AI: Everyone Can Create Training Content. Most People Shouldn’t.

Artificial intelligence has permanently changed the content landscape. Today, anyone with access to an AI assistant can generate a training outline, a script, or even a full eLearning module in minutes. At first glance, this feels like a long‑overdue win for L&D teams under pressure to do more with less. Faster development. Lower costs. Endless content.

But abundance is not the same as effectiveness.

As Lacy Thompson (Unboxed Chief Learning Officer) and Jamie McAvoy (Unboxed Senior Learning Designer) explored in Elevating Narrative‑Based Training With AI Tools, the true opportunity of AI in learning is not speed alone — it’s the ability to protect and elevate story‑driven, intentional learning experiences that actually change behavior. In a world flooded with generic, AI‑generated content, organizations that invest in custom, purpose‑built learning will be the ones that see real performance impact.

This article expands on that idea: why narrative‑based learning matters more than ever, where AI helps and hurts, and how intentional design separates meaningful learning from forgettable noise. Grab a cup of coffee and lets go!

The AI Content Explosion: A Blessing and a Risk

The numbers tell a compelling story. According to LinkedIn Learning’s 2024 Workplace Learning Report, 89% of L&D professionals say skill development is critical to navigating the future of work, yet over 60% report learners feel overwhelmed by the volume of available content. AI has accelerated that tension.

At the same time:

• Gartner predicts that by 2026, 60% of corporate training content will be generated or augmented by AI.
• McKinsey estimates generative AI can reduce content development time by 30–50%.

Speed is no longer the bottleneck. Meaning is.

When content is easy to create, it’s also easy to overproduce, resulting in libraries full of courses that look polished but lack relevance, context, or emotional pull. Learners disengage not because they don’t care about growth, but because the learning feels disconnected from the realities of their work.

This is where narrative‑based, custom learning becomes a competitive advantage.

Why Narrative‑Based Learning Cuts Through the Noise

Decades of cognitive science support what storytellers have always known: humans learn best through stories.

Research from Stanford University shows that stories are remembered up to 22 times more than facts alone. Neuroscience studies demonstrate that narrative activates multiple areas of the brain — language processing, sensory experience, and emotion — creating richer memory encoding.

As Lacy outlined, narrative‑based learning succeeds because it:

Builds Transferable Mental Models

Stories don’t just explain what to do; they show why decisions unfold the way they do. Learners form situational maps — who wants what, what constraints exist, and what consequences follow. These mental models are far more adaptable than step‑by‑step instructions when conditions change.

In practice, this means a learner who experiences a story‑based coaching scenario is more likely to navigate a difficult real‑world conversation than someone who memorized a list of “best practices.”

Reduces Cognitive Load

The human brain has limited working memory. Bullet‑heavy slides, dense policies, and disconnected visuals force learners to assemble meaning on their own.

A well‑crafted narrative does that assembly for them. Cause and effect are clear. Visuals reinforce the message instead of competing with it. Cognitive energy goes toward understanding and application — not interpretation.

Sparks Curiosity and Emotional Investment

Curiosity is the gateway to attention, and attention is the gateway to memory. Cliffhangers, consequences, and moments of surprise create emotional hooks that dramatically increase retention.

This is why learners remember stories about mistakes, conflict, and tension far longer than perfectly executed examples. The learning sticks because it felt like something.

Where Traditional Narrative Learning Has Struggled

If storytelling is so powerful, why isn’t all training built this way?

Because historically, it’s been expensive, slow, and hard to scale.

High‑quality narrative learning requires:

• Strong instructional design and writing
• Authentic voice and tone
• Visual and media production skills
• Iteration and testing

For many organizations, this put rich storytelling out of reach. The result was a compromise: stock images, generic scenarios, and stripped‑down narratives that lost their impact.

As Lacy shared, cinematic, high‑production learning experiences were once reserved for marquee projects with equally marquee budgets. That reality forced many teams to choose speed over substance.

AI changes that equation — if it’s used intentionally.

AI’s True Role: Enabler, Not Author

The biggest mistake organizations can make is treating AI as the storyteller.

AI is exceptional at acceleration: drafting, branching, iterating, generating assets, and handling production mechanics. What it cannot do — at least not well — is understand your culture, your learners’ lived experience, or the emotional nuance of real work.

This is where custom learning design matters.

AI as a Narrative Accelerator

Used well, AI helps teams:

• Turn SME bullet points into scenario drafts in minutes
• Generate multiple decision branches that reveal misconceptions
• Create consistent visual assets and accessibility text
• Prototype role‑plays and simulations quickly

This frees learning professionals to focus on what matters most: the story itself.

Instead of spending weeks formatting content, teams can invest time in:

• Identifying the moments that matter
• Designing meaningful consequences
• Writing debriefs that translate insight into action

AI as a Practice Partner

AI also unlocks dynamic learning experiences that were previously impractical at scale. Simulated conversations, adaptive role‑plays, and in‑the‑flow coaching allow learners to practice decisions safely — and repeatedly.

When trained intentionally on real personas, language, and goals, AI becomes a believable counterpart rather than a generic chatbot. The difference is trust.

Why Personalized, Human Centric Content Matters More Than Ever

Ironically, as AI makes content easier to generate, custom learning becomes more valuable, not less.

Generic content fails for three reasons:

1. It lacks context. Learners struggle to see themselves in the scenario.
2. It feels disposable. If it could apply anywhere, it applies nowhere.
3. It doesn’t drive behavior change. Without relevance, there’s no urgency to act.

Custom learning solves these problems by grounding stories in:

• Real roles and workflows
• Authentic language and tone
• Actual constraints and tradeoffs
• Business‑specific consequences

According to Brandon Hall Group, organizations that use highly customized learning content are 3.5 times more likely to report strong business impact than those relying primarily on off‑the‑shelf materials.

In an AI‑saturated world, relevance is the differentiator.

Intentional Design: Form Must Follow Function

The future of learning is not about more content — it’s about better decisions.

Intentional learning design asks:

• What decision do we want learners to make differently tomorrow?
• What mistake do we want them to recognize faster?
• What consequence do they need to feel — safely — before it’s real?

Narrative‑based learning answers these questions naturally. AI simply helps us deliver it faster, cheaper, and at scale.

As Lacy and Jamie remind us, the goal isn’t to teach people how to use AI. It’s to help people become better at their work — with AI as a support, not a shortcut.

Implementing Responsible & Scalable AI:

AI is here to stay. Content volume will only increase. Learners will continue to tune out anything that feels generic, irrelevant, or performative.

Organizations that win will be those that:

• Treat story as the engine, not the garnish
• Use AI to protect narrative quality, not replace it
• Invest in custom, intentional learning that mirrors real work

You don’t need a moonshot. You don’t need a new platform. You need clarity of purpose and the discipline to design learning that earns attention.

In an age of infinite content, meaning is the scarce resource.

That’s where custom, narrative‑based learning — powered thoughtfully by AI — becomes not just a strategy, but a necessity.