Do you know the biggest contrast between an effective artificial intelligence (AI) project and an ineffective one? It is the project focus.
In this article at Ayehu, Gabby Nizri explains that the organizations aiming to get the most out of AI have a tendency to focus on a specific business objective that needs to be achieved. They use these results to improve value and to scale up their business.
The Fact Check
As per a recent Deloitte survey, about 82 percent of early adopters of AI are now realizing positive financial results from their investment, with an average ROI of about 17 percent. If you are looking for diverse ways to translate AI into business value, keep these productive tips in mind:
- Target Real Problems: To recognize the true value of AI, focus on genuine business issues. Adding business value should be the bottom line of each AI project.
- Acknowledge Your Limitations: If you adopt an AI system that is trained to make predictions based on a certain set of data, chances are high that you will get an incorrect response completely while using a different set of data. To avoid such misleading conclusions, ensure the employees are trained to know the appropriate analytics model, fit for the corresponding set of data.
- Listen to Stakeholders: The teams or individuals spearheading AI initiatives not always have their best insight into the problem areas. Hence, it is vital to gather feedback and insight from the key stakeholders who will be directly impacted by AI. Engage them for a detailed discussion right from the beginning of the AI project to save time.
- Value of Real-World Testing: To gain the definitive proof of your AI project’s value, be ready to face the real world. Early exposure allows more time for the tool to learn, adapt and improve. The sooner you bring the project live, the better you can cover its loose ends and gain better value for it.
Click on the following link to read the original article: https://ayehu.com/hallmarks-ai-success/