Beyond bite-sized: Rethinking workplace training for the AI-native generation

Organisations that recognise this shift and go beyond superficial tweaks to truly reimagine learning will attract, retain, and empower Gen Z, writes Gabby Wong.

As the last of Gen Z steps into the workplace, a new cohort of 18- to 21-year-olds is reshaping not only the culture of work but also how learning and development must evolve. A large percentage of these new workers will start their career, be it part-time or full-time, in quick-service restaurant chains (QSRs), retailers, pubs and bars, multi-location restaurants, gyms, and other such entry-level working environments.

The conversation around training this group has so far centred on familiar buzzwords: bite-sized content, mobile-first delivery, gamification, and visual storytelling. While these are still essential, they are no longer sufficient. The rapid adoption of generative AI over the past 18 months has fundamentally altered how this generation learns, thinks, and interacts with information. It’s time for organisations to reimagine training with a deeper understanding of what makes this group tick in an AI-enabled world.

AI as copilot: a new cognitive model

Unlike previous generations, today’s 18- to 21-year-olds don’t just use AI tools like ChatGPT, Grammarly, or Notion AI to assist with tasks – they integrate them into their thinking process. AI has become their cognitive copilot. They ask questions, refine outputs, test alternatives, and iterate rapidly. This has led to a new model of micro-inquiry and iterative learning. They are less concerned with memorisation and more focused on synthesis, navigation, and contextual application of knowledge.

Traditional training programs often assume a linear learning path: teach, practice, assess. But the newest cohort of Gen Z now learns in loops. They explore a concept, test it using AI, apply it in context, and seek feedback – not just from peers or mentors, but from AI systems that are responsive, immediate, and always on.

Organisations need to respond to this shift by designing training that allows for flexible exploration, experimentation, and co-creation with AI. For example, offering open-ended AI-assisted scenarios where learners use tools like ChatGPT to role-play difficult customer conversations or simulate negotiation tactics, with feedback loops built into the learning journey.

Performance over process: the end of the syllabus

The classroom-style, sequential training models used even five years ago now feel obsolete. The last of Gen Z is not conditioned to follow a rigid syllabus. Instead, they are outcome-driven and value performance-based learning: “What do I need to do, and how do I get there quickly?”

This shift mirrors how they consume learning content in their personal lives. They Google how to fix a problem, watch a two-minute tutorial on YouTube, or prompt ChatGPT for a formula. In the workplace, this means organisations must prioritise outcome-based training, where learning is embedded in real tasks rather than abstract modules.

Rather than onboarding courses that explain company policies in dull presentations, consider role-specific simulations that place the learner in the middle of a realistic challenge. Provide them with tools, including AI, to navigate those scenarios. Assess their decision making and adaptability, not just their knowledge retention.

This generation is deeply aware of algorithmic bias, data privacy, and the ethics of technology. They are not blindly trusting of platforms, institutions, or even their employers. As AI becomes a foundational part of training, transparency becomes critical.

Organisations must not only teach employees how to use AI tools effectively but also how to question them. Is the recommendation biased? Is the summary accurate? Has the AI hallucinated? These are critical thinking skills that Gen Z must develop in parallel with their technical proficiency.

Forward-thinking employers of this cohort of staff should embed AI literacy and ethical reasoning into their L&D strategies. This includes helping team members understand the limitations of generative models, the risks of over-reliance, and the importance of human judgment. The most successful training programs will treat AI as a partner, not a solution, and help young workers develop discernment and responsibility in their use of it.

Learning as a social activity, rather than solo

While AI has made self-directed learning easier, this younger Gen Z cohort still craves connection and validation. They want social learning.

In practical terms, this means integrating collaborative challenges into training: shared AI workspaces, peer-to-peer feedback, team-based problem solving using digital tools, and live reflections. Imagine a cross-functional cohort of new hires solving a business challenge using AI tools, guided by a facilitator but evaluated by each other.

AI should augment, not replace, human connection in learning. The younger Gen Zs value learning environments where their contributions matter, their voices are heard, and they can co-create knowledge with others. This shifts the role of L&D from content delivery to community design.

Real-time, always-on feedback

The traditional feedback cycle of completing a course, taking a quiz, and waiting for results feels archaic to a generation used to instant gratification. They expect feedback that is real-time, contextual, and actionable.

This is where AI can become a force multiplier. Tools that give in-the-moment feedback on communication, decision making, time management, or presentation skills are highly valued. AI-powered coaching, smart nudges, and personalised learning suggestions can help bridge the gap between knowing and doing.

However, feedback must be meaningful. An AI-generated comment like “Great job!” carries little weight. Feedback that identifies patterns, suggests alternatives, and points out blind spots is what makes the learning stick.

Training for ‘generation fluid’

Perhaps the most critical shift in workplace training is to stop training for today’s tools and start training for tomorrow’s change. The most valuable learning outcomes are adaptability, curiosity, and meta-skills: how to learn, how to evaluate tools, how to pivot when things break, and how to build resilience in the face of change.

L&D teams should prioritise training that develops “systems thinking” so team members can understand how tools, data, people, and processes interconnect. Also, creative problem solving where AI is a launchpad, not a crutch.

The 18- to 21-year-olds entering your organisation today are the first true AI-native workforce. They are curious, fast-moving, discerning, and values-driven. They don’t just want training that fits their schedule or device; they want training that aligns with how they think, how they grow, and what they believe in.

Organisations that recognise this shift and go beyond superficial tweaks to truly reimagine learning will attract, retain, and empower this generation. This means moving from courses to experiences, from content to conversation, and from instruction to exploration.

It’s not just about training Gen Z. It’s about preparing for a future that neither they nor we can fully predict. That’s not a challenge. It’s an opportunity.

Gabby Wong is the CEO of FranConnect.