This requires a delicate balance between engaging smart, predictive technologies, such as ML and AI, and honoring the ethical standards that build trust between brands and customers. The trend toward collecting and cultivating zero- and first-party data through an open and transparent value exchange with consumers has become table stakes for creating personalized customer experiences that result in long-term loyal relationships. But using only historical data to build black-box algorithms that continuously learn upon themselves can perpetuate intrinsic biases with regard to such characteristics as gender, race, ethnicity and economic status. Ethical AI offers a unique opportunity to establish trust with consumers, who I've found are increasingly seeking humanized communication from the brands with which they engage. The question of ethics in marketing and AI has been a hot topic for some time, and many brands have worked hard to ensure their targeting algorithms aren't biased.

Like every other industry, marketing has been on a decades-long journey of change driven by constant advancements in data management, analytics and technology, along with external influences such as privacy legislation, market fluctuations, consumer trends and social sentiment (not to mention a global pandemic). But I think the next era of transformation in marketing will be like no other, with technologies like machine learning (ML) and artificial intelligence (AI) playing a more prominent role than ever before. With new technologies come elevated restraints and the need for moral metrics. Today's shifts revolve around the clear truth that consumers have raised the bar by controlling their relationship with brands and determining their own levels of engagement. And every business survives and thrives based on its command of the customer experience.

As a recent CIO article observed, artificial intelligence has been "the next big thing" for a long time now. It has promised to relieve us of many mundane, day-to-day tasks while simultaneously helping us achieve feats of science and engineering we can barely imagine. There have also been the more dystopian visions of AI displacing wide swaths of the human workforce, leading to millions of people whose jobs are taken over by the AI-powered machines. While neither of these visions is likely for a long time to come, there are practical applications of AI that are coming of age. So how will organizations use artificial intelligence and machine learning to transform themselves and become more competitive?