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Author: Dr. Alexander Borek, Head of Smart Data & Analytics, Volkswagen AG
The reason why Smart Machines are so much more powerful than conventional computer programs are the advanced AI algorithms and the data that they can absorb. Smart Machines can sense their own state and their environment, can communicate with other Smart Machines, they are self-learning and can solve very complex problems, and they can act, sometimes autonomously. There are many technologies behind the capabilities of Smart Machines. The most important enabler is the massive amount of computing power and storage that is available today for a relatively cheap price, which makes it finally possible to apply computational heavy artificial intelligence algorithms that would have not been possible some years ago.
Many characteristics distinguish traditional software applications from Smart Machines. Computers have always been pretty good in repetitive and clearly described tasks and in applying strict logic and complex mathematics. An abundance of tasks today are solved by computers much faster, cheaper and more reliable than by humans. Yet, in many ways, computers appear oftentimes annoyingly stupid. Have you tried to have a meaningful and interesting conversation with a computer? It can be a difficult and typically very frustrating endeavour. What computers are missing is the ability to understand the meaning of what we have to say. This is because language is very ambiguous. The very same sentence can mean something completely opposite if said in another situation or by a different person. “I love this computer” could mean either did I really like my computer a lot but it could also mean that I really hate my computer because it doesn’t do what I want it to do. It is very unlikely that love refers to romantic love in this context. The idea that computers can think like a human sounds stretched, it is, however, closer than you might think.
It is changing with the up-rise of Smart Machines. It makes machines being able to handle situations with ambiguity, sparse information and uncertainty, thus, be able to solve human kind of problems. Instead calculating the optimal solution using a predefined algorithm, smart machines evaluate different options and choose the best option out of the possibilities. Problems do not need to be provided in a specified machine readable format, they can be simply formulated in natural language or even normal speech. Looking at the context of the problem makes it possible to interpret the question correctly. When I ask a smart machine “what is the best restaurant?”, it should understand that I am probably looking for a good restaurant that is not too far away from my current location. Based on the outcomes of an action, smart machines can learn and improve their problem solving. Instead of being programmed, they can read PDF documentations to understand a business process and observe how humans perform a business process to build its own knowledge base and eventually be able to handle the business process on its own.
The key components of a Smart Machine are depicted in the figure and will be explained in detail in the following. An incentive and rule system needs to be set for a Smart Machine which provides a purpose for the Smart Machine to exist (e.g. as a self-driving car) and the rules it needs to obey (e.g. ethics, law, company procedures, business goals).
In order for machines to see, feel, hear, smell, and taste like human beings, all aspects of the physical world need to be translated into “digestible” data for machines to process, reason, and act. The rise of low-cost sensor technologies and the Internet of Things with its connected devices enables the collection of data from the physical world without human interaction. All senses are needed to cover an entire customer journey from inspiration to usage. The augmented senses of machines allow a broader, deeper, and more personalized customer experience. Sensed information is fed, interpreted, filtered, interlinked and used to initiate further activities.
The most important ability of Smart Machines is to process the sensed information similar to the way us humans process information (i.e. empirical learning). Smart machines are able to think and solve problems by understanding and clarifying objectives (and sometimes coming up with their own objectives), by generating and evaluating hypotheses, and by providing answers and solutions like a human would do (and unlike a search machine which gives a list of results). Smart Machines are self-learning, they can adapt their own algorithms through observing, discovery and by doing.
Finally, Smart Machines can act, by visualizing and providing the responses to a human decision maker, by informing or even commanding a human to execute certain activities, or in the extreme case, by completely autonomously executing a business process or any other actions. Based on the results of the actions, Smart Machines are able to re-calibrate their goal setting.
The impact of Smart Machines will be observable in three domains for Marketing Professisonals. First of all, customers will get a more contextualized and personalized experience. Secondly, the marketing departments will be able to do more with less people building on automation and scale of intelligent algorithms that take over some of the human labor. Thirdly, there will be advances in the customer journey possible which are of disruptive nature.
The marketing profession will be impacted fast and significantly by Smart Machines and the Algorithmic Economy. Personalizing and contextualizing the customer experience is the aim of everyone. But, creating meaningful continuous 1:1 interactions can only be feasible on a large scale with thousands or millions of customers if Smart Machines take over a lot of the work. This means that smart machines take over work reserved for humans in the past, as, for example, generating new content, and supervising staff in retail stores to ensure high customer engagement. It also means that those companies that still struggle with data-driven marketing will be in deep trouble. Those who embrace Smart Machines will be able to drive productivity beyond the imaginable for marketing and sales within the next decades.
Like all things in life, Smart Machines are all a matter of perspective. For marketing divisions in traditional companies, they might be seen as the biggest threat in history. The way most marketing departments work today is very reliant on human labor and decision making. Shifting the work to Smart Machines will make a lot of the abilities needed for traditional marketing personnel redundant and will require new capabilities that the workforce does not necessary have. For others, Silicon Valley startups and companies, Smart Machines generate an once in a lifetime opportunity. Smart Machines enable them to scale their limited resources and, thus, be able to challenge even the largest established players in their own strongholds, irrespective if it is retail, consumer goods, banking, insurance, manufacturing, entertainment or any other type of industry which requires Smart Machine Marketing.
About the author:
Dr. Alexander Borek is responsible for Smart Data and Analytics, Digital Platforms, Digital Customer Ecosystem and AI Assistants in the Group Digitalization of the 12 automotive brands of Volkswagen AG. Before, he worked as a consultant at Gartner and IBM, where he had advised Global Fortune 500 executives in multiple industries with regards to their digital transformation, data governance and analytics innovation strategy. He is a recognized international thought leader in data strategy and the author of the books “Total Information Risk Management” and “Marketing with Smart Machines“.