Future of Marketing Scenarios
An overview of Scenario Planning
Scenario planning employs an outside-in view of the future. It purposefully creates context by specifying futures that embody the key topic without being beholden to it. The process encourages people to identify uncertainties that will be critical to the future of a topic, not within the domain, but across the spectrum of social, technological, environmental, economic, and political factors that will influence the direction of that domain.
Future of Marketing class learners at the University of Washington’s Communications Leadership program voted on brainstormed uncertainties about the future, identifying two uncertainties they saw as most critical and uncertain to the future of marketing.
They determined that the nature of truth and the role of artificial intelligence in personal and work situations would shape, and act as constraints, on the future of marketing scenarios.
The role of AI and the robustness of truth were overlaid to create four quadrants. The quadrants gave rise to stories about the future built on the core uncertainties and many other uncertainties about the future. Rich narratives emerged that offer a stark contrast between the quadrants, which is a primary goal of scenario planning.
The following sketches provide a glimpse of these four futures, all extrapolations from the present but asserting very different values for the role of AI and the value of truth, resulting in consequences and opportunities that may inspire hope as much as they do fear.
Future of Marketing Scenarios: Singutopia
Singutopia is a world where information and facts are respected. This is also a world where AI creates powerful and unique value, but its results do not dominate, threaten, or suppress. Highly regulated data ensures that when AI is employed, it offers the best insights—and safely drives automation.
People trust brands and governments, both of which police AI and AI-generated content for accuracy to protect themselves and the public good. Interventions often take place in public, so consumers and citizens experience them. People are often credited with pointing out flaws derived from poor data or algorithm errors.
AI rolls as a backdrop to Singutopia. Robots pick up trash and clean streets, respond to natural disasters and employ the wealth of data on human health to create new treatments and provide healthcare improvements even to remote populations.
Data-driven policy helps put facts over politics, but people remain the adopters and implementors of ideas. AI helps even the playing field by removing the politics from the creation of voting districts, creating strangely convoluted but fairer voting maps in the United States.
The influence of large, multi-national NGOs wane in the face of better global conditions. The use of AI-augmented decision-making has created a more functional government with less need for outside entities to supplement them. Details shared transparently from government data allow people to see how and how well their money is spent, which has resulted in meaningful government budget allocations that address the most dire problems first while informing more direct democratic involvement in priority setting.
Climate change is recognized as a multi-generational issue but one that must continue to be earnestly addressed. AI offers alternatives and tests ideas, creating a positive feedback loop.
Massive amounts of data help hone entertainment and learning opportunities, but AI does not make the choice about what content people consume or what they learn—people retain agency.
Long-term plans may actually have a chance of working, guided by AI to examine the detail and present advice and revisions that help keep humanity on the path toward reduced greenhouse gases, the reduction of consumed plastics and other contaminants, and quickly identify social injustices that need to be addressed.
Future of Marketing Scenarios: Trust the Algorithm
AI uses data to inform its decisions, which humans have increasingly given over to the technology. The proliferation of divergent AI models was curtailed, giving way to centralized systems that consolidate knowledge representations. Distributed AI is limited to narrow use cases, such as medical diagnosis, where the data works best in a constrained, domain-specific model. The results, however, are part of an individual’s profile.
Large entities, like governments and big brands, dominate. Unfortunately, their motivation stems from selfishness rather than magnanimity. The most critical bias in AI is that scale is good—bigger, more centralized, more controlled, more efficient, wins—in the models and in reality.
While AI represents autocratic tendencies, the data is the data, and it has revealed the negative aspects of inequality and income disparity and worked with government and business leaders toward solutions to those issues, albeit through strong social controls.
Cities are well maintained by the central powers and prove relatively safe, but rural life is relegated to a second tier because the big automation of farms and transportation requires few people between its hubs.
In the cities, data rules the day, as people start their day with coffee pre-ordered to their schedule and produced precisely to their likes.
Less and less industrial work is required, also disrupting employment at scale. AI has done the math to convince policymakers that a universal income is not only desirable but necessary—as there is no longer a need for traditional employment. The boom-and-bust cycles of the past are now opaquely managed by algorithms charged with keeping the economy on an even keel.
Future of Marketing Scenarios: Polar Arctic
In Polar Arctic, big AI failed, leading to another AI Winter. The promise of generative AI ran its course, coming up against its increasing propensity to produce bland content as it continued to average its inputs. AI investments collapsed. People yearn for personal connections again after nearly a decade of false hopes, broken promises, and unnecessary disruption.
People rally around causes, generating new communities and affiliate groups. Small businesses thrive as loyal consumers focus on connections between makers and consumers—trusted merchants re-emerge through vibrant business-to-consumer markets.
Rather than cryptocurrencies, consumers sometimes barter for time or things as an alternative to traditional money—and direct selling thrives.
Online brand influencers have given way to influencer activists aimed at fixing the problems their world has inherited.
Future of Marketing Scenarios: Return to the Wild West
AI is everywhere, but the truth is hard to find. Many organizations have launched their own generative AIs, training them on diverse versions of the truth. As with the Internet of old, for anything you believe, there is likely an AI that will reinforce your belief system. AI dehumanizes more often than it enlightens.
Divides rule as people cluster around their echo chambers. Fake influencers pop-up quickly to hawk a conspiracy and just as quickly disappear—some of them are not human.
Being mediocre is okay. Everything is dumbed down.
Some groups, including many trade associations, create their own AIs trained on industry data to ensure the propagation of knowledge and related skills. They create islands of trust.
Many prosper from the uncertainty and unrest, but many more suffer. Conflicts of various sizes affect personal life and impact international perspectives. People don’t travel much because they don’t feel safe.
In some places, very small businesses form accelerators that attempt to jumpstart the lagging economy.
NGOs struggle to thrive as their resourcing, in terms of people and money, proves inconsistent. Perceived missteps alienate donors quickly, which also makes the NGOs lean toward consistent averageness.
People feel like they are part of a broken system, one they have a difficult time identifying or understanding. They feel like they have no control over their destiny, but they also know any sense of control from others is likely short-term, if not completely illusory.
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