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Robots will wipe out 6 percent of existing U.S. jobs by 2021, according to a new report from market research firm Forrester. But that doesn’t mean unemployment lines will soon wrap around the block.

Even the most sophisticated algorithms and machine learning technologies can’t replicate human creativity and ingenuity. As machines take over rote tasks, employees will have more time for work that demands uniquely human talents. In the age of widespread artificial intelligence, the most successful businesses will be the ones that use AI to help employees make smarter, faster, more informed decisions.

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Artificial intelligence can make humans vastly more productive. When machines take care of crunching data, conducting micro-analysis, and managing workflow, humans are free to focus on the bigger picture.


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Imagine a marketing team huddled around a table, plotting strategy. Right now, if they have a question, they might have to ask an analyst and wait hours or days for a response.

In a few years, that team will be able to ask an AI chatbot and get an answer within seconds. That will allow them to brainstorm more productively. It’s still the humans’ job to come up with a brilliant marketing strategy — the robots just help them do it quicker.

Or consider Kensho, a financial analytics AI system. According to a Harvard Business review, the program can answer 65 million possible question combinations — even off-the-wall ones like “Which cement stocks go up the most when a Category 3 hurricane hits Florida?”

Kensho doesn’t replace human wealth managers, who must still use their reasoning and intuition to invest wisely. But the program ensures that they make the most informed decisions possible.

The AI revolution will also enable companies to predict and preemptively respond to customers’ needs.

Consider cable companies. If they could detect when a customer experiences a connection problem or has a bad viewing experience, they could reach out before the customer files a complaint or cuts the cord.

AI could analyze viewing patterns and online searches for signs of dissatisfaction. And chatbots could reach out to customers at the first hint of confusion or trouble and loop in customer service representatives as needed.

Such ultra-responsive service means happier consumers — and more revenue for companies.

AI may be more efficient at number crunching and pattern analysis than humans, but it isn’t as daring. Machines can “learn” from past iterations to improve future outputs, but they struggle to come up with completely fresh material that challenges the status quo.

Consider the iPhone. A computer tasked with designing the phone might have arrived at an ugly mashup of past designs — think a Blackberry keyboard with a Nokia screen. Steve Jobs’ minimalist iPhone design contradicted past thinking in a way that only a human could. But that’s exactly why it was successful. As Jobs said, “A lot of times, people don’t know what they want until you show it to them.”

As we head into the AI era of business, there will certainly be winners and losers. So how can executives prepare to come out on top?

For one, they should remember that algorithms are imperfect. If we put machines in charge of making decisions, we need to have humans check over their work. Thanks to a price bidding war among robots, listed a book about flies at more than $23 million (plus shipping, of course). While slightly amusing in this case, such mishaps could be catastrophic for a brand’s reputation.

Business leaders should also make data a company-wide dialogue. Microsoft’s Azure Machine Learning Studio, for example, allows the non-data scientist to make predictive analysis models with a simple drag-and-drop tool. If firms invest in unified data stacks that combine information from all departments — from human resources to marketing to legal — workers will be able to develop more effective, holistic solutions.

Finally, companies will only be successful if they prize human talent more than their shiny new machines. Tech leaders are noticing a dearth of data savvy employees that can communicate their insights well. McKinsey execs are calling such rare employees “the translators.” Companies should be on the hunt for employees who can get in the data science weeds but also view data in terms of company growth.

Smart business leaders recognize that AI improves human decision-making but can’t replace it. In the end, AI is only as good as the employees acting on the data.

Sid Shah is director of business analytics for Adobe’s Digital Marketing Business.

Above: The Machine Intelligence Landscape This article is part of our Artificial Intelligence series. You can download a high-resolution version of the landscape featuring 288 companies by clicking the image.

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