Many enterprises set out with good intentions to transform their organizations with AI, but fail to deliver without a strong AI Strategy in place. A game plan that overlooks business requirements and scalability often sets AI journeys up for disappointment and turn leadership off to future investments.
But you don’t have to let your past AI projects haunt you. Here are key ways to overcome foundation barriers and end your AI-driven transformation nightmare.
Think Big. Start Small. Act Fast
When adopting AI it’s important to consider what will make the biggest impact. That’s not to say you should be looking to take on the biggest project ever though.
A good AI strategy will take all of your organization’s use cases into account and figure out how you want to transform your business. Some strategies tend to look at AI technology and try to find a place to implement it, instead of examining the technology requirements needed specifically for your use cases. Overlooking this factor of your AI strategy will likely affect your ROI and also your scalability for future projects.
Once you’ve established this baseline, you can begin to figure out what use case to begin with that will allow you to achieve value in a meaningful amount of time. Choosing the right use case that is relatively small, but will also have a big impact will establish a proof of concept and pave the way for other successful projects down the road.
An AI Strategy for Scale
The Future of Big Data
With some guidance, you can craft a data platform that is right for your organization’s needs and gets the most return from your data capital.
So we understand that identifying uses cases is critical, but breaking them down into capabilities further strengthens your AI strategy. Implementing a use-case-decomposition step to your process will reduce functional requirements down to key components and technical capabilities. From there, you can create a personalized “magic quadrant” for each capability, incorporating technical and strategic vendor alignment factors.
Your magic quadrant will show you what capabilities line up with multiple use cases in your organization and move you to select a vendor platform that will allow you to scale and create models that are reusable.
After this group of use cases has been identified, you can prioritize projects and solidify a road map for success now and in the future.
Cast Out Bad Strategy
Whether you’re just beginning your AI journey or you’re still reeling from a disappointing implementation, you can still create an AI strategy that supports your organization. You don’t need to be an AI expert to know how you want to transform and drive your business forward. What it boils down to is your ability to identify your use cases.
Don’t throw spaghetti (AI tech) at the wall (your business) and see what sticks. Instead, identify use cases and the capabilities associated with them in order to identify the technology and path you need to follow to reach success. And knowing the multiple capabilities that apply to more than one use case will allow you to scale in the future. Being able to apply the tech you’ve invested in to more than one problem will extend value and maximize your opportunities for success.
And don’t stop at investing in a quality AI Strategy. Learn more about why and how you should be adopting AI now rather than waiting in our latest guide Artificial Intelligence: Your key to achieving competitive advantage.
