Why Use AI?

I get this question a lot: "What are your thoughts on using AI?"

My first response is always the same: Why?

“Why” is a powerful question. It forces you to get to the root of what’s actually being asked. And when it comes to AI, I’m not sure everyone knows why they’re asking the question in the first place.

What they’re usually trying to say is…
“How can we move faster?
How can we get more done with less?
How can we standardize processes for better efficiency and predictability?”

Let’s dig into that. Because while AI might seem like the obvious answer, it’s not always the top one. The real answer is approaching each system with holistic efficiency in mind. This might mean AI, or any other number of tools at your disposal.

What AI Can Do

I’m not going to rattle off a giant list of all the things AI can do. The list is covered better by others smarter than me, and it’s ever changing and getting longer every day. With the notion of Operators or Agents on the horizon, everyone is excited about the infinite ways it could help us do.. whatever.

AI can boost efficiency. It can generate ideas at lightning speed, analyze massive datasets, and automate repetitive tasks. It’s great for streamlining operations and creating consistent workflows.

It also creates average, mediocre, content written in a sterile, lifeless, robotic voice. It is often wrong, to the point where every claim and citation must be fact-checked by an editor. It takes so long to write prompts, it can turn a 1-paragraph re-write into a 3 paragraph prompt exercise. It can remove even the last shred of life from the most boring piece of work.

AI can boost efficiency in some situations. It can also totally clog up your flywheels like pouring concrete in a gas tank.

Faster doesn’t always mean better

There are plenty of situations where AI misses the mark – or worse, makes things more complicated. Relying on it solely to produce content without editorial on top of it, means none of your content will stand out, rank, or convert. It will become relatively pointless to pump out a bunch of crap – which makes “faster” actually quite risky, if it is not pegged to quality.

And honestly, there are still faster, smarter ways to tackle most of the challenges people think AI was designed to solve.

Half the time it’s not even AI

In many cases, the companies that are bragging about using AI, actually aren’t. They’re using filters, triggers, automations, and decision-trees to automatically bucket you into certain marketing segments. This isn’t AI, it’s just segmentation and an attempt at personalization. Or maybe it is AI, and that’s why the semantics of it all are so confusing.

Programmatic or dynamic pages that use APIs and shortcode generators like Twig can allow editors to create templates that update every time the data updates - so every 15 minutes - guaranteeing fresh data and sentiment across hundreds or thousands of pages.

It’s not actually learning like we expected the machines to

Unlike Machine Learning, AI doesn’t yet get better with time. It just scans narrative to put sentences together that it has seen before, using similar signals as Search to determine what’s a reliable answer or not. The issue is that as the AI trains on trash, we get trash out (glue on pizza anyone?).

As long as AI is abiding by rules given to it, instead of making its own based on principles, we’ll avoid skynet but we’ll also not truly have a more-intelligent-than-all-humans system because it can’t reason or logic.

It’s like… trying to teach it gravity, or up and down. Never gonna get it, never gonna get it. Never get it.

Faster Than AI: What Actually Works

AI isn’t the ultimate shortcut. Sometimes, it’s overkill. Here are a few things that can get the job done better, faster, and with more humanity:

1. Operational Efficiency with Lean Six Sigma Principles

Want faster results? Start by evaluating your operations.

• Export a “control chart” report that shows you data about your tickets: Who, what, how long, resolutions, speed, pacing.

• Look for the “seams” in your processes where inefficiencies hide.

• Make a list of your entire publishing process, all the way down to “then email the article to amanda” or what have you. Truly understand the physical steps that are taken (buttons pressed) to get the thing from topic to Live on the internet.

  • How often do your tickets move backwards?

  • How long does it take to get to the end on average?

  • Which steps seem like they overlap or are in the wrong order?

  • Consolidate, reorder, roll out, then measure the new process with 25% less bulk.

• Streamline workflows to improve where things connect.

• In my experience, simply refining existing systems can double both output and quality.

Source: Atlassian help center: See summary data, rolling average and standard deviation, customize timeframes and isolate teams and issue types.

2. Dynamic Pages with APIs

Automation isn’t limited to AI-generated content. You can use APIs combined with editorial insight to create pages that update dynamically with fresh data and sentiment. It’s efficient and keeps the human touch intact.

3. Human Writers

Yeah, I said it. By the time you craft a three-paragraph AI prompt and spend hours tweaking the results, you could have written something better yourself. Why? Because human writers understand nuance, humor, and emotion in a way AI simply can’t replicate.

4. Transcribing Video to Text

This one’s simple. Use your voice. AI transcription tools can help you turn spoken words into text. And because it’s your actual voice, the content will feel more authentic.

Why AI Isn’t the Answer to Everything

AI (right now) is just a tool. It’s not a replacement for creativity, strategy, or human connection. A hammer is great for construction, but it’s just a hammer without humans. AI is great for companies, but without humans, AI is just AI. Humans consume our content, so without human connections, getting to your audience’s hearts is impossible.

The best AI applications? They’re the ones that amplify human efforts, not replace them. Think:

• Automating tedious tasks so teams can focus on high-value work. Let humans do what’s important, and AI do the boring things.

• Use it to analyze large datasets to uncover insights people might miss (again, boring stuff).

• Adding scripts to sheets to help get a head start on creating briefs for real writers.

But here’s the catch: If your systems and strategies are a mess, AI won’t magically fix that. In fact, it might make things worse. AI is structured and at the end of the day, must be operated by a human. If you’ve been doing things messy, don’t expect AI to do miracles.

Garbage in and out and back in and back out

Elon reminded us how AI has already eaten up all of the trustworthy data available through search engines, and has turned toward smaller and more niche datasets that may be more specific and trustworthy.

Yet on the other side… They are creating synthetic data from existing data to train models on. What could go wrong! Trash in, trash out, then eat it again, then throw it up again, then eat it again, STOP IT FIDO!

The reality is that AI development is “flawed at its core” because it’s already built on unreliable or misused data. If the foundation is shaky, the results will be too.

Remember that tools are just tools, and you have to be extremely careful about how you use them.

Predictions

I’m not a psychic, but without a crystal ball, I can clearly see the pendulum is swinging. For the past 3 years, businesses have treated AI like a magic wand for every problem, especially marketing. I think we’ll see increased use of AI in marketing language as it rolls further out to the masses (we are still in “early adopter” phase after all). But internally, we’ll see a shift toward using the most powerful perspectives in the right places.

In 2025 I think we’ll see a shift back to basics, with more balance back to editorial oversight and seeking more efficient ways to infuse authority and expertise into pieces, even if the base content is written by AI.

People are going to get tired of recognizing when something was clearly written by AI.

What are those shifts?

• Hiring great writers that get to the core of things and speak to you through their written words.

• Investing in thoughtful processes, where AI can help get to next step faster rather than replacing entire systems. I see people reusing their brains and generating good ideas to implement in their businesses.

• Creating genuinely helpful content that speaks to humans as humans; we’re not robots; please have some respect for your readers and audience.

Because at the end of the day, what works hasn’t changed; there’s nothing new under the sun; you need to understand your audience, deliver value, and build trust. AI can help, sure, but only if the fundamentals are strong.

Why Use AI?

Back to the first question that got us here, before diving into AI, ask yourself: What are we actually trying to achieve?

AI has its place; understand what it is and let it thrive doing the things that it can actually do nicely.

The risks of AI are real if we treat it as an all-encompassing solution without addressing its flaws or limitations. The question isn’t whether AI can help, it’s how we use it responsibly and effectively.

I think you may have meant, is there a simpler solution available to us?