Forget ChatGPT. “Boring AI” will forge the future of business

What is generative AI, and why is it hogging the headlines?

Generative AI is a type of artificial intelligence that uses deep learning algorithms to learn from huge amounts of content based on billions, sometimes trillions of parameters.

It generates things like images, videos, audio, and text by learning from patterns in the data it has been trained on.

The algorithms that drive generative AI tools have been in development for some time, and some projects in beta have been made available to consumers.

Companies like OpenAI (the creators of ChatGPT) have productized, packaged and marketed their tools expertly, clearly with the aim of gathering a huge userbase. And they delivered on that aim, with each tool boasting millions of users.

It’s no surprise. Who could resist the temptation to type in a prompt and see the results of its complex algorithms in just a few seconds?

These tools can show consumers the power of AI algorithms in just a few seconds. Even better, it’s showing you that power in a way that’s relatable to most people — communicating through word and image.

But it’s not just curious consumers tempted to these tools, businesses are recognizing the potential use cases, which are really exciting.

Whether it’s creating smarter chatbots, enhancing copywriting and design, accelerating work on software development projects or integrating explainability into AI models, there are clear and compelling use cases for generative AI.

I’m personally really excited to see how generative AI can enhance our AI applications in the near future.

But I’m asking you to forget ChatGPT, forget DALL-E and all the other attention-grabbing generative AI tools for a second. Here’s why.

Is it time to forget ChatGPT for now?

Generative AI is really good at certain things, generating hype is one particular strength. But the hype around this AI is a double edged sword.

On the one hand, it gives AI a much-needed boost in public interest. But on the other hand, the extravagance of generative AI can distract from the value of commercial AI, what the Economist recently called “boring AI”.

This isn’t the sort of AI that hits the headlines with ease. This is the type of AI that’s been modestly serving business needs for years. It’s the type of AI that, if effective, consumers wouldn’t even know was there.  

But the impacts of this AI are real. Boring AI can increase efficiencies across your value chain, reducing your cost to serve. It can give your customers a personalized omnichannel experience, driving up key metrics like customer lifetime value.

It can help you set the optimum price for your products throughout each product’s lifecycle. It can optimize decision-making across your business, including when and what technology you invest your time and capital in.

This AI is game-changing to business fundamentals. It can’t write you a Mother’s Day poem, but it can give your business exactly the boost it needs to win in a competitive market.

For those who’ve had their interest in AI heightened by tools like ChatGPT, the real question shouldn’t be “how can we get an equivalent tool in our own business?” To deliver truly game-changing AI, we need to take a step back from the hype of generative AI and understand what’s happening in our business.

So where should I start with AI?

That’s why every AI journey should start with an assessment of the opportunities and weaknesses of your business. It’s only from this vantage point that you can see which areas should be prioritized and know what AI solutions might fit.

Many businesses assume the next step on their AI journey is to modernize their data infrastructure. Often this is because they assume their data quality is too poor to be AI-ready.

But data infrastructure projects can be costly and take years and, with AI competition heating up, most business can’t wait years. The good news is you don’t have to. Your data doesn’t have to be perfectly organized in a data warehouse to be AI-ready.

We’ve built our Peak platform to work with all kinds of data, from enterprise data warehouses to single datasets, meaning you can get started right away use Peak as your data platform, too. Or simply plug Peak into your existing data platform.

Before trying to integrate generative AI into your products, it’s important to first explore how other types of AI can help you make and automate great, data-driven decisions.

You can start small with AI applications, and add use cases over time. For instance, many of our customers get started with AI-powered demand forecasting or customer segmentation. From there, they add additional AI capabilities like AI-driven recommender tools or inventory management.

The really cool thing is each application enhances one another, and combines into a single connected AI that levels up every part of their business.

We’ve worked with businesses who’ve seen incredible results through so-called “boring AI”. Whether that’s a 28% uplift in email revenue, a 73% increase in recommender-driven average order value (AOV), or using AI to make stock distribution decisions in one hour that used to take them one week.

To business leaders, these outcomes are far from boring.  

So yes, generative AI is really exciting. I’m personally looking forward to the opportunities it brings Peak to level up the explainability of our AI applications. But, for now, forget ChatGPT; forget generative AI, forget any particular solution. First, use your data to fully understand your business, and let boring AI help you.

This will give you the necessary foundations for further AI investment: an optimized business, with the data and tools it needs to know when to invest in the next big thing. 

So, maybe boring AI isn’t so boring after all?