Marc Carrel-Billiard, global managing director of technology research and development at Accenture Plc.
Marc Carrel-Billiard took charge as the global managing director of technology research and development (R&D) at Accenture Plc in October. In this role, he oversees Accenture Technology Labs and Accenture Open Innovation, and directs Accenture’s annual Technology Vision research, which forecasts the future of enterprise IT. During his more than 18-year tenure at Accenture, he has worked on voice recognition, knowledge-based systems and neural networks, among other areas. One of 105 Accenture-certified Master Technology Architects, Carel-Billiard is also a keynote speaker at the two-day EmTech India 2016 event, to be held in New Delhi on 18 March.
In an email interview, he speaks about his new role, disruptive technologies and India’s role in R&D. Edited excerpts:
As head of technology R&D at Accenture, what steps are you taking to strengthen existing R&D processes to future-proof your business?
I’m proud to lead an exceptionally talented group of technology experts who wake up every day and create new ideas and fresh innovations that completely disrupt the status quo. We use Accenture as our “test-bed”.
In addition we are strengthening our processes in two ways: first, we are launching new labs–we launched our new artificial intelligence lab in Dublin and will soon launch a new lab focused on cybersecurity, expanding our footprint and capabilities globally; second, we are strengthening our connections around the world through our open innovation program, forging new working relationships with leading universities, start-ups, venture capitalists and corporate R&D groups.
Given that you also lead Accenture’s annual Technology Vision research, what are the five main tech trends that you see having a significant impact, or disrupting, business models in the next couple of years?
This year’s Technology Vision focuses on People First: The Primacy of People in a Digital Age. As technology advancements accelerate at an unprecedented rate—dramatically disrupting the workforce—companies that equip employees, partners and consumers with new skills can fully capitalise on new innovations. Those that do will have unmatched capabilities to create fresh ideas, develop cutting-edge products and services, and disrupt the status quo. We identified five trends:
Intelligent automation: Leaders are embracing automation—powered by artificial intelligence (AI), robotics and augmented reality—to fundamentally change the way their business operates and drive a new, more productive relationship between people and machines.
Liquid workforce: By exploiting technology to enable workforce transformation, leading companies will create highly adaptable and change-ready environments that are able to meet today’s dynamic digital demands.
Platform economy: Industry leaders are unleashing the power of technology by developing platform-based business models to capture new growth opportunities, driving the most profound change in the global macroeconomic environment since the Industrial Revolution.
Predictable disruption: Fast-emerging digital ecosystems are creating the foundation for the next wave of disruption by straddling markets and blurring industry boundaries; forward-thinking leaders can proactively predict these ecosystem trajectories to gain a competitive advantage.
Digital trust: Trust is a cornerstone of the digital economy. To gain the trust of individuals, ecosystems and regulators in this new landscape, businesses must focus on digital ethics as a core strategy; better security alone won’t be enough.
How is the India R&D team contributing to Accenture’s global vision?
Our Bangalore lab is a crucial part of advancing our artificial intelligence capabilities. It is undertaking a journey to help transform businesses from being largely human-driven to becoming more machine-assisted. The Accenture R&D team in Bangalore applies advanced technology-based, patent-pending intellectual properties in several areas, including natural language processing, model-based engineering, program analysis, application security analysis and cloud computing.
One example is the work the lab is doing with Accenture Operations to apply artificial intelligence, machine learning and robotics in order to help clients execute business processes with greater effectiveness and quality. In support of this work, the lab built the Intelligent Text Analysis Platform, which uses state-of-the-art natural language processing and machine learning techniques to analyse data from different domains, and then intelligently extracts information and relevant insights for the user.
Our Bangalore lab has been working side-by-side with Global Testing Services to differentiate Accenture’s software testing offering from the competition. Currently, automation exists primarily in the test execution phase; however, our artificial intelligence research is succeeding in automating the more difficult and challenging phases of test planning and preparation.
Is artificial intelligence a much-bandied term, or is it gathering enough momentum to change the way business is done?
It’s being bandied about for many reasons, and one of them is because it is advancing much faster than it has in the past. It will fundamentally transform and improve how we work and live. The concept of artificial intelligence was born at the dawn of the information age. However, recreating the vast computing power of the human brain, with its ability to process different sensory input, reason solutions to problems and express empathy has proven to be largely a fool’s errand—until recently.
What’s changed technologically is the availability of massive, inexpensive cloud-accessible computing power, low-cost storage, combined with algorithms to sift rapidly through enormous volumes of data. These technologies are igniting the development of new applications of artificial intelligence across multiple industries.
We now have self-driving cars that navigate the highways, voice-activated computing that instantly searches the world’s libraries and databases, and video analysis solutions that can infer suspicious events from closed-circuit television feeds. Advancements like these help to unleash new levels of business productivity and, in turn, innovations that power greater business agility.
When you say that cognitive robotics will be forward thinking, what do you mean?
We see cognitive robotics as a new generation of robotic process automation (RPA). Cognitive robotics can automate manual processes using UIs (user interfaces), recognising fields and labels from UIs and accessing multiple systems to automate complex transactions. This technology can be used to automate testing, claims processing, and various other business transactions. Coupled with virtual agent technology it can deliver fantastic automation opportunities while interacting with users in natural language.
Give us some examples of how the adaptive learning power of robots is being used in companies?
Virtual agent technology can leverage interactions with users to learn from them and augment their semantic network, For example, those agents can be used to replace CRM (customer relationship management) agents for simple tasks. When a user is asking a more complex question the agent can hand-over to a supervisor but listen to the conversation between the supervisor and the user and learn from it so that next time it can answer the question directly. Companies in various industries are starting pilots using this technology.
What does AI mean for Accenture? What does an intelligent machine mean to you?
Right now, we are seeing artificial intelligence at a tipping point, quickly coming of age and beginning to mature at a much faster rate than ever before. Progress with semiconductor technology, including sensors, improvements with communications infrastructure and analytics and the maturation of cloud technologies have unleashed a new wave of technology innovation that we believe will disrupt and transform how business operate and compete and how we work and live.
That said, we see tremendous opportunities ahead, but a there is a whole lot of hype and confusion in the market right now. First of all, there is a lot of what I call “cognitive washing” in the market—characterizing one tool or domain as cognitive. It is not one tool or one capability like machine learning. It is a not a single bullet technology, and not one that can just be bolted onto your enterprise to suddenly solve your hardest problems.
Artificial intelligence is a constellation of technologies that when integrated together, can create a highly adaptable, nimble business capability. It must be technology rich, meaning it must feature multiple key technologies such as the computer vision, natural language processing, machine learning, deep learning, knowledge representation, expert systems, biometrics and video analytics.
Secondly, it must be business-oriented. Artificial intelligence relies on business domain to comprehend and act. The general program solver system, once imagined, does not exist. Like human experts specialised in one or few domains of expertise, artificial intelligence solutions need specific business domain expertise to be able to reason and deliver tangible business results.
This means that it absolutely must access and work within not only your latest digital applications and technologies, but also your legacy environment. In all the hype about cognitive, the business domain knowledge and necessity to integrate within your entire IT environment regularly gets overlooked.
And lastly, it must be people-first. Fundamentally, artificial intelligence will be about making humans super, not making super humans. This means you have to take a People First mindset. Enterprises must focus on enabling people—consumers, employees and ecosystem partners—to accomplish more with technology. They will have to create a corporate culture that harnesses digital to enable people to constantly adapt, learn, continuously create new solutions, drive relentless change, and disrupt the status quo.
In an age where the focus is locked on technology, the true leaders will, in fact, place people first. It’s time to relook at your workforce and identify what tasks should humans do, what skills do they need now – for example robotics engineers – and how they are going to work with machines from intelligent agents to robots and more.
You appear to be bullish about deep learning too. Your reasons? Please give us a specific example of how it is being used in companies.
Deep learning is one of the most exciting technologies within the Artificial Intelligence suite because it will open up entirely new types of capabilities for humans. Accenture, for instance, worked with a major insurer that wanted to automate vehicle damage claims processing. When receiving photos of a damaged car, the client wanted to have the ability of automatically detect the level of damage and use this information to, for example, order spare parts and possibly detect fraud.
By combining machine learning with knowledge representation and computer vision into an Intelligence Augmentation capability, Accenture helped this client achieve more than 90% accuracy in automated claims analysis and reduce travel requirements for adjustors. The insurer’s intelligent claims processing system also allows agents to spend more time on the subset of claims where their expertise is needed. The machine learning systems not only flag the appropriate claims for adjusters, it highlights the features of the claim that deserve attention, and then present similar claims to the same agent, who is now well versed in the particular issues at hand. Now the client is expanding this capability to other lines of insurance, such as home and valuable personal property.
You also head Accenture Open Innovation—the group that works with start-ups, venture capitalists, leading academic organisations and corporate R&D groups. What’s been your experience with these partnerships so far? Can you provide a specific example to explain how these partnerships help your business?
Accenture Open Innovation gives us the unique ability to harness the best innovation across the technology industry. We have a wide variety of partnerships. For example, we are providing grants to some of the world’s best academic institutions to gain access to leading technical and scientific research in critical growth areas of our business. One example is with Stanford University, where we are experimenting with new workforce models using crowdsourcing technologies to gather the best talent on demand, from both inside and outside the enterprise.
We also work with start-ups, and have a watch list of more than 700 of them. We assess these start-ups to determine which have the most enterprise-relevant and enterprise-ready technologies. Then, we help clients identify which are best suited for them. We call this Open Innovation as a Service. For example, we worked with a leading company to connect their business leaders with several start-ups that are helping them add new digital capabilities to create really disruptive new products and services for their customers.
Have people learnt to trust the advice being doled out by intelligent machines?
Yes and no. People trust things like the autopilot on an airplane, but don’t think about this as an Intelligent Machine—and it is. However, people are sceptical about new technologies. One of the things I like to say is that first, people are afraid of new technologies. Then they are intrigued and finally, they are bored as it will be part of their everyday life. And that’s what we are going to see with intelligent machines.
Take autonomous driving cars as an example. At first, people have been afraid of losing control. Then they were intrigued because they could start testing new things, like changing lanes automatically, or turning without acting on the steering wheel. And then very soon they get bored as they do not think about it and they start to adopt unsafe behavior like reading newspapers, answering mails or playing crossword on their tablets while the car is driving. Then, they’re bored because it becomes imbedded in their lives. And I think that’s the evolution we will continue to see as new intelligent machines enter the market.
Given that the technology treadmill is moving so rapidly, can you list three important things that CIOs should do to keep pace with these trends?
• Be built for change so you can embrace disruption
• Create a data-driven organization
• Incorporate digital trust into everything you do
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