Tag Archives: ai

Three Ways AI Will Start Impacting Marketing in 2024

Wave Images - Free Download on Freepik

As the old quip goes, “predictions are difficult, especially about the future.” That witticism serves to remind us of the hazards of predicting the future of AI and its impact on marketing. But there are three outcomes that seem self-evident as we witness the early applications of AI to the marketing toolkit.

The size of marketing and agency staffs will decline

There are debates about whether AI will inspire more or less creativity. On one hand, AI is a great enabler that will allow ideas to develop with less constraints on executional limits on bringing them to life. On the other hand, AI is a great imitator that will respond to prompts with a tedious recycling of what’s already been done. Agency viewpoints have tended to emphasize the second view as a basis for saying that the creativity they bring to clients will be in more demand than ever. Whether most agencies actually are truly a source of creativity or are just human recyclers is beside the point. The point is that the business model of agencies is based on the executional effort rather than the intellectual effort of marketing. Most agencies have an hours or people-based model similar to that of a law firm. They may attract clients through the strength of their creative ideas, but they make money from those clients by how many bodies they can assign to produce and distribute those ideas. Clients may value the “big ideas” of the agencies even more in an AI world, but they won’t need large staffs to produce the marketing materials, create the media plan, and optimize media channels.  Agencies have given lip service to getting paid for their ideas in the past. But they’ve never convinced clients or themselves to adopt that model. The role of agencies may be enhanced or degraded by AI, but their billable revenue will decline as more human tasks become automated.

For the same reasons, company marketing departments should grow smaller in number as well. The relative scale of the ipact will depend on how they were organized. Marketers than built large in-house teams to handle creative and media tasks will shrink in line with agencies. Brand managers will be less affected but their skill set and responsibilites will change as they spend less time and task management and more on true brand development.

The best marketers will shift their focus from local optima to global optima

That’s an admittedly jargon-filled phrase. But these mathematical terms do the right job for describing the main marketing challenge of the early AI era. The figure below illustrates the general idea. Imagine you’re kicking off a marketing campaign represented by the blue dot. As you move to optimize your messaging, target, and channels, you move nicely along increasing your performance until you get to the top of the first curve. As you move beyond that peak, the metrics will tell you that you are going in the wrong direction and push you back to the first peak. But there may be a new audience, a new selling point, or a new channel strategy further down the path that would actually get you to an even higher maximum return. But the data won’t take you there incrementally. You’ll have to push past the optimization signals to move from a local optimization to a global optimization.

The challenge is that you’ll never know if you’re at a global maximum or a local maximum. You can’t tweak yourself to the highest outcome. Marketers will rely more and more on AI to get them to an optimal local maximum. But to unlock superior performance, they’ll have to explore ideas that are beyond the A/B testing mentality to constantly explore whether there is a better outcome than the current approach can give you.

The best job of humans will be to interface with other humans

There has been a lot of conversation around the jobs that will be lost to AI. If historical trends are a meaningful precedent, AI will eliminate many jobs and create many others. But of course, the losses and gains will be spread unequally. Middle-skilled physical laborers bore the brunt of machines and manufacturing robots. Similarly, middle-skilled and many high-skilled administrative jobs will quickly fall away in AI. Media planning, optimization and reporting will become mostly automated. A good portion of pre- and post-production workers will also be replaced by AI. The jobs that will survive or even grow are those related to human tastes and connections. Humans are a mess of reason, emotions, and instinctual quirks. How we react to things is difficult to interpret or predict. Taylor Swift was not named Person of the Year because of the accuracy of her pitch and efficiency of her lyrics. She created a cultural moment that people wanted to be a part of. The ultimate goal of any brand is to create a human connection that transcends the attributes of the product. The nature of that connection is elusive. But humans recognize when it happens and, more importantly, are the mechanism by which it happens. The people who can inject humanity into customer service, product design, and marketing strategy will always be in demand. To the extent that AI frees up people for more human-centered thinking, there is even potential for growth.

1 Comment

Filed under 21st Century Marketing, Artificial Intelligence, Innovation

What’s in Store: The Transmorpher Experiment

magic-machine1There’s a geeky thought experiment I used to ponder with friends to pass the time in the pre-smart phone world. It came back to mind as a way to plot how a world of AI, robots and infinite computing power may shape our future. It went like this. Imagine we perfect a brilliant machine, called the Transmorpher. The Transmorpher takes any material you feed into it, breaks it down into sub-atomic matter and then reassembles it however you instruct it to. You could shovel a pile of garbage, sand, or dirt into the machine, and it could reassemble it into a pile of precious metals. Now further imagine this machine not only generates basic elements, but assembles them together in the order and form you instructed. In today’s terms, it’s like the ultimate recycling machine combined with the ultimate 3-D printer. So, the right size pile of garbage would not only be transformed into various pure metals and plastics, but with the right instructions, combined in such a way that it was a fully-operational automobile. The first Transmorpher would be enormously expensive of course. Yet once it was up and running, it could be used to cheaply turn out duplicates of itself for anyone with stuff to pour into it. Eventually every person on earth would own their own Transmorpher.

What would be the social, political and economic effects of worldwide Transmorpher ownership? Hey, I said it was geeky. But think about it for a minute. Everyone with access to a supply of garbage, dirt, or any other physical substance can now own a Mercedes Maybach. They could also make all the gas they need to run it. The same goes for food, furniture, computers, clothes, gold, diamonds, and anything physical thing in the world. Who would win and who would lose in a world where most everything was nearly free?

Winners

Status and wealth would rely less on pure mass of ownership since everybody could own most any thing they wanted. People could no longer differentiate themselves on how many things they owned or how expensive those things were. They’d have to own unique or better things. In this environment, people would seek out the instructions to things nobody else had or had thought of yet. Transmorpher instructions would be more valuable than Transmorpher outputs. So designers and engineers who knew how to build those instructions would be in high demand.

Since the Transmorpher can only make things, human experiences would also remain at a premium. Singers, actors, professional athletes, comedians and party planners would escape commoditization in this world and would likely increase in value because of the comparative scarcity of experiences in a world of infinite stuff

Not all physical assets would lose value. Real property holdings would remain valuable. The Transmorpher couldn’t make the world any bigger. I could use the Transmorpher to make a house, but if I didn’t have anywhere to put it, it wouldn’t be of much use. Assuming we still value places to live, interact, and work together, land would retain its desirability as long as property rights were maintained.

Losers

Clearly manufacturers would lose. Knowledge about how to make things would remain valuable, but the actual making of things would be taking over by the Transmorphers. The making of things, both skilled and unskilled would lose its added value worth. Retailers would also lose out. There’d be little benefit to having a centralized provider of things when anything you want is available immediately from your Transmorpher. Distributors would then fall in that domino chain.  The Transmorpher world would severely reduce the need for things to be made in one place and then shipped to another.

In Between

 The future of service providers would be murky. On one hand, Transmorphers don’t do things, they only make things. They couldn’t paint your house, execute a marketing plan, or figure out if that lingering cough was anything serious. In that direct sense, services would not be replaced by Transmorphers. But the question would be whether designers, freed from cost constraints, could design new things to perform those services.

Government would probably both win and lose. It would be harder to regulate things in a world where anyone with a set of instructions could make whatever they pleased, whether it be narcotics, small arms, or patented products. Imagine how hard it would be to police controlled substances when there are infinite untraceable sources of supply. As a result, the job of government would get harder. Yet these same factors would lead to higher demand for just this type of enforcement. People wouldn’t want their neighbors making mini-nuclear reactors for their backyards. The size and role of government would likely expand to replace the restraints previously enforced by physical limits.

The Transmopher is a fantasy of course. But it’s a useful fantasy to plot the possible paths our world is headed, for good and bad. We’ll never arrive at the Transmorpher, but that’s the path we’re currently on. The most interesting implication for us is that many of the things that determine our social and economic order are based on the natural constraints of our physical world. As we engineer ourselves beyond those constraints, we’ll have to choose how and whether we replace them with a self-imposed order.

Leave a comment

Filed under Artificial Intelligence, Innovation, trends, Uncategorized

Taking the Artificial Out of AI

In case you haven’t noticed, Artificial Intelligence is the It Girl for marketers these days. Just about every ad tech tool now claims to be powered by AI components. Agencies and consultants are touting their AI capabilities. CMOs are bragging on their AI initiatives. As a result, the definition of AI has become stretched beyond recognition. Many people are defining it by what it does (language processing, data manipulation, visual recognition, etc.). But the real mark of artificial intelligence is how it does it. A chess-playing computer could be AI or not. If it plays chess by analyzing every possible move on the board, assigning it probability of success, and selecting the move with the highest probability, then it isn’t Artificial Intelligence. If it plays chess by applying certain principles, and refining those principles through feedback gained from multiple games, then it is AI.

While the more technically-minded would have more specific and accurate definitions, marketers can practically characterize Artificial Intelligence applications by two things:

  • The ability to perform tasks for which they’re not explicitly programmed
  • The self-directed capacity to improve that ability as it is exposed to more tasks.

At the core of the computing age is the power of If-Then processing: If a certain condition is true, then perform a defined operation. For example, you might program a traditional application by coding “if Speed is greater than 55mph, Road = Expressway and Weather = Rain, then reset Speed to 45mph.” This is an explicit direction. Using AI, you could effectively program an application more along the lines of “If driving conditions become less safe, then slow down to meet the conditions.” Using the definition outlined above, AI would use a variety of input (weather, traffic, type of road) to determine what is “less safe” and the speed appropriate to the conditions.  Based on feedback(e.g. how many accidents occurred), it would improve its definition of “less safe” over time without a developer having to go in and explicitly recode every conceivable definition of “less safe”. So while the first explicit program will never change its behavior, an AI program would learn to distinguish between rain falling at 70F and rain falling at 32F. In essence, AI allows applications to refine their If/Then engine autonomously.

There are many things being touted as AI that really aren’t. For example, increased processing power is allowing for even more extensive and sophisticated searches of ever larger databases. So, if you ask a Dinner Bot for recipes using tofu, asparagus and mayonnaise that’s quick to make, it can search multiple recipe databases, correlate those ingredients with preparation times under 20 minutes and send you back the 10 most popular recipes fitting that description. It can do all that using explicit instructions. While it may be impressive, it is not AI. Here’s one test to apply to see if something is really powered by AI. Will the results of the applications change over time depending on who is using it? The answer should be “yes.” In other words, two identical AI applications should start to yield different results if they are used by two distinct groups of users. That’s because they’ll be exposed to different situations and different feedback that should affect its autonomous development.

For marketers looking how to start thinking about applying AI to their businesses, Shelly Palmer provides a typically insightful view of the topic.

 

Leave a comment

Filed under Artificial Intelligence, Data Science, Innovation