What is Old is New Again: Digital Transformations and the Lessons for AI

Since the mid-1990s, the world has experienced several digital transformations that have profoundly impacted society, marketing, and marketing research. These include the internet and email, search engines, social media, mobile technology, cloud computing, big data, and analytics, and, most recently, AI. In this article, I will focus on the internet and email, social media, and mobile, drawing parallels to our current experience with AI.

The intent here is to explore the parallels in concerns consumers and marketers have faced during the rise of the internet, email, social media, mobile, and now AI. As we navigate this new age of AI, there are valuable lessons from past digital transformations that can guide our approaches in marketing and marketing research today.

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My Personal Experiences

Internet and Email
As someone who worked in academic computing in the mid-1980s, I was an early user of email, primarily for communication between universities. At that time, sending an email required so much coding that a simple phone call might have been more efficient - but there was a certain thrill in using this groundbreaking new form of communication.

By the time I started my marketing research business in 1991, email use was becoming more widespread. However, I still remember the days of printing, binding, and physically mailing marketing research reports. Standing at the fax machine, sending pages one by one, and shipping bound hard copies of reports via FedEx was a painstakingly long process.

Between 1998 and 2000, while living in Australia with my family, email and the internet rapidly gained traction. By the time we returned to the U.S. in mid-2000, the business world had transformed. No more printing, faxing, or shipping - reports were sent via email, saving an enormous amount of time.

However, this newfound convenience brought concerns. Would the internet connection hold long enough to send important files? What if confidential information was sent to the wrong recipient? And would clients appreciate receiving reports in digital format when they were used to polished, hard copy presentations?

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Social Media
The rise of MySpace, Facebook, YouTube, and Twitter between 2004 and 2006 ushered in a new era of digital interaction. By the late 2000s, social media marketing was emerging, and as an active participant in local marketing organizations, I attended monthly events where social media was frequently discussed.

I recall the excitement as forward-thinking marketers discussed how to leverage these platforms for marketing. However, concerns quickly surfaced - concerns that are still relevant today: Did we want to live our lives out in public on the internet? What about privacy, oversharing, or potentially embarrassing posts or comments from friends and family? How much of our personal selves should we reveal to our professional networks? And did marketers need to personally use social media to engage effectively in social media marketing?

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Mobile
The 1990s and 2000s saw the introduction of various mobile phone brands, with the iPhone making its debut in 2007. Mobile apps and GPS tracking soon followed, fundamentally changing how we interacted with technology. I remember my early mobile phone heating up during calls - leaving me concerned about brain cancer! Despite the occasional discomfort, I appreciated the mobility and convenience when I had coverage.

But there were persistent concerns: cost, usability, battery life, privacy, and the intrusive nature of being constantly connected. These issues did not detract from the fact that mobile technology transformed communication, but they were challenges, nonetheless.

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AI
While AI has been with us for decades, it is only recently that it has become a dominant topic in consumer and marketing conversations. By now, everyone reading this is familiar with the concerns surrounding AI - ranging from job displacement to privacy and ethical considerations. What is fascinating is how many of the challenges we face with AI today parallel those we saw with the internet, email, social media, and mobile.

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Strong Parallels in Concerns Between These Four Major Digital Transformations

There are significant parallels between the concerns consumers and marketers have shared across these major digital transformations:

‍Consumers’ Concerns

• Privacy: Worries about how personal data is collected, used, and shared.
• Control: Fears of losing control over personal information or how technology affects daily life.
• Adaptation: The time and effort required to learn and adapt to new technologies.
• Trust: Skepticism regarding the reliability and fairness of these technologies — be it the internet’s connectivity, social media’s accuracy, or AI’s transparency.

Marketers’ Concerns

• Measuring Effectiveness: Challenges in tracking and proving the ROI of new technologies.
• Privacy and Ethics: Balancing the need for data with ethical considerations around consumer privacy.
• Control Over Brand Narrative: As social media and AI take hold; brands have less control over how they are perceived online.
• Cost of Adaptation: The expense of adopting and integrating new technologies into business strategies.

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Key Learnings from the Internet, Email, Social Media, and Mobile, That Apply to AI

As we enter the age of AI, there are several key lessons from past digital transformations that can help marketers and researchers address AI’s challenges:

• Transparency and Trust: Early internet and email use was plagued by mistrust around privacy and security. As with AI, rebuilding trust through transparency is essential.
• Balancing Personalization with Privacy: Social media platforms offered personalization but faced backlash over privacy concerns. AI must navigate this balance carefully.
• Adapting Quickly: The mobile revolution showed that early adopters of new technology thrive. Marketers must embrace AI swiftly to capitalize on its potential.
• Shifting Control: Social media shifted control over brand narratives to consumers. AI will further decentralize control, and brands must adapt to this reality.
• Measuring New Metrics: Just as marketers developed new KPIs for social media and mobile, they must now establish new ways to measure the effectiveness of AI-driven marketing.
• Investing in Education: Businesses that trained their teams in email marketing and mobile strategies succeeded. The same applies to AI—education is key.
• Experimentation and Agility: Social media showed that experimentation and real-time interactions were highly effective. AI offers similar opportunities for innovation.
• Proactively Addressing Ethical Concerns: Whether it was social media addiction or data privacy, ethical concerns must be addressed early. The same goes for AI to avoid potential backlash.

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The Role of Marketing Research in Addressing AI Concerns

Marketing research can play a pivotal role in mitigating AI adoption concerns. Researchers can:

• Gauge consumer sentiment around AI and shape strategies that build trust.
• Test and refine AI tools, ensuring they deliver value while addressing privacy and ethical issues.
• Develop new metrics to measure AI’s impact on customer engagement and business outcomes.
• Identify bias in AI systems, ensuring that AI models are fair and inclusive.

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Summary

As with the digital transformations of the past, AI brings both immense opportunities and significant challenges. Marketers and researchers must remain adaptable, proactive, and transparent in their approaches, ensuring that AI serves both businesses and consumers responsibly.

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Kirsty Nunez is the President and Chief Research Strategist at Q2 Insights a research and innovation consulting firm with international reach and offices in San Diego. Q2 Insights specializes in many areas of research and predictive analytics, and actively uses AI products to enhance the speed and quality of insights delivery while still leveraging human researcher expertise and experience.

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