Navigating the AI Landscape: Key Points for Prospective Buyers

It’s an exciting time for businesses looking to leverage the capabilities of generative AI. But if you’re a decision-maker at a business considering a major move, it doesn’t take long to realize that achieving widespread gains isn’t magic: it’s complicated.

In other words, you’re going to have to do a lot more than simply your biggest business challenges into the ChatGPT prompt box.

Right now there’s also plenty of hype out there, which can make it tough to see which solutions offer real transformative capabilities.

To help you navigate the current AI business landscape, here are five key points that can frame your thinking.

Understand Your Needs

First, it’s vital to start with understanding what you need to get out of AI. Do you need a way to analyze or generate text or debug computer code? Do you need something industry-specific? Are your needs so complex that it would take five minutes or more to explain them?

Start by defining exactly what your needs are. (And if you’re not sure, skip to the next key point and then come back to this one.)

Identify the Business Problem You Need to Solve

Related to the previous point yet distinct, don’t spend much time exploring AI tools until you identify the business problem you’re solving.

Maybe you’re a startup that can’t hire a copywriter and you just need the words to sound good. Maybe you’re short a developer or two and you need a tool that can complete code snippets or debug existing code. And again, maybe your business problem is deeply complex in a five-minute-or-longer-explanation sort of way.

Once you’ve defined exactly what the problem is that you need an AI tool to solve, you’re well on your way to finding the tool or next step.

Define Your Specific AI Requirements

Your business problem doesn’t always define your specific AI requirements, so make sure you do this now. If your business problem is that you’re short on coders, then you need an AI that can work with code. That’s easy: ChatGPT and most of the other off-the-shelf products can.

But do you need the AI tool to be able to read your database or cloud repository? Do you need it to be able to output that code directly into a software build? Which code languages do you need it to work with?

These and many other questions make up specific AI requirements—detailed descriptions of what you need your AI tool to be able to do.

Also in this phase you’ll want to answer the question of whether you have regulatory or information security restrictions that would influence what data you can give an AI tool access to. Many larger companies are banning the use of off-the-shelf ChatGPT or Bard because of data security concerns.

Assess Your Organization’s Readiness for AI Adoption

AI tools are only as useful as your team is ready to use them. Building your own custom software based on a large language model might be smart if you’re a billion-dollar corporation. But it’s not going to work if you’re a seven-figure agency or small business.

In general the more complex your needs and use cases, the more you’ll need to ensure that your entire team is ready to implement AI at scale.

Consider Ethical and Regulatory Factors

Last, remember the many ethical and regulatory concerns inherent to generative AI tools built on LLMs. These tools pull their “ideas” from everywhere, and it can be hard to be certain that generated code (or text or art or music) is free of any copyright or ownership concerns. And if you’re in a field like finance, healthcare, or government, you may deal with regulatory concerns that limit your AI options

For any business in the knowledge economy, it’s ultimately a question of when and how, not whether, generative AI will change the way business is done. Forward-looking businesses are laying the groundwork now to be ready for this future.