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Have you ever been on the receiving end of AI content or interaction that didn’t work well?
You know the type: Emails written entirely by bot, with wording that sounds slightly (or mostly) off and a message that isn’t cohesive. I’ve even had the misfortune of attending webinars created entirely by ChatGPT.
Marketers want to stand out from the crowd and showcase their creativity and capabilities, and they want to do it quickly. And AI is a new and exciting way to do that.
But there is such a thing as too much AI.
The rise of generative AI has led to many companies’ debating the role of humans in marketing. Some are opting for a largely automated approach, whereas others are recognizing the value of the human touch.
Brands need to balance human and machine intelligence to create useful and meaningful interactions. Here are some ways to accomplish that.
1. Avoid the ‘uncanny valley’
Has a computer-generated character ever looked strange to you? Not necessarily bad or fake, but unintentionally creepy? That happens because of what roboticist Masahiro Mori called the uncanny valley.
An industrial robot is very unlike a human, so we don’t think of it as human. But when a robot closely emulates human characteristics, we notice the differences far more than the similarities, making the robot feel wrong and even unsettling.
The same holds true for AI conversations. Just because an email or LinkedIn message starts with “Hello” and a prospect’s name does not mean that it sounds original or authentic to a receiver.
The best way to avoid the uncanny valley in AI-generated content is to make it clear to people when they are interacting with a bot or its product. Set expectations properly by how you name the bot and how you set up the AI interaction. It should be clear to the human they aren’t interacting with another human. As the description of the uncanny valley explains, the more distinct a robot is from a human, the less likelihood someone will experience an unsettling interaction.
On the other side of your interactions is a real person with needs, questions, and emotions. Match your tactics—mostly AI- or mostly human-based interactions—to your target audience and consider what information and value you’re offering.
Don’t fall into the trap of using AI too broadly; you’ll miss your target audience completely.
2. Lead with conversations, but use AI for scale
People don’t want to be shuffled through an impersonal lead funnel. They enjoy controlling the direction of interaction with things that matter to them, and converting to sales only when they are ready.
Lead conversations are quickly replacing conventional lead generation. But hiring enough staff to have individual, early-stage conversations with every single prospect may be impractical.
AI is easily scalable, just like other modern enterprise software. By conversing with AI, large groups of people can acquire the initial information they want in a personalized, self-directed way. Potential customers win because they get quick answers, and you win because you are smarter about how you allocate your human resources.
Fully 40% of executives are looking to hybridize digital and physical customer experiences to enhance personalization, innovation, satisfaction, and inclusion, Deloitte found. Supplementing your staff with AI can help improve those areas and drive more fruitful engagement.
3. Leave the relationships to real people
Recent AI improvements have been remarkable: the quality and clarity of the content produced by AI can almost surpass that of human authors. Despite such advancements, some tasks are still best handled by humans, such as dealing with escalating customer objections or helping a contact prove a business case for new enterprise software.
AI cannot provide sound judgment, exercise original thought, or provide the satisfaction of connecting with another person.
For real depth, creativity, and subtlety, you need humans. Humans can express empathy and build trust for long-lasting relationships. When you allow AI to handle introductory conversations, the resulting reduction in the volume of work will help the complex cases be less of a burden to your team. Your AI database will continue to learn and grow with additional prompts, evolving the work needed by the team.
For example, when prospects begin asking detailed questions about your product or service or wants to escalate a topic, it is likely time to advance them from an AI to a human. Another signal to move them to the next step is if they start asking questions about custom implementations or anything that hasn’t previously been “taught” to the database. That means they are ready for a personalized conversation.
The AI-to-human pipeline can streamline your lead generation process. Lead automation requires keeping a potential customer’s attention from initial contact to sales conversion and collecting the right data to inform that process.
A well-trained AI model can help with data collection by inferring emotions and categorizing the results. That data can then be used to time further contact and guide Sales and Marketing on how to approach each prospect, personalizing the sales funnel so that potential customers do not feel like they are being pushed into a mold.
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When customers recognize you for your speed and level of personal care, you will know that you have found the best balance between AI and human talent.
Marketing is all about the customers, so measure your success by them. If you keep a singular focus on solving their problems, regardless of the technology or tactic, you will be successful.
More Resources on Generative AI in Marketing
Three Ways Generative AI Will Change B2B Marketing
