The coming of computers with true humanlike reasoning remains decades in the future, but when the moment of “artificial general intelligence” arrives, the pause will be brief. Once artificial minds achieve the equivalence of the average human IQ of 100, the next step will be machines with an IQ of 500, and then 5,000. We don’t have the vaguest idea what an IQ of 5,000 would mean. And in time, we will build such machines – which will be unlikely to see much difference between humans and houseplants.
– David Gelernter (attributed), “Artificial Intelligence Isn’t the Scary Future. It’s the Amazing Present,” Chicago Tribune, January 1, 2017
Imagine an agency where:
Creative execution begins after this, and leverages what algorithms have identified as ingredients in the non-conscious mind that are already connected to the topic and category.
By definition, the work of traditional market research and advertising agencies has always been rooted in nineteenth- and twentieth-century labor models. Which is to say, the work performed by people. From the initial strategies and tactics developed to the finished end product, these professions, like many others, have depended on – and thrived from! – the fruits of the human mind.
It is no exaggeration to say that AI and ML are hard at work changing that basic premise today – just as they are in so many other fields. But it is a mistake to take that remarkable proposition and extend it to conclude that people will become peripheral to the tasks at hand. Certainly, automation of many labor-intensive types of work is inevitable. AI- and ML-powered systems can simply do the work faster, and arguably better (if you accept the idea that “better” means more accurately and with far-greater resources applied), so naturally they will preempt human labor because they make more economic sense to use.
But at the close of this book it behooves us to remind ourselves that while AI and ML are truly game-changing advances, they should serve us, and not the other way around. Perhaps it is oversimplifying to say that they are tools – highly powerful, sophisticated tools, to be sure – but in the fields of market research and marketing agencies, that is essentially how they should be viewed.
If the goal and the benefits of marketing research revolve around the gathering and analysis of useful data that can be applied to better understand consumers and their behavior . . . and if the goal and the benefits of marketing services companies (broadly stated) revolve around creating methods and messages designed to inform, persuade, and motivate consumers . . . then the human element should always be at the center of the work.
The experts who are building the next generation of advanced AI and ML platforms designed specifically for helping drive innovations in new products and marketing are doing so with the view that the “work product” their systems deliver are intended to enable professionals to do their jobs better, smarter, more efficiently, and more effectively. These systems are designed to provide superior bodies of information. Superior guides to greater inspiration. Superior avenues toward achieving new products and features that consumers will innately find attractive and responsive to their needs – felt, and unfelt just yet. Superior resources to spark the creative “aha!” moments that lie at the heart of the most successful marketing messages.
Business leaders said they believe AI is going to be fundamental in the future. In fact, 72% termed it a “business advantage.”
–“How Artificial Intelligence Is Pushing Man and Machine Closer Together,” PwC, April 2017
An AI-enabled research agency looks remarkably similar to those of today: an office full of computers, where people are feeding data in, then retrieving and analyzing useful patterns of information. A key difference is that, unseen, powerful AI and ML systems are unleashed to scour multiple databases at speeds and with such analytical prowess that no human or team of humans could match them. A very key difference in the type of work done in this “new” market research company is that staffers are now giving directions to these systems, and refining their output continuously.
One of the most useful aspects of AI and ML for market research and creative purposes is that they can point us in new and perhaps different directions. On the best days, at the heart of both industries is that “aha!” moment – the point when, unexpectedly, a data point, a partial song lyric, an image, a metaphor, or any number of other “stimuli” are delivered by the system. That can, and hopefully will be, the departure point for the experts who work there. Those facts, those insights, those inspirations are what can lead to true (better) understandings and innovations in the marketplace.
Another difference in the new models of market research and marketing services agencies will be the presence of a new tier of staffers. They will be people who are schooled in the basic architecture and operations of AI and ML systems. In the very largest firms, there will likely be data scientists who can help gather and distill the output that AI and ML systems will deliver.
Creatives will increasingly look “outward” for ideas and inspirations; meaning they will depend a bit less on individual or team brainstorming sessions and more on directing their AI and ML systems to go out and gather everything they can find that might be relevant and applicable to the marketing challenge clients are facing.
The defining aspect of the agency is – rapid iteration. The ability of this agency to continuously iterate creative that singly breaks the dysfunctional world of checkpoints and copy testing.
Advertising will increasingly shift towards experience creation – passive entertainment will migrate to active, and interactive entertainment and brand storytelling. Augmented reality, and augmented decision-making will enable consumers to enter and be present in virtual environments of their creation.
An AI- and ML-based agency will be able to leverage the bits and pieces of creative already embedded in the non-conscious human mind. As outlined above, AI- and ML-enabled research and marketing services agencies will differ from their traditional predecessors in a number of important ways. Being able to generate insights in real time, and being able to creatively act on them in real time is another big difference. High frequency trading enables computers to convert miniscule differences in equity prices into profit. Algorithmic creative will similarly convert miniscule differences in cultural nuances into brand awareness and purchase intent. The integration of AI and ML systems will enable research and marketing professionals to make better informed, more insightful, and more impactful decisions at a much faster pace.
An AI- and ML-enabled market research or marketing services agency also lets marketers look into the future and run models to help clients plan their business strategies, new product development processes, and creative development paths. Again, the speed and flexibility with which these processes can operate far exceeds anything that is possible with legacy systems and procedures.
RAD JAD – Rapid Advertising Development and Joint Advertising Development – methodologies will start to proliferate. The RAD JAD methodology – first called Rapid Application Development and Joint Application Development – are core methods for rapid prototyping and user testing of software. Paradigms from the world of software development and user interface development will shift into the world of advertising and interactive consumer experience creation.
The non-conscious mind functions like the Github for Marketing. It already has bits and pieces of code that have been worked out and proven. All the agency has to do is to assemble them in different ways to create fundamentally different designs.
Forty-seven percent of digitally mature organizations, or those that have advanced digital practices, said they have a defined AI strategy.
– “Fifteen Mind-blowing Stats about Artificial Intelligence,” https://www.adobe.com/insights/15-stats-about-artificial-intelligence.html
As AI and ML resources – both in-house and external – increasingly penetrate almost every business of any size, globally, the interactions between “client” and “vendor” will evolve.
Ad agencies especially have been enamored of thinking of and referring to themselves as “marketing partners” with their clients. That concept has lost ground in recent decades, for a variety of reasons. But with the advent of AI and ML systems, that idea of “partnering” toward marketplace success will likely be reborn.
The swift sharing of information and insights . . . the speedy implementation of ideas and learning into new products and new messaging campaigns . . . and the ability to adapt to changing marketplace conditions with far greater agility will be the universal hallmarks of these client/agency partnerships.
Clients will benefit from knowing that their marketing campaigns are derived from far larger and superior reservoirs of information and insights. Agencies will benefit from clients having more overall confidence in the creative solutions offered, and from somewhat faster and more assured client decision-making about budgets and choices in the production process.
The key disruption is the arrival of strategic consultants like McKinsey and the likes of Accenture and Deloitte to the world of creative. Unleashing software-enabled design, data-driven creativity, and app-driven consumer experience creation will change the nature of this partnership.
For those enterprises already in the AI fray, top-performing companies said they are more than twice as likely as their peers to be using the technology for marketing (28% vs. 12%). Unsurprisingly, analysis of data is a key AI focus for businesses, with on-site personalization the second most commonly cited use case for AI.
– “Digital Trends,” Adobe, 2018
Awards serve several purposes, and as a species we seem to love them. So the question begs: With AI and ML advancing at such a rapid rate, and new algorithms and digital innovations being created constantly, does it makes sense to stage an event where the latest AI and ML ideas and products can be showcased and celebrated?
Why not? We live in an age when technology drives most aspects of our daily lives, and where tech icons are idolized. Such an event could keep us better informed about the amazing progress made in these fast-moving fields, and provide ideas and guidance about how best to apply these hyper-intelligent tools to achieve the best results.
It might also serve to help allay some of our concerns about the potential rise of “super machines” that theoretically could threaten our freedom, or even our existence. Recognizing outstanding achievements in AI and ML that help improve our lives, through granting better access to the most useful information we seek, better performing and more relevant products and services, more engaging entertainment, and other positive outcomes seems worthwhile.
Now all we need is an AI/ML program to design the ceremony, create the award, process all the entries from around the world – and perhaps even select the winner!
Digital products and services connect us not only to each other and information and entertainment sources, but also to a hitherto-inconceivable range of consumer products and services. AI and ML power the internet’s abilities to understand (track) our current needs and interests, deliver things that respond to those desires, and also infer from them what we might want or enjoy next.
The issues surrounding this data collection and usage are the focus of much debate, and disagreement. Post-argument, though, are the foundational platforms that we rely on to an ever-growing degree worldwide. Whether it is social media outlets, online retailers, or entertainment sources, the fact is that AI and ML are already at work driving the engines that get us what we want, when we want it. And they suggest to us other products and services, or information and entertainment providers, we may find worthwhile.
The challenges this poses to businesses large and small are becoming geometric in growth and complexity. Product life cycles are narrowing. Product quality is becoming more and more standardized, at higher and higher levels (think automobiles, computers, software, medical technology, entertainment, and so many more categories). Product differentiation is becoming more difficult to achieve and maintain as a long-term competitive advantage. Pricing is under pressure. Consumer expectations and demands are becoming more sophisticated and focused.
At the same time that global competition is heating up at inexorable rates, the global marketplace is splintering in terms of societal pressures and governmental regulation. What’s permissible and acceptable on a social media platform here, may well run up against opposing cultural and legal obstacles there.
On top of that, media are simultaneously fracturing and coalescing. News outlets have multiplied beyond measure, while “legacy” structures like traditional stand-alone Hollywood movie studios are narrowing in number, merging into conglomerates, and encountering an array of international competitors (China has recently built the world’s largest and most technologically advanced studio), as well as digital purveyors from Amazon to Netflix.
All of these trends are impacting the marketing of consumer goods and services in ways that were largely unimagined just a few short years ago.
What can AI and ML contribute to addressing these central issues – and to offering solutions that meet both consumer and business needs?
The most basic answer is these twin technologies’ abilities not just to see around the next corner – but instead to “fly over the mountain” and capture both short- and long-range insights and sources of inspiration that defy and far exceed humankind’s core intellectual and instinctive resources.
To put it bluntly: we are simply not biomechanically designed to investigate, analyze, filter, incorporate, and ultimately synthesize the sheer scale of information that AI and ML systems are designed to do.
On the scary sci-fi front, this fact conjures up doomsday scenarios of “the machines taking over.”
As titillating as the “end of humanity as we know it” storyline can be, it is not a foregone conclusion. What is a foregone conclusion is that AI and ML, in all of their near-infinite scope and variety of applications, are not only here, they are here to stay and are multiplying – again, geometrically – to form the unseen basis of much of human activity, products, and services as the century extends.
Acknowledging that there will inevitably be negative – perhaps evil – embodiments of AI and ML, the same can already be said for other advances in human history. Nuclear power can heat and light our homes, and it can also explode in lethal fireballs.
But this final chapter’s focus is on a couple of the “better angels” of our nature, when it comes to AI and ML being a positive and productive force. There are more profound examples that can be cited, outlining AI and ML’s contributions to science, medicine, knowledge access, and too many more areas to mention. But here are some thoughts to consider about these technologies’ contributions to, and impact on, creative elements in marketing, and market research.
The old adage that if you “give 100 monkeys typewriters and enough time, sooner or later a Shakespearean play will appear” – even if theoretically and arguably possible – has always been a far-fetched notion. Explaining, much less scientifically replicating, human creativity has always been more like capturing lightning in a bottle: if attempted, it’s likely to end badly.
It is conceivable (and predicted by some) that, at a point, AI and ML could become so advanced that for all intents and purposes, they are capable of imitating human creativity to a degree where the two are virtually indistinguishable from each other. Notice we said imitating. Driven by enough processing power and sophisticated supervised/unsupervised learning protocols, creative ideas and elements could be brought forward with little to no human interaction. These deliverables might prove to be “good” enough to serve certain needs without enhancement by human minds and hands. Especially when it comes to technology, “never say never” is a wise premise to follow.
But this is a somewhat dystopian view of the future. Unless and until that creative “singularity” is ever reached, the sheer magic of creative inspiration and its application will remain with and reside in the human mind.
That said: things will change in this realm of creative imagination and expression. In fact, they already are.
Software systems that can learn video editing have already produced segments where visual sequences, and specific styles and paces of cuts and visual effects, are respectable competitors to what a human editor might assemble. Could a master editor conjure a “better” version though? The answer can be argued endlessly. The point is: due to AI and ML, technology today can already perform a task that until now has relied exclusively on human skills and creative vision.
Storyboards, mood boards, music tracks, and more can all be automated to one extent or another. With access to vast and varied digital databases of images and sounds, and driven by expertly coded algorithms, AI and ML platforms can and will gain ever more ground in coming closer to what could be acceptable levels of creative quality compared to exclusively human-curated examples.
So are copywriters and art directors, editors, music composers, directors of photography, sound engineers, musicians, painters, set designers, costume designers, location scouts, and others approaching extinction as creative species?
No need to roll out the rocking chairs just yet.
AI and ML’s immediate promise and potential – and this will be true for the indeterminate future – is their ability to accomplish what would otherwise take a human to do, but so much faster . . . with such greater breadth and depth . . . accessing so much larger bodies of resources . . . and capable of assembling the findings more quickly and in ways that can be helpful and yes, even inspiring to the human observer of the process.
So perhaps the wisest way to view this emerging brave new world is to anticipate that first, human creative inspiration is not going to wither and die; and second, that the “creative function” will be elevated, not eliminated.
As useful, surprising, and arguably even brilliant as the end product of AI- and ML-based systems will likely become, the spark of human creativity will not only not be extinguished – it will be the final arbiter, the “god in the machine” if you will. The best creative minds will sow these systems with ideas and instructions, and reap what they want from them.
Just as online search engines may produce somewhat different results when posed with a slightly different query, so too will AI and ML systems when directed toward the production of creative ideas and materials.
What are the implications of this “elevated role” for creative professionals and creatively based industries? A useful comparison is the autonomous automobile. Yes, it can “drive itself.” But it still needs to be told where to go before it can take you there.
The different skill sets that will evolve over time will entail creative professionals understanding how AI and ML systems work, and how to employ them for the best results. Does this mean mastering coding as a prerequisite to becoming a successful twenty-first-century creative? Not necessarily. But understanding how to guide these systems, through “directed questioning” and database selection, will be a very valuable asset in the creative toolbox.
The term “Big Data” is both overused and misunderstood today.
As remarkable as massive warehouses of digital data are, obviously in and of themselves they don’t do much. It’s terrific to have assembled petabytes of loyalty-card usage patterns and customer profiles – an accomplishment unto itself. But obviously, that data can’t “tell” you much all by itself, in terms of how best to put it to use to serve customers better, improve products and services, solve current and possible future problems, and gain a competitive advantage in the marketplace.
The same is true for the creative elements used in developing marketing materials. How wonderful is it to have instant access to millions of recorded songs? Very wonderful, until you have to find that one lyric, or those six unconnected songs, or that obscure international musical jingle that – with some human thought and creative inspiration – might be the key to a successful new marketing campaign.
In the most general terms, AI and ML are technologies capable of not just assembling those disparate elements for you. They can also take “one giant leap” forward and create something from them that might take you to the solution for that marketing challenge that your company, or client, are seeking.
Let’s begin at the beginning: strategy.
Few will argue that a successful product, service, or marketing effort can be achieved without a sound strategy at its core. Examples otherwise are the exception, not the rule.
How can AI and ML help arrive at smart, effective marketing strategies? By elevating the strategic development process to a higher level. The ability of AI and ML-driven systems to gather, compare, contrast, infer, and convey learning are orders of magnitudes more than anything the human brain can accommodate, much less accomplish.
To draw a crude parallel, it is along the lines of attempting to understand the cosmos through Galileo’s Earth-based telescope, versus the view of the universe through the Hubble Space Telescope. Both can see stars. But only one can capture and analyze light from countless numbers of invisible sources billions of light years away.
Asking the right questions – directing AI and ML systems to go out and retrieve the most relevant and useful data – will be at the heart of the most sophisticated (read: effective) strategic development processes. Instead of sitting around a conference table crunching numbers, studying a competitor’s strategies, and brainstorming possible solutions, the modern strategist will beckon his or her trusty AI/ML system to deliver findings that offer a much broader, varied, and unobtainable-by-any-other-means series of possible strategic paths.
In a very real and practical sense, strategists will now have an actual tool kit to perform their work. And it will be a tool kit with the most advanced, sophisticated tools in it.
Such learning may confirm the strategist’s initial understanding, thoughts, and inclinations; in which case, a great deal of time, effort, and informed guesswork can be saved.
Or they may offer up an unexpected, and therefore unseen, set of other possibilities. “Surprise” may well be the best strategist’s near-constant work companion – and that emotional/mental response will be warmly welcomed, because it’s the appropriate response to a fresh and inspiring set of findings.
So the new skillset for business and marketing strategists – and for those in the fields of politics and other “soft” categories as well – will be a fundamental grasp of what AI and ML are in terms of their broad capabilities, and an increasingly knowledgeable sense of how to apply them in pursuit of the smartest strategy. Just as with a Google search today, the more these systems are used by someone, the “better” someone can become at employing them to achieve the most effective results.
Vendors in the field of market research, strategic development, and business consultancy will compete – and prosper – on the basis of the quality, depth, and breadth of their grasp of AI and ML technologies, and the demonstrated commercial success of their outputs for clients.
There may well be one more step in the search for the best strategy – and that may be the singular, brilliant “leap of logic” from the human mind that takes a strategy from the merely mundane to the magnificent. That does of course occur today, even without the digital dynamism that AI and ML deliver. But those authentic and extraordinary leaps are few and fitful. With AI/ML harnessed to the task, that “aha!” moment will become much more frequent, more easily obtained, and more actionable.
“Actionable” is where AI and ML play their next role in the creative process as applied to marketing.
The twin technologies’ ability to search for, summon, and synthesize data from virtually unlimited digital sources sets them apart from any other method of creative development and execution. At one level, AI/ML deliver practically limitless variations on a given theme; set the systems going, and in very short order they will provide a proverbial fountain of inputs: songs, movies, TV shows, poems, speeches, artwork, trends in online inquiries on any specific subjects, favorite phrases in Swahili . . . you name it (ask for it, even in general terms), and the mind of the machine will circle the globe and retrieve it all for you.
For creative people seeking fresh inspiration, this can be the Fort Knox of ideas and expressions. Tweak the systems a bit, refine the parameters, and they will immediately procure a whole new set of stimuli. With machine learning at work, the system will refine itself, seamlessly fine-tuning to gain even more focused and relevant results.
At this level, the products of the search and analysis processes are simply there for the taking. Rummage through them, unearthing a visual nugget there, a partial song lyric there, an up-to-the-minute glimpse at what consumers are inquiring about online, and allow the human creative instinct to extract and apply what it will (obviously, not violating IP rights in the process, of course!).
But here is an excellent example of where the concept of an “elevated” creative process made possible with AI/ML can take hold.
Let’s say the assemblage of bits and pieces of the stimuli listed earlier has been gone through, anywhere from superficially to an in-depth dive into that nearly bottomless ocean. Let’s further say that the restless drive for creative inspiration has not yet been fully satisfied – it just feels like there may be something more, something powerful, something that would take a commercial or a campaign to a whole other, higher level.
With the right algorithms, you hold the keys to a creative universe essentially of your own making. Intelligent systems unleashed in this way will race headlong to fracture and recompose, combine elements together in ways that would take a million human minds a million years to complete, and find entirely unexpected connections that elude the conscious human brain.
Ultimately, combined with CGI/VR/AR capabilities, a “finished” end product could be delivered. Don’t like the aircraft image in the fifth scene of the spot? Task the system to make it different.
Want the music bed of that radio commercial to be less bass-y, more upbeat? Cue the algorithms and then listen to what you heard in your head.
As we approach the age when holograms become mainstream parts of our visual environment, the opportunities that AI/ML will present for using that technology for marketing purposes will become manifest. Near-lifelike individuals appearing at your beckoning, addressing you by name, entertaining you, reminding you, educating you, encouraging you . . . the possibilities tempt the imagination.
Neuroscience teaches that the non-conscious mind responds quickly, strongly, and positively to “personalization.” Starbucks figured that out intuitively – their ordering process involves writing your own name on the cardboard cup. Not only does that ensure that you get the nonfat mocha cappuccino that you want, but it also has another, invisible effect: it satisfies the subconscious. It makes you feel recognized – and that in turn “binds” you more effectively with the whole Starbucks experience.
Project that same effect into your living room, when George Clooney appears before you at your beckoning, to tell you – by your first name – all about the latest Mercedes model that you’re interested in. AI and ML are at work here, not only tracking your expressed interest in a new Benz, but also triggering George’s image and programming the hologram to personalize the message.
Follow that with a VR test drive, all in the comfort of your own home, and a visual rundown of all the choices available to you in terms of color and options. Of course, you’ll be able to order at your will as well.
This example begs the larger question of these technologies’ impact on brick-and-mortar establishments, and the economic and societal impacts that will flow from that. Amazon has already revolutionized the shopping experience. Apple and Netflix have done the same with entertainment. Other examples abound, in a host of categories.
AI and ML will effectively “bring the world to you” in much the same sense as digital technology overall brings us the world at our fingertips. The key difference is the power that AI and ML systems have to customize your experience, refine offerings to whatever degree you wish, render aural and visual (and ultimately tactile) stimuli that actively engage you, respond to your needs and desires increasingly intuitively, and generally render unto you an alternative, parallel environment to the real world. We’ve all seen enough sci-fi movies to understand that, over time as the technology becomes ever more sophisticated (and yes, powerful), these two worlds will become increasingly indistinct from each other.
Human nature rules, however. It will no doubt continue to even in this brave new world. We are tribal. We crave human interaction, much as we seek information and entertainment and physical and emotional sustenance. So AI and ML systems will bend to those drives.
Car dealerships are likely to morph from their traditional showroom orientation, to a hybrid of local physical service centers and VR sales methods. Futurists have already predicted the shift from the old-school department store to new models where large-scale entertainment is the centerpiece, and personalization at the POS is keyed to individual needs and interests. Movie theaters will be much more fully immersive multisensory experiences, tailored even more to the “blockbuster” phenomenon we enjoy today.
Marketing in the age of omnipresent AI and ML systems will not only benefit from the powerful potential these systems offer and deliver – it will also face very real challenges.
The human brain is exquisitely attuned to what is “real” and what is not. We evolved that way because such discernment could mean the difference between survival and extinction. Even as immersive as some gaming and entertainment products are today, the non-conscious mind still draws the clear distinction between what it “knows” to be genuine, versus what it perceives as “manufactured.”
AI- and ML-powered processes and products will have to address that eternal truth about the human mind, and strive mightily to achieve the delivery of stimuli that the non-conscious mind will accept as close enough to real to be virtually indistinguishable.
Over time, our brains may adapt to VR worlds to such an extent that they become literally indistinct from reality. A small indication of that kind of adaptability is the pace of visual stimuli today, versus the pace found in the early 20th century. Our visual systems were already capable of processing data at very high/fast rates – all it took was for delivery systems (film, television, and digital) to catch up and deliver data at those higher speeds. Today, we take that for granted – the proof being that watching “old” forms of visual information and entertainment now seems hopelessly slow and labored.
What will it take for marketing to succeed in the Age of AI and ML?
Technological infrastructure is one starting place. The basic assumption is that technological advances in terms of hardware and software capabilities, digital transmission speeds, and related factors will continue and accelerate. Rendering stimuli and environments that will truly engage and motivate discerning consumers is a tall order, but all indications are that we will approach and achieve that systems standard sooner rather than later.
But the rendering of marketing messages and materials that will also win consumers’ attention, emotional engagement, and memory retention poses its own formidable challenges. Coming back to the Big Data point made earlier, having the capacity to do something is not the same as creating methodologies, taxonomies, and skillsets to accomplish something truly worthwhile and effective with it.
Marketing professionals will need to master more in this new age. A fundamental grasp of what algorithmically driven systems are, what they can and cannot do, and most importantly how best to marshal all of the resources necessary to explore and exploit their capabilities, is going to be the new norm.
Business schools will need fundamentally to revisit and revise their current curriculums. Core competency in AI and ML systems and best practices will be “baked into” B-schools’ course offerings, and across more than just marketing. Case studies will bore into how finely tuned algorithms helped drive successful business, product and service, and marketing strategies. (This extends to finance majors as well – AI- and ML-driven investment decisions and products will be even more of a central component in boardrooms and on Wall Street than they are today).
Marketing service companies will undergo similar seismic shifts. Consultancies will compete for (and with) in-corporation talent with well-honed AI and ML skills and know-how. What we think of today as advertising agencies will have to become much more holistic in their strategic and executional approaches to creating and crafting marketing materials. Again, a basic but also sophisticated grasp of AI and ML systems will be the starting point.
Media buying will move from today’s increasingly programmatic-buying technologies to a multidimensional, matrix approach that will factor in more than demographics, viewing, and purchasing patterns. Relying on AI and ML-based systems, media buyers will be “looking over the mountain” as well as at the immediate road ahead, in order to anticipate marketplace and media trends that will arrive at far faster paces than before.
The smartest, most tech-savvy suppliers of information and entertainment will welcome the near real-time feedback from viewers, powered by AI/ML systems, that enable them to adapt their products to respond quickly and accurately to that feedback.
Compensation across many sectors of the business and marketing realm will become more variable and less fixed than today. Fees will ride (on a real-time basis) on the measurable marketplace success achieved by AI and ML systems. Those suppliers with “better” algorithms, more expansive and sophisticated methodologies, smarter and more adept staff, and swifter adaptation skills will prevail and earn the compensatory rewards that reflect those advantages.
An apt, if somewhat incomplete, analogy is a season-winning Formula 1 racecar team. The company with the best/most effective technologies, the most well-trained and motivated pit crew, and a smart and highly skilled set of drivers handling it all have the highest likelihood of succeeding.
It is – and will increasingly be – the core algorithms at the heart of an enterprise that drive it to the finish line ahead of the pack.
But it is not only those core algorithms that will be the decisive factors in achieving that win.
It will be the particular vision of how to combine algorithmically driven technologies, with digital resources, with a deep and meaningful understanding of core neurobehavorial science, with a set of gifted individuals who master them all and make the resulting combination produce something extraordinary: something that not only looks over the mountain – but moves it as well.
It begins with algorithms.
It ends with that glorious, mysterious, elusive, magical moment of “aha!”