathways for technical skill development are creating an advantage that compounds. Technical talent attracts technical talent. Engineering cultures generate referrals. Organizations known for interesting problems and genuine investment in people’s growth build pipelines that self-reinforce over time.
The technology transformation of retail is not waiting for the talent strategy to catch up. AI investment is accelerating, cloud infrastructure is expanding, and the competitive gap between retailers that can execute digitally and those that cannot is widening every reporting cycle.
The question for CHROs, Chief People Officers, and Heads of Talent Acquisition is not whether to build a technology talent strategy. It is whether to build it now, while first-mover advantage is still available or later, when the cost of catching up is significantly higher.
Retail has always been built on the quality of its people. The definition of quality is expanding. The organizations that recognize that earliest will lead the industry’s next chapter.
How AMS can help
AMS partners with leading retail organizations on the full spectrum of technology talent strategy from RPO programs designed specifically for technical hiring at scale, to skills framework design, employer value proposition development for technology audiences, and early careers programs that build the internal pipelines retail will need for the long term.
Our sector intelligence and global delivery capability mean we understand the specific talent markets retailers compete in and can move at the speed technical hiring requires.
Sources: Gartner Digital Transformation in Retail 2026; Deloitte 2026 Retail Industry Global Outlook; National Retail Federation 2026 Technology Survey; LinkedIn Jobs on the Rise 2026; Robert Half 2026 Technology Salary Guide and Hiring Trends; IDC IT Skills Shortage Research 2026; Fuel50 State of Skills-Based Work 2026; WEF Future of Jobs Report 2025; GoodTime 2026 Hiring Statistics; Mojotrek Tech Hiring Trends 2025; Lorien Global Tech Workforce Trends 2026; CompTIA State of the Tech Workforce 2025; Axiom Search AI/ML Engineering Analysis 2026; Signify Technology ML Engineer Salary Benchmarks 2026; Bureau of Labor Statistics Occupational Outlook 2025.
