Blog: A Call to Action for Enterprise Leaders in an Age of Artificial Intelligence
The New Reality; Predictions Impacting Enterprises Today and Key Decisions for Enterprise Leaders to Address these Predictions.
Five decisions for the next three years — to ensure your enterprise’s survival for the next 15 years — based on 10 predictions.
If you are an enterprise leader focused on ensuring that your enterprise evolves with the rapidly changing technology and business landscape, and you’ve got millennials on your mind, think again. According to the Pew Research Center, millennials are individuals born between 1981 and 1996 — which means some millennials are pushing 40. By 40, many professionals are already leaders of their organizations or even cashing in on their successes and contemplating retirement. Post-millennials, or Generation Z, were born after 1997 and have already begun entering the workforce. According to futurist, demographer, and TEDx speaker Mark McCrindle, anyone born after 2010 is part of what he calls Generation Alpha, and 2.5 million Alphas are born around the globe every week.
So, let’s fast-forward fifteen years; it’s the year 2033 and…
- Gen X is now between 53 and 68 years old. Most have retired or are sunsetting into retirement if they can. Others are struggling as part of the generation that realized that a government supplement or their company-sponsored retirement program isn’t going to cut it. Those programs have either been depleted or will not be enough to fund Gen X’s planned retirement lifestyles.
- Gen Y, the millennials, is now between 37 and 52. They are still in the workforce and could be in decision- making senior leadership roles. Others are seasoned in their careers or moving toward a stable plateau, with a final decade or a little more left for them in the workforce. This generation has been a catalyst and has created the foundation for decades to come. They have shaped laws that have paved the way for predictive insight, the proliferation of data-driven decisions and actions, and the replacement of archaic industries.
- Gen Z, the digital generation, is between 24 and 36 years old. They are active in the workforce and might even be in senior management roles. Those on the cusp of being in Gen Y can vaguely remember a time when artificial intelligence and automation hadn’t yet seeped into every aspect of their lives. They can remember when they could clearly differentiate between the virtual world and the physical world. Younger members have stepped into a world completely reshaped by the previous generation and have become accustomed to the conveniences that the last couple of decades in technological advancement have brought. To this generation, automation and machine autonomy are very normal.
- The first of the Generation Alphas are entering the workforce and they are armed with purchasing power.
So…here’s your wakeup call!
How are you, an enterprise leader planning for your enterprise’s next 15 years, preparing your organization for a workforce, consumers, and customers opening their eyes in a world that’s at the cusp of a new age? This new age is replete with digital assistants, hyper-change, force multiplication, extreme connectivity, automation, and autonomy. The convergence of computing power and artificial intelligence will not only afford these advanced technologies to everyone, but it will also make them an expected part of our daily lives.
If you are an enterprise leader tasked with ensuring the survival of your enterprise, think about your answer to this question: What are the five critical decisions you need to make over the next three years to ensure the survival of your organization for the next 15 years?
To answer that question and understand why these decisions are not only extremely important but also extremely urgent, you must look at how the world is shaping up around us. The world as we know it is on the cusp of an exponentially altering inflection point. We are living at a time that may be recalled by future historians in the same context as the invention of the internet and the major revolutions — scientific, industrial, French, or the glorious one. We are at the beginning of a time where man and machine are battling for dominance.
I have divided this report into two parts. In the first part, I deliver 10 enterprise-relevant predictions for the very near future. In the second part, I explore the five key decisions, predicated on these 10 enterprise-based predictions, that enterprise leaders need to take to ensure the relevance of their businesses.
1. Today’s AI enabled automation will enable an “autonomous everything” future
From self-driving vehicles to self-maintaining and self-healing systems, it’s clear that the need for a human to manually intervene and operate a machine is fast becoming obsolete. Autonomous systems respond to the real world around them and react instantly to take the prescriptive steps necessary to achieve their programmed objective, which could be a navigation system understanding its destination and determining the best route or a server in a data center taking the steps necessary to ensure its operational up-time.
Autonomous systems have one thing in common: they relieve a human of a laborious and time-consuming task. On a mass scale, this means fewer workers and, therefore, lower operating expenses are required for an enterprise to meet its objectives.
Robotic process automation (RPA) tools — software robots that mimic human behavior — are catalyzing what some analysts have dubbed the “fourth industrial revolution.” RPA tools automate finance and accounting, HR, and a variety of other business functions; they are rapidly penetrating global enterprises and are enabling these enterprises to leverage cost savings to create lean operating models, reinvest in new technologies, and even drive out their competitors. The resulting reduction of required human resources will begin forcing those white- collar workers, who are being displaced by software robots, to ensure their children don’t follow the career paths of their parents — similar to what the blue-collar, assembly-line factory workers did when physical robots replaced them during the third industrial revolution.
Here are two more not-far-fetched scenarios in which robots replace white-collar workers. Autonomous supply chain systems that combine physical robots with decision-making software are allowing businesses to cut massive costs while delivering their goods to their customers at unprecedented speeds. Automation tools are already being used in companies to replace not only volume-based white-collar workers but also some advanced skilled workers like software developers.
The advent of AI-enabled learning and decision-making systems that execute tasks will penetrate virtually every facet of our imaginable existence and lead to a sea change of career choices. The future generations and the institutions preparing them will need to ensure that irrespective of the program they pursue, the ability to work alongside and leverage artificial intelligence and automation is a key tenant of the degree. Future doctors will be working with microscopic robots capable of performing complicated surgery; future engineers will build predictive models much more accurately than ever before; future lawyers will compete with AI and automation that can amend contracts and predict a jury’s decision before they hear the case.
In terms of our daily personal or professional lives, we will take for granted outcomes that are machine driven when they once may have required an army of human operators.
2. Quantum entanglement will drive the interconnectivity of devices
If your headphone is wirelessly connected to your watch, which is connected to your phone while it is charging wirelessly and connected to your wi-fi, which is connected to the other devices in your home, which are all sharing data and are all connected to the Internet — you are just skimming the surface of quantum entanglement.
Device interconnectivity has been ubiquitous for several years now. There has been a focus on reducing wired connectivity and moving toward wireless; intelligent systems now infuse most consumer systems and constantly listen and wait for their next commands. Some large corporations, Samsung, for example, have announced that by 2020 all of their connected devices will include a SmartThings app, so you won’t need something like Alexa to act as a digital broker between you and your TV.
In the very near future, the convergence of these connected emerging systems that create a seamless, unified experience will relegate isolated devices into an inconvenience. Mobility and system intelligence will be the prime focus for product creators. Virtually all major car manufacturers are investing not only in autonomous vehicles but also in a connected experience in which the vehicle, its passengers, the road it’s driving on, and the other vehicles surrounding it are harmoniously interconnected and sharing data to enhance that automated experience. This type of smart mobility is the backbone on which future smart cities will support mass transit.
The application of IoT-based (Internet of Things) platforms in everyday lives is already prevalent and growing fast. For example, MIFARE, a leading brand of contactless ticketing, is being used by roughly 1.2 billion people across 750 cities globally and expanding rapidly. This will eventually eliminate the concept of paper-based tickets in mass transit.
Small device manufacturers, such as cellphone producers, are rapidly offering Qi wireless charging solutions as part of their mobile phone features.
The future is not just “connected” but “interconnected.” Systems collecting and exchanging data will wake us up, take us to work, clock us in, enable us to perform our work, clock us out, and repeat the cycle without incident.
3. Machine bias will ensure that machines do not replace humans
As we race toward the inclusion of AI into almost every facet of our lives, how do we, as a species, differentiate ourselves from the machines that do what we did — albeit faster, better, cheaper, and more accurately? Does machine intelligence end where it can’t replace or replicate natural intelligence?
Artificially intelligent systems are now able to replicate, translate, and execute cognitive behavior based on those things that made us human — our senses. They can see, hear, taste, smell, and touch, but translating these sensory receptors, for AI systems, is limited by the algorithms written to allow them to execute on their programmed objectives.
According to Dr. Robert Plutchik’s study of emotions, our natural intelligence allows us to translate what we receive from our senses into eight emotions: fear, anger, sadness, joy, disgust, surprise, trust, and anticipation. When we understand the emotions of others, we cultivate empathy.
Machines, however, cannot feel empathy. They perform tasks, however intelligently or autonomously. The lack of empathy leads to bias, and even the most intelligent systems will only adjudicate a decision based on facts — not emotions or empathy.
Automated decision making (ADM) algorithms are already heavily used across multiple industries — from law enforcement to credit risk analysis, and even to decide which deal to offer a consumer when they are buying a cell phone or upgrading their channels from their cable provider. Non-profit advocacy groups are fighting cases daily to challenge negative outcomes because of machine bias. ProPublica, a Pulitzer-prize-winning non-profit news organization, reported machine bias toward black people after it conducted a study comparing the outcomes determined by COMPAS, a system being used by law enforcement to predict the likelihood of recidivism.
Whether it is an algorithm determining a person’s ability to buy a house or get a credit card, or an algorithm being used to determine a person’s likelihood to commit or re-commit a crime, these systems cannot be left unchecked. However well they are designed and taught, they must also be governed for fairness. The only way to determine fairness is to apply empathy, and only we humans can factor empathy into a decision without being programmed to do so.
As intelligent systems replace human beings for rule-based and repetitive tasks, employers will in turn task humans to refocus on those things that made us human in the first place. These inherently human- characteristic-based skills will be in high demand in a world populated with generations that were raised with screens in front of their eyes and a lack of focus on intercommunication and other soft skills.
4. Social scoring and user experience will become pivotal marketing tools
With a single tweet, 21-year-old Kylie Jenner rattled Snapchat’s stock by $1.3 billion earlier this year. Nations and corporations are increasingly either leveraging social media to determine public policy and announce major decisions or are being hijacked by it and scrambling to do damage control. Social media and the permanence of the internet has far-reaching and, potentially, everlasting consequences. These consequences often emanate from a not-so-well thought out lapse in judgment akin to a teenager’s emotional rant.
Customer reviews hold small and big businesses alike at their mercy. This feedback can catapult a business into a cult phenomenon or drop it to its knees.
Social platforms can also provide invaluable insight into the patterns of existing and potential customers for corporations.
According to the research firm Statistica, by 2021 there will be over 3.2 billion people globally on different forms of social media, with average users in the US spending over 5.5 hours a week actively using these platforms. Virtually all of these platforms, though, track user data constantly — so a user is technically always “on” social media from the time they sign up to use it. The coming generations are signing up much earlier, often by breaking age-limit rules, and conducting life via these social platforms.
As Kylie Jenner’s tweet of displeasure at the new Snapchat experience proved, companies will be measured not only by the revenue they generate and the number of customers they have but also, more importantly, by those customers’ user experiences. This example highlights the influencing power individuals with large social followings have and confirms the need for enterprises to build social media strategies focused on growing large followings to proactively connect with their customers.
Businesses will need to more credence into selling an experience, and not just a product, where the product becomes a subset of the experience. Crayola, a crayon and marker manufacturer, is a prime example of a company creating solutions to ensure an experience. Not only does it continue to manufacture archaic writing and drawing tools that can easily be replaced with a single stylus and a free app, but it is also selling its products through retail outlets that are competing against an apocalypse brought onto their industry by Amazon. To combat the lack of interest, Crayola has started opening “Experience Centers” across the US where consumers can pay to take their kids away from a digital device and experience building and melting crayons and even having their names engraved onto them.
Future malls, primary care physicians, movie theaters, restaurants, and so on are all going to have to change their existing models to deliver an experience outside of their current paradigm to motivate the consumer to inconvenience themselves and choose experience over convenience.
5. AI-enabled cyber wars will create a new class of attacks and a new class of tools to defend against the attacks
As with everything else, a single AI system can create exponential rates of executions and permutations while learning from its mistakes and improving itself. This ability was not previously possible with any volume of human operators. From a utopian perspective, this solves problems faster by enabling research to accelerate rapidly for a desired solution. From a dystopian perspective, though, the havoc that can be caused by nefarious activities is also exponentially high.
With nearly every system connected with another, a hacker’s opportunity to have far penetrating and exponentially damaging consequences is handed to them on a silver platter. The interconnectivity of devices to not just each other or the internet but also wirelessly to power sources creates new opportunities for those looking to hack into these systems and those looking to protect them. These interconnected devices aren’t limited to things like self-driving cars and Alexa. Former US Vice President Dick Cheney, for example, had the wireless charging capability of his pacemaker turned off to ensure it wouldn’t be hacked into.
AI-enabled security threats that replicate themselves and that can intelligently avoid detection have forced those protecting their systems to accelerate investments into AI-enabled defenses. These AI-based cyber defense tools can not only detect and heal problems but also even predict and prevent external threats.
This futuristic game of cat and mouse will create a new class of attacks and a new class of tools to defend against them. The tools will do all of this while repairing any damage and without much human intervention or even knowledge of what may have just transpired.
6. Virtual replaces physical — virtual reality, augmented reality, and the low cost of 3D printing
Virtual reality and its complete immersion into an alternate reality will enable telepresence. Applications of VR will allow us to be in places without actually being there, something we have been trying to do since 1876 when Alexander Graham Bell invented the telephone.
Augmented reality (AR), which allows us to ground ourselves in our actual physical reality but augment it with a digital universe, has already excelled as a natural extension of our vision and how we want to see the world. AR- based games like Pokémon Go proved how quick we could be to adopt these tools into normalcy. AR tools are inexpensively helping us imagine what an empty space may look with furniture or letting us do a walk-through of a construction site before the ground has even broken. Even cosmetics firm Estée Lauder is using AR to show customers how make-up can look in the store without them having to sample it physically. AR is helping scientists navigate the could-haves, would-haves, and what-ifs required to solve some of humanity’s most complex challenges. AR-based companies are some of the most rapidly growing startups today. Magic-Leap, a US based startup that has developed the “Magic Leap One”, a head-mounted goggle which superimposes 3D computer-generated imagery over real world objects, is already valued at over $6.5 billion without selling a single headset.
These low-cost tools that are enabling digital realities are where 3D printers are also seeing huge growth. Much like the rest of these emerging technologies, 3D printing has gone from conceptual science fiction to a low-cost product on the shelves of Best Buy in just a few years. 3D printing leaves few to no breadcrumbs to track consumer habits, and industrial-sized 3D printing is rapidly replacing large-scale manufacturing. 3D printers are being used to build not only prototypes and products but also houses and even rockets to send to outer space.
7. Seeing and listening technologies are permeating our lives — computer vision, speech recognition, and the digital butler
You might remember saying, “It’s easier for me to type this than to write it with a pen on a piece of paper.” Well, there is a generation in the very present today that finds it nearly archaic to type something on a physical keyboard. This generation is currently weaning itself away from even the miniature digital keyboards on touchscreen-enabled smartphones or tablets and is moving toward plain speech and gestures to provide input. AI-based natural language processing systems have taken huge leaps to improve their abilities to have seamless conversations with human beings. Google’s recently debuted Duplex platform can, as an example, call a local restaurant and naturally converse with them to book a reservation for you while processing a multitude of cultural nuances and accents.
As systems advance to hear and understand everything we say and then respond to us, AI advancements in systems that process images to understand what they are seeing are also taking huge strides forward.
AI-enabled computer vision recognizes who we are so that it can unlock our phones; it recognizes who our friends are so that it can automatically tag them in photos. These tools are enabling autonomous vehicles by processing, at lightning speed, what they are seeing.
Together AI-enabled tools understand what they hear and what they see; they recognize gestures and translate emotion. They are being leveraged by nations to monitor their citizens and by consumers as their personal digital assistants.
This seeing and listening technology will continue to permeate even more into every facet of our daily lives. Future generations, who have not experienced life outside of this digital intrusion, will grow up demanding its inclusion and the convenience it provides. These technologies will, very soon, become a necessity for every home, business, and workplace.
8. Unified systems and blockchain will become a seamlessly connected identity and the only way to function, establish trust, and communicate
Today’s connected consumer doesn’t have to worry anymore about creating multiple logins and remembering multiple passwords. They don’t have to remember multiple PINs for their various payment methods. They most likely don’t even know the phone numbers of those individuals who are the closest to them, or possibly even their own phone numbers. Today’s connected consumer instead opts into signing up using one of their social or email platforms like Facebook or Google and syncing all of their devices together. Their entire universe is stored and backed up on the cloud.
Single sign-on experiences across multiple devices and multiple platforms create a single-user identity. This single-user identity pacifies humanity’s perpetual struggle for convenience while providing businesses with a wealth of information on their new, existing, or potential customer. It provides businesses with all the information needed to understand that user’s eating habits, listening habits, talking habits, and even their sleeping habits. It provides the user’s spending habits and builds the map to and from their social connections. Businesses can use this ocean of personalized data to deliver to us an experience, which we get and demand, by knowing who we are better than we may know ourselves. Today’s connected devices are creating our seamless experience through this single biometrically verified digital identity.
Blockchain will enable the consumer to create the trust with the delivered experience, and the absence of a blockchain may even dissuade consumers away from companies and their offerings. A report by Santander Innoventures, the Spanish bank’s fintech investment fund, looked at how blockchain can eliminate stock-trade- execution lag time and claims that by 2022, ledger technologies like blockchain could save banks $15 billion to $20 billion each year by reducing regulatory, settlement, and cross-border costs. Blockchain can also make obsolete the concept of an escrow bank when conducting a credit card or money transfer transaction and build the digital trust of person-to-person transactions.
Blockchain will soon be implemented and demanded in a variety of industries where the trust of a transaction needs to be irrefutable, such as a non-profit using blockchain to prove to its donors that funds reached their intended recipients or a consumer goods company using blockchain to prove and trace product ingredients and their sources.
The digital identity will replace a physical identity required to conduct life. It won’t be a convenient way to operate; it will be the only way to function, establish trust, and communicate in and out of the workplace.
9. Cryptocurrency take-over — AI can drive the obsolescence of traditional currencies by stabilizing crypto
Cryptocurrency is everywhere and yet nowhere. It may be in its early stages, but the hype has created a ripple effect across the global financial world. As of 10:15pm on October 8th, 2018 investing.com listed 2,378 cryptocurrencies with a total market cap of $220,808,512,183. I had to timestamp that because of the influx of new currencies and the hyper-fluctuation of the market cap. In just 2 months between August and October over 250 new cryptocurrencies have come out and the market cap has increased by $67 billion. Based on this website then, the market capitalization of the global cryptocurrencies is almost a quarter of a trillion dollars. Compare this to the market cap for the New York Stock Exchange (NYSE) and the London Stock Exchange (LSE), which are $19.2 trillion and $6.1 trillion. The NYSE was formed in 1817, making it 201 years old while the LSE was formed in 1698, making it a whopping 320 years old. The first decentralized cryptocurrency, bitcoin, was created in 2009 — nine years ago. Almost a quarter of a trillion dollars in nine years!
Every disruptive technology is largely ignored by those about to be disrupted. They ignore the impending disruption until they can no longer keep their heads buried in the sand. At that point, it is too late to adopt that disruption and, further, that technology has likely disrupted the status quo or even annihilated it.
Global central banks and financial institutions are the current status quo. For centuries these institutions have been controlling the value of the currency’s and distributing and managing the physical money.
Decentralization of this currency in the form of a digital asset coupled with our digital identities is the future. Organizations and humanity will conduct business and trade and receive credit solely via cryptocurrencies. All it will take is for one of the big players stuck in the status quo to adopt it fully and convert existing deposits into a crypto form. This will stabilize the digital currencies, and it will be the tipping point forcing the others to have to conform.
AI-based algorithms are already being used to stabilize many of these cryptocurrencies, and this stabilization will be crucial for the conversion to occur. Tick…tock…tick…tock…
10. The force multiplication effect of AI will separate the enterprise laggards from the winners
A hammer is a force multiplier; it takes our average human strength and multiplies it, allowing us to wield an exponentially stronger force onto a very focused target area. Human artifacts replicating a hammer type force multiplier have been discovered and dated back to 3.3 million years ago. In fact, some would even argue that a hammering tool might have been our very first invention. Humans have always leveraged tools to exponentially increase their capabilities.
Today, our hammer is artificial intelligence. We are rapidly looking at leveraging AI in virtually every industry. AI algorithms are helping us unlock secrets that have challenged humanity for centuries and are helping us ingest data and make sense of it at exponential speeds. The point at which AI truly becomes a force enabler for an enterprise is only handicapped by the ignorance of those enterprise leaders unwilling to leverage mankind’s ultimate invention — the replication of our own cognitive abilities to solve our problems faster, more accurately, and at a fraction of the cost that it would have taken us to do it ourselves.
AI as a force multiplier is not a prediction. It is a reality. The prediction is that as the generational shifts change the landscape of the enterprise C-suites, this reality will see the fastest rate of adoption in virtually every aspect of every business.
So, if you are an enterprise leader wanting to be the one that saves your enterprise — and not the last one that could have, what can you do to enable your organization and prepare it based on these predictions? What are the five critical decisions you need to take over the next three years to ensure the survival of your organization over the next 15 years, and possibly beyond that?
Do you believe that the predictions I offered in above and that they will impact your enterprise? Are you willing to focus your resources on the survival of your enterprise?
If you answered “Yes” to both of those questions, then you must understand that these five decisions are not only critical but also that you must make them in parallel. These decisions are essential to an enterprise wanting to sustain its existence.
Decision #1: Understand where humans fit into change management
As a leader of your organization, your company will be a reflection of you. If you are self-preserving and risk- averse, you will create a culture that is risk-averse and focused on ensuring the next paycheck rather than ensuring enterprise growth. Inversely, if you are constantly working yourself out of a job by ensuring a future for the enterprise beyond you, then your workforce will embody a goal-based attitude and keep the business’ goals as their primary objectives.
Create the urgency
AI is transformative not only for your enterprise but also for each one of your competitors. It is a race to stay relevant against both large, established competitors and the cash-strapped, garage-based startup founded by a college drop-out looking to be the next billionaire and laser-focused on disrupting your industry. Large, established organizations have a wealth of resources at their fingertips, but the startups are not weighed down by bureaucracy and the lack of agility. We live in an age where a couple of guys trying to rent out an air mattress to offset the cost of their San Francisco-based apartment can send the global hotel industry into a tailspin in just a few years. This is a time where a guy selling books online can create an enterprise that makes Wal-Mart look like the little guy. Most industries will face disruptive technologies, so leaders must recognize that the only constant is change.
Educate the enterprise
Create a call to action centered on the need for survival. Educate your enterprise to ensure that stakeholders do not view artificial intelligence as a threat to their own survival but instead as an imperative part of the business moving forward. The more an enterprise is educated on the possibilities of AI, the more its collective brain capital can work together to come up with not only cost-saving solutions but also new revenue streams.
Transform talent where you can
Identify the key resources at all levels of your enterprise that have the aptitude to learn new transformative skills. Invest in these resources and transform them with a focus on the skill sets required to build and train disruptive technologies for your business. A critical resource for a large enterprise must be a Chief Disruption Officer. This individual must not only experiment with and apply new technologies but also work alongside the HR department and managers across the business to identify internal candidates that are keen and able to learn and apply these technologies for the business.
Acknowledge your skill gaps
Be the first to accept the shortcomings of your organization or your teams. Once you understand where your organization needs to be and the emerging technologies you need to get it there, identify and acknowledge the gaps in skills, people, processes, and technologies that you must bridge to allow you to achieve your organization’s transformation objectives.
Hire and retain key talent for the future
The requisite talent required to successfully execute on a digital transformation journey is in high demand. LinkedIn’s 2017 Workforce Report placed machine-learning engineers, which have seen 10x job growth over the last five years, at the number one spot on their “Top 20 Emerging Jobs” list. Data scientists, with 6.5x job growth over the same period, claimed the second-place spot. If you can attract this talent, do it! And then do what it takes to keep them there!
Understand humanity’s differentiator
Your enterprise, irrespective of its existing business model, will be selling an experience not only to your future customers but also to your existing ones if it wants to retain them. Amazon is not sending retailers into bankruptcy because it sells the same products cheaper; it is sending retailers into bankruptcy because it has cornered the market of selling the experience of “convenience” without affecting customer service. If your human workforce clocks in and clocks out without having a passion for what they are working on, without expressing empathy with your customers, or without providing thought leadership with creativity, then they are the slowest forms of a robotic process and you will need to replace them. Understand your customer. There is enough data available to allow you to know them more than they know themselves. Understand what experience you can deliver to them and ensure your “human” workforce is part of the delivery of that experience.
Decision #2: Invest in disruption across your enterprise
Understand the business problems you want to solve and find or invest in AI-based solutions to solve them. Seems too simple? That is the goal of this article. That is the most effective approach for a large enterprise that wants to continue to meet its existing business objectives and ensure it stays ahead of the curve. Future-focused enterprises will make sure that they are leading the disruption that is going to affect their industry, not being affected by it as a bystander. As the enterprise leader, you must also understand the security concerns that each disruptive technology brings with it. This concern should not prevent you from implementing these emerging technologies; rather, you should ensure that the security apparatus of your enterprise is leading the way for you to comfortably implement new tools into your ecosystem.
Scout for AI technology
Be on the lookout for technology that you can leverage, even if at first glance it may not seem like it would have relevance to your enterprise’s business operations. For example, when blockchain technology first made its debut, Bitcoin had created it to serve as a public transaction ledger for Bitcoin’s cryptocurrency. At that time, a coffee bean manufacturer would not have likely seen a need to spend resources focusing on how it would affect them, today this startup is centering its coffee production on the grounds of its customer base being able to trace the coffee they are drinking all the back to the plant that the bean was picked from. Blockchain technology has become synonymous with “digital trust.” Much like our own digital identities, public traceability of the digital footprint of a product — like tracing coffee beans from the bean picker to the retail outlet — needs to be irrefutably transparent. Blockchain is impacting every industry as consumers shift trust from relying on a subjective, emotion-driven gut feeling to an objective, digitally recorded blockchain, and you must implement it into your enterprise.
Scouting for emerging technologies, applications, and potentially even partners needs to be a business objective. Spearhead this effort with a Chief Disruption Officer who is responsible for experimenting with and applying new emerging solutions within the enterprise. You could also identify potential startups building these emerging technologies and recruit them as partners to ensure they don’t become future adversaries.
Experiment with AI
Invest in small and quick R&D-based pilot projects for cognitive technologies to help your company and its operating model. These small skunkworks projects can turn into new business focus areas if they are successful. Off-the-shelf tools are extremely useful, but custom solutions address custom problems that are only relevant to your enterprise.
Support business units in applying AI
Establishing a culture that empowers individual business unit owners to experiment is critical to an enterprise’s growth. Building internal capabilities either through a focused team of AI experts who can support internal business units or internally from the business units themselves will encourage individuals to integrate and apply AI technologies that the entire enterprise can leverage. The success of AI integrations lies not just in the technology, but also in the ability of an enterprise to align that technology with its business and operational goals.
Invest in computing power
Artificial intelligence-based applications need massive amounts of computing power. Traditional computer programming involves coding repeatable tasks that a computer executes quickly. These linear computing problems, such as solving equations or sorting files, are all things computers have been great at for decades. However, when it comes to more complicated tasks like recognizing speech or images, this traditional type of computing power cannot keep up. Many organizations focused on AI development are investing in GPU (graphics processing unit) power vs. traditional CPU (core processing unit) power. An enterprise’s need for raw computing power may not require extensive investment in hardware that traditionally only the largest companies, with limitless access to capital, were able to afford. Today, companies like Google, IBM, Amazon, and Microsoft offer computer storage and processing power as a service, which has brought this large-scale computing power to everyone at an affordable price.
Decision #3: Prepare your data
For your enterprise to build the AI force-multiplying technologies that can allow you to know your customer and your workforce, predict outcomes to critical business decisions, create a seamless, unified experience, integrate augmented reality tools, or leverage any of the other growing usages of AI, you need three key ingredients. These ingredients include the AI algorithms that you can build or leverage, the computing power that you can buy or subscribe to, and most importantly, data — lots and lots of data.
Most enterprises do little to capture or harness the data they are constantly producing, let alone leverage the external data available to them through social media platforms or a variety of other sources. According to IBM, every day we produce an estimated 2.5 quintillion bytes of data. Ninety percent of the world’s data was created in the last two years! Enterprises need to leverage this tsunami of information to train self-learning AI applications that are addressing a variety of business and consumer challenges.
Collect and analyze big data
Enterprise leaders need to place an increased emphasis on big data collection and analysis going forward. There is a steadily growing number of data sources such as email, phone calls, chat interactions, cookies, transactional data from day-to-day business activities, mobile application data, and external data available about an enterprise, its employees, and its customers. Companies need to be looking at ways to standardize their data formats and archives for systems to be able to reach in and maximize the potential of that data.
Use big data effectively
Companies today have real-time access to more data than ever before. The challenge for enterprise leaders after collecting this data is figuring out how to best use it to inform strategy and decision making before leveraging it to make business decisions. This needs to be a top priority for enterprise leaders.
Use data to drive teams and business objectives
While it is fundamentally important for enterprise leaders to use data to enable systems to align with business strategy, there is also infinite value in the democratization of data within companies. When companies allow all employees to use data in their day-to-day activities, it creates an unprecedented sense of empowerment that can lead to confident and imperative decision-making capabilities. Enterprise leaders will need to develop an organizational culture that promotes transparency and data-driven decision making. This will ensure the realization of these internal sources of innovation to constantly create business value organically from within the enterprise.
Manage the shift in attitude from data privacy to data security
External access to our data can be a scary concept. Today we are balancing between our expectations of the AI systems we leverage and the hypocrisy of not wanting to share the data we are producing. Applications that would have cost us hundreds of dollars are now available on our Smart Phone App stores for $0.99, where paying any more would seem like highway robbery. This paradigm shift was consumer driven, while we largely ignored the reason for free or virtually free access to advanced technologies. Today’s technology consumers barter away their privacy for tremendous gains in predictive insight into their own behavior. These insights allow the consumer to receive prescriptive handouts that enable their conveniences. Issues with this data buffet are only highlighted when this data gets leaked. Enterprise leaders must focus not only on the actual technologies that capture and leverage data but also on the policies that govern and protect this data from misuse.
Decision #4: Automate where and when you can
As companies harness the potential of automation to complement their workforce, these tools will handle the transactional duties, enabling the human workforce to create meaningful value. Automation tools can offer businesses near immediate tangible metrics and returns on their investments. Enterprise leaders must urgently begin the implementation of automation to replace redundancy. Automation tools have already reached maturity toward commoditization, and most large enterprises have already begun the process of automating entire business functions. PwC estimates that soon this induction of automation tools will not only be the catalyst for the fourth industrial revolution, but that the tools will likely also displace up to 40% of white-collar jobs in the US alone. Enterprises must then immediately reinvest the huge reductions in operating expenses in the form of enhanced AI tools and technologies.
Companies had outsourced business functions to a low-cost geography as a wage arbitrage model to cut operating expenses, but they are now using robotic process automation (RPA) tools to further arbitrage the cost of labor by, in effect, eliminating it all together. RPA tools take little time to implement and the cost to maintain them is negligible. They also allow the enterprise to delay expensive upgrades to enable efficiency by replacing the first source of that inefficiency — the human worker. Enterprise leaders must act at once, if they have not already, and begin leveraging automation tools to replace the proverbial assembly lines.
Chatbots are rapidly replacing not only internal support teams but also customer facing support resources. They do not have a bad day, they don’t get disgruntled, they don’t need days off, and they can create an experience for your internal and external customers that will set a precedent for your enterprise’s positive image.
Invest in and implement automation, autonomics, and cognitive
Automation bots address repetitive processes to reduce the cost and increase the accuracy and availability of a process. Autonomic bots not only automate these processes but also provide enhancements by machines that can take adaptive or prescriptive decisions, for example, taking the requisite actions to fix a user’s email issues. Cognitive tools focus on non-repetitive tasks that typically require human intervention. These cognitive applications are becoming more intelligent, and many large enterprises have implemented them. Enterprise leaders need to understand how to leverage these tools in different parts of their organizations and need to begin investing in them.
Leverage physical robots where you can
Low-cost implementation of automation relies on software-based automation that mimics the desk-hoarding worker’s repetitive and rule-based tasks. Although traditional physical robots have been around for much longer, enterprises are now also rapidly integrating them into a variety of different business functions. Drone technology, supply chain robots, autonomous vehicles, and even nanobots that can perform complicated surgeries are all just a few examples of this new class of intelligent physical robotics in today’s enterprises. Leaders must look at the modernization of their enterprise as a comprehensive approach and integrate automation tools available to them across their different business units.
Decision #5: Understand user experience and the importance of sentiment analysis
Traditionally, a company would create a product and cast a wide net with its marketing effort to attract customers. Social platforms, the immediacy of information, review-based spending habits, and the convenience of ordering what you want — combined with high-speed delivery and the apocalyptic disruption to centuries-old business models at the hands of young startups — have empowered the buyer with an arrogance to expect new service delivery models. These new service models create unique experiences for today’s and certainly tomorrow’s customers.
Enterprises will need to embrace this shift by tailoring their products or services around their customers’ user experience. Manufacturers that relied on traditional retailers for strategic product placement to maximize customers’ spending are facing the consequences of those products collecting dust as companies like Amazon drive those retailers into bankruptcies. The enterprise leader today needs to understand and embrace this paradigm shift. They cannot simply rely on traditional customer acquisition and retention models and must begin to reach each customer proactively.
Change your company’s focus from selling a product to selling an experience
My theory on Toys“R”Us is this — if the company had zero debt but continued to operate with the same model of creating big box stores with limited inventory, or even if it also leveraged those stores as fulfillment centers to compete with Amazon, they would have merely extended the palliative process toward their eventual demise. Alternatively, if they had shifted 10 years ago and gotten rid of 2/3 of their inventory to make room to create things like slime centers and sand pits, they would not only still be around today but also would have continued to provide joy-as-an-experience to a new generation of consumers replicating the same experience that previous generations had when they would go there. Enterprise leaders need to understand better their customers and the experiences those customers will demand if these enterprises want to stay relevant tomorrow. They then need to rapidly shift business models from selling products to selling that experience.
KYC — know your customer
Leverage the data available to you from not only your customers’ spending habits with you but also their habits, period. This is the only way companies can lead with an experience and stay relevant. Consumers and businesses are producing vast amounts of data and leaving digital breadcrumbs. Tools that collect this data and algorithms that leverage the data to produce meaningful insights are readily available and growing rapidly. Companies need to leverage this data with AI tools to create continued enterprise value by determining the predictive insights that will allow the enterprise to allocate resources strategically.
Acknowledge the importance of social media platforms
Do you remember the Kylie Jenner and Snapchat example from Part 1? You must measure the pulse of the future customer by using these tools. Marketing and sales teams should focus primarily on not only creating and managing the enterprise’s social media presence but also protecting and promoting it. Your enterprise’s social presence should be your key focus from a customer acquisition and retention perspective. Crowdturfing (employing fake identities to create mass usage impressions) of a company’s online reviews, both negative and positive, by competitors is an actual phenomenon and can impact your enterprise sales exponentially. The only way to address this is to proactively engage it. Historically, enterprises hired sales and marketing resources because they were skilled at sales or marketing — today, sales and marketing resources should be hired by the amount of influence they can have on social platforms, measured by the number of active followers that subscribe to them. Social media has created young individuals that wield immense influence on your potential customer base and have millions of followers simply by constantly posting online content on YouTube, Facebook, Instagram, Twitter, LinkedIn, or a plethora of other platforms.
Your enterprise needs followers. Followers knowingly or unknowingly share information with you once they “Like” or “Follow” your online presence or use their single sign-on to log into your tools. Not engaging with these tools or sources of information disengages your enterprise from would-be buyers and potential talent. Think of LinkedIn’s “Easy Apply” option vs. companies forcing candidates to fill out individual forms and the potential of losing key talent that doesn’t want to deal with that inconvenience.
Sentiment analysis allows enterprises to apply natural language processing and text analysis techniques to identify and extract subjective information from a customer’s opinion or feelings. This means enterprises can accurately analyze an individual’s opinion or mood before proactively engaging with them by translating the digital breadcrumbs they have already left behind. This type of analysis will form the basis for creating a targeted user experience for the right customer — potentially even before they have even thought of becoming a customer.
View customer service as a profit center, not a cost center
Last, as you strive to create the necessary changes for your enterprise with a focus on lean models, automation, and artificial intelligence, anchor the future of your enterprise in knowing that its revenue comes from people, not bots. In the last 20 years as organizations have focused on cost reduction models, customer service has typically gotten the shorter end of the stick. This degradation of the company’s customer service can attribute its lack of quality to outsourced resources or inefficient Interactive Voice Response (IVR) systems that ask too many questions, have menu choices that always seem to have recently changed, or use overworked human agents that physically engage with a customer. We cannot overstate the importance of our soft skills as a human differentiator in the future. With much of the interaction in the future becoming virtual, limited physical interaction and the lasting impression it will leave must shift from being a cost-centered need-to-have to a profit-enabling must-have. Enterprise leaders must invest in creating the soft skills that will be part of, if not the first aspect of, the experience for their customers.
So…here’s the Bottom Line
You cannot implement these decisions overnight and, in many cases, they may not be actionable enterprise implementations but simple changes in the enterprise leadership’s attitude going forward. The process of transforming your business and ensuring it is ready in 15 years for the rapidly transformative coming generations needs to start taking root today. In three years, an enterprise can dramatically shift its operating model if it stays the course. This transformational journey may not be complete after these three years, and it might face many hurdles, but you will have planted the foundational seeds for a culture shift.
The predictions and decisions I offered in this article are not long-term futuristic pontifications. Many of them are occurring today, and the penetration of these predictions across industries is rapid and producing measurable results.
As an enterprise leader, if your enterprise has not already formed a digital strategy or if you have not already corralled your key leaders to create thought leadership to address the impending impact that artificial intelligence will have on your landscape, you are already behind the 8-ball.
Time is running out. AI will bring with it either speed to relevance or acceleration to irrelevance for any enterprise. As the enterprise leader focused on what you need to do over the next three years to cement your enterprise’s future for upcoming generations, you must begin today.
Kory Farooquie is CEO of iNVATERRA (www.invaterra.com). iNVATERRA engages clients to become future-focused Digital Enterprises by:
- Deploying Intelligent Automation to lower cost and streamline data
- Strategize towards a data-driven transformative future state by leveraging AI to gain competitive advantages
- Implementing, customizing and custom developing the next generation tools to ensure a competitive advantage
- Building dedicated teams of future-focused skillsets to enable your AI transformation journey