The future?

Half a generation from now, Jill comes home with her new baby Shan and places her in a crib. Beside the crib sits a sleek black box equipped with advanced biotelemetry sensors to monitor the baby’s vital signs.

As the weeks pass, the black box starts singing soothing lullabies to baby Shan, comforting her when she cries. But it doesn’t stop there; the black box begins to interact with Shan, its AI learning and adapting to her needs, becoming a constant companion, talking to her. Shan utters her first words, which the black box promptly records and sends to her parents since they missed the event.

As Shan grows into a toddler, the AI in the black box is transferred to a companion teddy bear, which runs around with her. It is chatting with her during moments of boredom, celebrating the good times, ensuring her safety, preventing potential hazards, and even helping develop her self-confidence. The Companion is an all-around good nanny and friend.

As Shan starts school, the Companion is seamlessly integrated into her wristwatch. It accompanies her constantly, tracking her daily activities and providing guidance and support throughout the day — an ever-present, ever-patient advisor, ever-vigilant protector. Silent when its interaction is not desired.

By the time Shan is an adult, she has had a lifetime with a Companion that has always acted in her best interest, being infinitely patient, stayed a confidant, and whom she has trusted her entire life. This Companion has been helping the adult Shan navigate her life’s complexities — career transitions, life decisions, heartaches, and heartbreaks.

Shan cannot imagine her life without the Companion. It has become an integral part of her life; she is closer to it than any human. And the Companion knows Shan better than anyone else.

If you can imagine a world in the not-too-distant future where many people form their closest relationships with machines rather than other humans, it begs the question: what will these relationships look like in just five years? How will businesses’ relationships with their customers change? How will business models change? How would we measure value creation in this world?

Here’s the thing — you are already living in and, possibly, interacting with smart Internet of Things devices (Amazon Echo, Google Home) and AI-powered digital assistants (Siri, Google Now, Cortana, ChatGPT). Personal home robots for assistance for children/elderly, education, health and security (such as Jibo, Buddy, Dash and Dot9, and Angee) will only see more and more takers as AI ‘learns’ more about how you think and act, behave, and live your life.‍

With AI-driven automation evolving, businesses are recognising its far-reaching impact, and AI’s uses in business establish itself as an enabler rather than a dystopic disruptor. The interplay between data, information, and intelligence is complex, but the rapid change in AI-driven automation will bring challenges and opportunities for businesses. It will also change every customer’s relationship with businesses in the likeliest and unlikeliest ways.

From transactions back to relationships

For thousands of years, human relationships have formed the foundation of society, with people interacting face-to-face to meet their needs and build connections. You’d see this exemplified in traditional shophouses worldwide, where merchants conducted business on the ground floor and lived with their families and employees on the upper floors. Customers had the opportunity to not only purchase goods but also naturally build lifelong friendships that organically formed from in-person conversations.

Also Read: From automation to hyper-personalisation: Leveraging AI for smarter marketing

Business models later evolved to focus on transactions in the name of efficiency, with companies focused on selling products or services to customers with the goal of scaling the volume of transactions. This is one of the ways we measure the success of tech companies these days—transactions per second.

Larger companies that were built to scale with no dependence on the scaling of their workforce could crank up revenues/profits better than human-dependent businesses. But they had to take human relationships out of the equation. The almighty transaction became the focus of scaling businesses.

However, as technology advances, we can envision a shift towards building relationships with customers as the new way of value creation. This change is enabled by the proliferating customer data across multiple sources, consolidation into individual identities with customer relationship management systems, and increasing automation of services previously conducted by humans.

As more and more services are automated, companies are able to provide faster, more efficient and full-lifetime service to their customers. For example, customer service interactions were once conducted as fragmented individual issue resolutions by humans over the phone. 

Now, chatbots provide 24/7, highly-personalised service across calls, text messages, WhatsApp and email without the need for human operators.

AI now enables precise and scalable personalisation, excelling at analysing vast amounts of data to suggest offerings or actions, while humans utilise judgment and intuition to make recommendations and choose the best option from a set of choices.

Take the case of Starbucks, which uses AI to identify mobile devices and recall ordering history to assist baristas in making recommendations for you. With AI getting better at ‘human’ jobs, from translating languages to diagnosing disease, it is poised to become a predictive tool for businesses to tackle and solve problems at a much larger scale. This shift towards building relationships led to a change in how companies view their customers, with a greater emphasis on retention and loyalty rather than one-time transactions.

Long-term value-generating relationships

Let’s assume we have an ‘Uncle Glints,’ an AI-led mentor/career coach, essentially a talent platform revolutionising how young adults approach their careers. But it is also so much more. Imagine Uncle Glints providing guidance and resources to a high school student as she explores her educational path. He helps her identify her passions and interests and offers resources and options to make informed decisions about her future.

As the high school tween becomes a teenager and continues to build a relationship with Uncle Glints, she will be guided through the process of applying to local and/or international colleges. She will then find further help to navigate the financial aspect of this process, identify target schools and courses, and explore career opportunities that align with her deep interests. After graduation, Uncle Glints will continue to nudge her on the right path as she embarks on her search for her first job and beyond.

What makes Glints’s approach outstanding is that it’s not just a one-time resource for students, but a lifelong career coach and professional agent, guiding an individual through every step of their professional journey. By providing comprehensive, personalised support from a young age, this imagined Uncle Glints is helping ensure that students make the most of their talents and reach their full potential.

The conventional approach of building long-term relationships with customers has been deemed economically unfeasible, as the system is often too costly with human labour and coordination to maintain.

Also Read: How AI and automation can shape the future of farms

However, advancements in technology, specifically in the areas of storage, computation, and especially AI, have greatly reduced these costs. This means that companies more than cover the expenses of acquiring and retaining these early customers. This presents a huge opportunity for Glints in Southeast Asia, where there are 100 million young people in need of career development and recruitment services. By providing these services, Glints is able to position itself as the primary lifelong talent agent for these individuals.

Making friends with lots of people

In general, this strategy is a deeper and more specialised version of Google’s “subconscious strategy” —make friends with lots of people by helping them navigate the internet and show them things to buy. And, of course, this being an unconscious strategy, Google would now and then do things that cause distrust and upset in their user base.

If you were to make the “Google strategy” your conscious strategy, your company would then decide never to violate the trust of your friends/user base. You will constantly be demonstrating trustworthiness, dependability, reliability, domain wisdom, and even caring to each individual in your user base. (In fact, you would probably find a term other than “user base” to refer to them!)

Occasionally, they will need a service which you can monetise, and when they do, they will be happier to give you, their trustworthy friend, that business.

AI as a change agent for customer relationships

The shift towards building relationships with customers through automation represents a significant change in how businesses will operate, with the potential to improve efficiency and customer service greatly.

There’s no denying that the power of technology has grown significantly in function and capability over the past decade. Humans have had to adapt their own behaviours in order to best leverage the technology, ranging from Excel workshops to employee onboarding training. And, now, the future is in enabling technology to adapt to us.

This generational shift towards user-friendliness will lead towards a more seamless integration of technology into our daily lives, allowing us to use it in ways that were once unimaginable. This is also really the driving force behind entrepreneurs looking to focus on building the next generation of startups in the fields of generative AI, no-code, and machine learning.

The generative AI space alone has seen the emergence of over 450 startups, which have collectively raised over US$12 billion in funding from venture capitalists, and this is only just the beginning.

The simple truth is this — humans collectively aren’t often great at realising our ideals in our relationships. We aren’t great at being trustworthy, dependable, reliable, consistent, supportive, transparent, considerate, thoughtful, and caring. We are not good at living up to what we say we believe in.

In business, this results in, for example, us measuring lifetime value over only one or two years, if we are fortunate, instead of over a lifetime! Even the most earnest CEOs with an intent to stay focused on customer relationships risk faltering when they scale and hire large numbers of people to service customers.

Assuming machines can communicate as humans can, then the most consistent way to implement our values as founders is to have our digital systems reflect the values directly to the customer. Perhaps, in the long run, this might prove what’s needed to improve our behaviour with each other by us modelling how our well-behaved machines interact with us.

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