AI Best Practices for Business Decision Makers and Practitioners
With companies in every industry leveraging artificial intelligence (AI), or at least wanting to, it has never been more important for technical practitioners and non-technical decision makers to understand how AI can benefit their business as well as the associated risks of implementing AI. It is critical for key stakeholders to articulate the business value of utilizing AI for solving their business problems, and to understand the associated costs and benefits of deploying AI-infused applications, the time to value of implementing AI and what success will look like over time.
In this guide, the CompTIA Artificial Intelligence Advisory Council leverages the diverse and expansive domain expertise of its members to provide curated insights on pain points and best practices associated with infusing AI solutions within an organization. To provide effective guidance, the information presented here is organized into best practices for two personas that are frequently involved in the adoption and integration of AI technologies: the practitioner and the decision maker.
Part 1: Decision Makers
Decision makers are focused on the macro-level goals and challenges of the business. They explore ways modern technologies can assist them in addressing current and future challenges in the most cost-effective manner that offers a generous ROI. They have job titles such as founder, CXO, CRO, line of business (LOB) leader, chief data officer, vice president of business intelligence, or vice president/director of engineering/IT. They are tasked with performing cost-benefit analyses and data visualizations that allow non-technical stakeholders to understand the business case for implementing AI solutions. They are also keen to ensure compliance and data standards utilized across the business.