Kaushal Kurupati has in his hands stupendous experience and knowledge about product leadership in consumer internet, enterprise & cloud

If you are a fan of Star Trek, as I am, you will remember the “tricorder” in the hands of the spaceship’s doctor, who scans a patient with a hand-held device and out comes a health diagnosis instantaneously. While that is still a dream, we are not too far from doctors seeking the help of an Artificial Intelligence (AI)-powered system to help with diagnosis. In fact,recently an AI algorithm was shown to be just as accurate as 21 board certified dermatologists in detecting skin cancer. This algorithm was trained on 129K images of skin cancer lesions and it became an ‘expert.’ Will it replace your human doctor any time soon? Perhaps not yet, because these systems, while good at recognizing pixel patterns, don’t understand what they are diagnosing or really have a full picture of a person’s health.

Let us consider another arena: computers have been rated better than humans at chess for a while now. In fact, Google’s AlphaZero algorithm mastered playing chess in under a day, by learning from over 44 million games, and then beating the world’s best chess playing algorithm 28 times in a 100-game match and not losing once! While this is an impressive feat, this algorithm probably does not ‘know’ what a board game is.

These areas that have been bent to the will of AI all have something in common – they can all be ‘codified’ with data and analgorithmic model trained it. There is mathematical structure to disease diagnosis, game playing and even human language. Yet, these systems lack a broader general understanding of the world. Turns out common sense is easy to spot and demonstrate but hard to define and teach to computers.

Let there be no doubt however that AI driven algorithms are changing our world across a swarth of industries. The phrase “Artificial Intelligence” itself was coined quite early on after the advent of the first computers – in the 1950s over a summer at Dartmouth College. The promise that AIsystems will do much of the thinking, automate everything and take away human drudgery has existed since then. Yet, for decades the promised benefits didn’t come, weren’t obvious to everyone, and didn’t make any dent in daily lives.

Many things must come together for a technology to reach the masses and make its impact felt. Three trends are intersecting at the right time to drive AI into new areas every day now:

• Ubiquity of data – fully digitized lives and most physical and online interactions being captured by some Internet connected device.

Off the shelf AI algorithms – drag and drop advanced machine learning algorithms without having to code like a PhD.

On demand computing power–spin up computing power and storage in the cloud instantlywithout needing a huge budget and dedicated servers to get started.

Consumer data is being generated at an unprecedented volume and rate across myriad devices. In our family, I count about 25 connected devices around us on a consistent basis. Each of them has a view of part of our daily activity. Piecing all that data together will give a full view of our family daily routine, where we live, work, go to school, shop, dine, browse, search, watch, chat online, how much we exercise – in general how we live our life. In other words, a goldmine for any advertiser! This sort of detailed view into consumer lives never existed before.Marketers have always chased the consumer—their data more precisely – as habits have changed from print to radio to TV to Internet and now to social media and smartphones. Combined with easily codable AI algorithms, and computing power on demand, marketing and advertising are surely getting transformed.

Many parts of marketing and advertising are already data and algorithm driven: consumer behavior is quantified; segments created based on data; audiences targeted; content personalized; media buys automated; and analytics available for all campaigns

Many parts of marketing and advertising are already data and algorithm driven: consumer behavior is quantified; segments created based on data; audiences targeted; content personalized; media buys automated; and analytics available for all campaigns. We at Oracle have a real-time consumer behavioral measurement platform called Infinity that can capture and quantify every minute thing a user does on a web page or a mobile app or an IoT device. Even if a user is on different devices, platforms, etc., we can stitch a 360-degree view by creating an ID-graph to reconcile the multiple identities of a single customer. This connected data forms the core of our marketing automationand intelligence software that can then help marketers deliver hyper-personalized campaignsthrough email, web, or app channels. Surveys show 8 in 10 consumers have higher purchase intent and loyalty to brands that serve personalized content. Personalized content recommendations make services like YouTube, Netflix, Amazon, etc., sticky and indispensable in our lives. Now even McDonalds wants to create a customized drive-thru experience and personalized menu choices with their recent purchase of a big data and machine learning startup. Taking that to the next level, companies ideally want to be able to predict what I will like (to eat or watch or buy).

Among other creative ways that companies are trying to get a predictive edge, Disney,for instance,is using facial tracking software to map people’s expressions to emotions while watching movie trailers and then using it to predict when audiences might laugh at certain scenes. Overall, they want to understand audience sentiment and extrapolate to box-office success. Because your face gives away the right feeling you had while watching. Surveys are a thing of the past in trying to understand audience reaction to a movie trailer. Predictive analytics is what will give organizations a competitive edge. Marketers can use software such as ours to predict customer journeys and target against anticipated behavior.

Despite all of these advances of AI in marketing, the task of coming up with a creative is still based on intuition and is outside the realm of algorithms, but even parts of that are changing. Human intuition can be informed by data. Algorithms can look at past campaigns and give the marketer the data insight as to which images/videos performed better in the past and tease out the characteristics that led to better vs. poor performance. Knowing the past success drivers will make the marketing process more efficient, and importantly more effective.

Organizations that can connect the data-dots on consumer behavior will come out ahead. People who can derive intuition from data and not get lost in it will come out successful.There is aneed to develop the ability to marry science and art. Organizations will need a serious skills upgrade – marketers need to train themselves on how to leverage data science and still not lose their creative touch.Don’t expect things to change overnight but know that in few years marketing as you know will change substantially. A quote by Roy Amara, the erstwhile President of the Institute of Future in Palo Alto, California, is appropriate here, “we tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.”