How Shopify Made AI Mandatory for Every Employee (And Why New Hires Need AI’s Approval First)

Shopify CEO Tobi Lütke issued a memo in early 2025 that every other CEO will eventually have to write but few have the courage to send today: AI usage is now mandatory for all employees across every role, from entry-level staff to executives. Not encouraged. Not optional. Mandatory. Performance reviews now explicitly evaluate how creatively and efficiently employees apply AI to their workflows.

The hiring policy goes even further. Before any team can hire a new human, they must first prove that AI cannot perform the needed tasks. This isn’t about reducing headcount. It’s about forcing every manager to think seriously about whether they’re hiring humans to do work that AI could handle, then getting frustrated when those humans can’t keep pace with AI-augmented competitors.

The mandate sparked predictable reactions. Some praised Shopify’s bold leadership. Others warned about job displacement and dehumanizing work. Both groups missed the strategic insight: Shopify isn’t trying to replace humans with AI. They’re ensuring every human at Shopify becomes an AI-augmented worker who can outperform non-augmented competitors by 10x or more.

The companies that don’t make similar mandates won’t fail immediately. They’ll just slowly lose ground to competitors whose employees leverage AI while theirs don’t, creating productivity gaps that compound until they’re insurmountable.

The Performance Review Integration

Making AI proficiency a performance evaluation criterion transforms it from technology adoption into job requirement. This seemingly small policy change creates massive implications for how employees approach their work and career development.

Traditional performance reviews evaluated employees on task completion, quality, collaboration, and leadership. Adding AI proficiency as an explicit criterion means employees who refuse to use AI or who use it minimally will receive lower performance ratings regardless of how well they do their jobs using traditional methods.

The evaluation doesn’t just measure familiarity with AI tools. It assesses how creatively and efficiently employees apply AI to business challenges. An employee who uses ChatGPT to proofread emails gets less credit than one who builds custom AI workflows automating entire processes. The bar is continuous improvement in finding novel AI applications rather than just checking boxes about basic usage.

This evaluation approach forces employees to take AI adoption seriously. When career progression, raises, and potentially employment itself depend on demonstrating AI proficiency, suddenly learning these tools becomes urgent rather than something to explore when time permits. The performance review integration ensures AI doesn’t remain isolated in technology teams but permeates every function.

The documentation requirement adds accountability. Employees must actively disclose and document their AI tool usage in performance reviews and resource requests. This transparency serves multiple purposes: it shares best practices across teams, prevents employees from claiming AI proficiency without evidence, and creates organizational knowledge about which AI applications deliver the most value.

I’ve observed that technology adoption without performance consequences typically achieves 20-30% uptake as enthusiasts embrace new tools while everyone else continues familiar methods. Making adoption a performance criterion typically drives 80-90% engagement because career consequences motivate behavior change that voluntary programs don’t achieve.

The “AI Before Humans” Hiring Rule

The hiring mandate represents Shopify’s most controversial policy: teams must prove AI cannot perform needed tasks before requesting additional human headcount. This inverts traditional hiring processes where managers identify work needing done and hire accordingly.

Traditional hiring conversations went: “We need someone to handle customer support tickets, write marketing copy, analyze sales data, or build features. Let’s hire for these roles.” The new process requires asking: “Which of these tasks can AI handle? Which genuinely require human judgment, creativity, or relationship skills? Only hire humans for what AI can’t do.”

This creates friction intentionally. Managers must now think deeply about whether they’re hiring humans to do repetitive work that AI could automate or whether genuine human capabilities are required. This friction prevents the default hiring response (“we’re busy, therefore we need more people”) and forces consideration of AI alternatives first.

The policy doesn’t ban hiring. It bans thoughtless hiring that adds humans to do work AI could handle, then experiencing the inevitable productivity disadvantage when those humans compete against AI-augmented teams elsewhere. Shopify would rather force hard conversations about AI capabilities now than discover later they’ve hired teams doing work that AI-augmented competitors perform better at lower cost.

The practical implementation involves teams requesting headcount submitting justifications explaining what tasks need performing and why AI cannot handle them adequately. This forces managers to actually test whether AI tools can accomplish the work rather than assuming humans are necessary without investigation.

The rule also changes how teams think about capacity. Instead of “we need three more people to handle this volume of work,” teams ask “can we use AI to handle 70% of this work, then hire one person to handle the 30% requiring human judgment?” This reframing leads to very different organizational structures than traditional hiring would create.

The Mandatory Usage Across All Roles

Requiring AI usage across every role from entry-level to executives ensures the mandate isn’t just symbolic or limited to technical teams. Everyone must integrate AI into their daily workflows regardless of their function or seniority.

Customer support teams use AI chatbots to handle routine inquiries, freeing human agents for complex situations requiring empathy and nuanced problem-solving. Marketing teams use AI for image generation, caption writing, and campaign optimization. Engineering teams use AI coding assistants to accelerate development. Finance teams use AI for forecasting and analysis. HR teams use AI for resume screening and candidate matching.

The universality prevents the organizational dynamic where some teams embrace AI while others avoid it, creating capability gaps that undermine collaboration. When everyone uses AI, teams speak the same language about capabilities and limitations, enabling better coordination across functions.

The mandate also ensures leadership practices what they preach. Executives using AI to analyze strategic alternatives, draft communications, and process information demonstrate that AI augmentation applies to knowledge work at all levels rather than just being automation for lower-level tasks. This leadership example legitimizes AI usage as professional capability rather than admitting humans can’t handle work manually.

The broad application also generates diverse use case discovery. Different teams identify different AI applications based on their specific workflows. Customer support discovers use cases engineering wouldn’t consider. Marketing finds applications finance wouldn’t explore. This diversity accelerates organizational learning about effective AI deployment far faster than centralized IT-driven rollouts where limited teams imagine use cases for everyone else.

The Cultural Transformation Challenge

Mandating AI usage requires cultural change beyond just adopting new tools. Employees must shift from viewing AI as threat or novelty to treating it as essential professional capability like literacy or numeracy in previous eras.

The cultural challenge emerges from legitimate concerns. Some employees worry AI will eliminate their jobs or reduce their value. Others fear looking incompetent if they struggle with new technologies while colleagues adapt easily. Some resist philosophically, viewing AI as dehumanizing or diminishing the craft of their work.

Shopify’s approach addresses these concerns through transparency about intent: AI isn’t replacing humans but augmenting them. The goal is enabling each employee to accomplish work that would previously require multiple people, increasing individual productivity and organizational capability simultaneously. Employees who master AI augmentation become more valuable, not less, because they can accomplish what non-augmented competitors cannot.

The mandate also forces confronting the reality that refusing AI adoption doesn’t preserve jobs. It just means losing those jobs to competitors whose employees do embrace AI and consequently outperform non-augmented workers. The choice isn’t between adopting AI or maintaining current work methods. It’s between adopting AI at Shopify or losing employment to people who adopt AI elsewhere.

The cultural shift also requires accepting imperfect AI tools that make mistakes and require human oversight. Employees accustomed to complete control over their work must learn to work with AI that’s highly capable but not infallible. This requires judgment about when to trust AI output and when to intervene with human oversight.

The Competitive Necessity Rationale

Shopify’s leadership frames the AI mandate not as optional innovation but as competitive necessity in industries rapidly automating core functions. This framing positions AI adoption as survival requirement rather than technology experimentation.

E-commerce faces automation across every function: customer service, marketing, supply chain, payments, fraud detection, and personalization. Companies that automate effectively serve customers better at lower costs. Those that don’t lose competitive position regardless of how skilled their human teams are because humans can’t match AI-augmented teams’ productivity.

The competitive pressure extends beyond direct e-commerce rivals. Shopify’s merchant customers expect platform capabilities that require AI: sophisticated recommendation engines, automated marketing optimization, intelligent inventory management, and predictive analytics. Delivering these capabilities requires Shopify building and operating AI systems at scale, which requires employees comfortable working with AI throughout their workflows.

The mandate also addresses the reality that Shopify competes for talent against companies already requiring AI proficiency. Technology companies hiring software engineers increasingly expect candidates comfortable with AI coding assistants. Marketing firms expect candidates proficient with AI creative tools. Shopify mandating AI usage ensures their employees develop skills necessary to remain competitive in the talent market even if they eventually leave Shopify.

The competitive framing also helps employees understand that resistance doesn’t preserve their jobs or roles. Shopify will either adopt AI aggressively and remain competitive or gradually lose market position to more automated competitors, eventually resulting in larger-scale job losses than would occur from AI adoption. The mandate chooses short-term disruption and adaptation over gradual decline.

The Human Skills Emphasis

Alongside the AI mandate, Shopify emphasizes developing uniquely human capabilities that AI cannot replicate: storytelling, curiosity, nuanced judgment, emotional intelligence, and creative problem-solving. The strategy isn’t replacing human skills with AI but dividing work so AI handles routine tasks while humans focus on capabilities where they excel.

This division recognizes that humans and AI have complementary strengths. AI excels at processing information at scale, identifying patterns in data, executing repetitive tasks consistently, and providing instant access to knowledge. Humans excel at understanding context and nuance, building relationships and trust, navigating ambiguity, and making judgment calls in situations without clear algorithms.

The emphasis on human skills also provides career development direction. Employees wondering how to remain valuable in AI-augmented workplaces should develop capabilities AI cannot easily replicate. Becoming better at building customer relationships, telling compelling stories, asking insightful questions, or navigating complex interpersonal dynamics creates sustainable competitive advantages that pure technical skills increasingly lack.

The human skills focus also addresses concerns about dehumanizing work. Rather than reducing employees to executing AI-directed tasks, the vision is liberating them from routine work to focus on activities requiring human judgment and creativity. Customer service agents stop answering routine questions and focus on building relationships with customers facing complex situations. Marketers stop writing basic product descriptions and focus on developing compelling brand narratives.

The Disclosure and Documentation Requirement

Requiring employees to disclose and document AI usage creates organizational transparency that drives continuous improvement and knowledge sharing. This seemingly administrative requirement serves important strategic purposes.

The documentation creates visibility into which AI applications deliver value versus which are just novelty. Teams can identify high-impact use cases to scale across the organization and discontinue low-value applications consuming time without generating returns. This learning accelerates as the organization accumulates experience with diverse AI applications across different contexts.

The disclosure requirement also prevents employees from claiming AI proficiency without evidence. In environments where AI usage is encouraged but not verified, some employees exaggerate their adoption to appear progressive without actually changing workflows. Requiring concrete documentation with evidence ensures claimed proficiency reflects actual practice.

The transparency also facilitates best practice sharing. When employees document novel AI applications that dramatically improve productivity, other teams can learn from and adapt these approaches. This cross-pollination accelerates organizational learning far more than each team independently discovering AI use cases through trial and error.

The documentation requirement additionally creates accountability for AI outputs. When employees use AI to generate content or analysis, documentation of AI involvement ensures appropriate oversight and validation rather than presenting AI-generated work as if humans created it independently. This transparency matters for quality control and ethical considerations.

The Industry Wake-Up Call

Shopify’s memo has been characterized as a “wake-up call” to other CEOs that AI integration is no longer optional but a core skill for modern workforces and a baseline requirement for evolving companies. This industry influence extends beyond just Shopify’s internal policies.

The visibility of Shopify’s mandate forces other companies to address AI adoption explicitly rather than allowing it to happen organically or not at all. CEOs must now decide: do we make similar mandates, establish different formal policies, or maintain status quo? The very existence of Shopify’s approach makes doing nothing a conscious choice rather than default behavior.

The mandate also changes talent expectations. As more companies adopt similar policies, job seekers increasingly expect employers to provide AI tools and training. Companies without clear AI strategies face talent recruitment challenges as candidates seek organizations offering opportunities to develop AI proficiency valuable for their careers.

The industry influence also affects competitive dynamics. Shopify merchants see Shopify’s aggressive AI adoption and expect the platform to deliver AI-powered capabilities rapidly. This creates pressure for Shopify’s competitors to match or exceed their AI capabilities, driving industrywide investment in AI systems regardless of whether competitors mandate internal AI usage similarly.

The precedent also emboldens other companies considering similar mandates but hesitant to move first. Shopify absorbing the controversy and demonstrating implementation approaches makes it safer for others to follow. This cascade effect means Shopify’s mandate likely triggers similar policies across the technology sector and eventually other industries.

The Implementation Challenges

Translating a mandate into effective practice requires solving substantial implementation challenges. Shopify must provide tools, training, support, and governance frameworks enabling employees to actually integrate AI successfully rather than just mandating it occur.

The tool provisioning challenge involves providing access to appropriate AI systems for diverse roles. Customer service needs different tools than software engineering. Marketing requires different capabilities than finance. Shopify must evaluate, procure, and integrate numerous AI tools rather than standardizing on single solutions inadequate for organizational diversity.

The training challenge involves teaching thousands of employees with varying technical sophistication how to use AI tools effectively. Basic “how to use ChatGPT” training doesn’t suffice. Employees need role-specific guidance about AI applications valuable for their particular workflows plus ongoing support as they discover implementation challenges.

The governance challenge involves establishing appropriate oversight preventing AI misuse while not creating bureaucratic friction that undermines adoption. The organization needs guidelines about what AI usage is encouraged versus prohibited, how to verify AI outputs are accurate, and when human review is required. These governance frameworks must balance risk management with enabling innovation.

The measurement challenge involves actually assessing AI proficiency during performance reviews. What constitutes creative and efficient AI usage? How do you evaluate someone’s AI proficiency in marketing versus engineering versus finance? Shopify needs consistent evaluation frameworks despite massive variation in how AI manifests across different roles.

The Job Displacement Question

The mandate inevitably raises questions about job displacement. If AI can perform many tasks previously requiring humans, does aggressive AI adoption reduce employment? Shopify’s position acknowledges some displacement while arguing AI creates more opportunities than it eliminates.

The displacement reality is that some roles will indeed change or disappear. Tasks like writing basic product descriptions, answering routine customer inquiries, or conducting simple data analysis become heavily automated, reducing or eliminating dedicated roles for this work. Employees previously performing these tasks must either develop skills for higher-value work or face displacement.

However, Shopify argues that AI adoption enables the company to grow faster, serve more merchants, and build more products than would be possible without AI augmentation. This growth creates new roles and opportunities that wouldn’t exist if Shopify maintained pre-AI productivity levels. The net effect might be employment growth despite significant displacement in specific roles.

The individual employee impact varies dramatically. Employees who successfully transition to AI-augmented workflows where they focus on human-centric work become more valuable and secure. Employees who struggle to adapt or who performed primarily routine tasks face career disruption requiring retraining or role changes. The mandate forces this adaptation proactively rather than allowing gradual displacement as AI capabilities improve.

Your Strategic Response Path

For companies watching Shopify’s mandate, the strategic question isn’t whether to follow but when and how. The direction is clear: organizations will increasingly require AI proficiency across roles as AI capabilities mature and competitive pressure intensifies.

Start by assessing current AI usage across the organization. Where are teams already using AI effectively? Where is adoption lagging? Which roles have clear AI augmentation opportunities? This baseline assessment identifies quick wins and major gaps.

Experiment with mandatory AI usage in specific departments or teams before organization-wide mandates. Pilot programs identify implementation challenges, surface valuable use cases, and build organizational capability before committing to universal mandates that might fail if infrastructure and support aren’t ready.

Invest in training and tools infrastructure before mandating usage. Requiring employees to use AI without providing adequate tools and training sets them up for failure and generates resistance. The mandate only works if employees have realistic capability to comply.

Develop clear evaluation frameworks for assessing AI proficiency appropriate to different roles. Generic “uses AI tools” criteria don’t provide meaningful feedback. Role-specific frameworks describing what effective AI usage looks like for particular jobs enable actionable performance conversations.

Communicate the strategic rationale clearly and repeatedly. Employees need to understand that AI mandates come from competitive necessity rather than management fads or cost-cutting exercises. The framing matters enormously for generating buy-in versus resistance.

The Future of Work Evolution

Shopify’s mandate represents an early example of a broader transformation in how work gets performed across industries. The future likely involves universal AI augmentation where employees across all roles leverage AI capabilities as naturally as they currently use email, spreadsheets, and search engines.

This future doesn’t mean replacing human workers with AI. It means every human worker becomes dramatically more productive through AI augmentation, changing the nature of work from executing tasks to orchestrating AI systems and focusing on areas requiring human judgment.

The companies that successfully navigate this transition build competitive advantages that compound over time. Their employees develop AI augmentation skills making them more productive than non-augmented competitors. Their organizations develop institutional knowledge about effective AI usage that accelerates innovation and efficiency. Their cultures embrace AI as professional capability rather than viewing it as threat.

The companies that resist or delay this transition face gradually widening productivity gaps that eventually become insurmountable. The gap between AI-augmented and non-augmented workers will reach 5x-10x or more for many tasks, creating competitive dynamics where delayed adopters cannot catch up through traditional means.

The Mandate That Changes Everything

Making AI mandatory for every employee isn’t about technology adoption. It’s about ensuring organizational survival through the competitive transformation that AI enables. Shopify isn’t being aggressive or innovative. They’re being realistic about what’s required to compete effectively in industries where AI augmentation becomes standard.

The question facing every other CEO is simple: do you make similar mandates now while it still feels bold, or wait until competitive pressure forces reactive policies after you’ve already lost ground to companies that moved earlier?

Requiring new hires to prove AI can’t do their jobs isn’t about reducing headcount. It’s about ensuring every human you hire adds genuine human value rather than just executing tasks that AI could handle better, faster, and cheaper.