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At RedSky strategy, we understand the nervousness around the increasing artificial intelligence in our world. However, we also understand that AI isn’t a threat to our jobs or society but a tool to help us function more efficiently. We still need people to perform the research, welcome people into a space, and truly understand HumanSight. AI cannot do this. AI isn’t a replacement for people, but an integration to help us all improve. 

The Waves of AI in Research

Just like any new invention/idea/thing, AI isn’t going to start off as perfect or as developed as it will be in the future. Things take time to be fully integrated and fulfill their purpose. That means that we will experience waves of AI being introduced into our lives and our research. These waves are The Now, The Emerging, The Future. 

Automation (The Now)

In this wave, we will see AI being used to handle simple but time-consuming tasks such as analyzing survey responses, generating reports, or even planning meals and recipes. While these are great uses for AI, a human still needs to look over the data and find the why. Or taste the meal to see if the recipe is good.

The adoption of AI for automation is already widespread. As McKinsey’s 2022 “State of AI” report highlighted, 50% of companies have adopted AI for at least one business function, with data analytics and automation being among the most commonly used applications. Likewise, the GreenBook GRIT Report (2023) revealed that around 60% of market researchers use AI for tasks like data processing and coding. The trend is even more evident in the research industry. Forrester’s 2023 “AI in Market Research” report found that over 70% of research firms now use AI for automated reporting, underscoring the growing reliance on AI to streamline workflows.

Wave 1: Automation (Now)

• Faster data processing
• Automated reporting
• Basic pattern recognition

Augmentation (The Emerging)

In the augmentation wave, AI is going beyond the simple tasks. Now, it’s being used for real-time insight interpretation. This can be analyzing text, voice, or others, and then predicting consumer behaviors. If used correctly, this can greatly decrease the time it takes a consultant to compile the data, review it,  and then interpret what it means. Even when using AI in this way, a human still needs to step in and give the data life. For example, while AI might predict what a customer is likely to buy next, it’s up to a person to decide how to turn that prediction into a strategy that fits the brand’s goals. 

The idea of “augmented intelligence” has gained traction, especially in the context of research. Gartner’s Hype Cycle for AI (2021) popularized the notion that AI should enhance human intelligence, not replace it. The work of Smith et al. (2023) further explored the capabilities of multimodal analysis—integrating text, voice, and video data—showing how AI can help businesses gain a deeper understanding of consumer behaviors. Similarly, the Advertising Research Foundation (ARF has provided guidelines on how companies can use AI for predictive consumer modeling, offering a responsible framework for leveraging AI in marketing.

 Wave 2: Augmentation (Emerging)

• Real-time insight generation
• Multimodal analysis (text, voice, video)
• Predictive consumer behavior modeling

Anticipation (The Future)

The Anticipation phase is about looking ahead, using past consumer behavior and trends to predict what’s coming next. It can offer insights before they’re even needed. This phase also enables research designs to be more flexible, adjusting as new data comes in. And as AI keeps learning, its predictions and models get smarter, making them even more accurate over time.

While still speculative, some forward-thinking ideas have been explored in Research World (ESOMAR’s publication) under the concept of “anticipatory insights.” Johnson & Lee (2023) documented early examples in their publication, The Future of AI in Market Research. 

Wave 3: Anticipation (Future)

• Proactive insight identification
• Dynamic research design
• Continuous consumer understanding

Despite its rapid rise, barriers to adoption remain. Many leaders are hesitant due to concerns about AI accuracy, biases, and over-reliance. However, with 71% of companies reporting a positive ROI on AI investments (Salesforce), it’s clear that integrating AI strategically can be a game-changer. AI is here to stay but not as a replacement for human creativity, strategy, or connection, rather, it’s a tool that can help us do more, and do it faster, while keeping people at the center of it all.

At RedSky Strategy, we embrace the possibilities of AI while staying grounded in what makes research meaningful, people. 

Curious about how we combine AI’s capabilities with human expertise? Reach out to us and let’s explore AI together.