The term “artificial intelligence” (AI) was first coined in 1956, but it is only recently that the technology has become more available thanks to new hardware, datapoints, and accessible software solutions. Natural language processing (NLP) and predictive algorithms are already inside billions of devices in our pockets, homes, cars, and workplaces. Algorithms power the experiences and content we digest on a daily basis.

In China, IBM created a project called Green Horizon, which uses AI to predict how bad pollution will be in Beijing up to 72 hours in advance. The solution employs adaptive machine learning to determine the best combination of models and data sources to use. Green Horizon’s creators hope they can extend accuracy to 10-day forecasts. Furthermore, this project’s capabilities are expanding to include pollutant source tracking, what-if scenario analysis, and decision support on emission reduction actions. The system could eventually drive remedies to resolve unacceptable pollution levels such as shutting down certain factories and temporarily restricting drivers on the road. On the mobile front, AI is already impacting how marketers and content creators do their jobs.

AI Now, Near, and Next

There are three evolutionary steps predicted for AI: now, near, and next.

Now, as in today, we are in an era of narrow AI (NAI). While there are some interesting early use cases, the current field of NAI is about facilitating repetitive tasks by learning and analyzing patterns in data to achieve a set outcome. It can—and should—be trained, much like a pet needs training. Therefore, as AI has not matured fully, like mobile has—it is still a work in progress and should be applied in a targeted way to solve a specific identified problem.

Near is artificial general intelligence (AGI), which has not yet been developed and is a state of AI that is defined by the Centre for Public Impact as being “capable of performing all intellectual tasks that a human brain can.” This includes reasoning, learning, and problem-solving in complex and changing environments.

Next is artificial superintelligence (ASI), a hypothetical stage in AI and human evolution wherein AI “surpasses human intellect and abilities in nearly all areas,” as defined by the Centre for Public Impact. This is beyond human potential.

AI is a great example of an exponential technology: In the coming years, there will be an exponential change in computer performance, as we have seen via Moore’s Law.

In the attention economy that we live in, every person and every brand is a publisher and has a near-zero cost of publishing around the world. That makes things very interesting, but also from a marketing and technology point of view, it makes things more complex. AI, even in its limited now form, can help.

To be a great global marketer, you have to embrace change, thrive on it, and be a sponge to absorb what’s new. It is equally important to embrace the things that don’t change. For example, customers like to look good in front of their peers, people make decisions using their left and right brain, trust is hard won and easily lost, and there are still 24 hours in the day. I don’t see these things changing due to blockchain, natural language processing, voice, or bots. These new technologies may enable new opportunities, but the basics remain the same.

Cultural nuance is another matter—one that changes in nearly every region. The way someone goes about mobile banking, or the degree to which content will appeal to an audience, will differ greatly depending on where in the world you are. An Indian farmer is not going to behave the same on mobile as a coder from San Francisco or an Australian trucker. Data and AI can create a shortcut to a better mobile experience for all.

Content and AI

We consume content voraciously, but we are living in a time of peak media, whereby people cannot physically spend any more time on their phones (and other channels) consuming content than they are doing today. The smartphone is the remote control for life, thanks to the range of tools at our disposal.

Algorithms and attention dictate success, which makes the world complex: right language, right wording, right place, right format, right time, right influencer, right seeding, right media, right message, right tracking, right landing page, right payment flow, right delivery firm, right notification vendor—right everything. So many variables, so little time.

In a few years, achieving perfection without leveraging technology such as AI is going to be like trying to hit a moving needle in a haystack with a bow and arrow, while wearing a blindfold. Local media campaigns often have thousands of different messages and formats. Global or regional coordinated media plays may have tens of thousands of variants. It is no longer sensible to continue to manage the bidding, targeting, and message optimization of a campaign using old technology.

Dynamic Personalization

Mobile is our most personal channel, and AI can help you use it to its utmost potential. Predictive or real-time segmentation can optimize the content on your website for customers—this means they get a more personal experience, which increases the chances of them moving down the funnel. So the second time they visit, they are served a tailored offer dynamically, and we track and test this using AI to get better over time. Leading CMS vendors around the world now offer this out of the box.

AI in marketing, when used well, can help save money—or even make it. Additionally, AI is great at saving time for marketers. For example, Qualcomm has created technology using AI to visually catalog images by automatically detecting the content and then adding metadata to the system, so that your content is better inventoried and labeled. A mundane task is done in minutes. 

What became clear to me in researching the state of AI around the world is that it is still a work in progress. The technology is not quite plug-and-play ready, and the people in charge are still not sure what they need AI for—they just know they need it for something. The good news is that accessing AI tech has become much more affordable, and companies are able to experiment. In the coming years, AI will go beyond delivering the right ad to your phone and even beyond solving problems like the air pollution in China. It will be exciting to see how AI will change the world.