Business Leaders: Do You Have a Digital Mindset?

  • “Leonardi and Neeley believe achieving a digital mindset requires a level of comfort with analytics. They stress data is not a natural substance. They say it is a misnomer to say data are collected. It is more accurate to say that data are produced.
  • Leonardi and Neeley suggest that having digital mindset means you are data literate and comprehend the risks from the processes used to produce data. Even automated data is not free from error or consequence.
  • To be clear, the issue isn’t having data; it is interpreting data and drawing conclusions from data. To do this, statistics represents the best means for analyzing the underlying data patterns. More specifically, it allows digital workers to draw conclusions about a population from a sample dataset.
  • The speed and scale of change in the digital era makes experimentation a requirement. Leonardi and Neeley say rapid prototyping and data analysis improve internal work processes, products and services. Central to making this work is establishing a culture that embraces experimentation.
  • For this reason, Leonardi and Neeley stress digital transformation isn’t a goal you achieve. It is a means to achieving changing business goals. To succeed, organizations must integrate data silos. MIT-CISRs research finds that 51% of organizations still have their data locked away in silos.
  • Without question, no business will be unaffected by digital transformation and every form of work will be changed. To succeed, organizations need technical resources, but it is just as important to transform the mindsets of business leaders.”

AI Should Change What You Do — Not Just How You Do It

  • “How do you reimagine what you do for a new era of AI-powered competition?
  • Machines are handling more work, but arguably without a high level of automation, UBS employees would find it hard to get their jobs done. The firm now has more than 2,000 software bots operating across the business, growing steadily
  • Marcus (Goldman Sachs) has been able to leverage a technology stack based on API microservices architecture to build distribution partnerships with Apple, Amazon, JetBlue, and Intuit.
  • In the first 6 months of 2020, his tech-teams have clocked over 45,000 training hours, with 50,000 courses available.”

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When AI Becomes a Part of Our Daily Lives – HBR

  • “There are more than 7,111 known living languages in the world today, according to Ethnologue.
  • Not only will they need to anticipate what we need before we ask, they also need to understand the context of our conversations and react accordingly.
  • Through collating an abundance of data sources, AI has the ability to establish a true 360-degree view of the consumer’s everyday life, based on his or her past habits and behaviors, well beyond the traditional data silos.”

The Future of AI Will Be About Less Data, Not More –

“In the future, however, we will have top-down systems that don’t require as much data and are faster, more flexible, and, like humans, more innately intelligent. A number of companies and organizations are already putting these more natural systems to work.

Common sense. A variety of organizations are working to teach machines to navigate the world using common sense—to understand everyday objects and actions, communicate naturally, handle unforeseen situations, and learn from experiences. But what comes naturally to humans, without explicit training or data, is fiendishly difficult for machines. Says Oren Etzioni, the CEO of the Allen Institute for Artificial Intelligence (AI2), “No AI system currently deployed can reliably answer a broad range of simple questions, such as, ‘If I put my socks in a drawer, will they still be in there tomorrow?’ or ‘How can you tell if a milk carton is full?’”