For many of us, our experience with artificial intelligence (A.I.) may be, for a lack of a better way to put it, “helpfully cool.” That can mean asking Amazon’s Alexa to play a particular song or querying Google’s Home to see if butter is a suitable replacement for vegetable shortening.

But the potential for A.I. goes far beyond cool. Its application in businesses and industries of all sorts will exponentially revolutionize how we both think and work.

That sort of change is coming faster than you might expect. And organizations that anticipate the most effective ways to leverage A.I. will profit handsomely.

A Hard Trend That’s Gaining Speed

I first identified artificial intelligence way back in 1983 as one of 20 core technologies that would become powerful drivers of exponential economic value creation. Looked at in the context of my overall Anticipatory Organization Model, A.I. is an ideal example of a Hard Trend – a future certainty – which in this case means our overall increasing use of this technology in a broad array of applications.

Further, this Hard Trend is not just a future fact, but one that’s accelerating in power and application at a predictable, exponential speed.

While many of us are familiar with A.I. thanks to consumer-oriented devices such as Siri, Alexa and Home, the fast-developing potential of A.I. was highlighted in May of this year when a Google supercomputer defeated a grandmaster in a game of Go, often considered the most complicated and involved board game ever invented. The computer bested its human counterpart using its advanced A.I. software.

That remarkable victory also underscored another component of my Anticipatory Organization Model – the role of the Three Digital Accelerators, specifically, the exponential growth of computing power, bandwidth, and digital storage. Since all three of those accelerators had reached a “tipping point” of sufficient growth and development, Google’s A.I. software was able to learn by playing millions of games of Go against itself to hone its tactics through trial and error. That helped ensure a victory that few expected.

The Power To Disrupt

The issue of disruption is another central element that pertains to the potential of artificial intelligence. As I repeatedly stress in my books, presentations and consulting work, many different kinds of products and services haven’t merely changed their markets or industries, they’ve thoroughly disrupted them, completely shattering the status quo.

Further, there are only two sides to this particular fence – either you’re the one causing the disruption, or you’re the one forced to react as best you can to this powerful disruptive force.

That’s the kind of disruptive opportunity that artificial intelligence affords organizations of all sorts.

Here’s an illustrative example with which you’re likely familiar – IBM’s Watson, a cognitive computer that learns over time. Cognitive computing, another form of A.I., is being increasingly used in a wide variety of applications including healthcare, travel and even weather forecasting, to name just a few.

With regard to weather forecasting, after IBM acquired the Weather Company to boost its cloud capabilities (no pun intended), cognitive computing such as that employed by Watson allowed the Weather Company to manage more than 26 million inquiries every day on its website and mobile app. And, in handling that enormous level of information and data, it learned from daily weather changes as well as from the questions being asked.

Consider the disruptive impact that sort of technology can have. Estimates hold that weather is responsible for $500 billion in losses across any number of industries. Think about how Watson could help farmers who not only rely on favorable weather conditions to plant and harvest their crops, but depend on worldwide weather conditions and forecasts that can help them strategically plan as well as inhibit or even prevent shipping to markets.

Nor is the effect limited to those out growing crops in the fields. Pharmaceutical companies are increasingly relying on accurate forecasts to predict increased demand for allergy, cold and flu medications.

Real-Time Analytics And More

The potential of artificial intelligence also relates to its capacity for real-time analytics from the ever-increasing amount of Big Data, and the ability to accumulate vast amounts of data and information as they occur and interpret them with the goal of producing knowledge that is both meaningful and actionable. Even better, by employing algorithms that iteratively learn from data, this sort of “machine learning” allows computers to identify significant insights without being specifically programmed to look for them.

Given that potential, it’s no surprise that numerous organizations and industries are racing to embrace A.I. I’ve been helping companies and governments both understand and identify new opportunities for applying A.I. For example, a few years ago, I was the keynote speaker at KPMG’s annual partner meeting, and in my speech, I suggested that if a company like KPMG had IBM’s Watson learn the tax laws and regulations for all countries, that company would have a major competitive advantage.

KPMG leaders took action and partnered with IBM to use Watson, and that partnership will greatly enhance KPMG’s ability to analyze and quickly act on critical financial and operational data, not to mention identify potentially lucrative new business offerings and services.

KPMG is anything but a voice in the wilderness. Other organizations including Deloitte & Touche, Ernst & Young, and PricewaterhouseCoopers are earmarking hundreds of millions of dollars into using advanced A.I. and high-speed data analytics to bring new insights and value to their audit, tax and advisory services.

One important question is, if you are a smaller firm in this space, does that mean you are left out? The answer is not at all! It’s not the tool; it’s how you use it that counts, and the use of any tool, whether it’s A.I. or anything else, is only limited by your imagination and foresight.

Other Areas Poised For A.I. Opportunity And Disruption

The financial services industry provides just one example of organizations employing artificial intelligence to both improve existing services as well as develop groundbreaking new products. In fact, optimism about the potential of A.I. is pervasive. As this article points out, a recent survey of 2,500 U.S. consumers and business decision makers identified widespread confidence in the role of A.I. in the future. In fact, more than 72 percent of survey participants labeled A.I. as a decided “business advantage.” If they understood the concepts I teach of Hard and Soft Trends, that percentage would be 100%.

That begs the question: Where else will artificial intelligence effectively transform entire industries?

Public safety is one. Artificial intelligence is poised to help anticipate and address such critical issues as cybersecurity, civil unrest and even outright acts of terrorism. It’s already been successfully used for these and many other areas. For example, officials at the 2016 Olympics in Rio de Janeiro were successful in maintaining security in a wide array of venues and locations using technology such as automated smart detection.

In the United States, a number of cities are using artificial intelligence for public safety and security. As this Stanford University study projects, by 2030 most metropolitan areas throughout the country will rely on artificial intelligence not only in combating crime but in “predictive policing” applications.

Here’s just a sampling of some other industries positioned to leverage A.I.:

Healthcare

Major medical and pharmaceutical companies are already using artificial intelligence in a broad array of applications. One example is A.I. health assistants being used to streamline clinical processes. Rather than doctors earmarking time for rudimentary tasks such as getting information from a patient and checking vital signs, medical assistants augmented with A.I. instructions, insights and actions can cover a large part of those sorts of clinical and outpatient services, freeing up doctors’ and nurses’ time to attend to more serious cases and patients.

AI is also gaining traction in disease diagnostics. Watson was first applied to oncology and now knows more than any one doctor. Does that mean we don’t need human oncologists? No! We need human oncologists who have access to Watson.

In addition, leveraging real-time analytics, A.I. algorithms can quickly evaluate millions of samples and identify meaningful patterns. Moreover, like any doctor at the top of his or her game, A.I. never stops learning as it’s working.

Transportation

Almost everyone is aware of the growing use of artificial intelligence in autonomous and semi-autonomous cars. That’s not just a matter of hopping in and enjoying the ride but also involves the vehicle’s capacity to gather detailed driving information about routes and destinations to anticipate and pre-solve problems, as well as the driver’s current and future needs and interests.

That same technology can be applied to public transportation, delivery drivers and other uses. The overall result will be a decreased number of accidents, less traffic congestion and significantly lower energy costs.

Education

Artificial intelligence is fast taking hold in a broad array of uses in education. For example, there’s “smart content” creation, including chatbot guides of textbooks and customizable learning interfaces. These are starting to show up from elementary schools to corporate environments.

Add to that intelligent tutoring systems. For instance, Carnegie Learning’s “Mika” software employs cognitive science and A.I. technologies to provide personalized tutoring and real-time feedback for post-secondary education students. That’s especially beneficial for incoming college freshman who would otherwise need remedial courses.

Manufacturing

Manufacturing companies have been using robots to assemble products and package them for shipment for a long time now. Automation and robotics are now moving into other, more complicated manufacturing areas, such as electronics, cars and even home construction with intelligent e-assistants.

Customer Service

With a focus on personalization and human interaction, artificial intelligence is increasingly becoming a major player in customer service. One such example is DigitalGenius, which helps companies automate basic text question-and-answer chats with customers.

Even more fascinating, that system and others are also using natural language processing and machine learning to create reactive robots that mimic human speech patterns, and soon emotion, with facial expressions. When there is a task that needs a human helper, the e-assistant routes the customer to a human with the correct expertise to help. Service is both quick and comfortable for consumers and much less expensive for companies.

Law

A.I.’s impact isn’t limited just to fields with an overriding focus on technology. With regard to the law, artificial intelligence is poised to streamline and improve efficiency in legal work. Additionally, with regard to litigation, natural language processing (or text analytics) can summarize thousands of pages of legal documents within seconds, as opposed to several days for a human employee – not to mention reducing the probability of error.

Further, as A.I. technology such as Watson can learn from all of those legal books, lawyers, their clients, and the entire legal community stand to benefit greatly.

 

Artificial intelligence’s potential across any number of industries is further supported by the financial activities of a number of major players. In addition to Google and IBM, Facebook, Samsung, Apple, and Salesforce are all jockeying to acquire private A.I. companies. Overall, more than 140 private companies working to advance A.I. technologies have been acquired since 2011.

They all see the game-changing opportunities afforded by artificial intelligence. So consider: How might you and your organization benefit from the potential – both realized and anticipated – that A.I. affords?

As I mentioned earlier in the context of disruption, you can be the disruptor or you can choose to stay on the sidelines and react after you are disrupted – quite possibly at your own peril.