A little over 200 years ago, Adrien-Marie Legendre published the least square method for regression and laid the foundation for many of today’s machine-learning models. While cognitive technologies have been in development for a long time, it was not until 2009 that the trifecta of innovative algorithmic developments, expansive data availability, and ever-increasing computational power came together to turn theoretical cognitive technologies into viable business solutions. As these technologies extend the power of information to tasks typically performed by humans, more and more industries and functions will reap the benefits—whether the long-term implications are recognized or not.
Broadly speaking, cognitive technologies fall into one of three solution categories: process automation, cognitive insights, and cognitive engagement. More specifically, cognitive technologies can automate digital or physical tasks, provide insights through data analysis, and/or engage with end-users like customers or employees. How these technologies are leveraged differs from one industry to the next. For example, as of 2019, the global retail industry used these technologies for customer engagement, supply chain logistics and management, supply and demand predictions, payment processing, digital/data security, product recommendation engines, post-sales customer service, physical security (security camera analysis), and product design and creation, in that order1. On the other hand, the automotive industry has largely benefitted from the automation of physical processes. Businesses embed cognitive technologies throughout their operations to increase efficiency, convenience, and safety or better differentiate their services. Here are a few famous examples:
1. Netflix and Amazon were early adopters of cognitive technologies to provide recommendations to their customers, which resulted in greater use of their platforms.
2. Domino’s Pizza introduced a virtual agent that allows customers to order pizza by voice, allowing the company to grow without needing more employees to answer phones.
3. NASA implemented RPA (robotic process automation) solutions for accounts payable, accounts receivable, IT spending, and human resources, allowing several business transactions to be completed without human assistance.
It is no surprise that large, well-funded companies are adopting these technologies, but can early-stage startups leverage these technologies? How specifically should they use it? In short, I suggest one question: are any day-to-day tasks tedious, repetitive, and mechanical? If the answer is yes, then there is almost certainly a way in which cognitive technologies can help. Small and medium sized business can specifically benefit to minimize administrative tasks like bookings, shipping and receiving documentation, and PO approval processes. As for breaking the bank, bots can range in price from $150 a month for Microsoft’s Power Automate RPA to millions of dollars for more complex RPAs that require consultants, developers, and maintenance. Somewhere in between, there is a cognitive technology from which you can benefit.
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