Your smartphone knows your wedding anniversary is coming up, and you have a chat with it about how you might celebrate the event. Based on its deep understanding of you and your spouse, the device suggests a romantic weekend in Paris. You agree.It knows from your photos and calendar that you got engaged at a small bistro in the 9th arrondissement, and from your travel history it knows you favour a boutique hotel near Parc Monceau and your preferred airline is Air France. It creates an itinerary and presents it to you for your approval.
After you’ve used your smartphone a few times to book trips, you trust the artificial intelligence (AI) that powers it so much that you authorise it to book everything — and to negotiate on your behalf — without even checking with you. Which leaves you time to get on with more important things, like deciding what to pack for your trip.
It may sound futuristic. But the truly AI-enabled smartphone could become reality within the next three to five years. In our broad definition, AI is a collective term for computer systems that can sense their environment, and, in response to their objectives, think, learn, and act. And in our view, smart devices, including the smartphone, will be the vehicle through which AI will have the greatest effect on the technology, media, and telecommunications (TMT) industry.
A quantum leap in capability for phone-like devices can’t come soon enough. Given advances in computing, the smartphone now feels increasingly dumb to most users.
To be sure, major manufacturers have added voice assistant capabilities and refined them. But, in general, the technology is still very brittle when it comes to understanding discourses or keeping track of an individual user’s transaction history.
In the coming years, the ubiquitous smartphones of today will be replaced by smarterphones.
Increasingly voice-activated and conversational, they will apply AI to anticipate human activity and support it autonomously.
The emergence of this new generation of devices will have profound and pervasive impacts for all players in the TMT value chain. Here are some of the main anticipated developments.
Users: Intimacy and productivity. AI will exploit ever more detailed data on individual behaviours and preferences to automate and assist what smartphone users do today and find ways to do things that were previously unimaginable. And our phones will do this with personality. People will experience greater intimacy and humanity in their digital experiences.
But developing AI as a human-friendly technology is going to be a big challenge. Using AI to help people actually make decisions and take actions — which we refer to as augmented intelligence — will create unprecedented alliances between humans and machines, with each learning and benefiting from the other.
Soon people will be able to select famous movie characters or even friends as the voices of their smartphones. Apps will understand our emotions by our speech or by seeing our faces, and will respond appropriately.
Automation of tasks and greater intimacy and personalisation will make it quicker and easier for consumers to search for, find, and choose what they want, saving them time. Productivity and work-leisure bandwidth will increase, with people freed up to pursue activities they’re really interested in.
Carriers: Evolving the smartphone. Echoing the trend seen in the satellite and cable industries, where nobody pays upfront to own the set-top boxes or rooftop satellite dishes, customers will likely migrate from owning devices, to leasing devices, to just paying for the service or experience through a single price that includes the equipment cost.
So, rather than collecting revenue primarily from device sales or usage, the carrier business model will also involve leveraging user data to create a new revenue source.
Carriers could become developers of a “digital twin” for each smartphone user. This digital representation of the individual — based on all their demographic, behavioural, and preference data — would negotiate with vendor sites (e.g., travel or hotel) to get the most cost-effective deals.
Consumers might have a choice between doing all the research and booking the cheapest flights themselves or using their digital twin to negotiate the best deal while paying a small commission on the total amount spent using the twin.
As a result, the effective price of the device or service will fall.
Crucially, the quality of the experience will not depend solely on the quality of the connection or the ease of contacting customer service, as is generally the case today.
As users’ dependency on their devices grows in tandem with devices’ functionality, the need for uninterrupted service, more bandwidth, and wider coverage will also grow.
Carriers will need to seek ways to become smarter in managing those devices by, for example, applying real-time data allocation adjustments. The question of whether carriers will be allowed to bill customers in innovative ways, such as surge pricing for data, is likely to be controversial.
Given the importance of personal data in realising the benefits of AI, concerns over security, privacy, and regulatory compliance could become barriers to AI innovation.
Other risks could include challenges related to device compatibility and consumers’ willingness to pay for more powerful devices and for connectivity over shorter cycles based on data or resource consumption.
Also, from a tax perspective, developed and developing nations will likely have differing views about how to allocate taxing rights and how to value data, intellectual property rights, and automated tools.
A possible lack of consensus between territories — and unilateral steps taken by territories to tax transactions — could increase the cost of doing business between source countries (where income is generated) and home countries (where these companies are based). — Strategy-Business.com