After 19 live events all around the world in 2026, in December we’ve gathered for our annual Offbeat Sparks Online. Last year, our questions to our guest speakers was “What question should L&D ask in 2025?” While a year has already passed, those questions still stand today, and should be visited or revisited.

This year, though, we decided to go deeper and explore how learning should be designed in 2026. The choice was intentionally made. We’re seeing AI being used in more use cases than ever before. We’re using it to learn. We’re using it to design learning. And it’s changing completely the way any other learning method is perceived and engaged with.

So we decided to look in our network for experts who are close to LXD, and could bring in different opinions. LXD as a field is such a vast domain, and we wanted to make sure we don’t just cover what’s hot, like AI, but also other things that have been on our minds, like neuroscience, behavioral science, measurement, experience design, among others.

So on the morning of December 12th, right when Zoom was about to crash and leave us without a meeting tool, we started our second Offbeat Sparks Online in Google Meet. 17 speakers from all around the world joined us, and over 200 participants came in to see what they had to say. We laughed, we learned, and we made each other’s day better.

Now, we’ve prepared for you a summary of all the insights we’ve gathered. Below you can find the general considerations, as well as main messages from each speaker. If you want to hear the messages yourself, don’t hesitate to head over to YouTube and enjoy each talk.

General considerations on how to design and deliver learning in 2026

Across all speakers, with their different disciplines, and very different lived experiences, a few patterns kept showing up again and again.

From designing content to designing behavior, attention, and experience

One of the strongest shared messages was simple and uncomfortable: content is no longer the problem.

We have more content than anyone could ever consume. AI can generate it instantly. Libraries are overflowing. LMSs are packed. And yet behavior rarely changes.

Several speakers challenged the idea that learning works just because people should engage with it. Humans don’t behave rationally. They follow habits, emotions, friction, convenience, social cues, and identity. If learning doesn’t align with how people actually behave, it won’t stick, no matter how well designed the slides or how strong the learning objectives look on paper.

The implication is that learning design needs to borrow much more from behavioral science, marketing, product design, and experience design. Not to manipulate people, but to respect reality.

Designing learning in 2026 means asking different questions:

• Does this grab attention in a noisy environment?
• Does it feel worth people’s effort and time?
• Does it make the desired behavior easier than the old one?
• Does it invite people back or is it a one-off event?

If learning doesn’t change what people do, it doesn’t really matter what people know.

Human connection becomes more valuable, not less, in an AI-powered world

AI showed up in almost every conversation. But interestingly, the dominant message wasn’t “use more AI to automate learning.”

It was the opposite.

As AI becomes better at generating content, personalizing pathways, summarizing information, and coaching individuals, the uniquely human parts of learning become more precious: connection, trust, meaning-making, vulnerability, shared reflection, collective sensemaking.

Several speakers warned about the “AI trap”, confusing efficiency and scalability with transformation. Learning is not only about insight. It’s about energy, identity, courage, perspective shifts, and seeing yourself differently through others.

Designing learning in 2026 isn’t about replacing human experiences with AI. It’s about using AI as a wrapper, amplifier, or enabler, while doubling down on the moments where humans learn best together.

If everything becomes individualized, automated, and screen-based, we risk losing exactly the conditions that make deep learning possible.

From isolated training to shaping systems, environments, and habits

Another recurring theme was that learning cannot compete with the systems people return to every day.

People might leave a workshop inspired, but if the tools, incentives, norms, workflows, and expectations stay the same, old behavior wins almost every time. Not because people don’t care, but because systems are stronger than intentions.

Several speakers framed learning less as “intervention” and more as “environment design.” Learning becomes one ingredient in a much larger ecosystem that includes:

• How work is structured
• What gets rewarded or punished
• How decisions are made
• What leaders model
• What friction exists in daily workflows

Designing learning in 2026 means thinking beyond events and programs, and into how behavior is continuously reinforced (or undermined) by the surrounding system.

If learning isn’t supported structurally, it becomes fragile and temporary.

Inclusion, accessibility, and cultural intelligence must be designed, not assumed

Inclusivity showed up not as a moral checkbox, but as a design discipline.

• Who has access to learning?
• Whose voices dominate the room?
• Who feels safe to speak, challenge, experiment, or fail?
• Whose cultural norms are embedded into facilitation styles, activities, and expectations?

Several speakers highlighted how easily learning experiences can unintentionally exclude, even when intentions are good. Power dynamics, language choices, facilitation habits, representation, and cultural assumptions quietly shape who benefits from learning and who stays on the margins.

In a global, hybrid, AI-augmented world, designing for “the average learner” no longer makes sense, if it ever did.

Designing learning in 2026 requires much more intentional inclusive design: making access easier, participation safer, expression more diverse, and power more balanced.

Protecting human agency in the age of AI

Another strong pattern was concern about what happens to thinking, ownership, and capability when AI removes friction from learning.

If people stop struggling, predicting, reflecting, and making sense for themselves, they may become faster, but also more dependent. Convenience can quietly weaken cognitive agency.

Several speakers emphasized the need to design learning that:

• Forces thinking before prompting
• Makes reflection systematic, not optional
• Preserves productive struggle
• Makes learning visible in community
• Strengthens identity and ownership

AI can absolutely accelerate learning, but only if we intentionally design for human agency instead of outsourcing it.

The future isn’t just augmented intelligence. It’s augmented responsibility for how people learn.

The role of L&D itself is shifting from builders to architects

Underlying many of the conversations was a quiet identity shift for L&D.

Less:

• Order taker
• Content builder
• Course factory
• Framework enforcer

More:

• Experience architect
• Behavior designer
• Ecosystem shaper
• Community builder
• Sensemaking facilitator
• Strategic partner

Several speakers highlighted the importance of borrowing perspectives from design, marketing, systems thinking, behavioral science, and community building, not to abandon learning expertise, but to expand it.

The future of learning design isn’t about doing more training faster. It’s about designing the conditions where learning, change, and capability can actually emerge.

What each speaker had to say about designing and delivering learning in 2026 at Offbeat Sparks Online

Rather than trying to capture everything that was said, we’ve distilled each contribution into the core idea the speaker invited us to sit with, the belief they challenged, the shift they advocated for, or the lens they encouraged us to adopt.

Some ideas overlap. Some contradict each other. That’s intentional. Designing the future of learning isn’t about finding one perfect answer, it’s about learning to hold better questions.

Tobias Grünfelder – Design for wonder, not certainty

Tobias opened the day with a magician’s reminder: the future can’t be predicted, but people can be prepared to meet it with curiosity, courage, and imagination.

Drawing from neuroscience, he explained how moments of wonder are created when our expectations collide with something we can’t immediately explain. That gap activates curiosity, learning, and openness. In other words, wonder isn’t fluff, it’s a cognitive gateway.

For Tobias, the future of learning isn’t about perfect forecasting or skill taxonomies. It’s about creating conditions where people feel safe to explore, question, and imagine together. Leadership, in this view, isn’t only about solving problems, it’s about creating cultures that invite experimentation, peer learning, and collective sensemaking.

If we want people to shape the future rather than fear it, we need to design learning that keeps curiosity alive.

Matt Furness – Stop designing for how we wish humans behaved

Matt challenged one of L&D’s most persistent blind spots: behavioral naivety.

Using the story of how a soap company succeeded where public health campaigns failed, he illustrated the difference between designing for how humans should behave and how they actually behave. Information alone doesn’t change behavior. Ease, emotion, social proof, identity, and desire do.

Too much learning still assumes that if people know better, they’ll do better. That they’ll attend because learning is important. That they’ll apply because it makes sense. That they’ll search the LMS when they need help. None of that reliably reflects reality.

Matt’s call was clear: build behavioral literacy into learning design. Study how habits form, how friction works, how motivation actually operates, and design learning that becomes irresistible rather than mandatory.

Samantha Clarke – Don’t replace human transformation with AI efficiency

Samantha posed a provocative question: if AI can personalize learning for every individual, do we still need to bring people together?

Her answer was a strong yes.

While AI excels at personalization and scalability, it cannot replace the transformational power of human experiences: witnessing someone else’s breakthrough, making meaning together, building trust, and feeling the emotional energy of collective learning.

Samantha warned against confusing content delivery with transformation. When learning becomes a solo activity between a person and a screen, something essential gets lost: synchronicity, vulnerability, shared courage, and the permission to change.

Her invitation was to use AI as a contextual amplifier, not a replacement for human intelligence. The future isn’t cheaper learning. It’s richer learning, designed around human connection and powered (not dominated) by technology.

Niels Floor – Expand your perspective beyond your own discipline

Niels reminded us that every learning professional designs from a perspective, and every perspective creates both strengths and blind spots.

Education brings rigor and tradition, but often resists innovation. Tech brings speed and experimentation, but carries ethical and environmental risks. Design brings empathy and creativity, but can oversimplify complexity. Learning professionals center the learner, but may unintentionally narrow their view.

Real innovation happens in the bridges between these worlds.

Niels invited L&D professionals to deliberately step outside their own professional lenses and learn from adjacent disciplines. When we combine learning science, design thinking, technology awareness, and cultural sensitivity, we create solutions that are more human, more responsible, and more impactful.

If we want better learning experiences, we may first need broader ways of seeing.

Shaheen – Inclusion isn’t a value statement. It’s a design practice.

Shaheen challenged the assumption that good intentions automatically create inclusive learning.

True inclusion shows up in access, representation, expression, responsiveness, and power, not in mission statements. Who gets invited into programs? Whose stories are visible? Who gets airtime? Whose feedback actually leads to change? Who holds authority in the room?

Small design choices quietly shape who feels safe to participate and who stays silent.

Shaheen invited us to become more intentional architects of inclusion: auditing barriers, designing for diverse ways of participating, actively balancing power dynamics, and honoring lived experience rather than flattening it.

If inclusion isn’t designed, it defaults to exclusion.

Bella Funck – Learning changes knowledge. Systems change behavior.

Bella shared a hard-earned lesson from years of designing inspiring learning experiences that didn’t always lead to real change.

People returned motivated, and then stepped back into systems that reinforced old habits. Structures beat intentions.

Lasting change happens when individual learning and structural design work together: tools, routines, incentives, workflows, leadership behaviors. Learning alone can’t compete with the environment people operate in every day.

Bella reframed the role of L&D from content creator to architect of behavior change, someone who helps shape the conditions in which new behaviors can actually survive and scale.

If we only design learning, we may miss the real leverage point.

Alaina Szlachta – Measure learning by what it enables, not what it delivers

Alaina brought the measurement lens back to first principles.

Instead of asking whether people completed training or liked it, she encouraged L&D to ask: how is learning enabling people, processes, and systems? Every business outcome is influenced indirectly through these three layers.

If learning isn’t clearly connected to how work actually happens, how decisions are made, how processes flow, how systems operate, it becomes difficult to demonstrate impact or design effectively.

Her challenge was pragmatic: if you can’t clearly articulate what people should do differently and how that connects to organizational outcomes, the learning probably isn’t focused enough yet.

Impact starts with clarity.

Romy Alexandra – Move from content consumption to experience and co-creation

Romy reminded us that the most impactful learning moments in our lives rarely came from information alone. They came from experience, emotion, presence, reflection, and connection.

In a world flooded with content, learning risks becoming passive consumption rather than active meaning-making. Her mantra went beyond “connection before content” to “experience before explanation.”

Instead of treating learners as empty vessels, Romy invited us to design learning that starts from people’s lived experience, engages their bodies and emotions, and invites co-creation rather than transmission.

Learning becomes powerful when people are not just informed, but transformed through experience.

Ashley Hinchcliffe – Treat learning like a product, not a project

Ashley brought a marketer’s lens to L&D’s biggest visibility problem: great learning that nobody uses.

Strong learning requires both a high-quality product (relevant, usable, frictionless) and strong marketing (clear value, compelling messaging, repeated exposure). Too often L&D has neither, or only one.

Single email launches, feature-led messaging, and invisible platforms don’t stand a chance in crowded organizational environments.

Ashley’s message was simple: if learning isn’t designed and marketed like something people genuinely want, it will remain ignored, no matter how strategically important it is.

Adoption is not accidental. It’s designed.

Tom – The magic is in the before and the after

Tom encouraged learning designers to stop obsessing only over what happens during a session.

The moments before and after a learning experience shape anticipation, emotional engagement, memory, and meaning. Mystery, playful pre-work, unexpected invitations, and meaningful mementos can dramatically deepen how learning sticks and travels back into daily work.

Small, human touches often create more lasting impact than scalable perfection.

Designing learning in 2026 isn’t just about efficiency. It’s about crafting moments people carry with them.

Milica Sapic – Protect human agency in an age of instant answers

Milica voiced a concern many quietly feel: as AI makes answers instantly available, are we slowly outsourcing our thinking?

True learning requires prediction, struggle, reflection, and identity formation. If AI removes those moments entirely, people may become faster, but not necessarily more capable or independent.

Milica proposed designing learning that strengthens agency: forcing thinking before prompting, making reflection systematic, designing progressive challenges, and making learning visible in community.

The future isn’t about smarter machines. It’s about humans staying mentally strong, curious, and self-directed alongside them.

Mike Taylor – Design for attention before you design for learning

Mike highlighted a brutal truth: most learning never even gets a chance to work because it never earns attention.

Human brains filter relentlessly. If something doesn’t feel relevant, emotional, visual, or personally meaningful, it never reaches the part of the brain that can learn and act.

Marketers understand this. L&D often doesn’t.

Mike urged learning designers to borrow attention design principles: hooks, stories, visuals, repetition, campaigns instead of one-off launches. Learning must first pass the brain’s “spam filter” before it can create impact.

If people never notice your learning, its quality doesn’t matter.

Adil Ibrahim – Add contact, not more content

Adil challenged the reflex to solve learning problems by creating more material.

Instead, he introduced a simple model: make learning more social, give learners ownership, create unscripted experimentation, and stretch learning over time. Small peer cohorts, reflection loops, accountability, and shared practice turned passive completion into real behavior change, without adding new content.

Learning scales through relationships, not libraries.

Saad Bin Tariq – Use play, embodiment, and story to make learning stick

Saad demonstrated how novelty, physical engagement, and storytelling radically increase attention, memory, and meaning.

When learners move, touch, build, play, and narrate their experience, learning becomes embodied rather than abstract. Bullet points fade. Stories stick.

Designing learning for 2026 means thinking less like a slide designer and more like an experience choreographer.

Surprise opens the door. Embodiment pulls people in. Story makes it unforgettable.

Emilia Åström – Build collective intelligence, not just individual capability

Emilia reframed learning away from courses and toward collaborative sensemaking.

Most meaningful learning happens in conversation, practice, reflection, and shared problem-solving, not in formal training. AI becomes powerful not as a content generator, but as a pattern spotter, sensemaker, and amplifier of collective intelligence.

Her warning was clear: if L&D stays focused only on formal content, AI may replace much of that work. If L&D steps into cultivating the social and experiential 90% of learning, its role becomes more valuable than ever.

The future of learning is collective.

Amito Li – Design for cultural reality, not cultural assumptions

Amito challenged Western assumptions about participation, authority, expression, and learning behavior, especially when working across cultures.

Quiet doesn’t mean disengaged. Authority doesn’t create trust. Abstract theory doesn’t always translate into application. Individual expression doesn’t always feel safe.

Effective learning across cultures requires authenticity, concrete use cases, clarity of purpose, collective reflection, and visual expression, not just energetic facilitation or open-ended discussion.

Global learning design requires cultural intelligence, humility, and adaptation, not one-size-fits-all methods.

Bogdan Manta – Stop building learning on brain myths

Coming from a neuroscience background, Bogdan challenged the learning field to become much more scientifically literate about how the brain actually works.

Too many learning practices are still built on oversimplified models, outdated research, or popular myths that sound credible but don’t hold up under scrutiny. 

The risk isn’t just academic. When L&D builds interventions on shaky assumptions about attention, memory, motivation, or cognition, we may unintentionally design experiences that don’t work, or worse, that mislead stakeholders about what learning can realistically achieve.

Bogdan’s message was a call for responsibility: learning professionals shouldn’t only consume neuroscience, they should critically understand it, challenge misinformation, and help their organizations become more informed about what evidence actually says.

If we want to design learning that truly respects how humans learn, scientific rigor has to sit alongside creativity and experimentation.

Conclusion

Designing learning in 2026 doesn’t feel like choosing a new framework, tool, or trend. It feels like letting go of some comfortable assumptions about what learning is supposed to look like, and what our role in it really is.

Across all these voices, a pattern emerges: learning is becoming less about delivering content and more about shaping conditions. Less about control and more about trust. Less about optimization and more about meaning, agency, and human connection.

It asks us to think like architects of ecosystems, not builders of programs. To design for behavior, attention, inclusion, systems, culture, and collective intelligence, not just courses and curricula.

None of this is simple. Many of these shifts challenge how L&D has been trained, measured, and rewarded for years. But pretending the world hasn’t changed won’t make our work more relevant.

Maybe the real question isn’t how learning should look in 2026.

Maybe it’s who we need to become as learning professionals to be worthy of the future we’re helping shape.