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James Larmer - Leading PwC's Center for Excellence in Artificial Intelligence

Wednesday, February 27, 2019   (0 Comments)
Posted by: Maggie Gisel
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By Stephanie Stewart (Colorado 1988)


James Larmer, who hails from AIESEC Australia, worked for AIESEC International, and is the former Chairman of the board of AIESEC US, has recently returned to New York as the Artificial Intelligence Leader of PwC in the US. He spent the past two years building PwC’s South East Asia Data and Analytics practice and continues to be part of the PwC global data analytics leadership team.

James’ new role is born out of the “Your Tomorrow” initiative, a multi-year digital transformation journey launched by PwC’s US Chairman, Tim Ryan. As the new lead of PwC’s AI Lab, James is scaling the firm’s AI capabilities, platforms and services to create AI-driven solutions that responsibly increase productivity, reduce risk and increase revenue for the firm and its clients.

PwC Labs connects all PwC lines of service, incorporating technology, data, automation and artificial intelligence with governance, data policies, client data utilization and numerous complex process that come with successful dynamic client engagements. As James described it, “This is the first time we will have a single data platform that is integrated with a work bench that all 55,000 staff can have access to and use. It will be combined with an internal portal called Digital Lab so associates, seniors and managers can easily connect with the data they need and publish digital assets that their work teams create. This will allow staff within the firm to find these resources and use it to do their work more effectively.” PwC has numerous industry specific client engagements where repetitive analysis and processes can be streamlined with artificial intelligence thereby making this work go more smoothly.

James explains, “Artificial intelligence is the ability of a machine to perceive its environment and then perform some sort of action that you would normally associate with a human.” The starting point of the journey is to increase productivity. This is especially useful for actions that people do systematically over and over again. There can be hundreds of variations on a tax document, for example, and if AI can be used to identify all those variations, it can save 5 minutes, 30 minute or an hour.

A properly trained AI model, using natural language processing, will be able to take a document, digitize it, learn to understand what is in the document and process that information at the lowest level, and generating content and taking actions at the highest level. There is also an image classification element to digitize and organize documents for clients and in PwC’s own work processes.

James explains that “AI gives you the ability to piece together patterns that you may not be able to see on our own.” In financial auditing, for example, teams traditionally would look at a sample of the client’s financial transactions once a year. Today’s audit can be 24/7, using AI techniques such as anomaly detection to constantly scan for financial errors and patterns. An AI algorithm will be faster at seeing the error than a human taking one off samples from a large number of transactions.

At a higher level, PwC created a whole new business for a car. James describes another example of AI - simulation modeling - where PwC helps a business to analyze a huge amount of data related to a business transformation or operational problem and develop scenarios for possible business decisions. James says that, “System dynamics is particularly powerful when the past doesn’t look like the future – which is often the reality in which many traditional companies find themselves. This technique enables you to simulate new market conditions and better understand how the complex realities of economic factors, consumer preferences and competitive forces play out. As an example, we created a whole new business for a car manufacturer looking to navigate the dynamics of new entrants such as Uber and the potential implications of driverless vehicles.”

James described one aspect of AI led transformation. “All of us are looking to make better and faster business decisions, based upon as many facts as you can assemble with cutting edge technology. If that means extending your data assets and incorporating responsible AI, then that is a conversation that we have with client leadership." PwC emphasizes that AI must be developed responsibly and that factors such as human bias in the data used to train models is accounted for. They focus on developing trust in AI by helping clients create transparent, explainable, provable, bias tested models that embed ethical, legal and governance considerations.

One challenge, James identifies, is that many businesses have silos where they are using data and AI to improve their department’s performance and realize the best results for the business unit and the client. It is challenging since managers maximize for their “piece of the puzzle” but the best interest of the customer and the overall company may not be maximized. James points out that it can be very productive for a company to develop a common view of how they value customers that moves across departments and is reflected in information analyzed and collected by the company’s systems, algorithms and artificial intelligence. Management may need to step back and do a review of the technology they are using and establish policies and processes for adapting the rapidly expanded breadth of new technology.

There is also the challenge of engendering trust in AI, particularly by those who did not grow up with computers as “digital natives” have. James states that, “The mentality that PwC has is that we code and develop our platforms so they ascribe to the highest possible standard. You have the ability to understand how the data is being used to control it and you have the ability to remove data streams if you want to change what data is retained.”

James encourages young people interested in working in this rapidly expanding profession to learn two or three coding platforms. More importantly, he explains, that you should, “stay on a continuous learning journey on your own and take courses in machine learning and advanced analytics,” pointing out that there are many free and low-cost online courses. Since many business schools don’t offer hands on machine learning, taking control of your own skill acquisition is essential. All of the large Silicon Valley technology firms are recruiting AI talent as are the large international consulting firms and the compensation and career tracks are very attractive. The expanding use of artificial intelligence in business and in our personal lives makes the work that PwC and James’ AI Center of Excellence Lab increasingly relevant to business and young graduates today.

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