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February 08, 2017
How artificial intelligence can be used to drive innovation
By: Kaushal Mody

So far we’ve explored how AI can be applied to improve business outcomes and to increase strategic agility and growth, now let’s examine a third feature.

A recent Accenture Research report on AI notes a distinctive value of these technologies: Their role in helping propel innovation as companies apply AI and spread it into the economy.

In a recent interview, Accenture Chief Technology & Innovation Officer Paul Daugherty described how the research study looked at different countries’ “national absorptive capacity,” or how well a country is prepared to absorb and spread innovation. Said Daugherty, “The kinds of things you need to look at arewhat’s the structure of their economy, what kinds of industry do they have, what’s their capacity of research and development, what kind of ecosystems do they have around innovation…you look at the underlying economic data, dig a little deeper and say...how can AI technology change productivity and how will that drive underlying economic improvements.”

The example of Japan

Using this approach, we found, for example, that Japan is expected to benefit dramatically from AI in part because of its capacity for innovation. The research found that AI will accelerate expected growth in Japan from 0.8 percent to 2.7 percent in 2035, resulting in US$2.1 trillion of additional gross value add (GVA). Among the countries studied as part of this research, Japan is expected to benefit considerably from additional innovation effects driven by its sophisticated research networks, dominance in patent applications and longstanding prowess in fields like robotics. Considering its large electronics goods industry, Japan offers a favorable context for the application of AI to stimulate wider growth impact.

As Paul Daugherty puts it, “Yet more than ever, I believe that technology innovations will be a positive impact on people, business and society because we as humans are in control. We are disrupting ourselves with technology, and we have the power to direct technologies to improve the way the world works and lives”.

But how is AI being used to stimulate innovation and create insights right now in advanced applications? Let’s look at a couple examples.

How can companies gather insights into how a customer feels about a product, or how an employee feels about a project or HR service? Here, the AI-based Accenture Sentiment Analyst reads large volumes of digital text to understand underlying themes and opinions and deliver near-real-time insights. Sentiment analysis classifies the polarity of text as positive, negative or neutral based on degrees of sentiment or tonality, and can help detect emerging trends.

The analyst can store up to 500,000 records, and has a repository of 1.3 million English words and their contexts. The advisor can process 10,000 records per day and 300 characters in a sentence in less than three seconds, which is equivalent to a graduate with three years’ experience—only 500 times faster. The advisor takes only a second to tag a sentence with 50 themes as compared to an average person who takes more than 10 minutes.

Driving innovation from advanced AI applications

But how is AI being used to stimulate innovation and create insights right now in advanced applications? Let’s look at a couple examples.

How can companies gather insights into how a customer feels about a product, or how an employee feels about a project or HR service? Here, the AI-based Accenture Sentiment Analyst reads large volumes of digital text to understand underlying themes and opinions and deliver near-real-time insights. Sentiment analysis classifies the polarity of text as positive, negative or neutral based on degrees of sentiment or tonality, and can help detect emerging trends.

The analyst can store up to 500,000 records, and has a repository of 1.3 million English words and their contexts. The advisor can process 10,000 records per day and 300 characters in a sentence in less than three seconds, which is equivalent to a graduate with three years’ experience—only 500 times faster. The advisor takes only a second to tag a sentence with 50 themes as compared to an average person who takes more than 10 minutes.

Dealing with multiple customer touchpoints

Among the practical applications of sentiment analysis is in industries such as automotive, where there are so many different customer touchpoints. Sentiment analysis using social media, surveys or other channels could help determine if a customer issue was related to the product itself, or service received, or interactions with a dealership or website. By generating such insights, companies can use the data to increase customer satisfaction and also potentially identify quality issues.

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Similarly, Accenture worked with a diversified mining company, using a social media analytics tool to gain insights into how the company’s stakeholders perceive and talk about the industry. This assisted in quantifying the company’s reputational risks. Text analytics identified the client’s reputational strengths and weaknesses by topic and sub-topic, isolated geographical differences in reputational risk, and identified key influencers in public sentiment about the industry.

Driving innovation at two levels

When talking about AI and innovation, it’s important to keep two perspectives in mind. On the one hand, AI is being used to drive innovation at a macro level, affecting countries and entire industries. But at a more immediate level, AI is being directed to generate business insights that can keep a company competitive and growing faster than competitors.

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