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Data, AI, & Machine Learning P. 4

Page 8 of 21

  • How AI Can Amplify Human Competencies

    The future of AI looks much like the present, with machines helping humans to do their jobs better, not replacing them.

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  • Why the Data Marketplaces of the Future Will Sell Insights, Not Data

    MIT professor Munther Dahleh proposes a marketplace for data that bases the cost of data on the financial value it generates.

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  • Wait-and-See Could Be a Costly AI Strategy

    Less than 5% of companies are using AI to reinvent how they do business, but the competitive intensity surrounding the technology suggests that a wait-and-see strategy could be a costly mistake. To get a share of the global profit pool of US$1 trillion that AI will produce by 2030, McKinsey’s Global Institute says companies should begin adopting it at scale within the next 3 years.

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  • Why AI Isn’t the Death of Jobs

    When pundits talk about the impact that artificial intelligence will have on the labor market, the outlook is usually bleak, with the loss of many jobs to machines as the dominant theme. But that’s just part of the story — a probable outcome for companies that use AI only to increase efficiency. As it turns out, companies using AI to also drive innovation are more likely to increase headcount than reduce it.

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  • How Human-Computer ‘Superminds’ Are Redefining the Future of Work

    Virtually all human achievements have been made by groups of people, not lone individuals. As we incorporate smart technologies further into traditionally human processes, an even more powerful form of collaboration is emerging.

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  • Beyond the Speed-Price Trade-Off

    In response to increasing consumer demands for faster deliveries without added cost, more companies are implementing IT solutions that enable access to real-time sales data and inventory data across the whole enterprise. Real-time sales and inventory information, coupled with advanced analytics enables networks to accommodate fluctuations and changes in the business environment quickly, a quality the authors call distribution agility.

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  • The End of Scale

    For more than a century, economies of scale made the corporation an ideal engine of business. But now, a flurry of important new technologies, accelerated by artificial intelligence (AI), is turning economies of scale inside out. Business in the century ahead will be driven by economies of unscale, in which the traditional competitive advantages of size are turned on their head.

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  • Building a Robotic Colleague With Personality

    Researchers are exploring how to create intelligent machines that work with us better as opposed to taking our place. Robots that can express human body language can have a positive effect on their human colleagues, enabling them to be more effective at their jobs, take on higher-level tasks, and realize psychological benefits. The overall result is a more productive human-robot team.

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  • Using Analytics to Improve Customer Engagement

    The 2018 Data & Analytics Global Executive Study and Research Report by MIT Sloan Management Review finds that innovative, analytically mature organizations make use of data from multiple sources: customers, vendors, regulators, and even competitors. The report, based on MIT SMR’s eighth annual data and analytics global survey of over 1,900 business executives, managers, and analytics professionals, explores companies leading the way with analytics and customer engagement.

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  • The Fundamental Flaw in AI Implementation

    Many executives are enthusiastic about the business potential of machine learning applications. But business leaders often overlook a key issue: To fully unlock the benefits of artificial intelligence, you’ll need to upgrade your people’s skills — and build an empowered, AI-savvy workforce.

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