Artificial Intelligence (AI) isn’t just a new chapter for tech, it’s a new chapter in business. By automating cognitive tasks, AI empowers businesses of all sizes to reimagine their operations. By embracing this new paradigm, companies can amplify productivity and increase efficiencies.
AI allows companies to reimagine business practices
The story of the industrial revolution is the story of automation. Centuries ago, engineers developed machines to automate physical labor. Then came the computers which took over many transactional processes. And now, we are entering the age of Artificial Intelligence (AI) where advanced digital colleagues like Amelia are taking on cognitive tasks that were once solely in the domain of human workers.
Just as each of the previous automation paradigm shifts empowered businesses to thrive in new ways, so will be the case with cognitive automation. Here are three important ways that AI will benefit business:
We can make some predictions about how new innovations will disrupt the future by studying how older technologies have transformed the past. Manufacturing is the sector with the longest history with automation, and the impact on productivity has been striking.
Since 1975, output of US manufacturing has nearly doubled, while the number of workers employed in this sector has been nearly halved. Some may see these numbers and fear the obsolescence of human labor, however history has also shown that automation doesn’t replace workers, it augments their roles. Indeed, despite the proliferation of augmentation throughout the US economy, employment numbers remain notably robust. The real takeaway here is how automation in manufacturing greatly amplified the productivity of workers and their organizations. Now as we enter the age of AI, there is good reason to expect similar amplified productivity from workers whose roles are built around transactional and cognitive tasks — in fact, this is exactly the trend that we’re beginning to see.
The Freedom to Reinvest in New Business Areas
Automation decreases operational costs while maintaining (if not accelerating) output. This means that organizations are able to invest their savings in other areas, such as the creation of new employee roles with specialized skillsets.
Research and development can also receive additional investment. The past century has seen a meteoric rise in private R&D investments. Automation wasn’t the chief engine of this rise, but it certainly enabled enterprise decision makers to invest funds in R&D that were previously allocated for operational costs. At the very least, enterprises that don’t choose to reinvest in this area (or don’t have the financial freedom to do so) will find themselves at a competitive loss.
Opening New Revenue Streams
Many conversations about AI center on the ways that customers benefit from things like ubiquitous access to services. This increased accessibility is indeed a plus from the consumers’ point of view — but it is also a win for companies.
Customer service departments and call centers are often only operational during regular business hours. Right off-the-bat, this disenfranchises users who can’t step away for personal matters during work hours, not to mention the millions of people who work nights and evenings. By automating the user experience with AI, business can happen at any hour.
With a digital colleague like Amelia taking on the front-end, users can self-execute business transactions on their schedule (e.g. apply for a mortgage pre-approval at 3 am on Christmas Eve or purchase a new life insurance policy at 11:30 pm on a Saturday night). In the cognitive era, customers no longer need to contend with “normal business hours,” which means businesses can engage in transactions around the clock, bringing in additional revenue streams while minimizing costs.
Just as past leaps in technology have reimagined how business is done, AI promises to be just as disruptive and beneficial. The companies that anticipate and exploit these changes will be the ones who thrive in the new AI-powered technological paradigm.