What are the Top Hiring Tips for Data Teams in the AI World?

The manufacturing sector can grow through AI maturity

The organizations that are adopting and planning to integrate with Artificial Intelligence technology are going to position themselves in a way where their cash flow is going to double by 2030, according to the latest study by McKinsey. But when you turn towards the manufacturing organizations, they have a chance to grow in terms of AI maturity.

Almost 55% of the manufacturing organizations are either starting or implementing AI maturity. They are planning to build an internal support system for Artificial Intelligence and to use simple applications for operations. AI in the manufacturing sector is beneficial for many reasons, some examples include reducing cost, real-time reporting, and analysis. Here are the top hiring tips for data professionals in the AI world.

Think beyond

Today's companies are keen to hire people with diverse skill sets that can benefit the organizations in every way. It is a great idea to have AI skills to go beyond and implement a comprehensive and sustainable AI strategy. It is advantageous to have knowledge of the AI model lifecycle. This can help to map the organization's needs to different data profiles available.

Transform Data Professionals

The mapping of the AI journey needs subject matter experts who are well equipped with business points rather than having a skill set purely of data skills. The key is to empower people at a very first individual level to contribute something good to the organization.  The best thing would be training people on data to make better decisions at every level of the company regardless of what skills or education they have. This can be impactful for the enterprise at even a macro level.

Upskilling

Even though data professionals are growing day by day, the talent and skills gap still continues to be the foremost roadblock to scaling data and AI efforts in the manufacturing sector. One of the ways to overcome this problem is to upskill the professionals for an inclusive and sustainable AI strategy. This can be done by providing training, education, and incentives to address business needs filling up the hiring gaps.

Helping staff understand the importance of AI, data science and ML can be the best strategy for educating people on that. The next comes providing tools that allow non-data scientists to also take an active part in the process. The data professionals such as data scientists, and data engineers need to be prioritized while upskilling and forming AI strategies that can add value to the business and operations.