Is AI Really Worth the Money? Why It’s So Hard to Tell
Hey everyone, John here! Welcome back to the blog where we make sense of the exciting world of AI. Today, we’re tackling a huge question that’s on every business leader’s mind: “This new AI technology is cool, but is it actually worth the cost?”
It’s a simple question with a surprisingly complicated answer. With me as always is my brilliant assistant, Lila, who helps keep us grounded.
Lila: Hi, John! So, are we talking about whether companies are getting their money’s worth when they use AI?
That’s exactly it, Lila! In the business world, they have a special term for this: ROI. Let’s figure out why calculating the ROI for AI is giving so many people a headache.
First Off, What Is ROI Anyway?
Before we dive deep, let’s clear up that little bit of jargon.
Lila: I was just about to ask! What does “ROI” mean?
Great question! ROI stands for “Return on Investment.” Think of it like this: Imagine you own a small bakery and you spend $1,000 on a new, faster oven. If that new oven helps you bake and sell an extra $1,500 worth of cakes each year, your “return” is that extra $500 you made after covering the cost of the oven. That’s a positive ROI!
Companies want to do the same math for AI. If they spend a bunch of money on AI tools and training, they want to see that it’s either saving them money or helping them make more money. The problem is, with AI, that math isn’t so simple.
The Two Flavors of AI Benefits: Easy Math vs. Fuzzy Math
According to experts looking at the news industry, the value you get from AI comes in two different flavors. One is easy to measure, and the other is… well, not so much.
- Direct Impact (The Easy Math): This is all about efficiency and cost savings. It’s the most obvious benefit. For example, a news company could use AI to automatically write summaries of long articles, translate stories into different languages, or even create simple graphics. These tasks used to take a person hours, but now they take minutes. You can easily calculate the time saved and translate that into money saved. This is the “cost-out” benefit.
- Indirect Impact (The Fuzzy Math): This is the tricky part. This is about how AI can improve the quality of work or create brand-new opportunities. For instance, AI can analyze tons of data to help a journalist uncover a hidden trend for a big story. Or, it can help personalize a news Web site so that every reader sees the stories that are most interesting to them.
How do you put a dollar value on “a better-researched story” or a “happier reader”? It’s incredibly difficult. This is the “value-add” benefit, and it’s where a lot of AI’s real magic lies.
Why AI is Like the Early Days of the Internet
To understand this challenge, the article we read suggests a great analogy: think back to the Internet in 1995.
Back then, when companies were deciding whether to build their first Web site, it was impossible to calculate a clear ROI. How much money would a simple Web page make? No one knew! But companies instinctively understood that they had to be on the Internet. It was the future, and not being there was a bigger risk than spending the money to build a site.
Generative AI is in a similar spot today. Leaders feel it’s a technology they can’t afford to ignore, even if they can’t plug it into a simple spreadsheet to see the immediate financial return.
The “Productivity Paradox”: Getting Slower Before You Get Faster
There’s another fascinating idea that helps explain what’s happening, called the “productivity paradox.”
Lila: A paradox? That sounds confusing. What does it mean?
It does sound odd, but it makes perfect sense when you think about it! The paradox is that when a powerful new technology is introduced, productivity doesn’t immediately go up. In fact, it often goes down for a little while.
Think about the last time you got a new smartphone. For the first few days, you were probably slower. You had to learn where the new buttons were, how to set up your email, and how the new camera worked. But after a week or two, you were flying around on it, doing things much faster than you could on your old phone.
That initial dip followed by a huge leap in productivity is what experts call the “J-Curve.” Companies are in that dip right now with AI. They’re investing time and resources to train their staff and change how they work. It feels slow now, but the idea is that it will lead to a massive productivity boost down the road.
So, What Are Companies Actually Finding?
A recent survey of news companies gave us a peek into what’s happening on the ground.
- About 56% of news companies are already experimenting with Generative AI.
- The number one benefit they are seeing so far is increased efficiency and productivity (the “easy math” stuff we talked about).
- What’s the biggest barrier holding them back? It’s not the cost of the AI itself. It’s a lack of people with the right skills and talent to use it effectively.
This shows that the biggest investment isn’t just in the software, but in the people who will use it.
Four Better Ways to Think About AI’s Worth
If the old ROI formula doesn’t work well, how should companies think about the value of AI? The article suggests four smarter ways to measure its impact.
1. How Much Time Is It Saving?
This is the most straightforward measurement. Teams can literally track how long a task took before AI and how long it takes after. For example, if creating a social media post for an article took 30 minutes, and now an AI tool helps get it done in 5 minutes, that’s a clear, measurable win.
2. What’s the Cost of Not Investing?
This is a big one. It flips the question around. Instead of asking “How much money will AI make us?” it asks, “How much will we lose if we fall behind?” If your competitors are using AI to create amazing, personalized content and you aren’t, you risk becoming irrelevant. The cost of doing nothing could be huge.
3. Can It Create New Products and Revenue?
Instead of just making old tasks faster, can AI help invent something entirely new? Maybe a hyper-personalized newsletter that’s so good, people will pay for it. Or perhaps an interactive story format that wasn’t possible before. This focuses on AI as a tool for innovation, not just efficiency.
4. Does It Help Us Achieve Our “North Star”?
Lila: “North Star”? Are we talking about astronomy now, John?
Haha, not quite! A company’s “North Star” is its main, guiding mission. For a news organization, the goal might not just be “make a profit.” It might be something bigger, like “produce the most trusted investigative journalism” or “empower citizens with reliable information.”
So, the final question is: does using AI help the company get closer to that ultimate goal? If AI frees up a top journalist from boring administrative tasks so they can spend more time on a deep investigation, then it’s helping the company achieve its North Star. That value is strategic, not just financial, and it might be the most important measure of all.
Our Takeaway
John: For me, this whole discussion is a great reminder that the most important things are often the hardest to measure. Judging AI purely on immediate cost savings is like buying a powerful computer just to use it as a calculator. You’re missing the point! The real power is in how it can transform how we work, what we create, and the value we provide to others. Companies need to have the courage to invest in the future, even if the returns aren’t obvious on a spreadsheet today.
Lila: As someone still learning, it’s comforting to know that even the experts are figuring this out as they go. The “J-Curve” idea really clicked for me. It’s okay to feel a bit clumsy and slow when you’re starting with something new and powerful. It’s a sign that you’re learning, and a big leap forward is just around the corner!
This article is based on the following original source, summarized from the author’s perspective:
ROI and AI: Why is this so hard?