Strange Ways AI Disrupts Business Models, What’s Next For Creativity & Marketing, Some Provocative Data
In this edition, we explore some of the more peculiar ways that AI may change business models as well as recent releases for the world of creativity and marketing.
Edition #11 of Implications.
This edition explores forecasts and implications around: (1) business models likely to become antiquated as AI proliferates in more industries, (2) reflections on another round of AI launches in the creative world, and (3) some provocative data and surprises at the end, as always.
If you’re new, here’s the rundown on what to expect. This ~monthly analysis is written for founders + investors I work with, colleagues, and a small group of subscribers. I aim for quality, density, and provocation vs. frequency and trendiness. My goal is to ignite discussion and add some kindling to the fire of feedback and serendipitous dot connecting.
New? If you missed previous editions of Implications, check out recent analysis and archives here. A few highlights (based on what has triggered the most commentary or controversy) include implications of humanity’s declining tolerance for friction, collapsing the talent stack in teams, and the massive wave of personalization coming for us. OK, now let’s dive in…
What business models may become antiquated as AI proliferates in more industries?
We talk a lot about how AI will transform products, industries, and everyday work and life, but what about particular business models?
Increasing perversion of certain business models that are liable to be gamed or constrained by AI: We’re shifting from a world where data analysis required long cycles (analysts need lots of time to run queries, analyze, and then present findings in a way that people understand) to a new world of real-time optimization and insights (AI will mine the data to surface insights and make optimization decisions in real-time). But when businesses start optimizing themselves, all sorts of crazy things might start happening (or at least be suggested by the AI). What wild examples can we think of here? For dating apps, where the perfect match of two people increases churn, will Tinder or Bumble constrain the efficiency of AI so the product doesn’t become too “unsustainably effective”? Or in the world of music streaming: Since Spotify pays artists per song, will Spotify automatically optimize its algorithms to favor longer songs, taking into account the number of minutes each customer listens per day? As AI gets really good at optimization, some industries and business models will need to change.
Time-based business models are liable for disruption via a value-based overhaul of compensation. Today, as most designers, lawyers, and many trades in between continue to charge by the hour, the AL-powered step-function improvements in workflows are liable to shake things up. Let’s first tackle this by considering the ultimate SOURCE of the differentiating value delivered to a client: It is less “time” and it is more “experience.” Of course, there are some exceptions like yard work or lawn-mowing where trade experience may be less of a differentiator in the value delivered, but let’s focus on trades where the spectrum of outputs is long and varied. In such fields, the differentiators that matter are one’s years of experience, honed skills from formal education and practice, one’s taste and intuition, one’s creativity, one’s network of relationships, and even one’s proprietary data and algorithms honed through volume of past experiences. In such a world, time-based billing simply won’t work anymore unless the value derived from these services is also compressed by a multiple (unlikely). The classic time-based model of billing for lawyers, designers, consultants, freelancers etc is officially antiquated. So, how might the value be captured in a future where we no longer bill by the hour? Perhaps there is a new source-of-truth for the “value” of tasks across professional trades via a third-party billing service that determines price. Much like the billing codes and market pricing for medical procedures, these prices could be negotiated with trades and could vary based on one’s years of experience. Or perhaps we enter an era of results-based compensation that is far more objective and measured? In some industries where we start paying less for something, perhaps we end up making up for it in volume? Just sharing early and unformed ideas here, but the implication highlighted here is that new pricing models are overdue to replace time-based and finger-in-the-wind pricing in the age of AI where time is magically compressed.
AI will threaten subjectivity in purchase decisions, and with it the sway of brand and marketing. As we gain trust in the guidance of agent-assisted experiences, will the impact of brand, referral, and relationships in purchase decisions be diminished? Whether we’re buying batteries, sneakers, potato chips, or kitchen appliances, we are often influenced more than we care to admit by brand perceptions as opposed to factual comparisons. However, as your “AI Agent” gets to know you better - infused by every personal preference and previous purchase as well as every online review and consumer reports determination - you may start trusting the guidance of your agent more than any other signal. Perhaps the stakes are even more pronounced in the enterprise, where a procurement process tainted by human emotions, laziness, and previous relationships is the persistent fear of any CFO. How many purchase decisions are made for the wrong reasons - like relationships strengthened by football games and steak dinners with salespeople as opposed to the value and quality of a solution? Companies like Globality (in my portfolio, tackling enterprise procurement) and many others are leveraging AI to radically transform every function of a company. And if you look at this wave of companies overall, they are tackling the tremendous costs of subjectivity in decision making and are designed to yield better and more cost-effective solutions. Ultimately, elevating product meritocracy solves problems in both the worlds of consumer and enterprise purchasing. AI threatens subjective decision making tainted by human error and bias and will usher in an era where the best product at the best value may in fact win. This is a win for buyers, but may be quite disruptive to sellers who fail to innovate and endlessly optimize.
The business of traditional entertainment creation will evolve, but not as we expect. There has been a lot of focus lately, especially from the unions representing actors and writers, on the consequences of AI and potential job displacement. However, I have come to view the future of entertainment as more of a “core and periphery” model, where the core (Hollywood - and all the players involved with original story creation) only gets stronger and more efficient, and the periphery (user-generated content, unsanctioned sequels, and long-tail spin-offs) grows by 100x. As every brand floods the zone of our consciousness with AI-generated content, we will crave story, meaning, and originality more than ever before. The efficiencies of AI reduce the cost of content creation so we can TAKE MORE CREATIVE RISK. Instead of green-lighting five ideas, perhaps we can green-light fifteen? Perhaps Hollywood will spend less time replaying safe playbooks (sequels and familiar storylines) and more time developing NEW franchises and imaginative storylines? With AI, the core can get 10x better, and the periphery will grow 100x larger. The business model disruption here is where the money is spent in traditional studios. Why not offload the derivative content (the sequels, the animated short offshoots, etc) to a select group of long-tail creators and fans that leverage AI…and then reallocate the saved capital to the core? My general thesis about implications of AI across industries: We need to value human ingenuity and free up the capacity of creative minds for higher order tasks.
Mechanisms that help match the best talent with the right opportunities will drive more creative meritocracy - and challenge “old boy” networks. One great frustration I have always had with creativity is just how much “luck” determines whether great ideas see the light of day. In Hollywood, you need to get a fateful intro to an agent. In many other fields, you need to know the right headhunter or be connected to the right agency, which is often more about who you know than the merit of your talent and ideas. Well, imagine a world where IP becomes a little more “open” to a longer tail of talent to play with, but with guardrails (this relates to the periphery type of content we discussed above)? Perhaps a brand like Marvel could invite 100 passionate creators beyond the walls of the studio to engage with their characters using AI models to explore new plot ideas? Perhaps AI will help user-generated content not only improve in terms of quality, but also get exposure from a higher-signal network of curators? So far, social platforms have surfaced content based on what the “critical mass” thinks (number of likes) rather than what the “credible mass” thinks (WHO actually liked the content, and how credible they are as tastemakers).
Reflections on another round of AI launches for the creative world.
This past week, I was in LA with our teams at Adobe launching our latest AI products across Creative Cloud, speaking with industry and financial analysts, and - most importantly - connecting with customers. Here are a few central messages and learnings as it relates to the future of creativity and digital experiences - and the role of AI.
While I try to avoid “talking our own book” in this newsletter, it’s worth highlighting some pretty wild new AI-powered capabilities for the creative world, many of which also empower marketers to modify and personalize content so brands can “think and act in real-time.” Highlights of our announcements included the ability to use text prompts to generate vectors (in the form of gradients, patterns, objects, or icons) in Illustrator, and a mind-blowing ability to generate new images (or vectors) with a reference image using a new feature we call “Generative Match.” Also, if you want a peak into some wild new things brewing in our labs, check out the “Sneaks” that we shared on stage at night. Overall, proud of the teams and also excited to see what customers do with these new capabilities.
The worlds of creativity and marketing are rapidly changing - and rapidly coming together. The stacks of tools used by the creative department and those used by professional marketers have always been rather siloed. As a result, legions of middleware and processes exist to help these functions work together. But in today’s world, where social campaigns need to be made and changed on the fly - and brands leverage more and more platforms and formats to tell their story, the model needs to be reimagined. I shared a few shifts with our investors that emphasize how AI is transforming the worlds of creativity and digital experiences.
Macromarketing and Agile Marketing need to work together. During the MAX conference keynote in LA, I tried to make the case that content is the lifeblood of most companies these days, and every brand is only as relevant as their latest ad, social post, or video. Today, there are more stakeholders of a brand’s stories than ever before – product managers, social strategists, campaign leaders, executives – everyone wants to be involved. To seize the moment, every brand needs to reimagine the way they tell their stories at the speed of social. If you think about it, there are really two tracks of marketing in the modern company. The first track is what I’ve come to call “Macromarketing.” Macromarketing produces big campaigns, the ones that we plan well in advance. It starts with a brief that gets everyone – dozens or hundreds of people – on the same page. It requires getting feedback and approval from a broad array of stakeholders. And going forward, generative AI will help brands hyper-personalize content to appeal to each customer. A steady flow of data helps brands optimize their campaigns. Macromarketing requires a lot of coordination but helps a brand establish its identity and sets the tone for the rest of a company’s marketing. The other track is “Agile Marketing,” and it is becoming more and more vital every day. If Macromarketing runs on a calendar, Agile Marketing runs on a stopwatch. For example, your social team notices a meme or a viral moment and realizes that – if they act fast enough – they can inject your brand in a fun and engaging way. When people around your company are empowered to quickly leverage a template with easy-to-use creative tools and quickly generate variations of an asset using AI, that is Agile Marketing. As marketing becomes more social, more real-time, and more personalized, Agile Marketing will help brands stand out. As storytelling becomes more real-time and social, the modern challenge for every brand is to maintain the integrity of Macromarketing (the core and iconic stuff) while also developing the systems to iterate these stories and outfit others to share them in real-time.
AI Models will win not only with quality, but with granularity. There is a ton of focus on the quality of a model’s output (which is incredibly important). But journalists and analysts often overlook the impact of integrations into workflows and the granular controls for the outputs of these models that often make the difference between viable creative control and commercial use vs. something just being fun to play with. At the MAX conference, we shared a brief glimpse of what we call the “Firefly Editing Engine” in one of our analyst meetings that showcases the power of granular, “non destructive” controls during an AI-powered editing process. It becomes clear that just prompting to get images is a rather elementary use case of AI, compared to the ability to place and move objects, change perspective, adjust lighting, and many other actions using AI.
The best companies in AI will parallel track innovation in features AND responsibility. There continues to be a ton of interest in Content Credentials, the open source effort to show how images were edited and what AI models were used in an era where we can no longer believe our eyes.
Ideas, Missives & Mentions
**Finally, here’s a set of ideas and worthwhile mentions (and stuff I want to keep out of web-scraper reach) intended for those I work with (free for founders in my portfolio, Adobe folks…ping me!) and a smaller group of subscribers. We’ll cover a few things that caught my eye and have stayed on my mind (including some provocative data points and a friend’s helpful framework for how we spend our time). Subscriptions go toward organizations I support including the Cooper-Hewitt National Design Museum. Thanks again for following along, and to those who have reached out with ideas and feedback.
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