From web 2.0 platforms to web 3.0 ecosystems

George Zarkadakis
Mar 22 · 8 min read

How Ai and Distributed Ledger Technology are changing the nature of work and reshaping what a “company” is

The global economy is undergoing unprecedented change, claiming cohorts of powerful and well-established companies as victims. Research by Richard Foster of Yale School of Management has shown that the average lifespan of firms has been consistently shrinking; from 67 years in the 1920s to 15 years today, and dropping fast. At current churn rate 75% of the S&P 500 will be replaced by 2027. We are witnessing a phenomenon of accelerated ‘creative destruction’, to use the terms of Austrian-American economist Joseph Schumpeter. This phenomenon picked up pace at the dawn of the digital era — around fifteen years ago — by nearly destroying the media and entertainment industries. Those industries saw their traditional, analogue business models become obsolete as content became digital, easily shareable, and virtually free. As the digital revolution extends rapidly into every aspect of the economy and our lives, no industry is immune to the transformative effect of digitalization, particularly as Artificial Intelligence and Distributed Ledger Technologies pick up pace and deliver consumer-grade applications. Software, once a means for increasing process efficiencies in established corporations, is corroding the very institutions and industries that are using it. As it does, it ushers in a new industrial era, where concepts like ‘company’, ‘corporation’ and ‘employment’ no longer define what it means to create wealth and to work. New models of organizing talent, capital and technology are being tested, pointing at an often disturbing and certainly very different world from the one that our parents and grandparents knew. But what would that world be like? And what would this profound transformation mean for business?

Human workers in a typical arrangement where they sit together but do not communicate, or collaborate. Such a top-down, process-driven arrangement denotes a high probability of work automation.

The deconstruction of the firm

Let’s start with the idea of the company. Business corporations — centralised, hierarchical and self-contained orchestrations of labour, capital and know-how — have been with us for so long that we imagine them as something ‘natural’ and given. But there are specific economic reasons for their existence. Nobel laureate economist Roland Coase with his theory of the firm proposed that corporations exist because they’re good at reducing three costs. The first is the cost resourcing; it is less expensive to find and recruit people with the right skills and knowledge inside a company than to look for them outside every time you want to do something. The second is the cost transacting, or managing processes and resources; having many outside contractors, for example, usually imposes a greater administrative burden that having teams in-house. And finally, the third is the cost of contracting; every time work takes place inside a company, the rules and conditions that govern the work are implied in the employment contract, as opposed to having to negotiate separate contracts with multiple external contractors. By reducing these three costs, Coase said, corporations are the optimal structures for increasing economic activity.

Yet thanks to software and the Internet, those three costs can now be minimised just as effectively outside the company as they can inside it. Finding workers via talent platforms, such as Upwork or Topcoder, is often less costly, easier and less risky than recruiting someone full time. Collaboration tools allow for agile forms of work, where managers are not just unnecessary, but are seen as obstacles, bottlenecks and inefficiencies. Finally, the advent of distributed ledger technologies enabling “smart contracts” promises to slash contracting costs by removing the need for a trusted third party intermediate. Because of these innovations, we are already seeing a new way of business organization emerging — one which is open, permeable, skills-based, and highly networked.

Destroying hierarchies

One of the best examples of this new type of organization is Bellingcat, a platform for citizen journalism established in 2014 by Eliot Higgins with initial funding from a Kickstarter project. Bellingcat uses material available on social networks to enable volunteering journalists to do in-depth investigations. When Malaysia airline MH17 crushed over Ukraine Bellingcat showed how effective their business model was, by exposing Russia as the instigator using social media data from the Facebook accounts of Russian military personnel. Although much can be debated about the merits of removing traditional, hierarchical editorial oversight in the media, Bellingcat, by providing tools and a channel for investigative journalism, has reinvented news media in the age of digital and gave more opportunities to any citizen becoming an investigative journalist. Many other companies are emulating aspects of the same model by removing managerial oversight and allowing more freedom to the person who actually produces the work.

Zappos, the digital shoe and clothing shop currently owned by Amazon, employs around 1500 people and has a billion dollar annual turnover. Tony Hsieh, the CEO of Zappos, in an email to his employees in 2015 announced that there will be no more managers and no job titles, and employees will be taking decisions by themselves, implementing the so-called ‘Holacracy’, a self-organization methodology introduced in 2007 by the HolacracyOne company. Instead of pyramidal hierarchies holacracies are organized around ‘circles’; each circle may encompass a traditional function (e.g. marketing) as well as other ‘subcircles’ that are focused on specific projects or tasks. No one prevents workers from freely moving across subcircles in order to achieve their goals, for there are no managers to report to. For such an organisation to function efficiently, workers need special software that enables cross-circle collaboration and measures individual and team performance.

As many other companies around the world begin to change their organisational models to become more agile, innovative and resilient to continuous change, the theme of removing traditional leadership and replacing it with worker autonomy is pushed centre stage. Haier, the Chinese manufacturing giant, is transforming into a platform for entrepreneurship by encouraging its employees to become self-governing entrepreneurs. Zhang Ruimin, the CEO of Haier, is effectively leading his organization so he can become obsolete, for he sees this transformation as the only path that can secure a future for his company. By getting rid of traditional leadership models and becoming a platform, companies such as Haier and others massively accelerate their innovation processes and their chances of long-term survival.

Enter AI and DLT

With the advent of powerful machine learning systems the journey of the digital transformation of companies is has entered new, turbulent, unchartered, but nevertheless very exciting waters. We are currently witnessing the “first wave” of AI-enabled automation impacting work, usually as a result of companies automating processes with RPA or by deploying chatbots to customer service centres, or — in specific industries such as logistics and warehousing — by reimagining work-intensive processes with the use of social robotics. The work dividends from this first wave of automation are mostly positive. Low level, tedious, hazardous and boring tasks are taken over by machines freeing up time for the humans to do the “higher level” tasks. This opportunity for redeploying humans and reconfiguring work is certainly a very good message for the future of human and machine collaboration. But it requires that companies think proactively and reskill their workforce accordingly. For example, by deploying a chatbot to take over more than half of customer enquiries a major international telephone operator has managed to increase customer satisfaction, but also reduced the number of contracted workers who were necessary before.

The “second wave” of automation is yet to come. When it arrives, big data and AI will profoundly disrupt the traditional business models of every industry, and indeed blur the boundaries between industries. The signs are there already for all to see. Take for example the car industry. In a driverless car world the experience of driving will be radically different. Driverless cars will democratize the experience that only the superrich enjoy today: using the car as a second office, or an extension of their living room, while their trusted chauffeur does the driving. So the question is: are car manufacturers ready for this profound transformation of their industry? Do they have the right skills to design, build and deliver these new experiences for their customers? The second wave of automation will meet with decentralized web 3.0 technologies and applications that shift the power away from centralized bureaucracies and corporations towards citizens, consumers and communities. This power shift, combined with AI and data, will change our traditional ideas on what a “company” is.

From platforms to ecosystems

In the Fourth Industrial Revolution the biggest challenge for every business will be “speed to capability”, in other words, how quickly a company can retool itself, both in terms of technology and skills, in order to perceive, analyse, understand and respond to continuously changing customer behaviour and expectations. Cloud technologies can provide retooling agility, but that is not enough. Companies will need to reorganize work in order to obtain “human agility” as well. They need to be able to access and deploy a wide range of skills quickly and on-demand. Increasingly, these skills can only be found by contracting “digital nomads”, knowledge workers who have made contracting and travelling a life choice. By some estimates there will be 1 billion digital nomads by 2035. This means that we must forget the concept of a “job”. This concept is a relic of the First Industrial Revolution where stability was critical for business success, and people were deployed in stable organizational units. In the new world of constant change and shifting trends stability is an obstacle. Human workers will be defined by their skills and not by job titles. In such a world leadership needs to radically change too. Instead of a “supervisory” role that ensures processes are dutifully followed by all, the new leaders should be more like orchestra conductors: bringing together diverse talent and technology into a coherent whole that can deliver an excellent performance whatever score you put in front of them. Such leadership needs a new mind-set, and the support of a new generation of systems that enable an agile, diverse and highly collaborative workforce. In a world of AI automation the real competitive advantage will come from unlocking human potential. The “age of the machines” is really the “age of the humans” — a realization that is already termed “the AI Paradox”. Unlocking human potential means empowering experimentation and collaboration, as well as capitalizing on the power of team diversity. This can be effected by scaling agile practices, breaking down silos, opening up the company to innovation from non-company actors, and thus transforming an organization into an “ecosystem” of agile and continuous innovation. But, how you incentivise innovation and collaboration between internal and external actors and technologies, while remaining organizationally adaptable and resilient? Optimizing for such diverse parameters is simply impossible in a centralized world where command and control, no matter how far away you push it, will always remain. Web 2.0 platforms, will have to give way to Web 3.0 ecosystems where the traditional idea of the secluded, self-contained, self-governed corporation will be massively revised. As companies transform into open collaborative ecosystems they need to consider how to incentivize a wide range of participants in adding value to the ecosystem. These participants may be customers or suppliers, or communities with an interest to participate in the ecosystem. Data self-sovereignty will catalyse the need for new revenue models, quite possibly by leveraging cryproeconomics as well as new forms of governance whereby impacted communities are included in decision-making. The future of companies would be to evolve into interconnected ecosystems with a purpose beyond the mere maximization of economic performance. It will be up to future business leaders to determine, and articulate, what that greater purpose should be.

George Zarkadakis

Written by

PhD in Artificial Intelligence, novelist, author of “In Our Own Image: the history and future of Artificial Intelligence”, founding member of Agorai.ai