AI: Discovery, Definition, Debunking

It’s safe to say that we’re all aware of the impact that artificial intelligence (AI) is having on every industry. More so than any tech or product trend, it is redefining what’s possible for software products. Like every emerging trend, it takes time to understand whether AI is a flash in the pan or a lasting solution. For me, I saw AI’s potential during the 2016 holiday season.

Specifically, I saw that the top-selling item wasn’t a cell phone / book / kids toy. Instead, it was Amazon Alexa – which to me was a sign that artificial intelligence is here to stay. Furthermore, the popularity of AI-powered consumer products like Alexa proved to me that this technology could expand into the workplace.

Fast-forward to present day, my company is doing just that.

Furthermore, every software company “wants in” with artificial intelligence. That said, many people don’t even know what it is and how it impacts software. To me, AI’s definition is simply software that learns. In other words, it’s much more dynamic than traditional software that utilizes a singular approach to generate a “common” outcome. Instead, artificial intelligence picks up patterns over time to refine the output and provide users with better results.

In addition to struggling with AI’s definition, I’m sure you’ve heard people asking about its relationship to machine learning. Simply put, machine learning is a subset of solutions that occupy the larger artificial intelligence bucket. For example, machine learning draws from AI’s broader array of software solutions to accomplish a variety of different tasks.

Most importantly, it’s vital to understand AI’s capabilities.

Said differently, you also need to understand where it’s been underestimated and over-hyped respectively. First, let’s consider how rapidly AI continues to reshape expectations for growth and overall impact. A few years ago, it was estimated that artificial intelligence products would reach $60 billion globally by 2025. Fast-forward to just a few months ago – that estimate is now $110 billion. Ultimately, we need to stop underestimating its growth potential and overall importance to future products. Furthermore, it wouldn’t surprise me if the AI market reaches $200 billion by 2025.

Finally, we also need to pump the brakes on AI’s ability to “run our lives” or understand everything about you in 10 minutes. For example, movies like Her and Ex Machina would lead you to believe that AI is advancing “Matrix-level” rates. However, if you use Siri for more than 10 minutes – you already know that this couldn’t be further than the truth. Ultimately, artificial intelligence is capable of plenty. However, we’ve largely overestimated what it can do in the short-term – and underestimated what it will become in the long-term.

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About the speaker
David Karandish, Founder & CEO Member

David Karandish is the Founder and CEO of - bringing AI solutions to the workplace by optimizing day-to-day processes with innovative approaches to managing tasks. Prior to starting, David was the CEO of Answers - one of the largest platforms serving Q&A content to more than 100 million users. In addition, David was the Co-Founder and CEO of AFCV Holdings - a portfolio company focused on acquiring new technologies and businesses focused on providing Q&A content to users. David is a graduate of Washington University in St. Louis and continues to live in St. Louis where he is an active supporter of the city's startup community.

About the host
Mark Pydynowski Products That Count, Podcast Host on Product Talk

Mark has deep experience (1) bringing new B2B products to market, (2) leading early-stage sales and business development, and (3) conducting user research. He has conducted 1,200+ user interviews over the past 10+ years building and selling new products (software and hardware). Mark runs, a blog to help WashU students learn how to land their first job from alumni that have already landed theirs.

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