Just Like Santa, Businesses Have No Shortage of Challenges. Here’s How AI Can Help

Every year, it feels like someone declares that this will be the holiday season when technology finally fixes everything we dread about gift shopping– shipping delays, supply-chain bottlenecks, product flaws, finding the right gift – all of it. And every year, the same problems return, wearing a fresh coat of snow, especially for the companies under pressure to get the holiday right.

This year, of course, the popular hymnal is that AI will make things better. But many companies have already invested significant resources in AI, with middling results at best.

There is a way forward, thankfully. If you really want to know how companies can make the most of the AI moment, don’t look at sleek demos or corporate roadmaps. Look at Santa’s workshop.

Yes, Santa. The one with the red suit, jolly laugh, reindeer, toys, and deadlines no one seems to appreciate. If you strip away the sleigh bells, his much-heralded, rarely-seen workshop starts to resemble every modern enterprise under pressure: well-intentioned, overextended, and running systems that grew faster than anyone could reasonably govern.

Buried inside the holiday chaos are the same questions companies across industries are asking right now: How do we build reliable software to get our products to market? How do we make better decisions with data? Can we use AI without creating a mess no one can explain later?

The North Pole’s “creative codebase” problem

Imagine a team of elves who’ve been shipping based on systems, including computer code, that has accumulated over centuries. Each one has a slightly different style. Some love last-minute fixes. Some swear their version of a “temporary patch” is fine. A few still test things manually because “it’s how we’ve always done it.” Any engineer reading this is probably twitching.

Holiday magic didn’t protect the workshop from the same things that affect real companies, like backlog buildup, inconsistent standards, and fragile systems that only behave occasionally. Those tensions are heightened beginning with Black Friday.

The fix isn’t more magic, it is more structure. Not rigid, bureaucratic process, but the kind that keeps creativity from collapsing under its own weight: lightweight peer reviews, automated testing, and pipelines that bring quality designs and updates forward instead of leaving it to chance.

And yes, a little help from machine intelligence: tools that can scan code for performance issues, flag security risks, and point out the “this will absolutely break on Christmas Eve” flaws no one catches in a rush.

None of this is glamorous. But it’s what separates a company from running into a wall from one that is shipping reliably, even during the peak holiday season. Once the workshop could actually see what was happening in real-time, it finally had space to learn from the season instead of just surviving it.

Rudolph’s tariff nightmare and the real anxiety in supply chains

The Workshop’s other quiet crisis this year? Tariffs.

If you think Santa gets exempted from geopolitics, think again. When toy components get pricier and deliveries slow down, not even reindeer can hide the impact from children (and their parents). What solved the problem this year wasn’t tighter reins, it was visibility. Thanks to AI, the workshop and other companies now have clear supplier data, forecasts that update in something resembling real time, and scenario models that can answer questions humans rarely want to ask out loud: What if the backup supplier goes offline? What if transport gets disrupted? What if demand spikes in one region and flatlines in another?

AI didn’t replace the reindeer. It gave the workshop a chance to act before things hit crisis mode. The payoff wasn’t just efficient production, it was calmer teams and fewer fires to put out at midnight. When tariffs shifted mid-season, the workshop could immediately see which components were now more expensive, which suppliers were suddenly uneconomical, and where it needed to shift to avoid going over its holiday budget. AI-driven visibility allowed the team to identify tariff-free alternatives, suggested locally sourced components, and offered better monitoring of upcoming weather patterns. By continuously comparing forecasts with actual outcomes, the workshop could refine processes, anticipate bottlenecks, and adjust proactively. This turned reactive operations into something closer to intelligence in motion.

AI consumers actually notice and trust

During the holiday season, most consumers aren’t thinking about back-end code or supply chains. They’re interacting with AI every day, whether it’s chatbots answering last-minute questions or recommending gifts, or personalized ads landing in their feeds. And this is where trust matters most.

Companies are discovering that if AI systems operate without human oversight, explanation, or context, they can frustrate users, ruin trust, and even cause reputational damage.

Take marketing and customer engagement as an example: AI makes it easy to generate content at scale, from holiday emails to social ads, but speed alone isn’t enough. Poorly designed automation can result in tone-deaf messaging, errors, or bias, which is exactly what some high-profile brands have faced this season. For companies relying on AI-generated content, the stakes are immediate. Consumer trust, engagement, and even sales can suffer.

Then there’s customer service. Chatbots can handle large spikes in volume during the holidays, but without human oversight they risk providing confusing, incomplete, insensitive or flat-out incorrect responses. Customers notice, and negative experiences spread fast. Designing AI with humans in the loop ensures that tone, empathy, and judgment aren’t overlooked.

Personalization engines also need humans in the loop. Whether it’s Etsy helping shoppers design unique gifts or retailers offering recommendations, AI must be transparent, explainable, and context-aware. Without it, suggestions can feel intrusive, off-base, or disconnected, especially during high-pressure holiday shopping.

The key idea is simple: design AI around people, not just technology, speed or scale. Clear guardrails and continuous oversight aren’t just about being ethical, they’re essential for businesses. Responsible AI amplifies human judgment instead of replacing it, and it ensures users feel understood, respected, and creates a trustworthy experience. During the holidays, that can make the difference between a frustrating interaction and one that keeps customers coming back.

So why are we talking about Santa at all?

The North Pole is a convenient stand-in for problems companies hesitate to admit publicly. Codebases held together by goodwill, supply chains that break easily, algorithms that exist but do not have proper guardrails or consumer protections.

These issues exist everywhere – from manufacturing to retail to public agencies – but holiday season pressure makes them harder to ignore.

There is good news, though. None of this requires a sleigh, elves, or a red suit to fix. Pragmatic engineering, clear data, and AI used responsibly and paired with human judgment can solve the same problems in the real world.

If Santa’s workshop can evolve without losing its heart, the rest of us should be able to manage it too, ideally without waiting until December to start.