Today Artificial Intelligence is viewed by many as a mysterious miracle technology. Tomorrow AI will be as commonplace as electricity, powering all sorts of software applications and smart devices. Whether it be conversational AI, machine learning, deep learning, NLP or RPA, a variety of these technologies will underpin not only discreet applications and workflows, but a series of applications and workflows to automate complete systems – thus the phrase Intelligent Process Automation, which we covered earlier this week at IASA 2019.
Our advice to the IASA audience as we wrote in these pages several weeks ago was to 1.) define your business problem, 2.) understand your data, 3.) Execute the AI project. No time like the present to capture learnings.
It is easier than ever to embark on an AI journey as technology behemoths such as Amazon (AWS), Microsoft (Azure) and Google (GCP), bake core AI capability into their respective cloud offerings. These giant cloud service offerings underpin everything from Netflix (AWS) to Starbucks (Azure) to startups.
Smart applications and smart devices will increasingly appear in the workplace and the home. More computing will be done on-device (i.e. on the phone) as more companies follow Google’s example.
The one gating factor will be the availability (or lack thereof) of Data Scientists and those with advanced degrees in Statistics and/or Mathematics – those who “know” data. Anyone who recruits Data Scientists knows what I’m referring to. Some companies will find it difficult to scale for this reason and will ultimately choose to sell to a strategic acquirer or to private equity. We may cover this “Data Scientist Recruiting War” in a separate article. Should you find yourself in this predicament, check out ODSC and KD Nuggets as recruiting resources. Until then, may AI be with you.