Balancing AI and Human Touch: The Future of Personalized Customer Engagement

AI and automation have the potential to transform customer engagement by providing the ultimate efficient, personalized, and accessible service.  But can technology alone provide the human touch sometimes required?  And do consumers want this from a machine?  

When brands strive for hyper-personalization and automation, they should carefully choose which interactions to personalize and when that personalization is purely mechanical.  And they should be transparent when doing so.  Otherwise, they will feel begrudged and disappointed.  Or worse, like a Turing test gone wrong, feel hoodwinked, disturbed, and betrayed.   

Let’s take a very simple example.  How does it feel when you receive an automated happy birthday or happy holidays message?  

Reflecting on that question, personally I’m unfulfilled when I receive one.  There is nothing personalized or human about the production or delivery of the message.  It simply compares the current month and date with a birthdate, takes a name from a database, and using an email template mass produces the message.  There isn’t a caring human behind it deciding to take time out of their day to reach out and provide well wishes. 

Or take this a step further.  What If this message were more carefully crafted and personalized, to appear to be from a human, would that be better? 

In fact, this is where AI technology is going, and some companies are already taking this too far.  Those small steps too quickly become impulsive giant leaps into a world forcing customers into interactions with machines and AI that don’t always end well.  Take this example scenario where someone needing mental support is interacting with AI, but then the conversation ends abruptly:

https://www.rowbotai.com/industries/health-and-wellness (scroll to #7 “Miserable” – it’s 1 min 28 sec)

Did the technology simply fail to come up with a follow-up response? Did the database or connection go down?  Was the technology programmed to recover and reach back out to the client, or better yet, escalate this to a human?  He still desperately needed help.

Pondering these questions is not suggesting firms ignore the potential benefits of using AI and automation in the right circumstances.  Instead, it points to the importance of understanding the appropriate times and methods for utilizing advanced technologies, as well as knowing when to engage human expertise, and how to ensure a smooth and acceptable handoff and transition.   

What consumers want

As businesses design the transition and inexorably march toward using technology for increased efficiency and more digital engagements, the goal should be to give consumers what they want – relevant, rewarding, and timely brand exchanges.  But what level of personalization and humanization should a company strive to achieve in each interaction?

That depends on the situation and the customer’s intent.  For example, AI can be deployed selectively and tastefully.  In some cases, it’s fine that no human is involved (and it should be glaringly obvious that’s the case).  In others, humans should be in the loop, where AI is used to amplify human capabilities and minimize human limitations.

A “Human Touch”

Consider these aspects of an agents’ human touch – and imagine here that an agent can mean a human or machine:

  • Sounds human & conveys unconditional empathy.
  • Listens, comprehends, and suggests reasonable courses of action based on the contextual understanding of the current conversation.
  • Displays good judgement, respect, resourcefulness, and common sense in real-time problem solving, achieving status as a strategic business partner.
  • Builds a level of trust with the customer, achieving status as a trusted advisor.
  • Personalizes the experience so that the customer feels special.
  • Relates to the customer by telling stories meaningful to the conversation.
  • Recalls important details of previous conversations.

All these may sound difficult for machines to mimic, however advances in artificial intelligence and machine learning are beginning to bridge even these gaps.  When asked, about 40% of consumers believe AI has the potential to improve customer service (in that same consumer study, only 26% did not believe it could), suggesting that once it does, and if it acts in a more human-like manner, they may not care who is servicing them provided they consistently get what they want.[i]

So, what is it that humans want?

  • Short or no wait times – Time is precious, and customers appreciate immediate responses.
  • Accessible service – Availability across all platforms and at any time is crucial.
  • Fast service – Once engaged, customers expect a prompt resolution.
  • Coordinated service – Seamless transition between service channels without repetition is key.
  • Accurate & fast answers – Quick and correct responses build trust.
  • Tailored and relevant recommendations – Personalized and non-intrusive product, service, and support recommendations that make sense are welcomed.
  • Warm and cordial experiences – Friendly and memorable service fosters loyalty.

Pitfalls to avoid when applying AI in customer engagement:

In planning for success, it’s essential to consider what to avoid, minimizing unnecessary mistakes. To improve machine or human performance, learn from the mistakes of others. Here are some dangers to sidestep:

  • Tendency to over automate before you carefully assess the impact total automation may have on customer experience. It may be improving the bottom line (in the short run), however is it ultimately improving customer satisfaction, or making it worse?
  • Placing a premium on playing parlor tricks with technology or customer information, while not focusing on whether the outcome is ideal.  Scrutinize the value of the use case. Improper use can backfire, such as wishing a customer happy birthday when they never gave you permission to gather and use their birthdate.
  • Losing sight of the root cause and fixing it. Why did the customer ask for support in the first place?
  • Designing programs based on the law of averages versus factoring in individual customer preferences & valuation.  Remember, some customers may require human interaction, and it might be economically justified to provide just that.
  • Falling victim to automation bias – Becoming sloppy, complacent, insensitive, and dulled, because machines take care of so many customer service tasks – and when humans are called on to provide service, they can’t – due to being rusty, incompetent, or rendered totally incapable.

5 ways to employ AI in customer engagement:

  • Automate the no brainers. For example, use automation & intelligence to lookup routine customer information, answer frequently asked questions (FAQs), get order status, or even process a payment.
  • Use automation & intelligence to classify and route emails, calls, and other requests. They’ll get faster to the right people that can ultimately close out the case.
  • Augment staff with intelligence, such as using a GPT knowledge base, with filtering and learning capabilities, to rank likely answers to FAQs, and provide those to staff so they can quickly answer questions, while still providing a human touch.
  • Take interest in what matters to the customer and knowing things about them pertinent to the relationship. Use AI to help store and recall critical material at the right moment, and let humans decide how and when to weave that into conversation for a natural flow.
  • Ensure warm handoffs between self-service technology and the humans who might have to complete the servicing. For example, when a customer engages in self-service, but then escalates, guarantee a comprehensive and seamless transition of the self-service transaction to human agents.

Advances in AI technologies that apply a human touch:

  • Experiment with chat bots, focusing on which interactions can be fully handled by machines, and which need to be either immediately routed to a human, or escalated to a human once its apparent the chat bot has reached its limitations.  This coincides with striving for an overall system that is friendly, helpful, and convenient to do business with.
  • Guard against AI’s detrimental potential, such as being tone deaf and discriminatory.
  • Test using prescriptive intelligence techniques that incrementally improve relationships.
  • Use real-time event processing technologies, voice AI, and journey analytics to gather contextual behavior, detecting and reacting to in-the-moment customer struggle and intent.  For example, paths that cause customers to repeatedly drop out or abandon an objective, such as failing to finish an application.  Or customers who raise their voice or rage-click a button, indicating high levels of frustration.
  • Select one next-best-experience engine and connect it to all channels.  Its role: act as the corporate always-on brain – a 24 x 7 x 365 customer memory bank, insight generator, and engagement hub that knows when to automate and when to escalate to humans.
  • Employ usability testing and customer surveys to monitor customer journeys and experiences.  Fine tune journeys so they combine the right mix of automation, convenience, relevant recommendations, and human touch to deliver optimal results.

Conclusion

We’re all developing relationships with machines and already extremely dependent on them. We talk to our devices, use them as assistants and navigators, and laugh at their jokes.  Ten years ago, the movie “Her” seemed like far-fetched science fiction, yet today there are apps like Replika where people form emotional relationships with AI.

AI is here to stay. Make no mistake – it’s going to automate more manual tasks and change the nature of many jobs and our consumer experiences, just as the industrial revolution did over 100 years ago.   An economic outlook published in 2017 by PWC predicted that by 2030 automation would replace as many as 40% of current jobs, such as transportation, manufacturing, and trade. [ii]  And that was 5 years before the generative AI revolution. 

Even so, where social skills are paramount, such as in customer service and social work, those same forecasters expected the impact to be radically less.  It’s hard to say precisely how this plays out.  No doubt, a significant share of jobs are at risk of automation, and there will be completely human-less customer journeys.  And although AI will create new jobs, and in some cases better experiences, the transition will be disruptive for many people, who will need to adapt and re-skill.

By avoiding common pitfalls and strategically employing AI, businesses can create a customer engagement model that is both technologically advanced and warmly human. The goal is not to replace human interaction but to enhance it with AI’s capabilities, ensuring that the customer’s journey is as convenient as it is delightful.  

Technology continues to change lives and create opportunities for businesses. Those that learn to use it effectively at scale, with a proper balance of automation, AI, and human touch in customer interactions, will be more relevant to customers, and win more loyal long-term relationships with them.


[i] What Consumers Really Think About AI: A Global Study, https://www.pega.com/ai-survey, 2022

[ii] PWC, Economic Outlook, https://www.pwc.co.uk/economic-services/ukeo/pwcukeo-slides-final-march-2017-v2.pdf, 2017