AI Business recently interviewed one of the UK’s leading experts in AI for Business, George Zarkadakis. George has a PhD in AI, is the Digital Lead at Willis Towers Watson, and the author of “In Our Own Image: will Artificial Intelligence save us or destroy us?”.
George is also a keynote speaker at The AI Summit London, presenting on the many different ways that AI will be shaping the business of tomorrow.


George answered a number of interesting questions giving us a taster of the insightful presentation to come at The AI Summit on the 5th of May.  


George Zarkadakis

George Zarkadakis, Digital Lead, Willis Towers Watson


 How do you believe AI will impact business overall and in what ways?


The impact of AI on business will be profound. Cognitive computing is the key driver of a new industrial revolution, the “4th industrial revolution” as it is often called. Businesses operate successfully at an optimal point where capital, supply chains, business processes, and human work and ingenuity meet to produce exceptional value for consumers. AI will impact every aspect in this economic synergy, but it will be human capital that will be affected the most. Machines that used to automate human labour will now be able to automate – and thus take over – many tasks of the human intellect. Replacing much of what we humans do with intelligent machines will cause a chain reaction from how we understand what a job is to what kind of training we should have, or indeed what kind of schooling. The other area where AI will revolutionize is how businesses capture, process, and use data. As businesses become more “digital” data becomes a critical resource. And yet most businesses nowadays are at a loss when it comes to their data. Using human data scientists to make sense of data and analytics does not deliver a good enough ROI. AI will be able to add a layer of automatic analysis and pattern recognition that will accelerate how businesses innovate and produce value from their data.


Where are we at the moment in terms of ready-to- implement technology versus wishful thinking?


There are a number of available platforms that provide AI capabilities. These platforms are already used by developers to build new applications with more intuitive interfaces, as well as more powerful analytics. Companies such as Google, Apple, IBM and Microsoft are increasingly embedding artificial intelligence in their products. I think that what Google managed to do with DeepMind and AlphaGo is a demonstration of how much faster than expected AI technologies evolve. DeepMind’s machine learning algorithm can learn by itself, and thus become an expert in a particular field, which means exhibiting creative behaviour. In my opinion this is, quite possibly, the most significant landmark in our technological evolution; the first time in history where a human creation is creative. Although this technology is not yet available to all I expect that Google will be very quick to rolling it out across its various applications.


What do you think are the main challenges in adopting AI technologies, from machine learning through to image recognition, in business?


The main challenge – as with every disruptive technology – is that in order to make the most of it, you need to rethink the way you do business. Engineers can do whatever you ask them to, but the result of their work will not deliver the value you expect unless you have the collective intelligence and appropriate culture in your company to think outside the box. As adequately demonstrated in Clayton Christensen’s seminal book “The Innovator’s Dilemma” big successful companies are big and successful for one reason: they are optimally operating in a given business environment. Change the environment and the business fails. Therefore, if businesses do not want to go the way of the dinosaurs as the AI meteorite approaches, they need to strategize around disruptive innovation. Thankfully, the startup phenomenon is full of great examples and models for businesses to follow. That’s where they should be looking at.


What about the financial services sector where would you see AI helping do things differently?


I was one of those who enjoyed watching the film “The Big Short” very much. The film recants the story of eccentric hedge fund manager Michael Burry (played by Christian Bale) who in 2005 realized that the US housing market was unstable because it sat on bundles of high-risk subprime loans.  What was very evident and crystal clear for Burry was completely opaque for the whole financial sector, not to mention the US government and the Fed. This unique vision of his analysis was the result of an exceptional mind capable of thinking and recognizing patterns without bias. This combination is more challenging that we would like. We are all victims of cognitive bias; which explains – at least according to behavioural economics – the boom and bust cycle of markets. AI will be like Burry. Which suggests that the financial sector, as well as the global economy, will have the opportunity to operate in a more stable and less unpredictable economic environment.


Which other Industries do you believe will be the pioneers in broadly adopting AI technologies?


AI will become a ubiquitous technology because of digital platforms. Applications build one those platforms will be able to power and disrupt every industry, and create new ones currently unimaginable. My PhD in AI was focusing on medical diagnosis, which happily coincides with one of the key areas that IBM Watson is also focusing on. Medicine is a good example of the type of industry that will be disrupted first. It has a number of inefficiencies that AI can address. First, it is the enormity of information and data that needs to be processed in order for a human doctor to deliver a good outcome. Secondly, the cost of medical services is rising and, given the ageing demographics of the industrialized world, this trend will persist to the detriment of national health, as well as individual, budgets. High cost of service delivery and high complexity of information processing are the two key criteria for an industry to be wanting to adopt AI as early as possible.