By automating business products with Artificial Intelligence, companies are able to decrease overhead, devise new revenue streams, increase productivity, and minimize risk. This doesn’t just open the door to mere growth, it can help companies find new ways to scale.
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AI intelligently automates business practices to facilitate unprecedented growth
Today’s business decision-makers are no longer looking to merely grow, they want to scale — that is, generate revenue at an exponential pace, while increasing costs at an incremental one. Thanks to the digital revolution, this objective isn’t only attainable, it’s expected.
With each technological breakthrough comes new opportunities to scale. We’ve seen previous massive scale-ups in the wake of the PC, Internet, and mobile revolutions — and now, Artificial Intelligence (AI) is the disruptor du jour. Following decades of research to lay the engineering groundwork, AI technologies are maturing into robust business products capable of generating bountiful new revenue streams while mitigating both costs and risk.
Automation fuels scaling by removing repetitive steps all along the value chain, while subsequently increasing productivity. By streamlining business processes, companies are able to decrease overhead and create value much faster. These savings can then be reinvested in other parts of the business (including new forms of automation). Each additional layer of automation adds to this positive feedback loop, which not only adds to a company’s potential, it amplifies it.
The positive feedback loop
In 2012, Amazon purchased automated robotic picking-and-packing company Kiva for $775 million and quickly saw quantifiable returns on its initial investment. In the packing centers where Kiva’s technology was implemented, the “click to ship” cycle time was slashed from 60-to-75 minutes to just 15. Due to more efficient use of space, inventory capacity increased by 50% and overall operating costs fell by an astounding 20%. Automation allowed Amazon to slash its overhead while maintaining (if not enhancing) its offerings.
The increased efficiency brought about by automation makes it cheaper (i.e. less risky) for a company like Amazon to invest in growth. Last year, for example, the company nearly doubled its physical footprint from 7.2 to 14 million square feet – this wasn’t all warehouse space, but in each of the previous two years the company swelled its warehouse footprint by 30%. More warehouse space allows Amazon to offer more products and better service, which earns them more money, which leads to massive growth and scale.
By streamlining business processes, companies are able to decrease overhead and create value much faster.
Now, as we enter the age of AI, it isn’t only physical tasks that are being automated by technology, it’s cognitive ones. In a previous technological era, tasks related to forecasting and decision-making could only be handled by the human brain. But now these tasks can be handled by machines, and likewise optimized for maximum impact.
One report from McKinsey found an unnamed European retailer was able to improve earnings after implementing AI-enabled forecasting, which helped it anticipate fruit and vegetable sales and allocate its resources accordingly. The German e-commerce merchant Otto cut surplus stock by 20% and reduced returns by more than two million items a year, using deep learning to analyze billions of transactions and predict what customers will buy before they place an order. By automating cognitive tasks, these companies were able to cut overhead (without sacrificing service) and increase productivity which further facilitates the positive feedback loop needed to scale.
Beyond decision making, AI can now deliver human interactions via an intelligent user interface (UI) that customers can access using natural language. A robust digital AI colleague (such as Amelia) offers comprehensive access into a company’s systems, which customers navigate using natural conversational language, so the bar is lowered to all customers, regardless of technical proficiency. For example, with AI, a banking customer has the ability to handle everything from simple queries (e.g. checking account balances) to more complex tasks (e.g. setting up a new joint checking account) without human intermediaries.
Cognitive agents on a company’s front-end also aids scaling by accelerating the speed at which new products and services can be deployed. A conventional customer service department requires time to learn about new products and integrate new business procedures, while a digital workforce can implement them around the globe at the speed of electrons. Not only can new products be quickly added to the marketplace, AI has the ability to be trained to intelligently upsell (e.g. a digital colleague can proactively offer a deal on joint coverage when it learns a customer has just gotten married).
As businesses devise new ways to automate tasks all along their value chain, they will decrease overhead and increase earnings which lowers the risk to further investments. As cognitive solutions become increasingly capable, it also increases the potential to scale.
