Mika Ruokonen - Growth Reinvented: Turn your data and artificial intelligence into money

Data and Al are an integral part of the reality we all live in but how can companies use these technologies to drive revenue growth? What commercial models and monetisation strategies are available to create data and Al-enabled assets with the capability to deliver powerful future gains? Existing literature frequently claims that data and Al can facilitate new business models; but it rarely explains what these models will look like. Growth Reinvented addresses the what and the how by exploring a detailed playbook of Al and data-enabled business models. Drawing on dozens of real-life case studies and existing company examples - including a brand new body of original research - it provides a practical step-by-step guide for companies looking to realise the value of and monetise their data and Al offerings. Rather than just focusing on current offerings with data and AI, Growth Reinvented shows how new technology can be designed as a standalone opportunity to drive forward systemic change. Business leaders are urged to consider using data and Al-enabled service and revenue models to enable a more radical transformation: one that disrupts industries and carves out exciting new avenues for growth. Mika Ruokonen is an expert in Al driven business transformation at digital innovation and engineering consultancy, Futurice. Mika Ruokonen is an expert in Al driven business transformation at digital innovation and engineering consultancy, Futurice.

His 15 years experience in digital technolo- gies and software solutions have included various roles such as P&L responsibility, business development, research, sales and consulting. During that period he has come to realise that while businesses quite easily solve tech-related challenges and invent great new products and services, they com- monly struggle with commercializing them. Growth Reinvented Turn your data and artificial intelligence into money Mika Ruokonen 1 Introduction: the importance of data and AI-enabled business models There have been mind-blowing advances in digital technologies and computing in recent decades. Today, there are very few companies that havent, in some respect, joined added value unlocked by digitalisation. Over the past ten years, companies have an industrial economy born in the late 19th placed particular emphasis on the impor century to a new knowledge-based economy tance of big data. how to turn data into new product/service offerings, and how to add more value to More recently, data has had to share the business through data have all become centre-stage with another hugely disruptive critical priorities. how to turn data into new product/service offerings, and how to add more value to More recently, data has had to share the business through data have all become centre-stage with another hugely disruptive critical priorities.

This preoccupation has dynamic: artificial intelligence (AI). While AI underpinned the seismic transition from is not an entirely new technology, the past 1.1 INTRODUCTION few years have seen it make its way out of academic discourse and trade press opinion pieces and into boardroom decision-making. Terms such as machine learning, deep learn ing, neural networks, predictive analytics, voice/image recognition and algorithms have become familiar to many business leaders. Global players including Facebook, Amazon, Google, Airbnb, Ford, IBM, Apple, Tencent, Baidu and Alibaba are investing billions of dollars in AI capabilities, and some of them have already described their focus as AI first.2/3 At the same time, new AI-powered companies are launching on a regular basis, all looking to disrupt different sectors with their game-changing ideas. In this new industrial paradigm, many of the worlds most valuable corporations are essentially businesses built around sophis ticated, powerful and lucrative algorithms.4 At Google, that algorithm is PageRank for ranking websites. At Facebook, the algorithm puts people in social contact with each other.

Amazon has developed a commerce algorithm to help people buy and receive goods. Uber, meanwhile has a navigation algorithm that enables people to book a driver nearby, and to find the best route between origin and destination. There are many other similar examples. 1.1 Why data and AI-enabled business models, and why now? To date, the conversation about data and AI has been dominated by the technical perspective (i.e. how algorithms what is technically possible when computers increasingly take advantage of data and new algorithms); and the societal perspective (i.e. what does the future of humankind, work and society look like, and what ethical issues does the adoption of AI raise?).

By comparison, while there has been some there are barely any descriptions of what discussion around the commercial aspect of these new business models could be. How AI, it has generally been vague, one-sided or can any company plan and implement new incomplete. The role of AI in driving busi data and AI-enabled business models when ness process improvement and automating no one has made the effort to describe operations has been quite well covered, what they are, how they work, and what the but AIs contribution to new business change towards them would look like? To creation has hardly been touched on. How sum up, while there are many pieces of work can companies grow and generate more envisioning the data and AI technologies revenues with AI? What are the relevant of the future, there are far fewer that commercial models and monetisation describe the resulting data and AI-related tactics when talking about AI as a corporate businesses of the future. asset? Answers to questions like these are badly needed and in short supply. What sets this book apart is that its key objective is to explore data and AI-enabled Business books, articles and presentations business models.

While current literature often claim that data and AI can enable focuses on how companies can use data completely new business models, yet and AI to amplify their existing product and services, we raise the bar by discussing reduce their own risks and costs, increase the commercial opportunities related to sustainability and safety, wish to benefit using data and AI to create new products, from the latest technology and ultimately services and business models, so high find more optimal ways to run their daily life lighting this technology as a standalone or business. opportunity. We believe that companies should approach data and AI as tools to While these variables were in place before expand their businesses by creating new the Covid-19 crisis, they have now further products, services, innovations and winning accelerated as various industries expe more market share rather than just seeing rience severe headwinds and companies them as a way of enabling cost reductions.5 need to redefine their formula for building successful and stable businesses in the Given the recent Covid-19 pandemic and the long-term. resulting changes in the global business climate, its appropriate to ask why data In a world of unrelenting turbulence, imple and AI-enabled business models should be menting new data and AI-enabled business on the agenda for companies right now. The models, combined with a commitment to answer is that even before Covid-related transition towards technology-enabled disruption, companies were coming under scalable new product/service offerings and pressure from: revenue models, could be key to building Rapid transformation in their business resilience in business. ities, a company can reduce its dependence Changing attitudes and expectations on legacy businesses and assets, stay rele among their customers. vant to its customers, open new avenues for Tougher global competition. growth, differentiate from the competition Commoditisation of existing product/ and build an ability to bounce back from service offerings. adversity. adversity.