What to Consider for your Insight Engine Rollout: Identify the Use Case

The applications a business can use AI for are diverse, making virtually all sectors more efficient. Before integrating AI-powered technologies, such as an insight engine, the company management must ask the right questions and consider five critical points.

Over the next few weeks, we will be taking a deep dive into these critical steps beginning with step one below – Identify and Determine the Use Case.

Artificial intelligence (AI) is not slowing down and continues to make monumental impacts that are fundamentally changing economies, industries, markets, and the world as we know it. Traditional business practices are no exception to the transformations we are seeing.

However, before hopping on the (AI) train, there are still a handful of things to consider. AI is filled with different methods, procedures, and technologies – all of which have various definitions.

For example, Gartner defines AI as the following: "Artificial intelligence (AI) applies advanced analysis and logic-based techniques, including machine learning, to interpret events, support and automate decisions, and to take actions."

Forrester speaks of AI as the following: "Artificial intelligence (AI) has the potential to fundamentally remake the nature of firms, employment, and how work gets done."

Those are just definitions for the broad term: AI. Imagine the differentiation when it comes to subsets like machine learning, deep learning, natural language processing, neural networks, and more. 

Step One: Identify Use Cases

Businesses often come to us wanting to rollout an insight engine but don't precisely know what they would be using it for. Being unclear is not necessarily a deal-breaker, but for sustainable implementation, pinpointing fundamental problems within your company is a critical step before allowing AI to "fix" everything. Selecting a specific use case gives you somewhere concrete to start. Then one can further discuss optimizing processes across more business areas – you have to take off before you fly.

If you deploy an AI solution for the sake of deploying an AI solution, becoming overwhelmed by its capabilities is almost inevitable.

Some questions management and CTOs should discuss are:

1. What are specific problems impacting my business today?
2. Why do these issues need to change?
3. Which department or business unit does this problem relate to?
4. How might information insight transform these processes for the better?

These questions take care of the what, why, who, and how. It's important to note that questions one through three are answers internal teams need to be able to identify, as the vendor has not been involved in day-to-day operations since the very beginning. Question four may come a little more difficult until you define success criteria, receive hands-on testing, and involve the users – upcoming topics in the blog series on "What to Consider for your Insight Engine Rollout." 

Be sure to tune in for next week's piece on defining success criteria. If you can't wait, feel free to contact our experts in the form below.