How women in tech can lead in an era of smart machines
Smart machines will be the most disruptive technology in the next 10 years. Women can guide visionary organizations into the future with new strategies and re-defined leadership.
As lean in leaders and social-savvy consumers, women are set to disrupt the industry along with the rise of smart machines. At last month’s Gartner Symposium/ITxpo, Gartner Fellow Darryl Plummer discussed Gartner’s top predictions for the tech industry: smart machines will be generating more of the content we read, managing our work, and performing economic transactions. It’s time to re-think expertise in terms of our vision as tech executives when our industry is undergoing serious change.
There is a parallel disruption with women’s leadership in tech and smart machines that we should engage by:
- defining a new work system that capitalizes on individual strengths of people, such as empathy and storytelling;
- adjusting our leadership styles in order to take more risks and focus on innovation;
- building alliances with vendors with smart machine technology to create competitive advantages for your business; and
- leveraging new expertise arisen from technological advances to augment opportunities.
A humanized work system
Women tech leadership can anticipate the rise of smart machines in their own organizations by initiating and supporting new work systems built on individuals’ strengths and deeper collaboration between people. New kinds of automation via smart machines (for example: proactive search, graphical analytics, virtual personal assistants) will eventually create a new-normal where both the customer and employee experience is defined through authentic human communication rather than a simple transaction.
Humans are less participatory in the transaction with smart machines becoming transactional experts and humans becoming the keystone of the overall experience. Human gifts such as empathy and storytelling will become imperative in the new work system. For example, in journalism, while data-based content become machine-generated, the writer’s task becomes one of weaving themes and applying higher abstract thinking to the facts at hand, leading to an overall richer experience for the reader.
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