Will embedded finance increase your organization’s revenue per customer 2–5x?

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Image Credit: GIlly on UnSplash

Embedded finance involves integrating payment, loan, insurance, and investment services into your organization’s technology platform and apps. For consumers, embedding financial services saves time, is more convenient, and can provide a significantly improved customer experience. In the short term, this minimal investment creates direct revenue opportunities for retail organizations by capturing a larger percentage of the benefits of each sale at a marginal cost.(1)

Over the long run, finance as a service provides sales organizations the data needed to fuel a deeper understanding of customer experiences that drive loyalty and…


If digital ethics is nothing new, each generation of information technology amplifies the ethical challenges in developing human intelligence

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Photo by h. heyerlein on Unsplash

As the applications of artificial intelligence in both business and society become more ambitious, digital ethics has become a growing concern for both individuals and governments. Ethics concern a set of social conventions that develop “our capacity to think critically about moral values and direct our actions in terms of such values”.[i] What is the specificity of digital ethics, and how do these considerations differ from those of ethics in general? These concerns are more a question of degree than of kind, for each new generation of information technology introduces increasingly salient challenges for humanity. …


Crunching the numbers isn’t enough to transform data into action

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During the SwissCognitive conference I gave online last week on putting AI in perspective, I studied the faces of several dozens in the audience to the right of my screen. Although their micros were muted during my talk, each figure offered me clues of their past experience, insights into how they live the present crisis, and glimpses of their perspectives of the future.

The social and economic consequences of the current Covid- 19 pandemic offer us a “Decisive Moment” where we can potentially choose to alter the course of history. …


We are in the eye of the COVID-19 storm, let’s use the data at hand to chart the course we wish to sail in the future.

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From Anxiety to Action

I sit nestled behind my desk in the French Alps, looking through the window at the growing green grass, bright yellow Forsythias, and budding cherry trees that signal the first premises of Spring. Although most of our close friends and colleagues are either well or mildly infected by COVID-19, I find my spirits dampened daily by the storm of bad news raining down on social media.

If we are indeed in the eye of the storm, let’s use the data at hand to chart the course we wish to sail once we have more clement skies.

The need to focus…


Human-centric AI depends upon corporate education’s ability to develop a clear understanding of what managers can bring to the table

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Image credit: SecureWeek

Is the managerial motivation behind artificial intelligence simply to reduce headcount by replacing employees with machines? If so, ‘’human-centric AI” is at best self-defeating nonsense. If MIT defines human-centric AI as “the design, development, and deployment of (information) systems that learn from and collaborate with humans in a deep, meaningful way” it is as important for management to learn where and how machine intelligence can enhance human potential. Human-centric AI depends upon corporate education’s ability to develop a clear understanding of what managers can bring to the table in increasingly digitally intermediated organizations.

What do business and engineering students need…


Managers needs to look beyond data and algorithms to explore how artificial intelligence is transforming the essence of management

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Image credit: Gearstd

In the rush to prepare management for artificial intelligence, both Academia and CorpEd are spinning together programs of statistics, information technology, and information sciences to train future professionals for commerce and industry. Lost in the shuffle is the need to address both how AI is transforming management practices today, and how it will impact careers in management in the foreseeable future. Let’s take a moment to underline the obvious- most managers will never become data scientists, but all managers need to look beyond the data and the algorithms to explore how artificial intelligence is transforming the essence of management.

What…


Academic degrees in Artificial Intelligence focus too often on Data Science per se than its transformative impact in organizations and markets.

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Image credit : Pat McConnell

Most academic programs specializing in Artificial Intelligence today focus on understanding data preparation, statistics, modeling, and algorithms while leaving AI’s impact on business to a footnote. This technocentric vision of Data Science may help explain both why Gartner suggests that businesses will invest $383 billion in AI this year, and why the largest majority of these AI projects will produce no real-world applications.[i]

As artificial intelligence gains a foothold in all aspects of business, what do students need to learn about Management and AI in engineering and business schools? In this three-part series*, we will examine and illustrate challenges ranging…


The business value of Data Science depends upon aligning AI projects with corporate strategy, culture and resources

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Image Credit: EB Bureau

Many companies are investing heavily in artificial intelligence because of the perceived need to “do something will the myriad of data that is being captured each day”. Gartner calculates that this year’s investments represent $383 billion, in spite of the fact that the largest majority of AI projects have no real-world applications.[i] If the potential benefits of AI are hard to ignore, successful projects depend upon the ability to weigh AI’s potential with organizational realities. …


Focused investments in human and machine intelligence that will add value to your career and your organization

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Image credit: Vijay Pullur

Two short years ago, my colleague Farid Makhlouf and I proposed our vision of the foundations of a data science education for management. Last week, my co-author Mohamed Minhaj and I submitted a somewhat different vision in Jay Liebowitz’s upcoming book on “Data Analytics and AI”. In today’s contribution commissioned by CoffeeChat, let’s review our original propositions, and then highlight some of the trends in 2020 that justify adding four additional themes to this list.

In our original proposition, after defining Data Science’s role in business, we suggested that working professionals refine their analytical skills in exploring the primacy of…


What are the sources and significant examples of implicit bias in artificial intelligence? What can be done to minimize their consequences in establishing acceptable data practices?

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Image credit: Bayeté Ross Smith

When we evoke the implicit bias of artificial intelligence, we are recognizing that machine learning reflects the unconscionable attitudes and stereotypes that influence managerial understanding, actions, and decisions in both repetitive and exceptional situations. Although this bias can be potentially either favorable or unfavorable, these implicit evaluations or beliefs can severely limit an organization’s ability to leverage Data Science objectively. There are four potential sources of implicit bias present in Artificial Intelligence: in the data, in the algorithms, in our own logic, and in our definitions of ethical behavior. Let’s explore each in turn.

Machine learning involves specifying a data…

Lee Schlenker

Dr. Lee SCHLENKER is a Professor of Business Analytics and Digital Transformation and a Principal Consultant of the Business Analytics Institute

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