Nasdaq reported today that they are investing in blockchain technology, and pushing for crypto and blockchain adoption. According to an official press release, Symbiont successfully closed a $20m Series B funding round. Nasdaq Ventures led the round which also included investors such as Mike Novogratz’s Galaxy Digital, Citi and Raptor Group among others.
Adena Friedman, President, and CEO of Nasdaq commented, “It is difficult to ignore the huge amount that investors, including some of the most sophisticated global investors, have poured into digital currencies in recent years. The invention itself is a tremendous demonstration of genius and creativity, and it deserves an opportunity to find a sustainable future in our economy …
At Nasdaq, we are working to help cryptocurrencies gain investors’ trust by offering our technology for trade matching, clearing, and trade integrity to start-up exchanges. We have also invested in ErisX, an institutional marketplace for cryptocurrency spot and futures. While this year will be another proving ground for cryptocurrencies, we believe digital currencies will have a role in the future. The extent of its impact will depend on the evolution of regulation and broader institutional adoption.”
The MIT Technology Review recently stated that the blockchain will become more useful, however, they also believe that blockchains will start to become boring this year. After the Great Crypto Bull Run of 2017 and the monumental crash of 2018, blockchain technology won’t make as much noise in 2019.
The blockchain enthusiasts are still working towards gaining world adoption for the technology, however as often cited, the level of investment into the technology should not be taken as a sign of its inevitable success. If that were the case the fate of so many grandiose startups in the 1999 – 2000 boom would have turned out quite different considering the level of investment that went into many of them. A leading venture capitalist told me once, “the graveyard is littered with many brilliant technologies.”
If google trends is any indication then interest in bitcoin and blockchain have been declining, or at least for the moment.
On this past Wednesday, January 23, 2019, VanEck, the firm that had sought SEC’s approval to trade Bitcoin ETF on the CBOE exchange, withdrew its application. Analysts and crypto followers believed that the launch of a regulated Bitcoin ETF would attract billions of dollars in investments and saw these initial moves as a positive step towards global adoption. Yet, now that they have withdrawn their application, the news is being spun as something positive for the crypto industry, or at least according to NewsBTC.
As the great baseball-playing philosopher, Yogi Berra once said, “It’s tough to make predictions, especially about the future.” Nassim Taleb views those trying to predict the future as simply “charlatans.” The problem is that almost all forecasters work within the parameters of the Gaussian bell curve, which ignores large deviations and thus fails to take account of “Black Swans”. Taleb defines a Black Swan as an event that is unexpected, has an extreme impact and is made to seem predictable by explanations concocted afterwards. It can be both positive and negative.
One of these so called deviations could be the advances of Quantum Computing, as we previously wrote about here, or it could be something not yet determined.
The simple fact is that you have two groups — interested participants and non-interested participants. The interested participants will keep investing time and funds in order to realise the original objective of creating a decentralised peer-to-peer network where no single institution or person controls it. The non-interested participants will only adopt the technology once they believe it is in their advantage to do so and it becomes as simple as handing a friend a dollar bill.
According to futurist George Gilder the era of Google could be coming to an end. In his recent book “Life after Google”, Gilder explains why Silicon Valley is suffering a nervous breakdown and what to expect as the post-Google age dawns.
Is it worthwhile paying attention to what somebody like George Gilder says? Putting aside the fact that nobody can accurately predict the future on a consistent basis (as has been shown by Gilder’s track record), it is possible to make informed statements about the future based on sound logic. Here Gilder does base his assumptions on more than conjecture.
So where does Gilder come up with such an outlook regarding Google? As Peter Thiel pointed out, “Google’s algorithms assume the world’s future is nothing more than the next moment in a random process. George Gilder shows how deep this assumption goes, what motivates people to make it, and why it’s wrong: the future depends on human action.”
The argument is based on an analysis of big data. Right now, big data looks like it holds all the answers for any questions a person or company might have. William Terdoslavich wrote in InformationWeek, “At the heart of big data is the search for “insight — some correlation or finding that eludes the seeker until he or she adds another terabyte or 10 of data, just in case it is lurking there. At a certain point, the law of diminishing returns has to kick in. Adding another 100TB becomes redundant.”
Nassim Taleb pointed this out by the following analogy, “We humans do not predict when it’s safe to cross a road by adding more different data-points, like e.g. the color of the eyes of by-passing car-drivers, to our decision-making process, but by filtering the data and only assess what’s relevant to get across safely.”
In 1972, Gordon Bell formulated what is now known as Bell’s law of computer classes. It describes how types of computing systems (referred to as computer classes) form, evolve and may eventually die out. New classes of computers create new applications resulting in new markets and new industries. Gilder believes that Google can’t continue on the present path as we now need an entirely knew infrastructure.
Kurt Godel, the brilliant Austrian mathematitian exposed the limitations of mathematics (the incompleteness theorems). He proved that there can be no human construct, no human system of thought that does not rely on some reality outside of itself. It shows that human intelligence could not be recreated by a traditional computer.
Google was built on ads. All these arguments can be seen as presenting a case where Google’s system of aggregating huge amounts of data to create adverts will inevitably break down. There is also the concern that Google and Silicon Valley in general have put security on the back burner. The fear is that Google has been avoiding the challenge of security across the internet by giving away most of its products for free, and financing itself with an ingenious advertising strategy. This has become more apparent with the recent massive data breach at Google+.
But is it really possible for a company such as Google, which is so engrained in everybody’s daily life, to cease to exist? A good way to understand the present and future is to look at the past in order to gain some insight.
Comparing the 1955 Fortune 500 companies (here) to the 2017 Fortune 500 (here), there are only 60 companies that appear in both lists. In other words, fewer than 12% of the Fortune 500 companies included in 1955 were still on the list 62 years later in 2017, and 88% of the companies from 1955 have either gone bankrupt, merged with (or were acquired by) another firm, or they still exist but have fallen from the top Fortune 500 companies (ranked by total revenues). Many of the companies on the list in 1955 are unrecognizable, forgotten companies today (e.g., Armstrong Rubber, Cone Mills, Hines Lumber, Pacific Vegetable Oil, and Riegel Textile). One recent name that was driven into extinction by its own technology was Kodak. They came up with the first digital camera but did not capitalize on it.
It’s reasonable to assume that when the Fortune 500 list is released 60 years from now in 2077 (although it could happen much sooner), almost all of today’s Fortune 500 companies will no longer exist as currently configured, having been replaced by new companies in new, emerging industries.
In any case there was a time when Google didn’t exist and the world was inundated with search engines. Nobody was really crying out for somebody to build a new one. To imagine Google being replaced by another technology wave is by no means difficult. It is probably just a question of how fast it happens.
When mentioning Payments War, some people think of Shopping Wars and fist fights at Walmart on Black Friday. This article is not about that. The Payments Wars are actually multiple wars. A war on cash. A war for your shopping behavior and data. A war for your wallet. These wars are raging both online in the digital world as well as offline in the analog world and the two worlds are converging as combatants vie for cashless digital transactions for offline payments. Why should you care? Every time you buy something, whether you like it or not, it is over you and your data for which the battle is being fought. Your payment behavior and your payment data is what they are after. How will you pay and which platforms will be used? Will that be cash, credit card, debit, PayPal/Venmo, Square, Bitcoin and other cryptocurrencies, Apple Pay, Samsung Pay, Amazon one-click payments, Visa, Mastercard, Discover, Amex or even a credit line offered at the time of checkout?
Many may not realize this war going on right before their eyes each and every day as they buy their coffee, their lunch, their gas, groceries, electronics and anything else. And it has been going on for a long time. The winner wants to be the master of how consumers pay for things. As hinted above, the reasons are several-fold. One is, that at scale, there is money to be made processing payments and slicing a few cents or more off of each transaction which amounts to massive amounts at scale. To put this in some context here were the quarterly revenue volumes reported by a few of the combatants in the summer of 2018
- July 2018 Visa reported $5.2B in revenue for the prior quarter (+15% YoY)
- July 2018 PayPal reported $3.86B in revenue for the prior quarter (+22% YoY)
- July 2018 Mastercard reported $3.67B in revenue for the prior quarter (+18% YoY)
- August 2018 Square reported $817M in revenue for the prior quarter (+48% YoY)
A 2017 report by Statista estimates that total payments revenues, which were 1.6 trillion US dollars in 2016 will reach 2.2 trillion US dollars by 2021. That is what the processors are earning on payments. The overall payments volume, what PayPal calls TPV or Total Payment Volume, is a much higher amount.
These massive volumes of payments occur each day online, in stores around the world, at market places, peer to peer, travel and transportation, domestic services, credit payments, business to business payments, cross border and international payments… in other words, there is a lot. We were unable to find exact figures for the total value and number of transactions comprising annual payment volumes including cash and non-cash world-wide, but you can easily see that this number is easily in the trillions. Effectively it would probably be very close to the sum of the GDP (gross domestic product) of all countries – in other words the Gross World Product which is currently near $80 Trillion dollars a year.
Alibaba, the world’s largest (454M buyers) online market place processed $547 Billion of payments in China alone in 2017. So while $547B is large, it is a small fraction, less than 1% of world GDP … or total world payment volume.
Secondly and some may argue even more valuable than the processing fees, generating revenues for payments companies such as the ones mentioned above, is the data that can be collected on consumer and merchant behavior. The Hutch Report recently chronicled how data is quickly becoming the new biological nerve gas. The credit card associations assign a merchant category code to each merchant and this code corresponds to the type of business or service the company offers. But this is just the tip of the iceberg, data is collected for each transaction on the amount, the location, the date and time, the type of transaction (purchase, refund, withdrawal, deposit, etc), the type of account, card number, identity of the card acceptor (eg. merchant), information on the terminal used for payment, and much more. Apple already has over 450 million credit cards on file related to iTunes, the iOS Appstore, and Apple TV. In addition to knowing what media you consume, with Apple Pay, they will know even more about you. In addition to advertisers and the merchants themselves, payments data is also super interesting to investors and market speculators. Investors and speculators will go to great lengths to collect data in order to build an edge for themselves. There are now even companies such as RSMetrics that produce and sell aerial imagery of retail outlet parking lots and production facilities. Payment data is much more granular and refined. In addition, the Government also loves digital data, particularly digital cash because then they can completely monitor it, control it, and even charge negative interest rates quite easily if they so choose.
Given the size of the battlefield, a fragmented regulatory landscape and the existence of a plethora of consumer segments, consumers and consumption types … these wars for how you pay and how your payments data is collected will continue to rage for some time.
Data is fast becoming the new weapon of choice. Those who dominate data will dominate power because power comes from insight into other nation’s activities. Harness that insight and you become more powerful than any other adversary.
One of the ways of harnessing that insight is through powerful computational power, such as Quantum Computers (see our special report on Quantum Computers here). These computers will have the ability to break codes and passwords in seconds. The US, China and Russia all know this, which is why they are racing to create the most powerful computers possible as well as the artificial intelligent algorithms that will be run by those computers.
Chinese scientists are currently developing a next-generation supercomputer capable of performing 1 quintillion (a billion times a billion) calculations per second, which, if successful, will further enhance China’s leading position in the field. Tianjin’s National Supercomputer Center is working with the National University of Defence Technology in Changsha, Hunan province, to develop the super scale computer. Meng Xiangfei, assistant director of the center, says the aim is to make the computer by 2020. All the hardware and software is to be developed by Chinese engineers.
Not to be outdone by the Chinese, the US recently unveiled “Summit.” According to Dave Turek, vice president of high-performance computing and cognitive systems at IBM Summit is “the most powerful, smartest supercomputer in the world,”. It will crunch through roughly 200 quadrillion mathematical calculations each second, a speed called 200 petaflops. That as fast as each of the planet’s 7.6 billion people doing 26 million calculations per second on a handheld calculator.
The marketplace is beginning to recognize that AI and high-performance computing are not separate domains but things that need be viewed as integrated.
“Artificial intelligence is the future, not only for Russia, but for all humankind,” explained Putin. “It comes with colossal opportunities, but also threats that are difficult to predict. Whoever becomes the leader in this sphere will become the ruler of the world.”
In that same speech, Putin also mentioned that he would not like to see anyone “monopolize” the field. “If we become leaders in this area, we will share this know-how with entire world, the same way we share our nuclear technologies today,” he told students from across Russia via satellite link-up, speaking from the Yaroslavl region.
China realized the power of data long ago. It is common knowledge, especially by those who have travelled to China, that China only allows internet sites with which they control the data flow. As of May 2018, more than 8,000 domain names were blocked in mainland China under the country’s Internet censorship policy, which prevents users from accessing proscribed websites in the country. That includes Facebook, Google, Gmail, Twitter, Instagram , etc., pretty much the top 500 websites that are not Chinese.
The US has taken advantage of their unique position of being home to many of the most innovative technologies over the years. It has enabled them to harness vast amounts of data on all other countries where these US companies reside (except China of course). We know that the government has sanctioned companies such as Apple, Facebook or Twitter to hand over data on their users in a number of occasions. We also know from the Edward Snowden revelations that the NSA has developed a vast network of data sources. In spite of this leadership roll, the US position is being eroded quickly as the others play catch up.
When it comes to applying facial recognition in China, the country seems to be farther ahead than any other. The Shanghai metro is developing facial recognition systems that will be placed at the entrance of each subway to verify the identity of commuters. A new police car can now do a 360-degree scan to identify faces at up to 60 yards away while traveling at 75 miles per hour. Railway police use facial-recognition eye ware to identify someone in just 100 milliseconds from a database of 10,000 individuals. Unmanned convenience stores use facial recognition for payments, while Kentucky Fried Chicken uses “smile-to-pay” technology. China’s answer to Airbnb, Xiaozhu, will soon use facial recognition for check-ins. Chinese exam authorities are using facial recognition to catch cheaters for competitive college entrance exams. So not only have they compiled a mass of data on their population, that data is now being made use of in powerful tools.
One of the Chinese companies leading the pack is SenseTime, founded in 2014. Surveillance makes up a third of SenseTime’s business. Their clients are local governments throughout China.
SenseTime’s clients also include private security firms and in fact, it supplies the core technology to seven of China’s 10 largest security firms in addition to financial services companies, banks, mobile operators and the smartphone industry. They have become China’s largest unicorn – defined as a startup worth $1 billion or more – with a valuation of more than $3 billion.
Megvii is the countries second largest AI company. ”The government is pushing the need for this technology from the top, so companies don’t have big obstacles in making it happen,” says vice president Xie Yinan. “In America, people are too busy discussing how they should use it.” At the same time, China’s State Council, has already laid out goals to build an artificial intelligence industry worth nearly $150 billion by 2030. China has consistently been ahead of the curve in terms of utilizing artificial intelligence (AI) for surveillance. The country’s CCTV system tracked down a BBC reporter in just seven minutes during a demonstration in 2017.
As technology advances, these governments and private companies will continue to compile data on each other and every individual they can in order to gain the upper hand on their adversaries. We recently learned that Cambridge Analytica had access to Facebook data, however they apparently only had access to Facebook likes. From this one input, their artificial intelligence programs were still able to design a profile of the emotional state of the users. Imagine what they will be able to accomplish with data coming from Amazon Echo (their data has already been subpoenaed in a murder trial to help catch a criminal), Google Home, Siri, iBeacons in thousands of retail outlets, cameras on the streets, Fitbits , etc., in addition to all those free websites, such as Facebook, Pinterest, Twitter or Instagram.
Remember, if the product is free, then you are the product.
Have you ever walked into a room of a small group of people and felt a blast of negative energy? Everything looks normal enough but you have an uneasy feeling. Later you find that a couple among the group have been arguing. You were not aware of the reason at the time you entered but you felt the presence of negative energy well before you even knew what was happening.
Equally, you may have met somebody who affects you in a positive way. They are fun to be around. They tend to make anybody that comes in contact with them feel good. They have a way of emitting positive energy. We have seen that by adapting a lifestyle that leads to emotional and physiological balance you may have a positive influence on all others around you. If not, the opposite becomes true.
So how does this apply to a world where people have become accustomed to communicating with each other by distance, through smartphones and texting? If we can no longer sense the presence of the person we are speaking with, are we truly connected? Mark Zuckerberg wrote in 2017 for the first Facebook Community Summit, “For the past 10 years, our mission has been to make the world more open and connected. We will always work to give people a voice and help us stay connected, but now we will do even more. Today, we’re expanding our mission to set our course for the next 10 years. The idea for our new mission is: Bring the world closer together.”
This prompts the question, “Does a world connected by smartphones, web interfaces, false personas and anonymity constitute a world that is more open?”
Zuckerberg continues, “I always believed people are basically good. As I’ve traveled around, I’ve met all kinds of people from regular folks to heads of state, and I’ve found they almost all genuinely care about helping people.” Ironically, Zuckerberg opted to travel and meet these “regular folk” in person, when he could have quite easily struck up a conversation with them via their facebook page.
He goes on to say, “We all get meaning from our communities. Whether they’re churches, sports teams, or neighborhood groups, they give us the strength to expand our horizons and care about broader issues. Studies have proven the more connected we are, the happier we feel and the healthier we are. People who go to church are more likely to volunteer and give to charity — not just because they’re religious, but because they are part of a community.”
The groups and communities he is describing are those that meet up personally to share thoughts and ideas. Meetings where they share the experiences together in the same location as opposed to sharing it through a text message. They are sharing each other’s company. They generate energy and nurture others as others generate energy and nurture them.
Ironically, what some may see as a connected world, others see as a world of human’s becoming more distant and isolated. Communicating with others via technology removes that energy that we all share when we speak with someone face to face. You do not get a sense of a person’s energy through a text message or tweet. You are not able to read the body language. As human’s, we communicate with the tone of our voice, our body language, our eyes etc. We communicate on many different levels.
Some call this intuition yet others believe that we, as humans, create energy and have the ability to transmit that energy, be it negative or positive. Any thought, intention or action triggers an emotion which gives rise to this energy. Our thoughts and memories are essentially energy.
Energy released by an angry individual is shared with all people including plants, animals, and objects that he or she comes in contact with. This is how the negative or positive energy gets passed on from one person to another. You can feel that loss of energy yourself when you fall ill. Negative energy robs you from your vitality and wellbeing, while positive energy rejuvenates, and keeps you in a state of joy, happiness and good health.
Social media claims to be connecting people but to what extent? Isn’t it a purely superficial connection void of any real feeling? Social media has its place but nothing is a replacement for human contact. Human contact and energy seems to be the missing link in our newly “connected world.”
From the time you wake up in your Nest operated home or apartment until Sundown, you have probably made a number of Google searches on your iPhone, used any number of messaging applications, or maybe purchased a few things from Amazon, unaware that they are all compiling data from you. But wait, maybe you just went brick and mortar instead and went for a walk downtown, amongst all the cameras watching you. You may have wandered into a Macy’s store where there is an array of iBeacons tracking your every move. Regardless, in a world of data tracking, it is clear that being anonymous has become an incredibly difficult task.
It is not difficult to understand why we have seen this explosion of data tracking. This data has become very valuable to companies and brands. We explained in our previous article, “Has the quest for marketing data gone too far?” how Target has the ability to know when a girl has become pregnant well before her family. Brands want to know everything about their customers. They want to know what they want, when they want it and how much they can use of it. Very simply, the accumulation of more and intrusive data translates into knowledge and knowledge translates into sales which translates into the holy grail, “greater profits.”
We identified 6 companies who are working with the latest in artificial intelligence technology to learn more about everything you do and feel.
Real Eyes believes that emotions drive behaviour. Understand a consumer’s emotional state and you will be able to better understand their behaviour. Using webcams and the latest computer vision and machine-learning technologies, they measure how people feel as they watch video content online. Their emotional intelligence enables brands, agencies and media companies to confidently target optimized content to the right audiences. You may never watch a video in quite the same way again!
Aura Vision Labs
Aura Vision wants to help brands discover why shoppers buy. They have a deep learning technology that seamlessly captures powerful, anonymous insights from any camera. They want to help companies harness their existing video systems or easily deploy low-cost cameras, in-store or on-street. They promise to reveal product performance with precise behavioural intelligence, from entrance to checkout. They are deploying solutions for brands, retailers, market research agencies, and commercial real estate. Smile when you look up at those cameras!
This company provides both predictive and historical queue information at security checkpoints and immigration. Their predictive queuing solutions, utilized in several of the world’s largest airports, are regarded among the most accurate in the world. With lane detection capabilities, they also provide lane open recommendations by hour and day to improve passenger flow through security. In addition to airports he company uses Bluetooth on mobile phones to tell big box stores, and grocers about consumers movements — where they go and how long they spend there. Companies are very interested in this kind of data so get in line!
Invoca helps the modern marketer optimize for the most important step in the customer journey: the phone call. They believe that the key to driving revenue is a set of insights into phone calls and conversation that are highly actionable, relevant to a business, and available in real-time. With Invoca’s Voice Marketing Cloud, marketers can get granular campaign attribution to understand why customers are calling, gain real-time intelligence about who’s calling and analyze what’s being said in conversations. Their product consist of a signal intelligence engine. Signal taps into hundreds of data points and uses marketer friendly tools and the power of machine learning to help you understand not only where calls are coming from, the outcome of those calls, and new insights into the customer journey. Next time you call customer service think about who else may be listening!
Affectiva was spun out of MIT Labs. They believe that in order to improve road safety and to offer a stellar transportation experience, there must be a deep understanding of driver and occupant emotions, cognitive states, and reactions to the driving experience. Affectiva Automotive AI unobtrusively measures, in real time, complex and nuanced emotional and cognitive states from face and voice. This next generation in-cabin software enables OEMs and Tier 1s to monitor driver state and measure occupant mood and reactions. Although they don’t mention it, as a standard technology in every car you could imagine how the police force would be very interested in having realtime technology understanding who is reacting irratically in an automobile.
As in the case of Real Eyes, BehaviorMatrix is a behavioural analytics firm founded on the principle that human behaviour is driven by emotion. Their approach is built on proprietary technology, which allows BehaviorMatrix℠ to delve deeper in the data mines of human perception and emotion, to deliver actionable data that a brand or company needs to be successful. Being able to find the emotional drivers and track them over time gives BehaviorMatrix the most comprehensive information in the field of behavioral analytics.
These are only 6 examples of how companies are diving deeper into data tracking with the use of artificial intelligence. Although the debate is only getting started, there is never any mention of who this data belongs to or if compiling the data requires some sort of consent. As Facebook founder Mark Zuckerberg stated clearly before his presentation before congress, “users own their own data” and essentially sign off to allow Facebook to make use of it. Providing data is one thing but this debate will only get more complex when we start to think about companies tracking and selling data based on your emotions and behavior. Stay tuned. The Future is here.
(This article first appeared on Tenfold.)
Today, it is no longer a question of adopting AI or not. Instead, ask yourself if you and your sales team are ready for the inevitable. Artificial intelligence for business is a reality. If your goal is to forge ahead and lead in your field, then you need to adapt to a workplace where AI plays a crucial role.
As J.J. Kardwell, founder and CEO of predictive marketing software company EverString, puts it: “Growth-focused sales organizations of every size and stage cannot afford to ignore the benefits of AI-assisted sales.”
Where is AI for Business Today
“Artificial Intelligence heralds dramatic potential for growth for both the economy and for humans.”—Accenture Institute of High Performance Managing Director-Economic Research, Mark Purdy.
According to research done by Accenture, artificial intelligence is projected to improve labor productivity by as much as 40 percent. Likewise, the growth of major global economies hinges on AI, with projections at 100% economic growth by 2035.
It is no surprise that investment in artificial intelligence has increased to $14.9 billion, as of 2014, according to a study conducted by the Bank of America Merrill Lynch. This is projected to increase further by at least 50 percent per year. The same study claims that the innate limitations of humans will make AI the core technology of the so-called “internet of things.”
The benefits of AI are apparent and we’re starting to fully embrace and leverage its advantages. With AI, you can count on fewer errors, faster response times, improved management of resources, and better use of legacy data. Businesses have experienced the difference, and adoption has moved faster across all industries.
Examples of AI Applications for Business
HANA (High-performance Analytic Appliance) by SAP: HANA is a database management application from SAP, a German multinational software company. Whether implemented from the cloud or through in-house servers, HANA is able to process massive RAM-stored data, allowing for fast real-time data-backed decision-making, transaction analyses, variance analyses, and process/ resource consolidation. It is used by big operations, such as Walmart; but, the application can also be retrofitted for small and medium-sized operations.
Avanade by Microsoft and Accenture: This Microsoft and Accenture venture makes use of the Cortana Intelligence Suite and its related solutions to provide business with data-based predictive analytics and insight. Businesses, such as Pacific Specialty Insurance Company, have used the service to build company-exclusive analytics platforms. In Pacific Specialty’s case, they use Avanade to see and understand trends in policyholder behavior.
Cogito: Cogito is an AI service co-founded by Joshua Feast and Dr. Sandy Pentland. It makes use of behavioral science and machine learning to provide real-time insight to support reps, in order to improve caller interaction.
Amazon.com’s Artificial Intelligence on AWS: Amazon is one of the leading proponents of machine learning, and they’ve been at it for 20 years. From its recommendation engine to Alexa, Prime Air and the company’s supply chain, capacity planning and forecasting systems, Amazon’s use of AI is nothing less than amazing. The technology is available to data scientists and developers through AWS’s AI stack, which is already used by high-profile companies like Netflix, C-SPAN, and Liberty Mutual.
AI For Sales and Marketing
Artificial intelligence has also made headway in the fields of sales and marketing.
Chatbots: Chatbots have come a long way, from basic AI applications to more advanced iterations that are capable of providing actual support. Today’s powered-up chatbots can handle mid-level queries, leaving only the more complex ones to their human counterparts.
Conversica by CenturyLink: CenturyLink is one of the United States’ top telecommunications services providers. In 2016, it invested in the Conversica AI, which helps sort through millions of leads to find hot ones; and then engages with these leads via email, sets appointments with human salespersons, and finally passes the leads.
AI for Business Dashboards by DOMO: DOMO is a software company that has developed an AI-powered cloud-based dashboard to help businesses make decisions. The DOMO AI makes use of more than 400 software connectors to pull data from applications, such as Shopify, Salesforce and Facebook. This gives businesses a comprehensive collection of data and, of course, an AI capable of processing it; which has helped managers track real-time trends in sales, product inventory and customers.
The DOMO team has recently added Mr. Roboto to the platform. Mr. Roboto is the collective name for new features, touted to help executives make better decisions with the help of machine learning and predictive analytics.
DOMO’s AI dashboards are currently being used by high profile companies, such as SAB Miller, MasterCard, eBay, Univision and the Honest Co. Univision’s VP and General Manager for Programmatic Revenue and Operations David Katz claims that their first quarter yield has increased by 80 percent when they started using DOMO to collect and process data from their Facebook, Google Analytics and Adobe Analytics.
Apptus’ AI for Sales Enablement: The Apptus eSales AI is an application that specializes in the path between the buyer’s intention to purchase and the company’s revenue. It features predictive sales and marketing functions, such as merchandising automation through customer behavior trends.
Companies, such as Bokus.com, a digital bookstore based in Sweden, use Apptus eSales to improve conversion rates. In Bokus’ experience, Apptus has helped keep their employee count low while achieving a 100 percent customer turnover rate for each opened personalized (through AI) recommendations newsletter.
The General Apprehension with AI
Unfortunately, even with all of the amazing applications that come from AI, the human labor force has not caught up. In terms of training and acceptance, this is perhaps the root of the general apprehension that surrounds AI and job automation.
The projections are worrisome:
- According to the Bank of America Merrill Lynch study, automation can affect job growth estimates in the US.
- The British Retail Consortium says that more than 30 percent of a million retail employees may be jobless in the next 8 years because of automation.
- An exclusive report says that the current wave of technological innovations puts almost half of the US labor force in peril.
- Robotics installations are poised to increase by a compounded annual rate of 10 percent for the next decade.
Prepare Your Sales Team for AI
Assess your sales and marketing processes.
One of the key steps in preparing for and integrating with AI technologies is to evaluate what you currently work with in your organization. Outline the processes implemented in each department. Within sales and marketing alone, you’ll notice a number of tedious tasks that are best automated and left to the machines.
Ask your team:
What aspects of your job are low-value and best offloaded?
What repeated tasks consume a lot of time?
The answers here will give you valuable insight on the many AI integration opportunities within various departments. AI doesn’t spell the end for salespeople and it’s vital that team leaders convey that message. A huge part of sales still depends on human interaction and personal engagement. Being able to offload repetitive tasks to artificial intelligence, you can look forward to an increase in sales productivity.
Talk about the impact of automation.
Like all advancements, there are tangible positives and negatives, and AI is no different.
A business will necessarily go through some form of restructuring in order to effectively integrate artificial intelligence into its sales and marketing tasks. This might result in reassignments or layoffs. Let your team know what to expect, especially if their jobs are in danger.
Of course, it’s not all bad news for employees. AI is a big help with mundane tasks, and its integration can result in improved work performance and sales production. For instance, with an application like Conversica, leads are already ranked and qualified before they reach a sales team. Once received, salespeople can focus on prospect engagement, overcoming sales barriers, and work towards closing a deal.
Think about redefining roles within your team.
Expect automation to cut down tedious tasks and redundant positions, which ideally will make your team more effective and productive.
Make the most of this by taking a look at the make-up of your team. Assess individual competencies and contributions to the team’s goals. Once you see where your strengths and weaknesses lie, you can redefine and reassign the workload.
Provide opportunities for learning.
One of the best team responses to a faster and more efficient AI future is to become faster and more knowledgeable too. So, alongside your investment in artificial intelligence, also give importance to employee development.
Create learning opportunities through flexible policies and investment in ongoing education. There are several online courses, as well as part-time advanced degree programs, available in the fields of sales and marketing. On-site workshops and training sessions are also good options, especially since you can tailor these training programs to suit your business’ specific requirements.
Improve team (and AI) collaboration.
Collaboration is key to a seamless AI integration. This means working as a team to adapt with the changes, and move forward. It means department-wide and organization-wide cooperation towards a smooth transition and a successful adoption.
Likewise, it also means collaborating with your AI machines. Remember that AI works for you, and it can only do so much. It takes what you give so encourage the team to provide input, especially when it comes to customers and the sales process. The more accurate data your AI platform has, the more it can learn and be of true help to your business.
Optimize Your Data Use
Data is one of the crucial elements in guaranteeing that AI adds to your operations. Remember the old adage: “garbage in, garbage out.”
So, make sure that your AI platform is able to collect the right kind of data. A good part of this depends on your team. For instance, current CRM systems require the agent’s input after calls or other prospect engagements. Make sure they do their part. This might seem small, or even ignorable, at first. But, it becomes part of your big data, which would eventually help you make better decisions.
The Fuqua School of Business at Duke University asked several Chief Marketing Officers regarding their data use. On a five-point scale, they scored an average of 3.2 when it comes to their organization’s ability to use customer data. Then on a seven-point scale, they scored an average of 3.4 for their ability to integrate data across different channels, in order to make better business decisions.
Monitor, Measure, Repeat.
Remember that artificial intelligence is not your wardrobe pathway to Narnia. Success with AI does not happen through magic. It takes consistent work – and repeated monitoring and measuring.
AI will introduce new processes and functions to your team. You can’t expect to perfect your implementation or use of your AI platform on your first – even your nth – try. So, keep at it. Focus on your key metrics and observe, with AI’s help, what factors into these key performance determinants. And, then tweak where necessary.
Look to an AI Future
One thing that we know for sure is that artificial intelligence is the future of business. While the field is still in its infancy stage, you can expect it to mature and become critical cogs in how your business and industry operates. AI will change you, your team and your organization. Jobs and business processes will necessarily evolve.
You can look forward to exciting years ahead. Prepare early and arm yourself with ample AI integration know-how.