Machine Customers Offer Limitless Opportunities

Machine customers are non-human economic actors that obtain goods or services in exchange for payment. Examples of this include connected devices, intelligent replenishment algorithms, and intelligent assistants. Gartner predicts that by 2028, 15 billion connected products will exist with the potential to behave as customers by being able to shop for services and supplies for themselves and their owners.  

Currently, most machines merely inform or make simple recommendations. However, some machines are emerging as more complex customers that have the ability to buy, sell, and request services. Advances in generative AI will accelerate the development and deployment of machine customers. These applications can diagnose a job to be done and break down complex tasks to make the right recommendations and service requests and execute other functions to complete the job. Other key technologies can enable machine customers, including edge and cloud computing, large language models, and digital commerce platforms.   

IT leaders must lead the construction of the platforms and applications capable of serving machine customers and can even build their own machine customers.  

Exploiting the machine customer opportunity isn’t about technology or marketing, it’s a business opportunity every executive in the organization should be involved in. All C-suite executives, including the CIO, must engage in a coordinated effort to decide how machine customers fit in the business model. Without that full team collaboration, progress will be partial, ineffectual and inconclusive.  

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Why Machine Customers Are Trending 

Machine customers represent a growth megatrend. This trend, especially with the advent of generative AI, will eventually become more significant than the arrival of digital commerce. 

On average, CEOs believe that 15% to 20% of their company’s revenue will come from machine customers by 2030. Gartner predicts that machine customers will be directly involved in, or have influence over, trillions of dollars in purchases by 2030.  

Machine customers are already among us performing tasks humans normally do such as the following: 

Companies that quickly learn how to create machine customers that purchase on behalf of the organization and from the organization, and those that learn how to sell to them, will gain an advantage in the trillions of dollars at stake. Others could find their traditional human buyers gradually disappearing. Machine customers can generate revenue opportunities, increase productivity and efficiency, improve health and well-being, and enhance the security of people and physical assets.  

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The Implications of Machine Customers on Organizations 

Machine customers impact a number of organizational functions including corporate strategy, digital commerce and customer service.  

Strategy leaders must investigate what kinds of machines will become customers in their industries. In some cases, machine customers could shrink a market, because their ruthless logic and efficiency will blast through sales that are overly dependent on human emotional or irrational behaviors. In many more instances, machine buyers’ vigilance, efficiency and reliability will create growth opportunities. Constructing machine customer platforms and apps requires advanced technology and skills. These might be beyond the reach of markets with resource constraints.  

Organizations will have a larger customer base to sell to because there will be more connected machines than human customers. They’ll also be able to capture hidden revenue opportunities that humans could miss. For example, when supplies run below the threshold or when equipment breaks down unexpectedly. Additionally, organizations will need to upgrade technology to support the larger volume and higher velocity of commerce orders. This will entail developing machine interfaces supported by application programming interfaces (APIs), data exchanges and event streams, where a traditional human-readable storefront doesn’t work. The main challenge is obtaining trust from human customers who will delegate purchase decisions to machines. 

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Organizations that embrace machine customers will be able to differentiate their value and set higher standards for effortless service. In customer service, GenAI can enable virtual assistants that can help human agents and can also interact with machine customers to understand the intent, help resolve the issue, and perform follow-up tasks. Automation and reduced human involvement can reduce operating costs and offer lower-effort experiences for customers. Customer service must shift from reactive customer service to proactive customer success management by using relevant data sources to gain a comprehensive view of the customer (and its machine) throughout the customer life cycle.  

IT leaders supporting customer experience and seeking to build a competitive advantage should plan for the future by architecting the data sources and API platforms needed to serve machine customers that shouldn’t, or won’t, use human-readable digital storefront. Become exceptional at digital commerce by modeling how selling to or serving a machine customer will impact existing processes across the operation.