Artificial intelligence is influencing our daily lives in multiple ways. Although it is still in its early stages, artificial intelligence has transformed the way we stay, work and conduct businesses. Starting from phones to self-driving cars to smart factories, artificial intelligence is everywhere. More importantly, AI is already having a huge impact on companies and businesses.
Whatever we do, wherever we go artificial intelligence is influencing us at every step. For example, we receive movies or content recommendations from video streaming platforms, receive portending words while writing texts or messages, get recommendations while shopping on an eCommerce website, etc.
AI maturity framework at an enterprise level
As the companies and businesses are progressing they are also incorporating artificial intelligence into their products and services and sometimes even constructing new artificial intelligence systems afresh. The application of artificial intelligence at the enterprise level includes fully automating certain tasks, offering insights, analyzing and predicting business results, recommending the very next steps, etc.
Although the use case of artificial intelligence in multiple industries is huge and most companies have already started their AI journey, a lot of them flounder during the process. To succeed during the AI implementation process, companies need to explore all the capabilities of AI at every level.
For optimal business solutions, a lot of companies have implemented AI in engineering lifecycle management, facilities management, asset management, and supply chain management. The work of the AI maturity framework is to measure the level of AI maturity any company or business has implemented at the enterprise level.
It has become a standard methodology to measure the efficiency of AI implementation in different companies and industries. This framework focuses on the different aspects of AI maturity while assessing the business and its technical characteristics.
Seven dimensions of AI maturity framework
To determine the prosperity of an AI application at the enterprise level AI maturity framework use the following seven technical and business capabilities:
- Influence in your company or business
- Technological finesse
- Ease of usage
- Value to the end customer
- Artificial intelligence operating model
The suffusion of AI maturity framework at the enterprise level
To maximize the AI maturity of any organization first, we need to understand the current state of its AI adoption and then we need to set long-term as well as short-term goals. There are multiple AI maturity frameworks available that can effectively help you in assessing and understanding the level of AI adoption.
After having a deep understanding of the AI implementation, you also need to understand how it is impacting the end user because it is one of the most important parts of your business. Regularly monitoring your AI performance will give you an edge in the market.
As a company or organization, if you have implemented AI at an enterprise level then you need to set some goals around your AI maturity. This will help you understand if you have been able to successfully deliver the values of your enterprise and have applied enough technological sophistication to cater to your enterprise-level needs.
It will also make sure that the AI you are using is reliable and easy to use for your business targets. Moreover, it will also ensure that you have an AI operating model that can manage your AI implementation (with proper data governance and robust data management).