Cracking AI, Technology’s Black Box of Opportunity

A Two-part Series on AI—Its Role Today and Opportunities Tomorrow

Business leaders all over the world can be forgiven for pushing their teams to “get into AI” without really knowing what that means. Who wouldn’t want to outpace disruption using intelligent machines that can solve problems and innovate all on their own? That’s how AI works, right? If you’re not sure of the answer to that question, here’s your chance to find out.

With this two-part blog series, we are cracking this tempting and long-hyped black box of mystery. The goal is to provide business leaders with insights to support strategic planning around AI, starting in this blog with an examination of how AI is used today and the kinds of business problems it can and can’t solve. In blog two, we take those insights and forecast the biggest AI opportunities ahead, outline challenges business leaders should expect and offer a timeline for when AI will be in widespread use. Ready to get smart about AI? Read on.

AI: What Is It?
Simply put AI or artificial intelligence is a field computer science that works to give technology the ability to take-on repetitive tasks that require human intelligence and behavior, such as analysis, consideration and decision making. AI algorithms are programmed to analyze large amounts of data and (here’s the intelligence part) make decisions and learn based on the data.

Traditionally software is programmed to take a specific action based on the anticipated outcomes. For example, in Fintech, an online loan application can advance in the approval process if certain requirements are met. If not, a request for more information is sent. The software isn’t thinking or solving a problem, it’s just programmed to fulfill a specific function.

According to The Brookings Institute, “Artificial intelligence algorithms are designed to make decisions, often using real-time data. They are unlike passive machines that are capable only of mechanical or predetermined responses.” With AI, massive amounts of data pour in from many sources. The algorithm learns from that data, identifies what is important and what can be ignored and uses the essential data to act.

How and Where Is AI Used Today?
Today, thousands of companies across numerous industries are using Deep Learning and Machine Learning to improve their customer journeys, revolutionizing the way they interact with customers to deliver more compelling experiences. Meal delivery services like Uber Eats and DoorDash are everyday examples of AI in action. The underlying algorithms take in massive amounts of real-time data (time, weather, date, season, restaurant offers, etc.) and provide targeted offers, deals and menu options to individual consumers to boost engagement and sales. The tech is learning and engaging without a human programmer architecting the next step.

Where Else Do We see AI in Action?
In addition to enhancing the customer experience, AI is easing human workloads and optimizing performance, safety and security across many industries. Here are a handful of examples of AI at work today: 

  • Finance: In finance, AI is widely used for security purposes, detecting issues like credit card fraud and money laundering. It’s also widely used in stock market trading, compiling complex, real-time points to analyze and execute trades. It’s so widespread in fact that it’s changed the industry and its workforce. Goldman Sachs’ trading desk in New York City once had more than 600 traders. Now it has just two, but it’s software engineering team has ballooned.
  • Self-Driving Cars: AI is used in the development of self-driving cars. Its algorithms are essential for identifying road risks in real-time and predicting hazards with weather and traffic data.
  • Media Streaming: Innovators in media like Netflix and Hulu use algorithms that monitor audience behavior and engagement to shape real-time user experiences and make programming choices.
  • Retailers:  B2C retailers use AI to provide targeted coupons and offers based on a complex mix of customer behavior, calendar, weather and inventory data. They also use AI-driven chatbots and virtual assistants to support customers through the shopping process and customer service journey.
  • Technology Development: AI is fueling product development across the tech sector as cognitive services, biometrics and speech, face and language recognition all become fundamental aspects of computers, phones and digital home assistants.
  • Education: Education providers are using AI to develop learning AR/VR technologies that advance and adapt to individual learners in real-time. As students master skills or encounter challenges, the technology adapts and changes to meet their learning needs.

Up Next: AI Opportunities Ahead
With AI driving next-level innovation across so many industries, it is no wonder business leaders are determined to get in on the action. If these examples have you eager to begin your AI adventure, stay tuned for part two in this blog, which we will release in the next few weeks. Don’t miss this examination of where the biggest opportunities and challenges are with AI right now and insights on how to strategically take advantage of AI’s vast analytical capabilities. Stay tuned.

 

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