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Machine Customers—AI Buyers To Control $30 Trillion In Purchases By 2030
The rise of machine customers and AI buyers is set to revolutionize the way businesses operate, with a projected impact of monumental proportions. According to a recent Gartner study, CEOs and senior business executives expect machine customers to generate at least 21% of their revenue by 2030. This staggering figure translates to a colossal $30 trillion worth of purchases under AI-driven commerce.
The concept of machine customers represents a subset of AI agents specifically designed to autonomously purchase goods, negotiate transactions, and influence commercial decisions without human intervention. As AI-driven commerce accelerates, it is essential for businesses to recognize that not all AI agents are created equal. While AI agents encompass digital assistants, chatbots, and automation tools, machine customers are unique in their ability to act as independent economic actors.
Don Scheibenreif, an author and Gartner analyst, coined the term “machine customer” in his book “When Machines Become Customers”. His research indicates that by 2030, CEOs expect machine customers to directly influence or participate in $30 trillion worth of purchases. This prediction is not without precedent, as it aligns with Gartner’s estimates that nine billion internet-connected B2B products will become potential “machine customers” by 2028.
In a recent Zoom interview, Scheibenreif highlighted the critical need for marketers to adapt to this new reality. He emphasized that traditional marketing strategies relying on emotional selling are ineffective against machine customers, which lack emotions. Instead, businesses must rethink their approach and cater to the distinct decision-making factors of AI-driven agents. These machines will prioritize factors such as product availability, pricing, environmental record, and diversity, equity, and inclusion (DEI) policies.
In order to maximize the potential of automated bot buyers, Sirte Pihlaja, a certified customer experience professional, emphasizes the crucial role marketing teams must play in this transition. Pihlaja suggests that marketers should rewrite content with machine customers in mind, ensuring AI-driven agents can efficiently find, interpret, and act upon information.
Moreover, Pihlaja underscores the importance of optimizing web pages for AI-based browser agents during an interim period to facilitate trust-building between humans and machines. Her insight highlights that the biggest challenge lies not uniquely within automated AI buyers but rather in companies’ inability to leverage AI for customer and employee experience due to skills gaps and slow upskilling efforts.
While some may view this shift as a passing trend, Pihlaja is adamant that machine customers are here to stay. She stresses the need for businesses to prioritize convenience by redesigning customer journeys to accommodate both human and AI decision-makers. By optimizing products, services, and transactions for machine customers, companies can ensure seamless buying experiences through digital assistants.
In conclusion, the impending rise of machine customers and AI buyers necessitates a profound transformation within the business landscape. As the world hurtles towards an unprecedented $30 trillion in purchases under AI-driven commerce, it is essential that marketers, CEOs, and decision-makers prepare for this seismic shift.
Source: http://www.forbes.com
