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How is artificial intelligence transforming organizations?

What is Artificial Intelligence, really? And, to be fair, do we even understand what intelligence is? Not really. At least we don't always agree on it.

With all the talks and buzz surrounding the topic, Susan Etlinger, Industry Analyst at Altimeter Group, looks to discuss the key questions - what is AI, and how real is it?

 

Driverless cars. Drones. Alexa! Siri! Algorithms. Black Mirror! Westworld! All of a sudden, it seems like AI is everywhere—in consumer products, in our entertainment, in our consciousness. Every day we hear stories from Google, Uber, Baidu, Microsoft, Amazon and others about unprecedented achievements in language translation, gaming, image recognition, music composition, beer-delivering driverless trucks, and a host of achievements, all powered by AI.

Susan_Etlinger_how_AI_is_transforming_organizations

In 1983, and long before what we think of now as the Internet, a developmental psychologist named Howard Gardner published what is now a seminal work on the "Theory of Multiple Intelligences". He argued that rather than one overarching intelligence, we humans have different kinds and to different degrees: Linguistic intelligence, which is a facility with language, interpersonal (which some might call "emotional" intelligence), logical/mathematical intelligence, and six others.

Whether or not you agree with Gardner's categories, it gives us a way to think about AI as something beyond pure number-crunching. Computers are terrific at math, but not so much with the feelings. They can move objects with precision, but few people would argue that they're creative in the way that humans are (but do listen to some of the AI-generated songs featured in this New York Times article).

And the idea of AI — of machines that can sense, classify, learn, reason, predict, and interact — has been around for decades. So why is it so inescapable now?

Machines that can learn from new data and transform their own algorithms hold huge promise for predictive analytics.

Kevin Kelly, in his book The Inevitable, argues that the combination of massive and available data sets, inexpensive parallel computing, and advances in algorithms has made it possible for machines to function in ways that were previously unthinkable.

While today the splashy examples tend to dominate the news, artificial intelligence really does have huge implications for organizations and yes, society. But they may not be exactly where you think they are.

What are the key findings?

A few things I discovered include:

1. The transformative value of AI is not always in the shiny examples. Machines that can learn from new data and transform their own algorithms hold huge promise for predictive analytics.

2. Your web-centric world is about to change. What happens when we can converse, using voice, text or touch and movement, with everything around us? You may want to take another look at that digital strategy. What happens to your website?

3. AI will affect jobs, but *possibly* not in the way you think. Repetitive tasks, physical labor and tasks that can easily be automated will be most vulnerable. Understanding a bit about AI —what it is and isn't—will help you plan, whether you are an employee or an executive.

4. Will you be a data have, or a data have-not? This is a thorny issue, not just for corporations but for government and other public institutions. Open data, shared data, data strategy, competitive advantage—expect these equations to change.

5. Ethics and transparency in AI will be a critical part of the customer experience. When we live in economies based on data and algorithms, how we use that data and those algorithms—ethically, clearly, fairly and in a trustworthy and beneficial way—will become a critical factor for competitive advantage.

Read the full report, The Age of AI: How Artificial Intelligence is Transforming Organizations, for more information on:

  • The current state of AI for business
  • Primary and emerging use cases, including the risks, opportunities and organizational considerations that businesses are facing
  • Recommendations for companies thinking about applying AI to their own organizations
  • Look at some of the business, legal and technical trends that are likely to shape the future.

 

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