#FutureOfWork: The impact of #AI on the workplace and employee engagement

• The digital workplace merges work and life — a virtual space with applications, services and information on demand. For users, this means access to the technology they need, when they need it, on whichever device they prefer to use.

• Employees expect their enterprise systems to be as engaging, exciting and intuitive as consumer devices. Technology research company Gartner calls this a shift from technology-literate people to people-literate technology.

• Companies now have more exquisitely detailed data about how their products and services are used than they ever had before, thanks to a vast network of sensors and advanced analytic tools.

• Cognitive systems can parse all that data and learn what employees need to do their job better — even if they don’t yet know it themselves. Cognitive systems will deliver the ability to visualize vast amounts of data, curated and analyzed, for a unique task and a unique user.

• The workplace of the future will embrace emerging new cognitive and analytic capabilities. These tools can provide insights into how employees engage most effectively, what the best technologies are for each task and for each individual, and help provide a seamless work environment — an environment that will help to attract and retain the best talent.

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#futureofwork: How AI will change fintech jobs, and advice to college grads how to benefit from this

  • The automation of the finance industry will hollow out jobs in that field in the same way that robotics and other technologies have reduced manufacturing employment. That is how:
    • Floor trader, of course, has long been the archetypal job on stock exchanges. But there are precious few left of them.
      • Most trading jobs have been taken over by servers running trading algorithms.
    • Much of Wall Street’s back office operations involve the performance of relatively structured tasks.
      • Many of these could probably be taken over by tools like robotic process automation, which can reach into multiple systems for needed data and apply rule-based decision logic.
    • Regulatory compliance has been one of the few growth areas in recent years on Wall Street, but systems from Digital Reasoning are automating internal fraud investigations.
      • IpSoft’s Amelia is focused in part on facilitating compliance in customer conversations.
      • Narrative Science automates the creation of anti-money laundering reports.
      • RAGE Frameworks automates the extraction of data for credit and wealth management, and can create automated compliance reports on the process.
    • Many entry-level jobs on Wall Street involve combing through data to make a case for a particular financial transaction. That is an it job:
      • Kensho, for example, is a startup that analyzes data on markets and generates reports on their implications.
  • Another common task of financial analysts and attorneys is to prepare disclosure data on a company’s financial history for potential investors.
    • iDisclose does that automatically.
  • Another common role in the finance industry is to provide investment advice.
    • The “robo-advisor” concept / automated advice is becoming pervasive at the lower end of investing.
      • Vanguard, Charles Schwab, and Fidelity have all taken some steps in that direction
      • startups like Betterment, Wealthfront, and Personal Capital are pursuing Millennial customers with money to invest.
      • The capabilities already exist for higher-end versions of robo-advice, and a few banks like UBS have begun to explore them.
      • Investment advice is complex, data-intensive, and rapidly changing, so it seems very likely that there will be substantially fewer human investment advisors in the future.
  • There are other finance-oriented tasks that will be performed by automation, including some new ones involving ongoing financial management for consumers that should have been done by banks long ago.
  • It is a process: Job after job will be whittled away over time. Entry-level jobs will probably be the hardest hit; if you can teach a recent college grad to do a task, you can probably teach a machine to do it.
  • Advice for entry level grads:
    • There will be a substantial number of jobs that involve working alongside machines.
    • If you’re already familiar with key financial processes, you’ll have a much better chance of keeping your job if you learn to work alongside smart machines that perform key aspects of those processes — monitoring the machines, fixing them, and picking up the ball when they drop it.
    • Or you can become skilled at overseeing them, understanding when the financial world has changed and when the algorithms are no longer well-equipped to deal with it.
    • Finally, of course, there will be many jobs involved in building intelligent finance systems.

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