AI 2030: AI for Insights Activation

Until insights are put into practice, they are merely nice to know. Activation makes insights matter, and AI must be part and parcel of activation.​
10 May 2024
AI and research
J Walker Smith
Walker Smith

Knowledge Lead, North America

Mark Visser

Managing Director, Consulting, Amsterdam

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Activation is the Whole Game

Insights become relevant only through activation. No matter how brilliant or ground-breaking, until insights are put into practice, they are merely nice to know. Activation makes insights matter.

Historically, though, insights functions have been siloed far from the action. Insights leaders advised on decisions and execution, and insights teams reported metrics of performance and accountability. But insights functions were typically a data hand-off or two removed from the ways in which data were put to work in the marketplace.

It was the advent of digital Big Data that vaulted insights functions into the fray. The turnaround time on data became real-time. The breadth of connections became much richer. And critical data started to be collected at the moment of truth rather than at some randomized sampling moment. Insights is now in the mix of activation.

Yet, at many companies, insights functions continue to reflect too much of the old, siloed approach and too little of the contemporary interconnected reality. Which is why leading companies that outperform the competition are much more likely to have insights functions that lean into activation as the point of engagement and learning.

Insights functions at leading companies work where the rubber meets the road. Activation is the objective not an intermediate step of strategy or planning. This is one of the critical learnings from Kantar’s industry-leading research into the future of insights, Insights 2030, or I2030. AI will embed insights functions even more deeply in activation. 


The House of Insights framework from I2030, shown here, recognizes that activation is the pinnacle of insights. Activation is how the foundational understanding of empathy, channeled through a galvanizing process of provocation, builds brand value. Activation is the payoff. Activation will shape the future of insights in the coming of era of AI, which we call AI 2030.

Activation in Action

Activation involves three critical skills and processes. Engagement with partners, or strong relationships to influence decisions. A drive for impact, or a total commitment to organizational rather than functional priorities. And real-time execution, or the ability to inform and adjust with speed and agility.

Activation means building trust and emotional intelligence, not just data skills and research IQ. Business leaders want an answer even before they’ve asked the question. Insights must make itself the sought-after authority, regardless of where and to whom it reports. A focus on activation builds a sense of indispensable authority for insights leaders.

In years past, the guiding call for insights has been to get more involved in creating strategy and advising planning. Strategy and planning are no less critical. But the shift of focus to activation requires insights functions to be more involved in the implementation of strategy and plans. Insights must operate with mettle and verve if it is to make itself heard.

A business-first focus on activation means holding insights functions accountable to business criteria not only research criteria. Kantar’s I2030 research found that leading companies are twice as likely as trailing companies to employ business oriented KPIs for evaluating the performance of insights functions. In other words, companies that out-perform competition make sure that insights functions are tied to the business outcomes that matter.

Brands must integrate AI into the flow of data influencing activation. When AI is integrated into business operations, it provides a connective tissue of efficiency and responsiveness. For which insights must deliver ideas at the real-time tempo of AI.  

Insights functions should be benchmarked against their ability to oversee AI in this way. This sort of organizational benchmarking is what Kantar offers insights leaders. 

AI as Activation

As companies bring AI into their operations, they will quickly discover that AI applications function better when they are managed jointly not separately. Efficiencies shared. Learning disseminated. Best practices put in place across the organisation. As this happens, insights will be tied tighter to every piece of the business. The natural evolution of the AI transformation now churning through commercial enterprises will bring insights even closer to activation.

For all the elements of activation—partners, impact, real-time—AI will provide enhancements that empower insights functions to make a bigger difference for activation.  

Six key things to highlight: 

Business leadership. It was clear from Kantar’s I2030 work that business leaders expect insights leaders to work more like senior managers than senior researchers. They want insights teams to be more competent in the sorts of non-research skills that make a difference with management, not simply in research.

The legacy challenge is that insights leaders are grounded in research and data, not strategy and vision. But AI is a resource that both augments strengths and counterbalances disadvantages. It is thus a tool that insights leaders should leverage to become better contributors to business leadership.

More than that, insights leaders should deploy AI for business issues not just for research needs. AI can drive what the business needs most, which is activation. Certainly, AI should provide what insights needs in terms of efficiencies and competencies. The bigger opportunity, though, is for insights leaders to step up as senior managers and make AI deliver for the business.

Trust. Activation is not just implementation. It is mostly persuasion, or convincing decision-makers to act. Engaging effectively with partners rests on trust, which is built up over time through shared experiences. It creates confidence and thus the willingness of business leaders to act as recommended.

With AI in hand, insights functions will be more knowledgeable and more quickly informed. Knowledge will be more readily accessible, both to insights teams and to other business teams. Displays and dashboards will be richer and more current. The entire insights toolbox will be augmented by AI tools to distill, summarize, report and monitor faster and more comprehensively.

The assurance of better knowledge, delivered in real-time and perfectly matched to the audience, will boost the ability of insights functions to influence activation for the better. This means using AI to translate insights into actionable nuggets. It is also ensuring that insights are current and complete. The reach and processing power of AI will provide a step up for the bona fides of insights leaders.

Expertise. In a related vein, AI will significantly elevate expertise, and thus impact. AI offers a learning system for insights teams. It makes knowledge more accessible by gleaning key information in an abridged yet usable fashion. AI can thoroughly and correctly compensate for experience or training that insights leaders or teams lack.

This is not to overlook the challenge of generative AI hallucinations. But this is a recognized hiccup that is temporary and manageable in the meantime. Work now underway will eventually resolve these hitches, which are the sorts of things that always arise with every sort of new model or analytics.

Even basic applications will make insights teams smarter. Things like pushing out content or summarizing conversations or assessing performance.

The biggest opportunity lies with the untapped potential of a company’s proprietary data and experience. Every company has its own unique view of the marketplace, but much if not most of this lies dormant and unutilized. It is often difficult to access, and generally speaking, it is hard to pull together. These are tasks at which AI systems excel. Internal conflicts can also play a part, which favors tools over people. 

AI systems are available to every competitor, as are third-party databases and systems. The competitive edge from AI will come from its ability to mine and activate an individual company’s unique expertise in the marketplace.

Continuous execution. Insights teams have traditionally operated at a stepwise pace—one project done and digested before moving on to do and digest the next one. It’s one step at a time, always methodical, often slow. AI operates at a different pace, which will advance real-time execution and impact.

AI can facilitate continuous optimization with faster assessments that connect the dots more exhaustively. But it is the accessibility, mentioned already, that will push insights the hardest. What slows the process of activating insights is the necessity of collating, extracting and absorbing information. Doing this really fast is the central genius of AI, especially generative AI, and thus the power of AI for fueling a speedier cycle of activation.

Norms. The drive for impact that is part of activation is not only cultural. And not just allegiance to goals and advocacy of vision and strategies. It is also the identification and establishment of best practices or norms.

The sorts of things that work best, or the norms that should guide activation, are often buried deep within the experience and tacit knowledge of a company. They are contained as well in the success or failure of past campaigns and business initiatives. Tracking studies, ad tests, concept tests, user experience studies and other aggregations of research projects provide cumulative databases from which normative learning can be extracted.

The value of extracting norms is that the rules of the road for high quality marketing are identified. And they can then be applied and enforced in all activation, The risk of relying on norms is that all marketing will tend to look alike. Everything will be normative—all better, of course, but all alike.

These normative risks of homogenization will have the happy consequence of elevating the importance of finding new ways of activating breakout success. When everything looks like the norm, more creativity must be brought to bear. This is where insights can have its biggest impact.

The key takeaway from I2030 was the, quote/unquote, “imperative of imagination,” or the need for breakout thinking in a marketplace characterized by rapid change, high volatility and serial disruptions. Normative marketing is not enough. More than ever, companies need curiosity, creativity and imagination. Insights must be the stewards of corporate imagination, and more so than ever in an era of AI.

Organizational readiness. Real-time capabilities offer no value if a company is unable to act upon real-time knowledge and opportunities. All touchpoints must be optimized, not just insights functions. AI will force the hand of companies that might otherwise be slow to adapt.

AI will raise the stakes of falling behind. At the same time, AI will make it easier for companies to get up to speed in a marketplace characterized by a quicker cycle of business. However, first-movers will also pull away faster if competitors fail to move immediately as well. AI has made it easier for companies to get better, faster and smarter. AI has also made it riskier to wait and see.

As the stewards of activation, insights functions must shepherd business leaders through the transformations that AI is bringing to the marketplace. The bottom-line is to make AI part and parcel of activation. Those are the processes and skills that insights teams must put to use to the era of AI.

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