Hybrid Intelligence For The CX-Driven Future

Considering human expertise and intentionality when making meaningful decisions, hybrid intelligence is changing the direction of the AI revolution.

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    Consider artificial intelligence (AI) to be the front and centre of operations, but all the while, it is human orchestration pulling the strings behind the screen. Harnessing the best of both worlds is the most viable solution today. For better understanding and context, let’s start at the beginning.

    The concept of AI was first discussed in 1956 at a conference at Dartmouth College. While the initial idea was to develop a mechanism to replace the human calculator, the idea of information processing became more rigid in the late 80s. And at the beginning of the 21st century, the concept of machine learning was born. Soon, high-performance computing systems made it possible to make the machine learn and accumulate experience using massive databases and multilayer neural networks.

    Furthermore, shortcomings such as understanding empathy and bias-based insights raised further concerns. “One of the things that we haven’t quite been able to teach technology is empathy. We can expect AI to be personalised and use data to create a personalised experience, but empathy goes beyond scripted language that says, ‘I’m really sorry you have a problem’. The tech that we use to engage customers has to go hand in hand with human interaction when required,” said CX expert Dan Gingiss and the author of The Experience Maker.

    As a result, the concept of hybrid intelligence (HI) has been garnering attention more recently.

    What is hybrid intelligence?

    A combination of human and machine intelligence, focusing on expanding human intellect rather than eliminating it. Considering human expertise and intentionality when making meaningful decisions, HI is changing the direction of the AI revolution.

    Intelligent AI hybrid systems can solve several complex issues related to the inaccuracy, uncertainty, ambiguity, and high dimensionality. It combines knowledge and data to solve problems rather than learn everything through data.

    Where does current AI fall short? Although it is better at pattern recognition and machine learning tasks, AI cannot apply common sense reasoning, and human capabilities like collaboration, adaptivity, responsibility, and explainability (CARE). Developing HI requires new and improved solutions to such core research problems in AI. Being complex, it involves the amalgamation of data strategy, change management, technology selection, tooling, deployment, and integration.

    Introducing expert context into good algorithms can prove more effective and powerful in solving problems. The Hybrid Intelligence Centre creates a national and international focal point for research on all aspects of Hybrid Intelligent systems.

    A promising use case for HI is in the automotive industry. Self-driving cars need  R&D, to understand basic rules, environmental signals, and other gestures to make proper and real-time decisions. Many technology experts who developed computer vision and language processing capabilities with deep learning are looking to re-strategise with HI, mainly because existing systems are prone to bias.

    Insurance companies can also use HI to their advantage. Using HI applications, deep learning models can learn to perform basic tasks such as airbag ejection and human detection and leave complex inferences to models controlled by live agents.

    Years ago, QuantumBlack made its name in Formula 1 racing by leveraging data science to help teams get the best possible performance advantages. And in 2015, McKinsey acquired the analytics startup. Since then, the startup has accelerated the analytics work of McKinsey and became its unified AI arm.

    The aspect that makes QuantumBlack unique is its hybrid intelligence. “One thing that hasn’t changed: our original principle of combining the brilliance of the human mind and domain expertise with innovative technology to solve the most difficult problems. We call it hybrid intelligence, and it starts from day one on every project,” said Alexander Sukharevsky, who leads the startup.

    Revolutionising CX

    Personalising every customer engagement with accuracy and speed, and maintaining the human touch is a CX winner.

    According to a Twilio report, the global pandemic accelerated companies’ digital communications strategy by six years. And businesses across industries are trying to innovate better processes to reach and satisfy their customers in real-time, across channels.

    With the rapid and continued rise of digitisation, the use of AI is bound to increase to allow businesses to do more in less time. It allows for a better customer experience (CX), increasing sales and ROI. But as AI and deep learning capabilities are not ideal, HI is a favourable compromise.

    Many business opportunities and goals can only be realised with human expertise and intelligent ML capabilities. From preparing the responses to answering queries incapable of the AI to fathom, HI can allow the AI solution to be better trained and learn from each interaction rather than leave customers unsatisfied.

    Experts recommend industry leaders harness this innovation across strategies, especially to enhance CX. Handling complaints, booking, payments, and other digital services in real-time can seamlessly be achieved by HI.

    While some industries such as telecom and autonomous transportation are already eyeing and leveraging HI in certain forms, this approach can work directly across other sectors and develop experiences to increase customer loyalty, CLV, and ROI.

    A NICE study revealed that millennials and Gen Z would be the main force of the digital-first future of CX. Being born in the era of AI, they have a much shorter attention span, are incredibly tech-savvy, and expect personalised engagement through various digital channels.

    According to Mark Liversidge, Chief Technology and Experience Officer at The Student Hotel, “the focus has shifted to the behaviour and customer demands of Gen Z and Gen Alpha groups.” The best approach to satisfy these customers is through HI.

    While a Jarvis-like AI assistant is still science fiction, the world is moving towards Hl as a new and improved opportunity and a powerful resource. The role of live agents becomes a vital component in the future of CX. Businesses across industries can no longer ignore its promising benefits.

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