Analog is our future.

Yes, artificial intelligence (AI) monopolizes the headlines and has undeniable benefits: medical discoveries, streamlined business operations and time saved on tasks like vacation planning. Yet, despite the AI tsunami, many people (who are not in the business of creating or funding AI start-ups) are eager to tap the brakes.

Many are asking: What are the costs of a system so antithetical to the way our brains work? More importantly, how will we adapt to the onslaught of computer-generated information? As AI proliferates, organizations must decide how to harness its efficiencies without eroding the thinking, discernment and relationship-building skills that drive performance.

The future of learning may depend less on rejecting AI and more on intentionally reintroducing analog experiences into digital environments.

The Decline of Cognitive Skills

Emerging research suggests that heavy reliance on AI can weaken learning outcomes. A University of Pennsylvania study found that students who relied on AI for practice problems performed worse on subsequent assessments than peers who completed assignments independently. Similarly, an MIT study found that students using an AI assistant for an essay writing task consistently underperformed at neural, linguistic and behavioral levels.

As trainers who are committed to skill development, we need to take note and plan accordingly. AI’s negative impact on learning should not come as a surprise. Coupled with addictive electronic devices practically glued to our palms, we’ve grown accustomed to relying on AI throughout our days, without having consciously chosen to do so.

AI is with us every time we Google a question, look for directions or scroll social media and news consolidators. Short on time, we absorb the information served to us without critically evaluating whether the data, images and videos are real or accurate. Something has to change, and it’s already beginning to.

Bring Back the Blue Books

Some universities have responded by returning to handwritten “blue book” exams to restore real-time thinking under authentic constraints and reduce AI-assisted submissions.

Tips for Trainers

• Build reflection time into sessions before introducing tools.
• Require learners to generate solutions before searching for them.
• Use device-free intervals during workshops.
• Encourage handwritten notes for deeper encoding and recall.

Designing for this productive friction is now a strategic responsibility for L&D.

Park Devices at the Door

Schools and workplaces alike are experimenting with limits on personal device use to improve focus and engagement. In fact, 35 states have implemented laws or policies regarding student cell phone usage in classrooms.

Tips for Trainers

• Establish shared norms for AI and phone use at the start of sessions.
• Designate electronics-free learning periods.
• Explicitly discuss the benefits of focused attention and deep work.

These small design choices protect what many L&D teams identify as a core challenge: learner engagement.

Back to Face-to-Face

The rise of remote work and digital workflows has increased screen time while reducing informal workplace interaction.

Coaching, mentoring and apprenticeship-style models embed learning in human interaction. These approaches align with a broader industry shift toward learning in the flow of work and just-in-time support.

While AI-driven digital coaching tools expand access, human coaching builds trust, accountability and contextual nuance in ways automation cannot replicate.

Tips for Trainers

• Go back to meeting in person, even if they’re smaller gatherings than in years past.
• Structure “connection sessions” with thoughtful questions that allow people to meet and build relationships.
• Use facilitation decks or planning tools to help groups think, vision and plan without the assistance of electronics.

For learning leaders, the opportunity is not to choose between digital and human support but to design systems where technology enhances person-to-person development.

Fulfillment From Creative Pursuits

We feel fulfilled when we grow, struggle, succeed and contribute to others’ well-being.

AI can remove repetitive tasks, but when it removes creative struggle altogether, it may also diminish pride in accomplishment. Learning programs that emphasize experiential practice, peer feedback and visible progress tap into intrinsic motivation in ways passive consumption cannot.

Tips for Trainers

• Provide time for learners to create original outputs before introducing AI refinement.
• Use AI to generate varied scenarios for group problem-solving.
• Encourage participants to critique and improve AI-generated drafts.

In this model, AI becomes a starting point, not the endpoint.

Knowing What’s Real

Humans love performance and appreciate professional sports, playoffs and Olympic Games because they reflect humans doing extraordinary things. However, if we see someone doing a quadruple flip in an AI-generated video, we feel duped and disappointed.

This isn’t to say that we can’t appreciate sleight of hand or magic. However, we appreciate it because we know something magical is happening. AI photos and videos can be magical too. The difference between magic and today’s AI illusions is that we don’t know whether something is human-made or computer-generated. We might enjoy the artistry of computer-generated art, but we want to know it for what it is. We want to know when our fellow humans have created something wonderful on their own.

Tip for Trainers

• Incorporate exercises that compare human- and AI-generated content.
• Teach employees how to evaluate sources, verify claims and recognize synthetic media risks.
• Facilitate discussions on how inaccurate information affects trust and credibility.

These conversations are particularly relevant in compliance, risk mitigation and leadership development contexts, where discernment directly impacts organizational performance.

A Practical Framework for Learning Leaders

Reconciling digital acceleration with analog cognition requires intentional balance.

Tips for Trainers

• Use AI to reduce administrative burden, not cognitive effort.
• Use tools like Google’s NotebookLM to reformulate work and thinking you’ve already created into other formats (e.g., podcast, game, video).
• Use AI to create a range of scenarios for group practice or critical thinking.
• Prioritize deep thinking in assessment and evaluation.

These practices align with L&D’s broader strategic priorities: improving engagement, strengthening leadership effectiveness and aligning training to business goals.

Analog Is Our Future

In the end, this isn’t a rejection of innovation — it’s a reclaiming of what makes learning (and living) work.

Our brains were built for sensory experience, friction, conversation and purposeful thought. If AI makes it easier to skip those processes, then our job is to deliberately design them back in: handwritten reflection, device-free stretches, real-time dialogue, practice with feedback and apprenticeship-style coaching that transfers both skill and confidence.

The good news is that this shift doesn’t require grand gestures. It starts with small, principled choices: ask learners to generate before they search; require thinking before tools; create spaces where attention is protected; build programs where people teach people. Use AI where it genuinely removes drudgery but keep the human work human.

Analog is our future because the future still belongs to human brains. And brains learn best when we slow down, show up and do the thinking ourselves.