Organizations around the world are embedding AI into their key business functions. Whether companies are using AI to increase efficiency, improve the delivery of services to customers, or predict market fluctuations, AI is fast becoming an essential tool for success in a broad range of industries. But despite the widespread adoption, research shows that AI projects often have a high rate of failure and that teams are lacking the key skills to ensure success.

DataRobot met with industry leaders to determine the ten key factors to ensure AI success in 2020. Our report focuses on a few key roles and the important part they play in achieving AI success:

• Executives
• Early Adopters
• Team Players

Executives

Executive buy-in is critical to AI success. Towards this end, educating executives on how they can support AI throughout their organizations helps to set the tone for AI adoption throughout the whole company. Furthermore, if executives don’t feel that they understand AI, they won’t feel comfortable bringing it into their organization. As a result, specialized executive roles, such as Chief Digital Officer or Chief Analytics Officer, have been emerging to provide technical insight and help drive adoption across the business.

Global companies have the additional challenge of managing widespread locations and resources. Getting executives to sponsor AI projects is key to getting the whole organization on board and invested in becoming AI-driven.

Early Adopters

Businesses who invest in AI and adopt it early will fare far better. In fact, those who are slower to adopt — or don’t adopt at all — will fall behind.

Many organizations are falling short in this area, only touching on AI in their business or only using it in a single business process. It’s not enough simply to pilot a program or apply AI to only a single use case. What sets early adopters apart as leaders of the AI revolution is a thorough commitment to AI adoption across the entire business.

Team Players

AI adoption can transform every area of a business, ranging from marketing efforts to customer experience. And in a world where the supply of data scientists doesn’t meet the demand for AI solutions, every player counts and can make a difference. To build all the AI that a company needs in order to beat its competitors means that everyone must get on a team and contribute.

We see this in the rise of the citizen data scientists who bridge the gap between data science knowledge and business insight. Automation enables even more non-technical people to leverage AI, further driving the democratization of data science.

AI in 2020 Is Essential to Success

In 2020, it is critical that businesses not only adopt AI as soon as possible, but also ensure its success by getting executive buy-in who can promote its adoption across their organizations. Automation also will help empower non-traditional citizen data scientists who can help even more people across an organization to leverage AI.

To learn more about the ten key factors to ensure AI success in 2020, read our report.