Artificial intelligence has generated considerable press for its ability to improve efficiency, perform certain tasks at a speed and level of accuracy beyond human reach, and potentially save businesses on costs through automation. AI certainly offers a chance to save money and increase the bottom line, but what if thinking about AI only in terms of cost cutting paints an incomplete picture? Can AI not only save businesses money, but create value as well?
[[24]7.ai co-founder and CEO PV Kannan and business strategy author Josh Bernoff pose this question in a recent article for Barron’s, arguing that AI is more than a savings tool – its “real value…may well be in generating revenue and growth, not in cutting headcount.”
The value add from AI comes in the form of an improved customer experience, due in part to now-ubiquitous tools like chatbots. One notable success story comes courtesy of TGI Fridays, who offers “an irreverent, brand-appropriate chatbot available through Facebook Messenger and Twitter.” This millennial-geared tool is available for interaction 24/7 and has proven exceptionally valuable to the restaurant chain’s bottom line during business hours – it “has boosted the chain’s takeout orders by $150 million a year.”
But value isn’t solely derived from automation itself – the real driver is “getting rid of friction in customers’ interactions with companies.” Kannan’s company worked in conjunction with Dish Network to create an automated support bot called DiVA, which eventually handled “4 million customer interactions per year…[or] the most common 30% of customer questions.” Its ability to facilitate last-minute pay-per-view orders meant an additional $6 million in event revenue for Dish; it also provided “an infinitely patient and consistent machine that provides definitive answers 24 hours a day, 7 days a week” for Dish customers.
Virtual agents have proven efficiency benefits as well. Their capacity to sort through information within a pre-programmed set of parameters means a way to separate the wheat from the chaff in processes like identifying sales leads. Kannan cites inbound marketing and sales software developer HubSpot’s Facebook Messenger chatbot as one success story: the bot “suggests useful content, pre-qualifies leads, and connects prospects with HubSpot’s salespeople,” leading to a higher quality of sales lead – one that is “40% more likely to engage productively with a salesperson.” Virtual agents can also collect information in advance of an interaction with a human agent – rental car service Avis-Budget “[collects] five key pieces” before passing the customer to a human employee, like pick-up and drop-off times and locations, creating a smoother customer experience.
Businesses are enjoying the value of automation, but it is clear that viewing AI as a simple cost cutting tool is just a piece of the puzzle. Artificial intelligence can build a better customer experience – and companies in the know can reap the financial benefits from not just cuts, but the ensuing growth.
The Investment and Financial Industry Faces the Same A.I.-Driven Revolution
Hedge funds and large institutional investors have been using Artificial Intelligence to analyze large data sets for investment opportunities, and they have also unleashed A.I. on charts to discover patterns and trends. Not only can the A.I. scan thousands of individual securities and cryptocurrencies for patterns and trends, and it generate trade ideas based on what it finds. Hedge funds have had a leg-up on the retail investor for some time now.
Not anymore. Tickeron has launched a new investment platform, and it is designed to give retail investors access to sophisticated AI for a multitude of functions:
And much more. No longer is AI just confined to the biggest hedge funds in the world. It can now be accessed by everyday investors. Learn how on Tickeron.com.
Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.
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The average fundamental analysis ratings, where 1 is best and 100 is worst, are as follows
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