AI is like pixie dust

I call myself a very forward looking and logical person, but one of my most inexplicable and annoying traits is that I am a hoarder! I just cannot get rid of anything, driven by the irrational belief that it may come useful at some point in the future. That is why my loft could double up as the perfect ‘treasure hunt’ playground for kids, full of boxes of hidden objects, toys and clothes, offering endless opportunities for dressing up and role-playing… well, if you ignore the layers of dust covering them…

As my rational self often prevails, I occasionally end up doing a big sweep to create… well… some space for new arrivals. I recently embarked on one of such endeavors and among many other long-forgotten items, I found my very first mobile phone. I still remember the day when I proudly received it when working for Barclays Bank – my new corporate toy, taking me into the new era of communications, beautifully innovative and definitely… big! No kidding, I had to buy a bigger handbag to be able to carry it around! Indeed, when I showed it to my daughters, they thought it was an army-style walkie-talkie, complete with satellite aerial and non-slip plastic grip!

Anyway, it is amazing to see how fast technology has changed in only 20 years and how much it has impacted our life. What was revolutionary then, today is just expected and part of the daily fabric of our daily routines. Similarly, I remember receiving my first iPhone exactly 10 years ago and being absolutely blown away by its ability to receive emails, access the internet and generally be connected anytime, everywhere.

But even this ‘connected’ concept has now evolved into new levels of contextually relevant and personalised interactions – often beyond our comprehension. Now we expect from smartphones relevant push notifications, accurate location services, predictive messaging, proactive assistance… The complementary power of data intelligence and artificial intelligence (AI) solutions is increasingly enabling personalised and beautifully blended experiences that ‘magically’ make our digital-first customer journeys easy and seamless.

In my previous blog, “I want a Bot and I want it now”, I already shared my thoughts on some of the challenges organisations are facing in an attempt to use AI to improve the customer journey, but a key question is:

Can AI create differentiated experiences?

Recently, LogMeIn commissioned a study to Forrester on this very topic. The study outlines the role AI is increasingly playing in complementing more traditional customer service solutions to handle and orchestrate new channels like chat, messaging platforms, chatbots, video, co-browsing etc. It explains that customers increasingly “demand context-driven interactions… at the right points in their journeys to educate and help them in their moments of need.” These contextualisation and personalisation capabilities go beyond those of the history-based knowledge of traditional CRM solutions and their rules-driven algorithms. AI can complement these through a range of technologies and prediction models that “will help companies provide deeply personal, intent-driven, contextual pre- and post-interaction customer service.”

AI is not only about cutting costs

Yes, AI can help organisations improve operational efficiency, which in turn will reduce costs. However, the main value added by AI is its ability to add some pixie dust to make us fly through our customer journeys in an easier, more relevant and personalised way. The sci-fi writer and inventor Arthur C. Clarke once said, “Any sufficiently advanced technology is indistinguishable from magic”. Like this technological magic, AI leverages customer and behavioural data and carries context between channels, supporting a flow of blended automated and human-assisted interactions.

But what is AI?

The Oxford dictionary defines ‘artificial intelligence’ as “the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making and translation between languages.” In other words, AI is the general field that covers everything that has anything to do with imbuing machines with ‘intelligence’, with the goal of emulating a human being’s ability to reason.

Within this context, ‘machine learning’ is the part of AI that is concerned with conferring upon machines the ability to ‘learn’, by using algorithms that discover patterns and generate insights from the data they are exposed to, for application to future decision-making and predictions through cause-and-effect sequences. ‘Deep learning’, on the other hand, is a subset of machine learning: it is the most advanced AI field, which brings AI closest to the goal of enabling machines to ‘learn and think like a human brain’.

Therefore, coupling technology, data and automation, AI learns from the patterns of the past to support present interactions and pre-empt future needs.

Supporting present interactions

Pre-programmed with industry and product knowledge, AI-powered systems can handle many customer transactional interactions and queries efficiently and fast, without incurring the costs of contact centres. No training or re-training needs, no queues or peak times, no shifts or holidays – AI offers immediate, scalable, always-on customer support, 24/7, reliably when customers need it.

Coupled with the increasing preference of new generations for self-service and personalised interactions, automated customer service solutions will become crucial in meeting customer needs without the associated service costs.

Pre-emptying future needs

The Forrester report “2017 Customer Service Trends: Operations become Smarter and More Strategic” touches on the concept of pre-emptive customer service. It highlights that “companies will continue to explore the power of intelligent agents to add conversational interfaces to static self-service content. They will anticipate needs by context, preferences and prior queries and will deliver proactive alerts, relevant offers or content. They will additionally become smarter over time via embedded AI.”

AI solutions monitor interactions in real-time to identify trigger signals and respond offering support through interactive FAQs or virtual service agents across platforms and devices.  This can solve issues even before they arise and therefore increase conversion rates and customer satisfaction.

The future is now

While it is still a field under continuous development, AI is already part of our daily lives. We regularly use virtual assistants like Siri and Alexa, but AI is showing up also in more common applications, from messaging and the recommendation algorithms of Amazon and Netflix, to the Nest learning thermostat or the predictive capabilities of Tesla cars. These AI-fueled systems will continue to evolve and become part of the fabric of our lives, adding some pixie dust magic to the customer service world and creating improved, more personal and engaging customer experiences – often totally undetected by consumers.


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