When evaluating the potential for use of AI within your organization, it's essential to make sure it aligns with your business strategies, goals, and objectives, and build a plan that will support its effectiveness.

Answering these key questions can help determine if AI will benefit your organization:

• Is there a clear business challenge or opportunity that AI can address?
• Does the organization have the necessary infrastructure, data, and skills to implement AI?
• Are there successful AI use cases in your industry?
• Do the potential savings/earnings/etc. of the intended benefit outweigh the cost of implementation?
• Is there a reputable AI tool or provider/advisor available?
• Are ethical, data privacy, and legal aspects well addressed?
• What considerations must be reviewed to decide if AI is the right tool for the job?

A decision tree can be a valuable tool for visualizing the steps and considerations involved in using AI to solve your organization’s challenges – and determining where to start. 

AI for fraud detection

As an example of a potential use case: AI can be a valuable tool in detecting fraud. The technology can easily consume and process large datasets, and identify in them complex patterns and trends that manual or rules-based systems may miss – which means that AI has the potential to detect sophisticated fraud schemes, through less-obvious trends, clusters, and outliers. 

But, the opportunity for – and path to – implementation will not be the same for all organizations, depending on their current processes and data.

• If needed as a first step, Document AI models can help parse and classify unstructured files – PDFs, images, videos, recordings, etc. – and extract relevant information. With some additional cleanup efforts, data scientists can transform unstructured data into usable formats (databases, Excel, csv files).
• Once available, data scientists can work with cleaned, standardized data to identify patterns, trends, and potential fraud schemes. Feature engineering will be applied to these signals, making them easier for AI/ML models to detect.

Download our decision tree to evaluate whether AI might be a useful option for your organization’s fraud detection – and, if so, where to start your implementation.