Artificial Intelligence (AI) may not have reached its full potential in terms of market saturation, utilization, capability or full benefit but it is well on its way. Investment into AI continues to grow with businesses anticipating wider-scale adoption of the technology in the near future. Indeed, in a recent report by eMarketer – Artificial Intelligence Roundup – figures from Gartner anticipate that investment in AI will reach $6.03 billion in 2018, rising to nearly $29 billion by 2021.

We stand on the brink of an age where chatbots, machine learning and natural language processing are commonplace, albeit that adoption is not quite there yet and many marketers (34% according to the aforementioned report) feel unprepared for the inevitable mass uptake. So what does the ever-growing presence of AI mean for mobile messaging, apps and phones? And how will our uncertain marketers and advertisers learn to grasp the opportunity that this technology offers in terms of better understanding their target customer?

As we all know AI provides systems with the ability to understand, learn, predict, adapt, and act autonomously. It’s not brand new technology as we have been talking about it for some time, as well as utilizing its capabilities in AI assistants such as Alexa and Watson, but there is still an element of the unknown around it – especially for the end consumer.

From a user perspective, and bearing in mind the many recent high profile cases of data leaks and breaches of trust, there is still an element of uncertainly driven by a lack of understanding and control over how their data is used by AI. How well would we want a machine to know about what we are interested in, and our likes and dislikes? When does AI monetization and personalization go from being cool to creepy; suggesting points of interest or relevant content which we are yet to offer up our data on? And will it be different for our millennial generation and those to come afterwards who were weaned on the web?

The fact remains that once we understand that AI searches data anonymously, that it looks at trends and patterns in order to focus in on preferences, and that is can be properly monitored and regulated, individuals may start to look at it differently. Why wouldn’t you want a technology in place that could learn, adapt and predict what you might be interested in and serve you content in a highly targeted way? No more annoying online ads for things you have no interest in, just relevant content based on your profile, interests and activity.

AI has a significant role to play in the future of monetized and personalized messaging, apps and phones, alongside a much needed move to give mobile users greater control over their preferences and what type of content they want to receive. Messaging, for example, could provide a ready-made home for AI, enabling organizations to market more effective to a wider community based on learnt behavior, as well as opt-ins in line with data capture legislation and regulations. The ability to deliver extremely targeted messaging campaigns with the additional layer of AI capability added on is an attractive proposition for many businesses and organizations.

In Cloudbanter’s own messaging, apps and phones monetization and personalization technology, which inserts banner ads at the bottom of the screen, AI will be able to learn from the habits, interactions and conversations of the user, and alongside their pre-determined profile choices and preferences, deliver highly relevant, provide contextual searches, lifestyle advertising and content directly onto their screen. It will also offer the capability to sort conversations and communications into categories and decide which conversations and communications are more important to the user. In today’s busy and data-driven world, AI within messaging has the potential to drive a better and more time efficient user experience. In addition, Cloudbanter is adding conversational UI/UX, additional AI features, chatbots, AR/VR visualization and more capabilities provide increased user effectiveness and communications across the messaging, apps and phones experience.

To be successful, it’s vital that this technology feels normal. What do we mean by this? Namely that there cannot be any concerns from the user, that data is being used inappropriately or that AI is using any other source than the user’s in-app habits and activity to select relevant content. It is also important that users feel that they are getting something in return for allowing advertisers and content providers to access them in this way. Again, in Cloudbanter messaging, apps and phones monetization and personalization technology, we’ve included a My Rewards feature which enables users to claim a range of incentives using a points based scheme. These include cash back, SMS, airtime or data allowances for using the app and accepting advertising and content. What’s clear is that once trust is established, there are huge benefits to be gained from utilizing AI within messaging, apps and phones and making it work for the consumer.

In order to realise the full benefits of AI in mobile messaging, apps and phones we need to trust it, and to accept that it has the potential to deliver significant benefits to our user experience. This combined with an application that rewards users for their loyalty and for accepting advertising and content that is relevant and targeted and you have a solution that drives revenue and customer loyalty for mobile operators, as well as delivering a new and exciting AI-powered experience for consumers including value added services and financial incentives.

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