Leading the Intelligent Enterprise

To prepare for the next phase of AI, leaders must prioritize assembling the right talent pipeline and technology infrastructure.

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The AI & Machine Learning Imperative

“The AI & Machine Learning Imperative” offers new insights from leading academics and practitioners in data science and artificial intelligence. The Executive Guide, published as a series over three weeks, explores how managers and companies can overcome challenges and identify opportunities by assembling the right talent, stepping up their own leadership, and reshaping organizational strategy.

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Artificial intelligence (AI) and machine learning offer new ways to boost productivity, develop talent, and drive organizational change by enhancing managers’ ability to make the right calls in complex situations.

Augmented intelligence tools have already made an impact for many companies, but the next revolution will happen when every aspect of a business, from top to bottom, is designed with AI in mind. Call this new construct the intelligent enterprise. Like other major revolutions in management, it’s poised to transform industries and organizations for decades to come. To prepare for this next phase, leaders will need to harness machine intelligence for decision-making across the business, assemble the right talent, and recognize the benefits and limitations of AI to shape organizational strategy.

Understanding the AI Advantage

It’s not hard to find examples of the amazing things we can do with artificial intelligence. AI and analytics have changed the centuries-old techniques of plant breeding, helped advance cutting-edge research into disease, and even been used to decipher damaged ancient Greek tablets.

What these achievements have in common is that they are discrete, structured tasks. In each example, algorithms are used to absorb available data, recognize patterns therein, simulate outcomes, and select moves or produce results based on the statistical likelihood of success. In plant breeding, for example, the simple step of designing a trial to see whether your breeding effort has succeeded or failed requires choosing from a set of 1.16 x 1012 possible combinations. Yet, increasing efficiency in this highly complex process through data analytics can save millions of dollars.1

If improving one aspect of one process through data analytics can have a massive payoff, imagine what can happen when an organization takes advantage of AI’s ability to learn, analyze, and optimize across all processes and business functions.

How AI Can Accelerate Leadership

Businesses, particularly large corporations with a global footprint, are complex adaptive systems. No one person, or even one group of managers, can know what’s going on at all levels of an organization consisting of thousands of employees. Even so, the CEO is responsible for keeping the board and shareholders happy, positioning the company for the future, maintaining employee morale, and developing an advantage over the competition — all while turning a profit.

Topics

The AI & Machine Learning Imperative

“The AI & Machine Learning Imperative” offers new insights from leading academics and practitioners in data science and artificial intelligence. The Executive Guide, published as a series over three weeks, explores how managers and companies can overcome challenges and identify opportunities by assembling the right talent, stepping up their own leadership, and reshaping organizational strategy.

Brought to you by

AWS
More in this series

References

1. J. Byrum, C. Davis, G. Doonan, et al., “Advanced Analytics for Agricultural Product Development,” Informs Journal on Applied Analytics 46, no. 1 (January-February 2016): 5-17.

2. “CEO Turnover at Record High; Successors Following Long Serving CEOs Struggling According to PwC’s Strategy & Global Study,” PwC, May 15, 2019, www.pwc.com.

3. “Reuters News Tracer: Filtering Through the Noise of Social Media,” Reuters, May 17, 2017, www.reuterscommunity.com.

4. “Résumés Are Scanned for Keywords by an Automated System,” USAJobs, accessed July 13, 2020, www.usajobs.gov.

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