Many AI projects encounter problems that can derail the effort or not meet the business objects. Check out this five-step plan for undertaking successful artificial intelligence implementations.
Business leaders in almost every industry are looking for ways to integrate artificial intelligence, but many struggle to hire talent, understand the benefits, or identify use cases necessary for AI success.
In a research study on AI adoption, Gartner said finding use cases and not understanding benefits were two of the main challenges highlighted by executives.
To ensure that an AI project delivers, businesses need to have a defined use case before approving it. This needs to be both feasible and of strategic value to the company, such as improving their product versus their competition or increasing their own productivity.
Once a use case has been found, another challenge regularly faced is data management, quality, and governance. In a Gartner webinar, director analyst Peter Krensky said data scope and quality is the biggest challenge to overcome to have successful AI deployment.
A lot of businesses have a limited understanding of their data and its usefulness. That can lead to a project not meeting its intended goals because the program is being fed inaccurate, outdated, or fragmentary data, Krensky explained in the webinar.
Building the right team for AI Success
To avoid such issues of data inaccuracy and messiness and achieve AI success, PWC recommends organizations take proactive steps, including determining the right AI investment path and nurturing their AI talent and culture.
Organizations should also recognize and address the fears and risks relating to AI in an organization to generate support among employees and potentially create new opportunities for them, according to PWC.
On the technical side, the choice between private, public, or hybrid is another consideration to make, as each one has different benefits and drawbacks. Each AI project is unique, and all have different latency, throughput, and security requirements.
Check out the five-step plan and recommendations below for undertaking successful artificial intelligence implementations.
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