The 2021.AI Blog
Get inspiration and read more about important trends & news from the world of Data & AI.
As an ethical and fair AI Platform provider, 2021.AI holds the highest standards when it comes to developing and implementing AI and Machine Learning models.
Usage of AI in many organizations often fails to scale because too few people across the organization understand AI from a business context. Developing skills and competencies around AI…
It’s a relatively simple question, but the answer is not straightforward. First, perhaps unfairly, let’s broaden the question to cover other constituencies than just your customers.
More and more business executives are facing their first AI business case. Executives such as CHROs (Chief Human Resource Officers), CFOs, CMOs, or CSCOs (Chief Supply Chain Officers).
At 2021.AI, we believe that the year 2021 will be the year of enterprise AI implementation. Over the past several years, we’ve seen AI adoption speed increase as the implementation barriers have lowered.
Fraud is a growing problem across many industries and banking is certainly no exception. Whether internal or external, all banking institutions should be aware of the potential risks as well as sources of fraud within their organizations.
AI is increasingly becoming the focal point of RPA, but RPA initiatives lack a focus on AI governance. That is a potential business risk!
Putting AI models in production is notoriously tricky, and the challenges have many different nuances. This blog post summarizes the fundamental difficulties of productionizing AI models and how we, at 2021.AI, accommodate these on our Grace Enterprise AI Platform.
At some stage over the next ten years, the average leader will be responsible for a business area where they are responsible for several employees, a dynamic evolving data platform, and several intelligent algorithms.