Editor's note: Jim Longo is co-founder and chief strategy officer at Discuss. He can be reached at jim@discuss.io.
Artificial intelligence (AI) is taking the world by storm as one of the most exciting, and sometimes controversial, technology trends. The latest tool getting all the tech buzz is OpenAI’s ChatGPT which employs chatbots to write essays, poems, e-mails, etc., and is one of the fastest growing apps, surpassing one million users within a week of its launch. According to Grandview Research, the global AI market is currently worth $136.6 billion and is expected to grow to $1.81 trillion by 2030.
While AI has been around for decades, it has never really lived up to the expectations until more recently. Why is that? The technology industry has evolved thanks to increased data volumes, advanced algorithms and improvements in computing power and storage, making it easier and faster for computers to think and act like humans.
As businesses become more inundated with data from various sources, gleaning insights from this data can be an overwhelming task. AI is helping to solve one of the biggest problems in the market research industry: culling through thousands of interviews and transforming disorganized raw data into powerful intel.
Researchers are beginning to experiment with AI to help turn unstructured data into actionable insights. The desire to draw meaningful insights from business data is not new but the large volume of data being generated every day has made traditional processing methods ineffective. In addition, much of this data is more structured like spreadsheets with rows and columns of data that is easier to analyze. For example, a spreadsheet of point-of-sale data can easily reveal which stores are performing well and which ones are not.
In the world of quantitative research, data is interpreted using mathematical algorithms and models. This kind of black-and-white,...