As IoT branches out over the next few years, transforming the way consumers live, work, and think, we will enter the age of ubiquitous computing. By 2025, there will be more than 100 billion connected devices – that’s 14 for every person on the planet – generating a revenue of almost $10 trillion.

The scale of data creation in this environment is too vast to imagine. But there’s no escaping data, and finding new ways to analyze and harness all this information will be just as critical as it is challenging. Enter artificial intelligence: Our key to unlocking never-before-seen opportunities in data and spending less time driving these insights into action. 

During the mobile era, devices became a distraction. As devices multiply going forward, AI will ensure they don’t continue to add distraction and friction, and instead add value. Devices will become so pervasive that they will essentially bring us full-circle to when the world was unplugged. This is the new age of ubiquitous IT – or AI 2.0 – in which AI will facilitate a human-focused world.

In this new world, everything operates at peak efficiency. Data is easier to read, humans skim over previously manual tasks, and organizations are aligned across business units. This reality will bring unprecedented opportunities to marketers, allowing them to capitalize on industry advancements and expand into new markets while focusing more manpower on go-to-market strategies. Marketing teams will no longer be wrestling with vast and varied streams of customer data and splitting ownership of the customer experience with other teams—they’ll instead be able to find meaningful stories in data and automate the delivery of personalized, frictionless CX. If they don’t, they’ll be left behind.

The lead up to this new age of digital will involve learning as much as we can about what to expect and conditioning ourselves for the change. First, we should ensure we’re taking full advantage of the opportunities AI offers today.

The Current State Of AI

Artificial intelligence powers a variety of technologies and tools, which, internally at least, are designed to mine vast amounts of unstructured data and improve productivity. Technologies such as language generation, virtual agents, natural language processing, machine learning, speech recognition, and sentiment analyzers are diverse in their applications and benefit first movers across all industries.

As they expand – either entering new markets or adding new products to existing markets –marketers are testing which of these technologies enable faster and less costly time-to-market. Not only do marketers need to keep up with the incredible speed of product development, but they need a cheaper way to access riskier markets to justify the investment of expansion. Added to that, marketers need to learn how these technologies will provide global customers with the most personalized experience possible.

Customer Journey Mapping

Every touch point from product to marketing to customer care constitutes an opportunity to interact with a customer, CX being the totality of these interactions. Without the ability to define the buyer’s journey holistically across products and distribution channels, we can’t refine these interactions and build brand loyalty.

Using machine learning, however, we can process large volumes of heterogeneous data across channels in real-time. This provides context unknown to us a few years ago: buying habits, social sentiments, goals, emotions, and locations of customers, among other identifiers. In marketing, a business function with immediate impact on CX, we’re uniquely positioned to achieve cross-functional visibility into experiences and address any inconsistencies – as long as we have the technology.

The Result: Personalized Experiences

Demand for personalization has gone mainstream. Equipped with deep knowledge of our customers’ habits, needs, and preferences, we can use AI to predict future behaviors and feed these predictions into more personalized experiences. This results in delivering the right content, across channels, to the right consumer, at the right time.

Another important application of machine learning is to segment customers right down to the individual. Predictive analytics can streamline digital advertising through real-time bidding and unveils customer sentiment before a purchase, informing more targeted content. Then there’s audio voice control, the new gateway to all digital applications. Consumers across the globe are adopting intelligent personal assistants like Siri and Cortana (including those without visual support, like Alexa and Google Home) at rapid rates because they are efficient, user-friendly, and secure – everything a customer wants and that AI can provide. The next step will be getting this technology to work flawlessly and investing in next-gen voice interfaces to create a more human experience.

In a 2017 study, PwC asked decision makers: “What AI-powered solutions do you imagine having the largest impact on your business?” The results show the multitude of ways companies are already vying for customers’ attention:

As the report concludes, “artificial intelligence will be the business advantage of the future.” So what does the future look like?

The Next Generation Of Tech

To organizations increasing their global footprint in competitive environments, AI innovations bring exciting possibilities. In the near future, virtual reality could breathe new life into interactive content or enhance product testing. Another initiative that recently caught my eye is Persado, a cloud AI platform that helps marketers optimize content. Collecting and understanding the huge volumes of data points available to us is a challenge, and for the human brain alone, it’s impossible. But since data drives better performance, it makes sense for machine intelligence to use this data to improve traditionally human tasks (copywriting, in Persado’s case).

Thinking about AI from a human-centered standpoint, marketing needs to improve the quality of data we feed through these technologies for increasingly actionable output. Resource optimization is also the next big step. Assigning the right projects to the right people to create the right content can be tricky in the creative space, but machine learning can tell us which team member has the skills to carry out a task most efficiently – not only with less supervision from other humans, but with support from machine learning technology itself.

The Next Generation Of Marketers

At this year’s Global Innovation Symposium, we addressed the elephant in the room. Does AI play a benign role in our work and only augment what we do, or will AI technologies end up replacing white collar jobs entirely?

Every big innovation brings difficult changes. AI hasn’t necessarily driven people out of their organizations – in many cases, these advancements have pushed marketers into new functions. Yes, copywriters may need to reshape their role around the automation AI now provides. But AI allows us to do more, faster, creating new jobs as companies access markets they’d never have been able to previously. More importantly, as we extract increased amounts of insights from data, we need the resources to figure out what to do with all this information. There’s still a lot of room for repurposing data as jobs change, so if we want to hold onto our jobs, we’ll need to think outside the box, consider new ways to apply data analytics, and equip ourselves with the necessary skills.

How To Plan For An AI-Centric World

With the above in mind, I see marketing zeroing in on two short-term applications of AI: first, predictive analytics to drive behaviors-based insights, and second, using these insights to automate content publishing. We’re still in the hypothesis stage for both capabilities and will need to work with our vendors to understand how to leverage them on a global scale.

In the long term, we need new skills to roll with the changes. Successful organizations don’t need to hire new marketers – they already have the talent. Nevertheless, teams should stay alert to new opportunities and train themselves on making the most of them. This next generation of marketers will need to know:

  • The language of data. Data-driven companies conduct A/B testing constantly, but nobody will listen to ideas for product improvements without concrete data to prove customers’ needs. Marketing teams need to be able to communicate these findings across organizational levels.
  • The skill of identifying opportunity. More information is created in a single day than we could possibly absorb in a lifetime – some of it relevant to us, but most of it not yet apparent. Making better sense of data through AI will clear the way for big-picture focus and identifying new opportunities for growth.
  • The skill of developing new skills. Marketing teams receive new types of projects (accompanied by new types of data) all the time. While seeking to identify opportunities, even with new streamlined, AI-powered workflows, we still have to monitor content quality and deliver in short periods of time.

In AI 2.0, we’ll see a shift from manual guesswork to judgment and decision making when pinpointing opportunities to globalize. Marketers then have more bandwidth to focus on what they’re good at – better understanding the buyer – and will feel less pressure to perfect customer experiences in increasingly demanding markets. Will AI take over? Yes. But as marketers, we’re used to embracing drastic change, however reluctantly in the beginning. In order to grow, it’s our job to adapt.

 

For more information, view the panel or keynote sessions from the Global Innovation Symposium, or download the whitepaper 5 Ways Artificial Intelligence and Machine Learning Will Transform Your Go-To-Market Strategy.