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Artificial intelligence will boost US productivity, says report

'The technology can learn the workers' capability, help them understand best practice and help workers do higher-skilled jobs with higher quality, higher productivity, more effectively,' says Daugherty.

A recent Forrester report found that within five years, AI-powered technologies will cut 6 percent of jobs in the U.S. While Daugherty acknowledges 'short-term displacement,' he believes the long-term economic benefits outweigh the near-term consequences, and the key to minimizing the impact to jobs is to educate workers on how to use AI so they can focus on high-value skills.

What can Michael Chui teach you about AI?

Are you still learning about artificial intelligence (AI) and researching how it can be applied to your business scenarios?

Michael Chui, McKinsey Partner Through a study of AI that included a survey of over 3,000 executives and case studies across 14 sectors worldwide, Michael and the research team identified 10 key insights CEOs need to know before embarking on a successful AI journey.

The events last three hours and includes a cocktail reception, dinner and round table talk on how to move forward with AI and analytics.

How to make AI work for your business

A survey of more than 3,000 executives sheds light on how businesses are using AI, offering lessons for CEOs, as we explain in this article for Harvard Business Review.

Through a study of AI that included a survey of 3,073 executives and 160 case studies across 14 sectors and ten countries, and through a separate digital research program, we have identified ten key insights CEOs need to know to embark on a successful AI journey.

We include five categories of AI technology systems: robotics and autonomous vehicles, computer vision, language, virtual agents, and machine learning.) For the moment, this is good news for those companies still experimenting with or piloting AI (41 percent).

Telecom and financial services are poised to lead the way, with respondents in these sectors planning to increase their AI tech spend by more than 15 percent a year—seven percentage points higher than the cross-industry average—in the next three years.

Thirty percent of early AI adopters in our survey—those using AI at scale or in core processes—say they’ve achieved revenue increases, leveraging AI in efforts to gain market share or expand their products and services.

While the question of correlation versus causation can be legitimately raised, a separate analysis uncovered some evidence that AI is already directly improving profits, with return on AI investment in the same range as that for associated digital technologies such as big data and advanced analytics.

AI tools today vary along a spectrum ranging from tools that have been proven to solve business problems (for example, pattern detection for predictive maintenance) to those with low awareness and currently limited but high-potential utility (for example, application of AI to develop a competitive strategy).

This distribution suggests that organizations could consider a portfolio-based approach to AI adoption across three time horizons: Short-term: Focus on use cases where there are proven technology solutions today, and scale them across the organization to drive meaningful bottom-line value.

Long-term: Work with academia or a third party to solve a high-impact use case (augmented human decision making in a key knowledge-worker role, for example) with bleeding-edge AI technology to potentially capture a sizable first-mover advantage.

Machine learning and its most prominent subfield, deep learning, have attracted a lot of media attention and received a significant share of the financing that has been pouring into the AI universe, garnering nearly 60 percent of all investments from outside the industry in 2016.

And as AI continues to converge with advanced visualization, collaboration, and design thinking, businesses will need to shift from a primary focus on process efficiency to a focus on decision-management effectiveness, which will further require leaders to create a culture of continuous improvement and learning.

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