These are workers who default to AI. Their mindset and methods offer CPGs and retailers a playbook for enterprise-scale hyperproductivity.
Five core working styles of AI-native employees
Here is how this AI-first approach is transforming how work gets done:
- Default to AI execution: Ideas move straight from prompt to prototype because the first instinct is to open a model, not a meeting invite.
- End-to-end ownership: The individual who conceives a feature also designs, codes, tests, and iterates it without any baton-passing or diluted accountability.
- Autonomy and trust loops: Because output is transparent and rapid, managers shift from gatekeepers to coaches. Micro-approvals die; velocity thrives.
- Continuous micro-learning: Each fast cycle produces data on what worked, seeding the next prompt. Learning becomes perpetual, not episodic.
- Full-stack creativity: AI tools blur functional lines, including copy, design, and analytics, so AI-native workers build talent stacks, solving problems holistically instead of in silos.
Six opportunities for large enterprises
Here are six ways large companies can benefit from an AI-native workforce:
- More speed at fractional costs: Coordination drag evaporates when one person can create a landing page, merchandising mock-up, or supply chain dashboard in one working day.
- Flatter, leaner structures: Operational roles created solely to herd projects fade away, freeing AI-native associates to spend more time on innovation and growth initiatives.
- Ownership-driven quality: “You build it, you own it” tightens feedback loops and pushes craftsmanship higher.
- Bold bets driven by cheap failure: With AI slicing the cost of experiment design and analysis, the appetite for risk rises while the downside shrinks.
- Trust as a talent magnet: High-autonomy cultures attract the scare and high-potential AI-native talent companies want to hire.
- Cross-functional skill fusion: When individuals can prototype marketing content and tweak code, silos crumble and insights travel further, faster.
Who Is already moving?
Walmart rolled out its “My Assistant” GenAI tool to 50,000 associates, accelerating everything from policy memos to benefits Q&A and expanding it to 11 countries this year.
Unilever has installed more than 500 AI applications across the business and partnered with Accenture to set a GenAI productivity benchmark for global CPGs.
Nestlé has deployed NesGPT, an internal ChatGPT-based tool now used by more than 7,000 employees and credited with saving associates an average of 45 minutes per week while slashing the product ideation cycle from six months to six weeks.
These initiatives signal that the world’s biggest retailers and brand owners are re-engineering work itself.
How to become more AI native
Here is how individuals and organizations can become more AI native:
- Prompt daily, not periodically: Treat every task, PowerPoint deck, SKU forecast, and shopper marketing project as a promptable moment.
- Ship a solo project: Build one tool (internal chatbot, automated dashboard report, personal GPT, etc.) end to end with AI assistance. Nothing accelerates learning like direct ownership.
- Tie recognition and rewards to AI-driven impact: Update performance reviews and incentive plans so employees earn credit for measurable gains, faster cycle times, cost savings, and incremental revenue that benefit from new AI-enabled workflows. When career progression and bonuses align with AI outcomes, adoption shifts from optional to instinctive.
AI-native employees are already rewriting run rates at Walmart, Unilever, and Nestlé. For major CPG and retail companies, it’s time to move yesterday’s processes to today’s AI tools, and watch a leaner, smarter culture emerge. The future of work — and the rapid innovation cycles that define it — is being shaped by AI-native employees operating with a startup and entrepreneurial mindset.
For a robust assessment of big picture trends and more agile scenario planning that can flex to current and future challenges, check out Kantar’s Business Not As Usual framework.
