Updated: January 8, 2020

Change is the only constant, and the rate of change is constantly accelerating.

Perhaps the main driver of change in today’s business environment is rapidly emerging and converging exponential technologies, such as AI, blockchain, and quantum computing. And though the capabilities of AI are often overhyped, it may be the most transformative technology of all, driving change through every organization in every industry. 

At the individual level, AI is rapidly transforming the professional lives of every sales and marketing professional.  How big is the impact of AI on the future of work?

  • Global spending on AI technology is expected to rise from $6 Billion in 2018 to nearly $29 Billion in 2021, according to Gartner group.
  • The global economy will grow by $16 Trillion by 2030 because of advancements AI, according to the World Economic Forum.
  • AI milestones seem to be arriving well ahead of schedule. AI technology was supposed to surpass humans at the game of Go in 2027. That already happened in 2015. The same research estimates AI could replace all human workers by the year 2141.

Great outlook for AI. What about humans? 

That question has prompted a lively debate. Are we facing a grim future where millions of humans are automated out of their jobs? Or is the AI future one where workers are freed from the drudgery of repetitive manual tasks to be more creative and experience a better quality of life? 

Whatever the case, today’s business news is filled with stories of how quickly AI is encroaching on formerly human domains. If you’re in sales and marketing, the AI stakes couldn’t be much larger. According to McKinsey & Company, AI will unlock the most value in marketing and sales – between $1.4 Trillion and $2.6 Trillion.

AI marketing trends for 2020 and beyond


AI and data are a dynamic duo

Many organizations following the exponential growth of AI and data analytics are inspired by the potential combinations of these powerful technologies, but not sure how to harness them to support their own strategic objectives. The remarkable volumes of data we generate every day provide fuel for AI—and all that data becomes more valuable as we learn new ways to extract its knowledge and insights. 

Most digital marketers understand that advanced AI capabilities enable better and faster operations, customer experiences, and product development. These advancements attract new users who provide still more data to improve operations, customer experiences, and products. If yours is an AI-first organization, it’s likely you’ll have some opportunities to apply those capabilities to strengthen marketing and sales.This continuous cycle of improvement, often called the flywheel model, is what enables today’s AI pioneers and tech titans to widen their lead over late-adopting competitors. 

My colleague Nick Davis explains the advantages of developing more sophisticated data analytics with the continuum below. As the predictive power of data analytics rises, so does our ability to make sense of the ever-growing massive datasets at our disposal.  

Personalization and machine learning

Personalization has been a challenge since the dawn of marketing. It seems counterintuitive, but technology really can help us connect to humans in more relevant ways. Machine learning (a subset of AI — see below) is enabling us to go beyond segmentation and targeting to personalize content down to the individual level. This level of personalization includes dynamic changes to images, offers and creative copy, driven by individual user preferences. . 

AI is enabling leading organizations to go far beyond traditional segment-based segmentation. Netflix is one such master of machine learning. It’s vaunted algorithm is said to serve up 80% of the video content its 100+ million subscribers consume. Similarly, Google’s responsive search ads use machine learning to continually tests various combinations of headlines and description lines to help you deliver more relevant ads and optimize performance. Google claims advertisers using its machine learning to test multiple creatives are seeing up to 15% lift in ad clicks. 

Some marketers call these advanced practices hyper-personalization, and the term individualization also is being used to describe the (formerly impossible) ideal of one-to-one marketing at scale. AI and machine learning may soon deliver on the age-old promise of putting the right message in front of the right people at the right time — every time. 

AI-powered marketing videos are here

Video content continues to rise and is used by nearly 90% of online marketers. People watch over 1 billion hours of video on YouTube every day, and they are tuning in for help making purchases large and small. Not surprisingly, more marketers are leveraging the power of video to drive traffic, engagement, and conversions for both B2C and B2B applications. You would be hard-pressed to find a major brand that does not make extensive use of video to increase engagement and increase social sharing. 

AI also helps to simplify the process of creating and distributing marketing videos. Tools like Lumen5, Hypercube, and Adobe Premiere enable non-technical marketers to create effective explainer and product videos that are ideal for social media sharing. At the higher end of the food chain, companies like BlueRush are providing more dynamic, personalized, and interactive video platforms for deeper engagement. How’s that work? The image below shows a video that was automatically generated when a potential homebuyer named Richard entered his information into an online mortgage calculator. 

Traditional mortgage calculators simply display estimated payments and terms. In this case, the information from the calculator is used to generate a personalized short video explaining Richard’s mortgage quote, along with a personal message from a loan officer. 

A link to the video is sent directly to homebuyers via text or email, while the sponsoring loan officer receives an alert to follow up. It’s likely that we’ll see more use cases of on-the-fly video personalization in 2020. 

Search continues to get smarter 

Early on, Google was not great at determining search intent. Users often had to make several attempts, sifting through irrelevant results and rephrasing their queries in an attempt to let the search engine know what they wanted. Today’s Google knows where you are, what you want, and that you want it fast, no matter what device you happen to be using — and it usually serves up the relevant content you expect. 

Google recently rolled out a new AI-powered search algorithm called BERT. It’s another step toward a more natural-language search interface, which makes sense as more than 50% of all internet searches are expected to be voice searches in 2020

While there is currently no definitive guide for marketers who want to serve up BERT-friendly content — BERT is shown below refusing to divulge the technical details of his eponymous machine learning algorithm — marketers will do well to write in a more conversational tone, quit obsessing over keywords, and above all, creating high-quality content that matches search intent. Search engines, led by Google, are getting better at understanding user questions, and successful content marketers will get better at providing the answer to those questions. 


Pixabay image by Cedric Yong

Evolving customer journeys

With increasingly sophisticated analytics tools at our disposal, our ability to analyze and track revenue attribution to campaigns is increasing. Google’s data-driven attribution model uses advanced machine learning to more accurately distribute credit to all ad clicks that led to a conversion, and it’s available to eligible advertisers for free. Attribution modeling is not new, but many marketers still use last-click attribution (the last action in the conversion path receives 100% of the “credit”) because it’s difficult to understand which customer touchpoints contributed most to conversions. Machine learning tools like those used by Google make it simpler to track and optimize for conversion at scale. 


Are sales and marketing careers in danger?

If you’re a marketer in a data-driven industry like retail, manufacturing, travel or ecommerce, you can expect a double dose of transformation. Industries driven by the analysis and processing of large datasets stand to gain the most, and change the most, from the use of AI.
AI is the leading technology where marketers expect the most growth over the next two years. Marketers anticipate AI use will grow by 53% – a much higher rate than any other tech type. – Salesforce
And it’s clear that AI is quickly becoming a key advantage for some of the world’s most innovative organizations. Companies like Amazon, Apple, Facebook, Google and Microsoft, Netflix and Salesforce are all heavily invested in AI and compete aggressively for talent. High-performing companies are more than twice as likely to use AI than low-performing companies, according to Salesforce. Anyone looking for insights on the future of AI should watch how these companies leverage the technology internally and what types of AI-powered products and services become publicly available.
So, transformation is under way and the rate of change is increasing. But what skills should sales and marketing leaders develop to join the innovators and avoid disruption? 
You will have your career disrupted. So you have to either proactively turn the impending change into something more enjoyable and fulfilling, or you sit in fear of the inevitable day when the hatchet comes your way… – Jay Samit
While it’s impossible to predict exactly which sales and marketing roles might be eliminated, it’s safe to assume that all roles will change. Here are some hard and soft skills that can be learned to minimize the impact: 

Commit to lifelong learning

In sales and marketing, a good start is to read up and absorb everything you can about AI. There are a number of blogs that cover AI developments from a sales and marketing perspective, including:  If you kicked ass in calculus or have a technological bent, check out Google’s free Introduction to Deep Learning course and the same Machine Learning Crash Course they provide to their own engineers. Sales and marketing pros don’t necessarily need to become Python experts, but it couldn’t hurt.   

Stay AI alert

One of the most powerful free tools available for sales and marketing is Google Alerts. These useful alerts can be set up in minutes and can save you hours by sending curated content straight to your inbox or RSS feed. For example, say you are a content marketer in financial services and you want to keep up with what’s going on. Simply visit the Google Alerts page and enter the topic you want to follow. In the settings, you can choose options like how often you’ll receive alerts and which sources you prefer. Some examples might be: 
  • “content marketing” AND AI
  • FinTech AND AI
  • “AI news” San Francisco
  • “your brand” + AI
  • “competing brand” + AI
Setting up alerts will enable you to see real-world use cases and how competitors and related industries are using AI.

Speak the language

It’s important to be fluent in AI terminology, for the ability to separate business value from buzzwords, and to understand AI projects that use a combination of technologies.  AI terms are sometimes tossed around and puffed up in the service of sales and marketing. For example, the terms AI, machine learning and deep learning are often used interchangeably. But as you can see in the image below from Nvidia’s blog, both machine learning and deep learning are subsets under the AI umbrella. Marketing and sales pros should understand which types of AI are at work and what value they bring to their audience.

For example, machine learning is a breakthrough technology because it uses training algorithms to learn from large data sets, rather than being explicitly taught by humans. But without high-quality, complete and current datasets, there are no insights to be gained about your prospects, conversions and customer experiences. 

Other key areas for sales and marketing leaders to understand include chatbots, computer vision, natural language processing, and neural networks.

Artificial intelligence + your natural intelligence 

The best way to avoid being blindsided by the growth of artificial intelligence is to grow your natural intelligence. Become a lifelong learner on the subject of AI and related disciplines.

Recently, Google Research changed its name to Google AI to underscore its commitment to CEO Sundar Pichai’s promise to make Google an “AI-first” company. It’s a clear sign that Google’s innovation is now clearly focused around deep learning and machine learning. Amazon, Microsoft and IBM are following similar strategies of reinventing their companies around AI. 

Clearly, the world’s most innovative and successful organizations are leading the way on AI. Today’s most innovative sales and marketing teams may do well to learn from that data and take action. 

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