Cloud computing, big data, and mobility enterprise tech trends have dominated the tech sector over the past several years. While Artificial Intelligence (AI) has occasionally re-emerged over the last 30 years, it has taken a back seat to what many viewed as these more “real” technologies. But recently AI has come back with a vengeance and the current buzz around it is growing louder as we near 2017. The Internet of Things has been one of the key catalysts in spotlighting AI’s value. The ability to ask your phone to look up local movie times with a quick voice command, a thermostat that learns your habits and temperature preferences, and the approaching availability of self-driving cars are very real AI-based applications. Could it be that AI holds more promise than previous technological innovations in regards to changing the way we live and work? It seems that investors think so: funding of AI companies has increased from $45M in 2010 to $310M in 2015, according to CB Insights.
With so much hype around which AI innovations are already here or around the corner, it is hard to determine which AI-based applications have the most potential to make the biggest impact. Below are the three AI impact areas I think will have the most staying power:
Virtual Assistants for Consumers
AI-enabled virtual assistants have opened up new channels for people to organize life and to engage with companies. Right now, you can ask your phone to schedule an appointment, or look to a chatbot to have a pizza delivered. As AI’s natural language processing capabilities become stronger, the uses for chatbots and virtual assistants will increase. For example, retail brands will be able to leverage this form of AI in conversational commerce.
Digitizing and Streamlining Legacy Business Processes
As much as we call it a “digital world,” many processes central to how businesses operate today still start with pen on paper. For example, most HR forms must still be printed to be completed, even if there is an eventual manual input of the same information into a central system later on. In health care, most intake forms are still on paper, and medical billing is subject to human errors. AI-based text analytics solutions hold the key to taking all of these unstructured forms with no standardization, and streamlining the flow of information from paper to digital without having to rely on human data entry and the associated risk of error.
Extracting Value from our own Data Surge
Perhaps it started with the ability to collect and store seemingly infinite amounts of information as a result of cloud computing, but today’s world is justifiably obsessed with data. Every device gathers information related to its use. Wearable fitness trackers do this; our cars do it; and our email servers certainly do, too. In theory, this onslaught of information related to our use and behavior is meant to inform, enrich and improve the next iteration of technology. However, an intermediate step involves the analysis of the raw data. At one time, it made sense to leave this responsibility to people and perhaps some carefully coded algorithms. However, the amount of data being produced now can overwhelm these traditional resources. Having AI extract value from the plethora of information at hand is both more reliable than an algorithmic approach, and can scale much greater than what we have available in regards to human capability.
AI has risen from the ashes multiple times, but it now can make a more compelling case to stick around given its ability to enhance practical solutions in the IoT, and beyond.