It’s easy to get lost in the “noise” around the term Artificial Intelligence (AI) everyone is talking about it, businesses, government entities, school-aged children, and young adults. It’s on social media, online ads, football commercials, video games and billboards. I would say it’s ubiquitous from an awareness standpoint but how much is it used in business? My general sense is that besides Facebook, Apple, Google, Amazon, Microsoft, Tesla/SpaceX/Twitter, and NVIDIA there isn’t an abundance of commonplace use cases just yet. There are many theories as to why this is. One of my thoughts is everyone wants it but doesn’t understand how to implement and monetize it correctly.
In a recent statement, the CEO of Microsoft, Satya Nadella indicated that “SaaS is Dead” and software companies need to rethink their strategy with the use of emerging technologies. It has long been said that in this era “every company is a software company.” With this in mind, businesses need to embrace and understand the impact of AI, frankly quickly!
For AI to work, it needs fresh quality data. That is not an easy feat since the data in a mid to large enterprise can be in multiple places (systems, databases, spreadsheets, and documents) not to mention in the head of the people working at the company. All pose a significant risk of not being captured correctly or lost based on employee turnover and/or contracts ending. All these entities have required years of teaching by humans either from Data entry and/or experience. This data group represents the majority of IP every company possesses, today it operates as the brain of the enterprise. The current way of feeding and using the brain is inefficient, prone to leakage, and frankly archaic.
My advocacy is that all companies need to realize that they are losing money and efficiency continuing with this approach and are not gaining intelligence and insight at the rate that will be needed to stay competitive in the future. Often when we speak to customers, we refer to RPA (Robotic Process Automation) as the “hands” of a human and AI as the “brain”. This analogy is acceptable when you think that RPA’s use of AI could be limited in scope based on its function. If you think of AI that can be consumed by many things (i.e. APIs, Chat Bots, Data Analytics, SaaS Applications), that brain can serve a lot of touchpoints.
Simply put, the use of AI can make an enterprise brain or brains that solve specific business problems, never forget anything, and improve over time regardless of who and what comes and goes at the company. There are various ways to create this in-house intelligence using automation, data, and teaching. Once we understand that, we will begin to see exponential growth in the adoption and use of the technology.
And we might be happier, I hope?
Written by: Peter Camp, CTO & Founder
