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Why AI Disruption Is Here To Stay

Esteve Almirall is an Associate Professor at Esade’s Department of Operations, Innovation and Data Sciences.

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Covid-19 redefined connectivity and immersed us in an accelerated process of digitalization. We may ask ourselves if this process will be reversed or if it has put organizations on the path to an increasingly digital society.

The change has been profound and we need some perspective on the pre-Covid-19 world. Believe it or not, the official definition of broadband in the USA is still 25Mbps download and 3Mbps upload. You may think that telecom lobbies are largely responsible for this conservatism and you are probably right. However, for the average citizen, connectivity before Covid-19 mostly meant surfing the net, buying online, participating on social networks, and of course, watching movies. 

Covid-19 changed this dramatically – starting with pupils and students who could not attend classrooms and had to make online learning the new normal. Similarly, work moved to homes sweepingly fast. Only this first step redefined what connectivity meant for all of us by smashing the 30Mbps standard in many places. 

Remote working gave birth to new tech giants such as Zoom and redefined the location of work and how it is performed, coordinated, and measured. ‘Being there’ became obsolete and remote working entered the checklist for new jobs. Organizations that for decades relied on physical presence and ‘eye contact’ to manage their teams needed to transform their KPIs to capture the incentives and motivations of remote workers in the new normal. Teamwork and meetings became virtual, and skills transformed radically.

All this was an earthquake for businesses. New companies appeared – such as Peloton, Zoom, or Apple Fitness – who could quickly adapt and thrive in this environment. It was also the case for companies like Amazon, Netflix, Glovo, JustEat, and many others. This adaptation had an unexpected characteristic – it was fast. Companies competed to gain territory in this new land of opportunity, and they competed with innovation. We can find this characteristic in any organization, but the war of conference apps showed what fast means in this new environment, and fast meant blazingly fast! 

The economics behind the disruption

The mechanism that enabled this disruption is very well-known: task decomposition through modularization, followed by digitalization. Let’s use the example of Uber.

Uber decomposed the customer taxi journey into its primary elements: find a taxi, call a taxi, ride, and pay. Uber then digitalized as many of these modules as possible and only one non-digital task remained: the ride. 

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Covid-19 brought this process one step further and enabled the complete digitalization of all the journey, including aspects that nobody thought possible before. Let’s compare Peloton with a traditional gym. You may find a gym using digital tools but joining a gym and the subsequent workouts are done on the premises (although followed by a digital payment). Peloton changed this by digitalizing the whole process and placing a connected bike in your home. 

Why is this so important? First, a digitalized process enjoys almost zero marginal costs, the cost of serving one additional client is negligible once the application is running in a cloud platform. Secondly, a digital process enjoys infinite scalability and complete agility, adapting its resources to the users on the system. This happens because processes executed in cloud platforms adjust to customer needs almost instantly. Finally, there are no diminishing returns on scale. Once created, the code does not need to be upgraded as users increase and cloud platforms do not have bottlenecks or increasing prices for scale – quite the contrary. Therefore, returns on scale increase rather than decrease.

The magnitude of this disruption can only be grasped if we compare before and after business and operating models.

In traditional business models, value creation comes from a cost strategy and a differentiation strategy or niche strategy; and value capture is achieved through pricing, marketing, or licensing goods.

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The operating model is defined by three factors: economies of scale, the scope, and how companies learn. Economies of scale have been traditionally defined by how volume and integration are managed (inside the company, or outsourced, and more recently using the web to scale). The scope is about the range, variety, and complexity that a company chooses to handle. And learning has traditionally been the territory of R&D projects with continuous learning through methodologies (such as Kanban and intellectual property management).

These two areas change radically in native or transformed digital companies.

Value is created through innovation and personalization that engages customers and captures their imagination. Value is captured through two mechanisms: firstly, growth with network effects and data products; and secondly, by capturing the attention of users through behavioral strategies.

The operating model is completely transformed because of digitalization and cloud platforms. The economies of scale mean achieving maximum possible growth because there are no decreasing returns. The scope is also as large as needed, and is either created internally or with platform strategies or user-generated and managed through personalization and recommendation engines.

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Learning is again an aspect of major change. It is now done through a process of continuous experimentation and validation in what is called fast incrementalism: a process that reduces risk, and most importantly, increases speed.

Digitally transformed organizations

In this process, organizations endured significant changes. By digitalizing every process, the AI disruption moved organizational functions to software and models in the cloud.

This changed the balance between exploitation and exploration. Exploitation was progressively made by software with little human intervention or none. Therefore, the focus and the action inside the organization is focused on exploration, competing with innovation, and moving even more organizational functions to models in the cloud. 

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This change in balance powers the AI disruption by creating more demand for tools and talent, and companies increase this process by powering a feedback loop that results in very technical organizations with small headcounts that are immersed in intense competition driven by internal and external innovation.

What has been the role of Covid-19 in this disruption? It has accelerated the process and widened it to areas where digitalization was unthinkable. Many of these processes are here to stay – and so the question that you face as an organization, country, or a society is how to position, compete, thrive, and maybe survive in this new market.

What do you think?

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