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How AI powers a human-driven operating system
Nagarro’s CEO explains how an AI-driven system is changing the way people interact with a variety of tasks and systems at his company
Artificial intelligence brings to organizational decision-making the type of scaling and standardization that IT automation brought to routine processes or, even earlier, mass production brought to the making of goods. How will this affect organizational design in the medium-term? This question makes for fascinating conjecture.
If we take Uber as an example, we can see how the future of the AI-driven organization can be viewed as either dystopian or liberating. On one hand, the human driver’s actions are governed by an insentient system, which would appear fairly dystopian to some people. On the other, Uber allows the human driver to be an entrepreneur of sorts and promises freedom from potentially painful human bosses. She can set her own personal goals for earnings or points and can manage her progress towards these goals. In that sense, the system may appear fairly liberating.
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What AI will, in the medium-term, bring to most organizations can be imagined as a super-advanced version of the Uber “human operating system,” with a lot more specialization based on function and role, personalization based on individual characteristics and preferences, and collaboration across activities.
Such a system’s key functionality may be divided into:
- Answers to any questions the employee may have regarding her work, her performance, company policies, and so on
- Alerts regarding news and events, plus actionable alerts more closely related to the employee’s day-to-day activities in the company
- Prescriptions that are not just about reiterating goals but also providing deeper analysis on how those goals might likely be achieved by the individual in question in her own context
- Insights that are essentially patterns emerging somewhat unexpectedly from the data the user is concerned with
The business case for such a system is:
- To increase efficiency and ease onboarding of new employees (think Uber)
- To standardize the way the company works, but also lock in the differentiation vis-à-vis competitors
- To make the company less hierarchical – reduce and focus the role of the middle manager and increase the autonomy of the individual
- To become agile to change – to be able to reflect the priorities of the company with some configuration tweaks (think Facebook)
The first two of these points are relatively prosaic, but the latter two are extremely powerful.
How we tapped into the power of AI
At my company, Nagarro, we recently developed and deployed an early version of such an AI-driven system for use by our 5000 colleagues. It is light-heartedly called Ginger, named after the project leader’s golden retriever. The light-heartedness is intentional and extends into the user experience.
[ How well do AI chatbots handle IT help desk tasks? Read also: AI chatbots for IT support: A CIO's lessons learned. ]
Ginger is the de facto interface for each employee to interact with the organization and its systems, regardless of whether that person works in engineering, sales, HR, or some other function. The system is multi-channel – there’s a web interface, but there are also interactions via Microsoft Teams, email, Windows alerts, and even SMS.
Each individual’s Ginger experience on any day is a function of her role, her own individual preferences and goal-setting, her reporting manager’s inputs, and theoretically even the company’s priorities on that day. One can also imagine that it can be endlessly tweaked using AI based on countless other factors, such as employee performance, time of day, and so on.
Ginger does not replace any of the company’s systems; e.g., our project system, ERP, collaboration tools, or reporting systems. It deliberately provides only snippets of information in a teasing way, along with links to these tools and systems. In fact, we see Ginger increasing the consumption of various systems and reports that were otherwise being ignored.
We envisage great possibilities of companies improving quality and efficiency with such AI-driven next-generation “human operating systems.” As mentioned above in the Uber example, the implementations of these can be viewed as either dystopian or liberating, and in fact, can be pushed in one direction or the other by the design choices made.
We believe that with the right design and implementation, the individual employee can transform from a cog in a large machine to more of an entrepreneur, equipped with all sorts of sophisticated and personalized information and analysis that help her achieve her goals without needing to depend as much on possibly difficult bosses.
In summary, I believe we stand at the threshold of a data- and AI-driven revolution in organizational design and dynamics. We need to proceed with great care, but standing still is not a viable option.
Manas Fuloria will be speaking on the topic “Human AI: Using AI to Optimize Your Business” at the 2019 MIT Sloan CIO Symposium in Cambridge, Massachusetts on May 22. For more information or to register to attend the Symposium, please click here.
[ Read also: AI's 5 biggest risks: Early implementers speak. ]