Lessons from Kodak’s Failure

How Qualitative Research Companies Can and Should Welcome AI

Kip Brown
Brand and Advertising Lead
October 9, 2024

Long before I became a qual researcher, I was an ad guy. In my 20s and 30s, I was part of the agency of record for what was then the dominant name in photography, Kodak. In that role, I helped the company build its film brand, specifically with professional photographers and photo-enthusiasts. I also had a secondary role developing ads that presented Kodak’s latest R&D activities to the scientific community.

In both roles, I gained a fairly unique understanding not only of Kodak’s marketing and business strategies but its technologies and innovations. Among those innovations: digital photography.

Not many may know this, but Kodak invented digital photography in the mid-1970s. They also tried to suppress it, at least, within their own company. In what they believed to be a strategic move of self-preservation, Kodak’s leadership viewed digital photography not as an opportunity but as a threat that could end up cannibalizing their profitable core film business. By the time Kodak realized its mistake and tried to embrace and commercialize digital, it was too late. The company had lost its dominant place in the market. The rest, as they say, is history.

Kodak was correct in identifying digital as a disruptive technology to the picture-taking business — much like AI has become a disruptive technology to the qualitative research business. The parallels between Kodak’s story and the current situation in qualitative research are striking — and instructive. As qualitative market researchers, we’re now faced with a choice: ignore AI as Kodak tried to do, fearing that it will make us obsolete and hoping it will go away. Or begin to embrace and leverage it — not to replace human insight, but to enhance it.

Kodak’s failure offers a valuable lesson: disruption is not inherently bad, but resisting it can be fatal. For qualitative research firms, AI is not only an opportunity but a necessity to stay competitive in a rapidly evolving landscape.

Kodak’s Mistake: A Case of Technological Myopia

Kodak’s decline stemmed from one fundamental issue: a deep reluctance to embrace digital photography. For decades, Kodak dominated the photography industry with its profitable film business, which was built on selling not just cameras but the recurring consumables that powered them — film, paper, and chemicals.

Digital photography, although invented by Kodak engineers, was seen as a threat to this established model. Instead of leading the digital revolution, Kodak doubled down on protecting its core film business, hoping digital photography would be a niche product. By the time Kodak realized digital photography wasn’t just a fad but the future, other companies had already seized the market.

The AI Challenge for Qualitative Research Companies

In many ways, qualitative research companies today face the same challenge that Kodak did. AI tools for qualitative research — automated text analysis, machine learning algorithms for data pattern recognition, sentiment analysis, and natural language processing (NLP) — are increasingly sophisticated and efficient.

Much like digital photography threatened Kodak’s film business, AI poses a perceived threat to the traditional model of qualitative research, where skilled human researchers manually analyze interviews, focus groups, and survey responses to generate insights. The fear is that AI will automate these tasks, making human expertise less valuable, thus disrupting core services.

The Risks of Ignoring AI

Qualitative research firms that ignore AI could face the same fate as Kodak: losing relevance. Here are the key risks of resisting AI integration:

  • Falling Behind Competitors: Just as Sony and Canon overtook Kodak by betting on digital cameras, AI-driven research platforms can rapidly outpace traditional firms by offering faster, more scalable insights. Companies that stick to manual processes risk losing out to competitors who use AI to enhance their research capabilities.
  • Misaligned Business Models: Kodak failed to adapt its business model to a digital-first world. Similarly, qualitative research firms that cling to human-driven analysis without integrating AI could find their services mismatched with market demands for faster, cheaper, and more data-driven insights.
  • Missed Innovation Opportunities: AI provides opportunities for more innovative research approaches — such as real-time analytics, deeper trend spotting, and predictive insights — that traditional methods struggle to achieve. Failing to capitalize on these advancements could make qualitative firms seem outdated.

A Strategy for Long-Term Success with AI

Instead of seeing AI as a threat, qualitative research companies should see it as a tool for transformation and growth. Just as digital photography opened up new opportunities for creativity and business models (e.g., smartphone cameras, social media, and online photo sharing), AI can expand the horizons of qualitative research. Here’s how:

  1. Augment Human Expertise, Don’t Replace It

AI excels at handling large datasets, recognizing patterns, and performing repetitive tasks like transcription and sentiment analysis. However, the nuances of human experience —empathy, cultural understanding, and deep contextual interpretation — remain best handled by humans.

The key is to combine human insight with AI-driven efficiency. For example, AI can rapidly analyze thousands of survey responses, flagging key trends and anomalies. Human researchers can then dig deeper into the meaning behind these findings, interpreting the “why” behind the “what.”

  1. Reimagine the Research Process

Qualitative research traditionally involves time-consuming tasks like conducting interviews, transcribing data, and manually coding themes. AI can streamline this process.

With tools like NLP, AI can automatically transcribe and code data, leaving researchers more time to focus on interpreting results and providing higher-value insights to clients.

By rethinking the process and utilizing AI, qualitative research companies can offer faster turnaround times without sacrificing depth.

  1. Expand Your Service Offerings

Kodak clung to its film business and failed to see the broader possibilities of digital imaging. Similarly, qualitative research firms should expand their view of AI beyond basic automation. AI can enable new services like predictive analytics, real-time data analysis, and enhanced data visualization.

For example, AI can analyze social media conversations to provide real-time insights into consumer sentiment, something that traditional qualitative methods can’t do at the same speed. Research firms can also use AI to analyze large amounts of unstructured data, such as social media posts, online reviews, or customer service transcripts, offering new layers of insight.

  1. Invest in AI-Driven Talent

Kodak’s resistance to change was partly due to its entrenched culture. To avoid this, qualitative research firms need to invest in a culture that embraces AI. This includes hiring talent with AI expertise and training existing staff to work alongside AI tools.

  1. Develop New Business Models

Kodak’s failure to adapt its business model was a key reason for its downfall. Qualitative research firms must think beyond the traditional project-based approach. By using AI, they can create more subscription-based models, offer real-time dashboards, or even build AI-powered research platforms that clients can use for continuous insights.

For example, qual research firms can offer an AI-driven platform that clients can use for self-service insights, with options to add human interpretation and bespoke reports for more complex projects.

AI as an Enabler, Not a Threat

AI doesn’t have to be a replacement for traditional qualitative research; rather, it can be an enabler of deeper, more impactful work. Much like how digital photography eventually allowed for more creativity and democratization of photography, AI can enable qualitative researchers to do more with their expertise, handling larger datasets, identifying patterns faster, and offering clients more valuable insights.

Proceeding with Caution

All this is not to say qualitative research firms must immediately and rapidly embrace and integrate AI tools, technologies, and methodologies to avoid Kodak’s fate. AI is still very much the Wild West — untamed, unpredictable, and unchartered territory in which a handful of key players are fighting it out for dominance.

The landscape, rules, and ramifications of AI are changing on a daily basis, leaving many organizations — including market researchers — chasing after it and never quite catching up. What’s more, there are still significant risks that come with using AI, particularly around data privacy, protection, and integrity. AI hallucinations and complete fabrications continue to be an issue. And we won’t even touch the complex moral and ethical quandaries entangled with the use of AI.

We expect the world’s governing agencies to keep introducing and adapting new regulations in an attempt to mitigate these risks, ensure AI safety, and create ethical frameworks. Staying on top of these evolving regulations adds yet another layer of challenge. So any embrace of AI on the part of qual market researchers should come with a healthy dose of prudence.

But there is a difference between inertia and caution; proceeding with care is not the same as standing still in fear, panic, or uncertainty. Cautious integration is the right path to take, one that will lead our field to better insight and innovation.

Final Thoughts

Kodak’s story isn’t just about missing a technological trend — it’s about failing to adapt to a shifting world. The lesson for qualitative research companies is clear: AI is not a threat to be avoided but an opportunity to be embraced — albeit with caution and care.

Just as Kodak should have led the digital photography revolution, qualitative research companies should aim to be leaders in AI-enhanced research. By augmenting human expertise, reimagining processes, expanding service offerings, investing in talent, and adapting business models, qualitative research firms can not only survive but thrive in an AI-driven world.  AI, like digital photography, isn’t the end of an industry—it’s a new beginning. The choice is whether to lead or be left behind.