With artificial intelligence (AI) deepening impact on the digital landscape, there is a general concern about marketer’s redundancy. To boost their marketing performance, companies are investing heavily in AI without actually considering the full implications.
Marketing involves three approaches towards the audience – connection, attention and trust.
Turning attention into a promise and a promise into a brand that matters.
AI in marketing is the collection of metadata to enable marketers to train data in the algorithms to make better-informed decisions. It’s actually about smart algorithms helping businesses to leverage the tasks and not replacing the human roles. When it comes to making nonlinear connection points and metaphorical contexts, humans are still far better. Also, computers are not yet good at questioning. For solving critical problems, it’s important to have thought-provoking queries and have philosophical perspectives. Thankfully, AI is not, however, designed to summarise contextual analysis and homologous (human analogy) ideas. As of now, the technology tries to make the complete task in abstract form, especially when it comes to repetitive and mundane work.
Top 5 Key Takeaways for Marketers About AI:
AI is all set to transform the marketing process, but not the way marketers are assuming it. One of the most significant assumptions about AI is that it could manage universal business solutions. With AI still in its infancy, there are many things to consider and get right about the technology, including:
1. Misconceptions About AI in Marketing
You have apps on your smartphone such as Netflix, Spotify and even Google Maps. These apps are based on AI that uses the metadata to try and predict your behaviour, i.e. the content or genre you like the most or would buy. Eventually, you are the one to make the purchase decision. The common misconception here is that AI’s effective decision making would take over human capabilities soon.
Many companies have started investing heavily in AI in the hope of leveraging sales and marketing. However, realistically speaking, they don’t have a mainstream implementation in marketing or proof that it works; instead, there are roadmaps for the future set of strategies.
This is where marketers can figure out what AI is all about at present. They need to proactively find smarter ways to reduce the friction on the consumer end and figure out more flexible ways of using intelligence.
2. Will AI Take Away Marketing Jobs?
This question doesn’t apply to the marketing jobs alone. AI has influenced nearly all the fields but also created controversial anticipation for future professions. As technology continues to evolve, AI is intended to augment our abilities and knowledge. What it is meant to do is take the manual, time-intensive and data-driven tasks and automate them. In turn, this allows marketers to spend more time being creative and strategic. Marketers make strategies, not for machines, but humans. So it’s important to share the emotions and implications of the actions.
In fact, as per Jeff Bezos, artificial intelligence will improve the quality of jobs.
“Humans like to do things, and we like to be productive, and we will figure out things to do, and we will use these tools to make ourselves more powerful,” he said. “What I predict is that jobs will get more engaging, b,ecause, you have to remember, a lot of the jobs today are quite routine.”
This is a conversion that marketers need not worry about. What is necessary is to get in critical analysis and engage in more humane aspects of marketing which connects the audiences, and that is hard to be replicated by machines.
3. Ethical Issues with AI in Marketing
The ecosystem equipped within AI is not just about marketing and sales but personalised concerns as well. In the competent global market, there is a race to build a smarter solution. To be ahead in the game of advancement, businesses are pushing themselves hard.
AI predictions are based on a massive amount of data. Google collects data from many data points from our smartphone, such as read emails, facial recognition via camera, map search data, and much more. AI-based Google Assistant remembers your voice search results on news, local weather or stocks and reminds you later based on the data it has collected.
When it comes to making accurate predictions, AI requires all the personalised data at the cost of your privacy. As a consumer, you might be amused with Google Maps, which uses powerful machine learning algorithms that can remember where you usually spend your weekdays and show you the best possible way to navigate there.
However, by giving up on privacy for convenience, we are making room for ethical concerns. Moreover, for any brand looking for AI solutions in marketing, sharing strategic information, even unknowingly, might make the business vulnerable to external threats.
4. Human-dependent AI, Not Just AI
Currently, many companies implementing AI keep most of the information under wraps. The secretive nature of this data is because most AI technology is driven manually. While we applaud the ability of intelligent assistants like Alexa and Siri to help us when we ask for it, what we don’t realise is that there are humans behind the technology using it to mine data we feed into such assistants through regular usage. Amazon has already launched an open-source eco-system for developing a better version of Alexa. However, the biggest concern for marketers is that the features within the ecosystem such as speech recognition, conversational AI, programmed advertising, ad targeting, and its native search engine only help the businesses, instead of focusing on customer benefits.
5. Understanding the Limitations
Human evolution took thousands of years developing unique perceptions and cognitive skills. For AI, to perceive the world in similar ways, it needs to think like us, not just act like us. However, since the dawn of AI, we directed the technology as we did with information technology. We have barely excelled in enabling it to think like a human. Therefore, there’s a need to focus more on developing the interactive design. AI must learn how humans conceptualise the world.
Similar to an intelligent newborn, AI processes data by reception, interpretation, and learning. You might feed the machine with all the data you have, but it’s yet unable to understand how the world works.
For now, AI for marketers acts as a companion by their shoulders. It can work on customers’ pattern recognition and help the marketers to build strategies. The dream of an absolute independent AI to communicate like humans and drive successful marketing is miles away from reality.