Evolutions in technology have initiated new and dynamic business models and digital tools that completely change how businesses connect and engage with consumers at every level. A perceptive move for companies to move away from human investment to technology has been underway for decades, particularly in those common repetitive skill-sets that tended to add significant costs to the production of products across industries.
Artificial Intelligence (AI) became a go-to solution for many applications that once were performed by human labor, but the idea of replacing workers who performed creative functions within an organization was often thought to be safe from the threat of workplace irrelevance. After all, artificial intelligence lacked the ability to parrot human empathy, to recognize and respond to subjective emotional responses, or the ability to replicate genuine human personality. Then came Alexa.
The use of artificial intelligence in marketing is trending rapidly as brands attempt to control marketing costs by leveraging machine learning to make automated decisions. Using AI, companies can boost the return on investment (ROI) of marketing campaigns through predictive modeling, advanced segmentation, and even personalization. The move appears to be significantly influenced by the desire to measure the real impact of total marketing costs on the brand’s bottom line.
To personally engage large segments of consumers on an economic scale, AI and machine learning are critical to implementing and measuring successful marketing campaigns and are accelerating the analysis and interpretation of data at a speed and volume beyond human capabilities.
A 2020 McKinsey survey found that those working in marketing and sales had the third-highest rate of AI adoption. It also was revealed that a small contingent of respondents, coming from a variety of industries, attribute 20 percent or more of their organizations’ earnings before interest and taxes (EBIT) to AI. The growth of AI in marketing continues to expand, making its adoption a strategic necessity.
Generating personalized marketing content has always been thought to be a creative function that was the purview of human capacity but numerous content service providers are employing algorithmic based artificial intelligence that mimics human-generated creative content. However, the challenge of developing complete trust in AI remains elusive to many brands because algorithms are wholly dependent on imputed data to generate a result. The persistent “garbage in-garbage out” variable appears to be alive and well. Going forward, those who employ the new method need to consistently revise the algorithms in order to remove biases and unfair assumptions often inherent in raw data. Reliability, safety, transparency, and accountability are critical elements necessary to infuse and promote trust in AI content modeling.
As digital technology continues to shape a new marketing landscape, brands will need to gravitate to accepting and utilizing creative AI content to reach audiences across multiple devices and marketing channels. Algorithms have, fairly or unfairly, earned a blemished reputation across social media platforms in the recent past complicating the technology’s ability to be seen as an effective and trusted method for marketers to employ. Brands can and will continue to engage customers without the use of AI, but it will become increasingly difficult to compete in a marketplace dominated by competitors who master and establish a measure of the trustworthiness in AI technology.