Businesses increasingly solve complex problems with data science. Access to very large data sets, accelerated advances in ML research fields, and inexpensive computing power are driving an AI-fueled transformation across industries. In a crowded market where consumers can have anything at any time, ML/AI applications that prevent fraud, mitigate churn, serve product suggestions in real-time, and manage predictive maintenance on infrastructure can be the critical differentiator. Yet as AI/ML projects come into the mainstream, businesses are finding just how hard it is to go from data science to business value. It's dangerous for any company to think of these AI-driven wins as coming for free.

For us and many other companies, trust has become a competitive advantage. As businesses race to adopt artificial intelligence (AI), their ability to use it ethically--and in ways that generate trust from customers, partners, and the public--will become a competitive differentiator. This means companies need to make ethics and values a focus of AI development. Some reasons for this are obvious: Three-fourths of consumers today say they won't buy from unethical companies, while 86% say they're more loyal to ethical companies, according to the 2019 Edelman Trust Barometer. In Salesforce's recent Ethical Leadership and Business survey, 93% of consumers say companies have a responsibility to positively impact society. Businesses are being held more accountable than ever for what they do and how they behave.