Why You Need Clear Business Objectives Before Launching An AI Solution
Artificial intelligence (AI) can make a great addition to your toolkit. But the truth is that AI can also be a waste of time and money if you use it to try to solve the wrong problems or don't have clear objectives from the beginning.
Understand What AI Can and Can't Dos AI becomes increasingly commonplace, it's important to understand exactly what it can and can't do. No matter what you may have heard, AI isn't going to solve all your problems. If you want to get the most out of AI, it's important to have the right expectations to avoid setting your team up for disappointment.
When establishing the goals for an AI project, we often begin with the intention of approaching the problem with automation. Although it's common to aim for process automation with any new technology, AI has its limits. Automation is a spectrum and can be used on a sliding scale, so to achieve desired results, it's important to define parameters before diving in to deploy a solution.
AI solutions come in all shapes and sizes — some are streamlined and cost-effective while others provide a lot of processing power that comes at a price. So, how do you choose the right one for you based on a clear business objective? Based on my years of experience with AI, I've found that there are general principles that will help when you decide on an approach. Let's take a look at those next.
Design Your AI Solution Around Your Business Objectives
When starting out with AI, it's all too easy to get swept up in the excitement of what can be accomplished. This isn't a bad thing, but it's important to remember that you're designing an AI solution to help you reach a goal. At the end of the day, you need an AI solution that's designed around your business objectives. To get the best use out of an AI system, it's necessary to ask a set of well-defined, domain-relevant questions so you're ensuring that the tool is correctly addressing the target goals.
Determine Your Objectives For AI
One of the first steps in implementing AI into your business is to determine your objectives. Are you looking to improve efficiency? Improve customer engagement? Reduce operating expenses? All of these are valid reasons, but they require very different implementation strategies. If you're not sure about how to use AI for your business, it's a good idea to find out if your objectives can be clearly defined.
The best way to do this is to reflect on how you'd like to evaluate AI's business impact once you have a better feel for what it can and can't do. Examine possible valuation factors like assumed revenue, marketing and selling models used to forecast future revenue, conversion and overall profitability for your company. Then think about what information you could get from AI reports and queries that would keep this info up to date and help increase profits.
Another aspect to consider when determining objectives for your AI solutions are the assumptions used to calculate your future revenue, including revenue share, average revenue per user and transaction value. Ask yourself how AI can be used to sort through your data to achieve a holistic 360-degree view of these topics so you'll never have to second-guess your assumptions again.
Test Your AI Solution
Once your objectives are firmly in place, testing your AI solution may be necessary to ensure that the business end goals can be met. Automation can only truly be guided by goals. Good AI software should automatically generate and then interpret input from human language. But companies today don't always have in mind which business goals they're trying to achieve by using AI. Some want to solve complicated problems, while others want to improve customer retention. This lack of focus can prevent achieving a good ROI on an AI solution.
If you're not fully sure of your business objectives and your tech stack, it's a problem. Just because it looks easy, it doesn't mean you can implement something without a solid framework. Just remember that when you're launching any AI technology, validation of the business objectives is necessary.