The rapid advancement of Artificial Intelligence (AI) technology and its increasing permeation across diverse industries has compelled businesses to ensure due diligence when selecting an AI vendor. A thorough evaluation can aid in mitigating risks while simultaneously maximizing the value of their investment. This involves assessing the vendor on numerous parameters that span their technology, expertise, support services, transparency, among other factors.
Written by Rahul Kapoor and Shokoh Yaghoubi of Morgan Lewis, this article provides informative and insightful details into the necessary considerations when evaluating potential AI vendors. Given the potential impact that choosing the right vendor can have on a business, it’s critical that thorough research is undertaken to ensure a suitable and successful partnership.
From a technical perspective, understanding the vendor’s AI technology and its compatibility potential with a business’s existing systems and processes is the first step. Evaluating if the vendor is utilizing the latest breakthroughs and techniques in AI technology to stay competitive in the increasingly dynamic business landscape is another pivotal consideration.
Furthermore, businesses should ascertain whether the AI vendor has the necessary expertise to effectively integrate and manage the AI technology within the business’s operations. This extends to support services, as ongoing service and maintenance are often integral to the successful implementation of AI technology.
In terms of transparency, the vendor should be open about their technology’s capabilities and limitations. Businesses must avoid vendors who overpromise outcomes or are vague about their AI product’s workings. A trusted vendor should openly discuss how their AI algorithms work and handle various scenarios.
Overall, the selection process requires careful and thorough due diligence, a comprehensive understanding of what the business needs from the AI technology, and a vendor who can provide ongoing support, expertise, and transparency.