Our founder and CEO Alessandro Di Fiore recently published a widely acclaimed article in Harvard Business Review, called “Why AI Will Shift Decision Making from the C-Suite to the Front Line”

In his article, Alessandro discusses how decision making and agile working methods will be changed with the impact of machine learning.

AI Enabling the Human Worker

Alessandro first considers the example of the healthcare industry, where AI is having a huge impact. Even if AI can support a doctor in making a diagnosis and suggesting medical treatments for a cancer patient, only the doctor herself would be able to factor in the overall health condition and emotional context of the patient (and of the patient’s family) in order to decide whether to proceed with, say, surgery vs. chemotherapy.

Most of what we do in healthcare is not simply about making a diagnosis, but working with patients to find an appropriate treatment that factors in a more holistic and emphatic view of the patient’s circumstances.


Agile + AI = Future of Work

The common wisdom is that companies with more data scientists have a better chance of generating business impact. But our own experiences at ECSI, supported by recent research, indicates a different view: firms that hire an army of data scientists do not always generate better bottom-line value. Rather, it is the democratization of access to AI tools and decision-making power among managers and employees which creates more tangible value.

Consider Internet platform companies such as Airbnb, where data is at the core of their business model. Airbnb believes that every employee should have access to its data platform to make informed decisions. This applies to all parts of the organization from marketing and business development to HR. For example, employees can monitor in real time how many of its hosts use the company’s professional photography services and in which location, with emerging trends, patterns, and predictions.

Since launching its Data University in late 2016, more than 2,000 employees were trained, and the weekly active users (WAU) of the internal platform — a proxy of how “data informed” the organization is — rose from 30% to 45%

Another case is Unilever. Orchestrated by the company’s newly created “Insights Engine”, the company introduced a number of AI-driven systems and tools that are accessible to all of its global marketers. The availability of real-time, frequent, data-driven consumer insights has generated even more need for distributed decision-making by the company’s marketers at all levels within the organization.

Best practices show how democratization of data skills can bring about quicker and better distributed decisions, making companies more agile and responsive to market changes and opportunities


Interested to hear more?

We at ECSI have advised many large firms how to best prepare their workforce and organizational design for the age of data and machine learning. Contact Alessandro today and learn how your firm can work AI into your organization

Email: alessandro.difiore@ecsi-consulting.com