The future of work is taking shape in kids' bedrooms

This post is a guest contribution by George Siosi Samuels, managing director at Faiā. See how Faiā is committed to staying at the forefront of technological advancements here.

If you've watched a kid interact with artificial intelligence (AI) lately, you've seen the future of work taking shape. Whether it's a 10-year-old calmly explaining to a chatbot why its answer needs more debugging or a teen tweaking an algorithm to brainstorm a school project, there's a new kind of thinking taking hold.

As someone building products with AI at a company like Faiā, I'm noticing interesting patterns. They go deeper than just tech adoption—we're seeing the next generation of talent completely redefine what the workplace will be. What's happening at kitchen tables today is a sneak peek into the cubicles, boardrooms and remote dashboards of tomorrow. Here's what we can learn and how it'll ripple through enterprise.

Steering AI with smarter inputs

Let's start with the basics: AI doesn't run itself—it thrives on human input. Kids are already masters of sharper questions getting sharper results. Ask a generic "What's blockchain?" and you'll get a textbook dump; ask "How could blockchain cut supply chain costs by 20%?" and you've got something actionable.

Now, that's not just a kid skill—it's a workforce superpower. A 2023 study from the Massachusetts Institute of Technology (MIT) found that professionals who purposely refine their prompts improve AI output accuracy by up to 40%. The employees of 2035 won't be the ones who can withstand the most data—they'll be the ones who know how to steer AI toward signal, not noise.

Enterprises that spot this early can build teams that don't just use tools—they optimize them. They'll integrate best practices for getting the most out of every query. It's a level of agility we'll need as tech evolves even faster.

AI as a workforce copilot

Then there's the partnership angle. Children aren't treating AI like a glorified calculator—they're turning it into a collaborator. A middle-schooler might use it to quickly mock up a business pitch idea, then add an image and have the bot suggest improvements in real-time as they type.

Sound familiar? It's the same dynamic we're chasing in agile teams: rapid iteration, creative problem-solving, human-machine synergy. Now, institutions like Gartner are predicting that by 2027, 70% of enterprises will rely on AI as a “copilot” for decision-making, boosting productivity by 25%.

The difference is, these kids see AI as a partner, not a crutch. For businesses, that mindset translates to workers who don't outsource thinking—they amplify it. Imagine a junior analyst who pairs AI's market analysis with their own instinct to spot a key trend faster than a legacy system ever could. That's the multiplier effect we're seeking.

Expertise as an efficiency edge

Here's a trend worth noting: expertise cuts through the clutter. A kid who's obsessed with coding can ask AI a question like, "How do I optimize this smart contract for minimal gas fees on PoS chains?" and get there in one shot, while a newbie will burn 30 minutes cycling through basics. It's efficiency in action, and in technical terms, it's about reducing token spend for optimal throughput.

A 2024 study by Stanford showed that domain experts use 50% fewer queries to achieve the same results as novices when working with large language models. On a large scale, that generation will value deep knowledge in blockchain, biotech or any field as a competitive edge. The blockchain architect who can code a protocol in three prompts will outpace the one who fumbles through ten. Expertise isn't dying—it's the fuel for smarter automation.

Setting boundaries for better outcomes

And finally, it’s all about questions. Kids today aren't busy memorizing encyclopedias—they're asking "Why?" and "What if?" to get the bot thinking. It's not trivia hunting; it's strategic thinking.

Now, the future workforce won’t be judged by what they know—AI will have that part covered. But they’ll be assessed by the questions they can ask to generate new value. Picture a supply chain manager asking, "What's the bottleneck in our Southeast Asia node?" versus "How do we cut container delays by 20% using real-time data from Southeast Asia to optimize routing and factor in seasonality for bulk cargo?" The second question drives value.

A recent McKinsey report forecasts that by 2030, 80% of new job growth will favor skills like critical questioning over rote knowledge. So, the enterprises that foster that curiosity now—through specialized training programs, internal culture or even