How wisdom makes AI more effective in marketing

Warren Buffett, a towering figure in the financial world, voiced his concerns about artificial intelligence during his annual meeting in May. He compared AI to the development of nuclear weapons: 

“We let a genie out of the bottle when we developed nuclear weapons. AI is somewhat similar — it’s part way out of the bottle.” 

This underscores the potential risks and benefits that AI presents to society. However, contrary to Buffett’s cautious stance, some analysts argue the genie is already fully out of the bottle. 

Since early 2023, AI-related stocks outperformed U.S. and global stocks by 30%. This is reminiscent of the dot-com bubble of the 1990s, when tech stocks, particularly those promising internet innovations, soared in value long before proving their worth. Like then, today’s environment is rife with naysayers cautioning against over-optimism and advising investors to seek tangible returns or evidence of success.

Gartner developed the “hype cycle” to describe this phenomenon. It begins with an innovation, such as AI. Startups emerge and develop, leading to a peak of inflated expectations. During this, there are often more suppliers than users. Press coverage abounds, but successful use cases are scarce. This eventually leads to the trough of disillusionment, where companies that invested in the technology may see poor returns and limited success. 

Historically, it took three to five years for all this to occur, but evidence suggests these cycles are accelerating. If this trend continues, we might navigate through the trough of disillusionment by the end of 2025.

The hype cycle’s rapid pace is unsettling many companies and their marketing departments. Intuit announced the layoff of 1,800 workers, with their CEO attributing the move to preparations for the “AI revolution.” It’s reasonable to infer that many of those laid off were in marketing and customer service roles, where AI is handling many more tasks.

Today’s marketing tools are rich with AI capabilities, enabling marketers to develop and manage strategies, personalize customer messages, utilize chatbots for online inquiries, streamline opportunity management and perform just-in-time predictive analysis.

Up to 87% of marketers have used AI or experimented with AI tools, while 68% of marketers use AI in their daily work, a recent study by The Conference Board found. For context, ChatGPT, a key player in the AI revolution, was only released on November 30, 2022 — less than two years ago.

Despite AI’s powerful marketing tools, something crucial is often overlooked — the accumulated wisdom of experienced workers and established processes. Wisdom ensures AI tools are used effectively and ethically, a quality not easily replaced by technology.

Dig deeper: Why traditional marketing systems can’t keep up with AI and what to do about it

The role of wisdom in AI-driven marketing

Wisdom combines knowledge and intelligence. To appreciate its importance, we must first understand these components:

Knowledge

• The collection of facts, information and skills through education, reading and experience. While one can know without wisdom, wisdom cannot exist without knowledge.

Example: Mary Marketer, the marketing operations manager at ACE Corp. for five years, has deep knowledge of the company’s customers through trade show conversations, small business marketing classes and her work experience. However, this knowledge alone does not guarantee she will always use it in the company’s or customers’ best interests.

Intelligence

• Thinking logically, conceptualizing and abstracting from acquired information. It can be a natural trait or developed through learning and it is essential for applying knowledge effectively.

Example: John New Hire, a recent Stanford graduate with limited work experience, joins the marketing team excited to handle an upcoming product announcement. While his intelligence and fresh knowledge are valuable, he lacks Mary’s deep understanding of the company’s customers.

Wisdom

• Goes beyond knowledge and intelligence. It involves discernment and judgment, often gained through social interactions, mentoring and life experiences. Wisdom integrates virtue and insight, offering sage advice and enlightened guidance.

Example: Bob Guru, the Chief of Staff to the CMO at ACE, has been with the company since its early days and has a profound understanding of customer data and the marketing team. His extensive experience makes him the team’s sage, guiding strategy and ensuring effective communication.

Wisdom in action

Consider the ACE marketing team’s launch of a new AI-driven product. The product aims to enhance productivity but requires significant upgrades and retraining. John New Hire tasks an outside consultancy with categorizing customers into three groups based on their receptiveness to new technology:

• Those who always tend to buy the latest technology.
• Those who are skeptical of the latest.
• Those who drag their feet before deciding on a new product. 

John plans to communicate detailed product information to the first group, propose discounts for those who purchase early and promise side-by-side consulting support as the product is deployed to the customer. He recommends a standard press release announcement for the other two groups, inviting them to schedule appointments with a customer sales representative to review their options. 

Mary Marketer, however, questions the categorizations, noting that the AI algorithm failed to consider influential customers who could significantly impact other buyers. Having worked with customers via the Customer Council, Mary says all the groups should get detailed information about the product. However, she does not know how to argue against the 25% returns the AI consulting agency promises with the tactics John approved. 

Moreover, when she evaluated the groups customers were assigned to, she found several designations with which she disagreed. For example, her favorite, most influential customer was assigned to the third group because the volume of their purchases was small but steady. However, when this company bought the product, others followed. The AI algorithm did not take into consideration influence capabilities or customer longevity 

To navigate the potential pitfalls of AI in marketing, ACE’s team could take these crucial steps:

Exercise sound judgment through human oversight

Judgment is the ability to make decisions or arrive at sensible conclusions from data. Mary used her judgment from her years of experience to evaluate the algorithmic selections. 

All AI output should be evaluated before anyone acts on it. This oversight can be part of the company’s governance program or the marketing process. The corporate culture and the industry may dictate where this oversight is located and how it is configured.

Evaluate AI efficiency

Measure the productivity and effectiveness derived from AI tools. Intuit’s recent layoffs highlight the need to assess whether AI truly delivers on its efficiency promises, as rapid deployment often precedes a trough of disillusionment.

Ensure empathy and personalization

AI can personalize messages and predict customer preferences, but marketers must ensure the personalization is accurate, empathetic, persuasive and not invasive. Testing and refining messaging to ensure it resonates well with customers is crucial.

Apply fairness and balance bias

AI algorithms can produce misleading information. Understanding and correcting biases is essential to ensuring fair and accurate messaging and customer segmentation.

Provide transparency and build trust

Be open about how AI algorithms are designed and the data used. Transparency helps build consumer trust and ensures ethical AI practices. Continuous monitoring of AI models is necessary to maintain their effectiveness.

Dig deeper: AI in marketing: Examples to help your team today

3 steps for integrating wisdom into AI marketing

Incorporating wisdom into AI marketing strategies may seem challenging, but it can lead to more engaged marketers and better customer relationships. Here are some actionable steps:

1. Tell a compelling AI story

Use storytelling to explain AI applications to customers, enhancing their understanding and trust. For instance, ACE could inform customers why they are receiving specific communications based on AI analysis.

2. Create a feedback loop

Implement a feedback system to gather and analyze customer responses to AI-driven messages. Engage stakeholders and partners in this process to ensure comprehensive feedback and necessary adjustments.

3. Invest in training and development

Marketing teams need training to fully understand AI capabilities and ethical considerations. Sharing this wisdom can establish trust and demonstrate expertise.

The future of AI and wisdom in marketing 

Andrew Maynard, professor of Advanced Technology Transitions at Arizona State University, talked about these issues in his monthly newsletter.

“As a global society, we are at a scientific and technological tipping point in human history, where the futures we are creating — and how we are creating them — are departing in radical ways from past norms, trends and expectations. … These advanced technologies confound our conventional thinking on how they will benefit society. This represents an opportunity and a challenge to us. We will require new thinking, research, knowledge and insights, philosophies, perspectives, skills, jobs and organizational approaches.”

Blending wisdom with AI: A path to smarter marketing

Marketing organizations have an opportunity to become leaders in AI, fostering responsible practices and combining human wisdom with technological advancements. By prioritizing ethics and empathetic engagement, businesses can navigate the complexities of AI by creating a more responsible and effective marketing landscape.

Dig deeper: How brands like Klarna and Mars are using AI in marketing operations