AI in Mobile – Driving Intelligent Experiences
There was a time when most everyone worked from offices and devices were designed to serve one specific purpose. Covid-19 changed the work environment for the majority of the world’s workforce in ways nobody imagined two years ago. The forced exodus from our office environments caused many to become more familiar with their mobile devices as they sought ways to productively connect with co-workers and be as effective as possible in their new work environments.
Historically devices, because of the limitations of technologies at the time, usually failed when they tried to serve multiple functions. To use an old-fashioned example Toaster ovens weren’t particularly good toasters or ovens. Things changed quickly as electronics became more miniaturized resulting in something most people at the time may not have appreciated when it was first introduced. The idea of a cell phone designed with built-in digital cameras. Suddenly you didn’t have to carry around a separate camera to capture moments and causing the world to go “selfie” crazy. Continued advancements in microprocessing, ubiquitous broadband cellular connectivity, and cloud-based data stores are leading to another great evolution as mobile devices are increasingly enabled with artificial intelligence.
Artificial intelligence (AI) on its own has grown exponentially to become mainstream enhancing, reshaping, even reinventing some customer experiences and business operations. And this movement toward AI is expanding quickly in mobile applications evidenced by the broad adoption of personal assistants like Siri and Alexa haves received broad adoption. There is a lot more to come as they continue to be adapted to serve tasks on the fly as you move through your day.
Picture this- You’re tied up in a meeting away from your desk and a zoom meeting invitation from an important client flashes a notification on your mobile device. Your digital mobile assistant knows from your many interactions that your tendency with this contact is to:
- Treat them as a high-priority contact so when meeting requests are received you immediately communicate a reply to the meeting request.
- The first step in communicating a proper response is to check for meeting conflicts.
- If there is no conflict an immediate meeting acceptance is triggered placing it on your schedule and sending confirmation to your contact.
- If there is a conflicting appointment alternative meeting times are identified matching the requested duration in the time zone appropriate for that contact.
- A message about the conflict matching the tone typical to your replies is created with alternative meeting times presented as part of the message.
- Based on your preferences the message is drafted and either automatically sent with immediate delivery or the draft is presented for your review then sent.
- During the meeting and without having to communicate with anyone your digital assistant has either drafted your meeting request-reply and sent it on your behalf or you have the response message drafted with alternative meeting time recommendations to be sent as soon as you’ve reviewed the drafted response.
Yes, while out of your office, behind the wheel of your car, while mid-flight, or disconnected while on holiday we’re moving from mobile technologies that can solve a task you initiate to mobile experiences intelligent enough to analyze your digital behaviors to assist you in executing workflows that reflect your pattern of behavior enabling leaps in personal productivity.
How is AI changing the app experience?
Most AI applications in mobile technologies are focused on specific individual tasks, they’ll analyze your writing patterns to suggest an auto-generated message, will review a calendar looking for appropriate alternative meeting times, etc. But as the scenario above suggests AI is moving beyond isolated tasks to integrate a collection of AI algorithms along with intelligent application integration to satisfy an entire process flow or series of tasks to satisfy a workflow that in its entirety resolves larger productivity and communication challenges. In the future, as businesses get more confident implementing AI in mobile technology to serve the needs of an increasingly mobile workforce, we’ll see a much broader and deeper application of AI to bring a paradigm shift in the app experience.
- Predicting User Behavior- AI is being used to interpret mobile user behavior and needs in real-time based on past interactions with the device and app. This data and information are then used to predict his future needs and requirements.
- Personalized, Prescriptive Experiences- We have taken giant steps in personalization as demonstrated by streaming services like Netflix knowing accurately assessing your preferences and recommending similar shows and movies. Applying what is understood from predictive algorithms will lead to greater availability of personalized, prescribed solutions. Like the example above, messages can be drafted that suit the communication style and meeting availability of the sender that also excludes meeting times that fall outside the recipient’s appropriate business hours. AI is being used in mobile apps to minimize overload of information, cut the clutter and simplify the user experience as per his needs and preferences.
- Building intimacy with the user- As mobile devices become personal assistants of users, there is a need to humanize the experience. Voice search or conversational AI is helping in humanizing the app experience. Advances in AI applications in apps will augment human capabilities to foster a stronger relationship between users and apps, with each learning and benefiting from the other. Soon we will have apps that respond to our emotions by interpreting our voices and faces and respond appropriately.
- Workflow Design – Just as important as the functional success of each AI element is understanding how to integrate them into a single workflow that serves the overall objective. This needs to take into account how the various data elements are ingested, stored, analyzed, and presented. And by “presented” we mean how is the analyzed result supposed to serve the objective. Algorithms could present visualized results to highlight insights often hidden in the data, but it can also be analyzed data sets available to feed other applications through ASP or other application interfaces. A collection of algorithms working in sequence can collectively satisfy the needs of a well-coordinated and comprehensive workflow solution.
All of these qualities when applied effectively in AI solutions make it easier to enhance mobile users’ experiences and productivity. As much as miniaturized electronics elevated mobile phones to multi-purpose mobile devices we can’t do without, AI technologies will elevate our productivity in whatever environment we may have to (or choose to) operate from in the future.
Qualetics is already assisting companies in planning for and harnessing AI. If you would be interested in a consultation about the opportunities for your business, please feel free to contact us here.
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