Automation

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Four Ways Jobs Will Respond to Automation

The robots are coming! But counter to popular belief, it’s not just low-paying jobs that are at risk of automation. According to research by Scott Latham and Beth Humberd, predicting which jobs are vulnerable requires analyzing the type of value job holders deliver and the skills they use to deliver it. Workers must understand four paths of job evolution — and factors behind each path — if they hope to adapt.

What Digital Transformation Means in 2018 and Beyond

  • Video | Runtime: 01:03:59

  • Read Time: 1 min 

New research shows that large organizations are still struggling to implement their digital transformations. Relentless, fast-paced technological progress and massive competency shifts present cultural/organizational challenges that make digital transformation a complex yet necessary exercise. In this webinar, Dr. Didier Bonnet discusses these findings and shares his thoughts on the barriers to digital transformation and what leaders can do to overcome them.

How AI Can Amplify Human Competencies

The fear of robots eclipsing human power in society, in particular the workforce, has persisted for decades despite the moderate progress of artificial intelligence systems. For professor and robotics researcher Ken Goldberg, a hybrid human-machine workforce is much more likely to take shape, and in many industries, it has already begun.

AI-Driven Leadership

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  • Read Time: 7 min 

Not many companies are there yet, but there’s a developing framework for what it takes to lead an AI-driven company. Leaders at the forefront of AI have seven key attributes: They learn the technologies; establish clear business objectives; set an appropriate level of ambition; look beyond pilots and proofs of concept; prepare people for the journey; get the necessary data; and orchestrate collaborative organizations.

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Why Supply Chains Must Pivot

Even today’s most digitally advanced supply chains still try to predict what will happen, then optimize performance against plan. The problem is, the world is not predictable. For operations teams, the challenge and competitive advantage becomes: how well do you respond and execute against ongoing uncertainty?

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.

The Risk of Machine-Learning Bias (and How to Prevent It)

Machine-learning algorithms enable companies to realize new efficiencies for tasks from evaluating credit for loan applications to scanning legal contracts for errors. But they are as susceptible as any system to the “garbage in, garbage out” syndrome when it comes to biased data. Left unchecked, feeding biased data to self-learning systems can lead to unintended and sometimes dangerous outcomes.

The New Economic Benefits of Older Workers

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Many countries experiencing fast growth in the aging of their populations, including Germany, Japan, and South Korea, are also experiencing growth in their gross domestic product. The most plausible explanation for this counterintuitive finding is that there has been a rapid adoption of automation technologies in countries with more pronounced demographic changes. In other words, technology isn’t just capable of offsetting potential negative effects of aging populations — it’s already doing so.

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Justifying Human Involvement in the AI Decision-Making Loop

Though AI is far from perfect, vast training data has given smart systems formidable accuracy in making independent decisions. Yet even as these decision-making capabilities improve, a Cold War history lesson reminds us that human involvement may still be needed to avoid intolerable consequences of incorrect AI decisions.

When Jobs Become Commodities

Most of us view our jobs as specialized or somehow differentiated, but the world of business and management increasingly feels otherwise. For many organizations today, the next big driver of job commoditization is automation driven by smart machines. Simply put, if a job is viewed as a commodity, it won’t be long before it’s automated. The key for workers whose jobs have traditionally seemed safe: Highlight the tasks that require a human touch.

The Fundamental Flaw in AI Implementation

Many managers are excited about smart machines but are struggling to apply machines’ limited intelligence. Indeed, computers can process data just fine, but to generate competitive advantage from machine learning applications, organizations must upgrade their employees’ skills. Companies will also need to redesign employee accountabilities to empower and motivate them to deploy smart machines when doing so will enhance outcomes.

Analytics as a Source of Business Innovation

The 2017 Data & Analytics Report by MIT Sloan Management Review finds that the percentage of companies deriving competitive advantage from analytics increased for the first time in four years. Incorporating survey results and interviews with practitioners and scholars, the report finds that companies’ increasing ability to innovate with analytics is driving a resurgence of strategic benefits from analytics across industries. The report is based, in part, on MIT SMR’s seventh annual data and analytics global survey, which includes responses from 2,602 business executives, managers, and analytics professionals from organizations located around the world.

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When the Luddites Fought Back

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  • Read Time: 2 min 

Anxiety about the destabilizing role of technology is hardly new. When new labor-saving technologies were introduced in the British textile industry in the early 1800s, workers lashed out. Smithsonian Magazine writer Clive Thompson describes how their anger and violence boiled over.

A New Approach to Automating Services

Early adopters of software robots exemplify how companies generate tangible benefits via service innovations in three ways: (1) by developing an approach to service automation supported by top management, (2) by initiating effective processes that deliver value to customers and employees, and (3) by building enterprise-wide skills and capabilities. Managers interested in capturing the benefits of service automation need to pursue all three avenues.

Why Digital Transformation Needs a Heart

Digital innovation is transforming every part of the company, from customer experience to business models to operational management. But it’s people who make companies work. The digital economy shouldn’t be one where automation squeezes workers — and managers — out, but one where computers help employees to collaborate fluidly, make decisions scientifically, and manage better with automation than they ever could without it.

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