The rise of Artificial Intelligence (AI) has sparked a fierce debate – are machines for us or against us? Whatever your point of view, there's one discussion point that's often missing: the impact that machines have on other machines. While we debate the machine-to-human argument, designers are creating machines to help enable other machines. And those other machines? They are your new customers called custobots.
In the emerging $30T Business-to-AI (B2A) marketplace, custobots are coming. In a recent article published in DC360, The Coming Era of Machine Customers, we shared that a custobot is a “non-human economic actor who obtains goods or services in exchange for payment” (Gartner.) In other words, a machine that orders from a machine. We shared an example of how it works in practice. It’s vital to understand this new market, because the use of custobots will not only simplify complex processes and reduce errors, but they rely heavily on logic to make their decisions, and your organization needs to get ready.
Custobots Leverage Logic and Data
Smart machines use sensors that capture and assess patterns. A chip or sensor provides data like usage level, power level, or tolerances. And a data point (or use case) will drive a purchase occasion. For example, when a commercial lawnmower needs oil, or a task light needs batteries, it will send a signal to the cloud that it’s time to reorder. The smart machine of the future doesn’t need product authorization from a person. At the right time the machine places an order (based on min-max levels) with a machine that manages inventory.
But what if the custobot doesn’t find an exact match, or the vendor is out of inventory? Custobots can use machine-learning (ML) and artificial intelligence (AI) for a smart search. If a Bill of Material (BOM) is programmed into another smart machine, a custobot can search using keywords or specifications. Previous history might also be added to the query, such as previous items searched or acceptable substitutions. And it happens at lighting speed.
And when a match is found, a custobot can evaluate pricing, shipping terms, delivery windows, and taxes to pick the optimal solution. And the manufacturer who wins will be the one with real-time data as well as the best credentials in their distributors’ systems.
Getting Started
Custobots will make purchasing decisions based primarily on information systems rather than personal relationships and will place a heavy emphasis on comparing product attributes. Quality data will be key. A focus should be placed on correct, detailed, real-time refreshed specifications and attributes - the best data you can offer.
This enables custobots to quickly and effectively compare products and pricing. When a custobot reaches a digital storefront (either as a guest or authenticated user) logic-based merchandising can help it find ample and relevant choices. Similarly, pricing should be transparent and contain an opening price point, so a smart machine finds it, and you don’t lower your search rankings in algorithms and in turn risk losing easy sales.
In Summary
Set a place at the table for this new customer with the help of your digital leadership team. A cross-departmental, cross-functional team familiar with digital use cases can not only help identify opportunities but also identify gaps in technology. They can also uncover roadblocks to data flow that inhibit optimal product and pricing management. At minimum your organization should be conversant in the language of machine-to-machine buying and be aware of custobots. For the sooner we embrace this new world, we'll find that machines are truly for us and for other machines.
