Introduction

Over the years, I’ve worked at the intersection of various sectors and innovation, always circling around the same question: how do we turn ideas into action in ways that are meaningful, collaborative, and sustainable? What I’ve learned is that creativity thrives when we listen closely, think systemically, and make complexity a bit more manageable.

That same question eventually brought me into the creative tech space. I’ll admit, technology hasn’t always been where I’m most comfortable. In fact, I’ve often been tech-averse. That discomfort pushes me to lean in, ask sharper questions, and stay curious about what’s really coming next.

At KoobrikLabs, where I now head up business development, our mission is simple but ambitious: help creatives explore and adopt new tools without giving up agency, rights, or control. 

This blog series is part of that mission. Each month, I’ll share foresight signals, some from public data, others from conversations with peers, customers, and friends; as well as insights from our Technically Creative Podcast, industry events, webinars, and conferences. The aim is to help creatives navigate complexity, anticipate change, and make choices that support their innovations.

Why foresight?

Foresight isn’t about prediction. It’s about holding multiple futures in view, spotting weak signals, and asking better questions about what might emerge. I was taught a framework by a former colleague and friend, Pippa Scott, that stuck with me – the Three Horizons framework. It represents an easy way to digest large amounts of conflicting information about emerging markets.

The framework was originally developed by Bill Sharpe of the International Futures Forum as part of the UK Government’s Foresight Programme on Intelligent Infrastructures. The horizons are explained below:

What to expect

Each monthly blog post will capture signals across these horizons: what feels stable, what’s emerging, and what’s shifting. Some of it will be practical, some exploratory, and some openly speculative.

And at the end of the year, we’ll gather these insights into a white paper. This will dive deeper into what we’ve seen and heard, with closer analysis of the trends that matter most for creatives. My hope is that this becomes a living record of how creativity and technology are colliding, adapting, and reshaping each other in real time.

If you’re creative, we hope this series helps you feel less overwhelmed and more prepared – not just to keep pace with change, but to shape it in ways that protect your voice, your rights, and your intellectual property.

Horizon 1: The now

Signals and observations about the current context.

The media and entertainment industry enters 2025 in a paradoxical place: both resilient and under strain. 

Global revenues climbed 5.5% in 2024 to $2.9 trillion, with forecasts pointing to $3.5 trillion by 2029, but the rate of growth will slow each year as consumer budgets tighten. Advertising remains the engine. AVOD platforms like Netflix and Disney+ dominate, while connected TV ad revenues have surged from 6% of the market in 2020 to 21% in 2024, on track to approach half of all TV advertising by the end of the decade. At the same time, legacy formats such as print magazines and physical PC games continue their steep decline. 

Beneath the numbers, the role of technology is shifting assumptions about work, trust, and creativity. The 2023 SAG-AFTRA and Writers Guild of America strikes reinforced a new baseline expectation: AI should support, not replace, creative talent. And yet adoption is uneven. 

Some companies are leaning in, 44% now identify AI as a revenue driver, while many artists remain ambivalent, resigned to the automation of lower-level tasks but insistent on the human contribution where it matters most.

Consumers reflect the same ambivalence. The World Economic Forum point to survey results that suggest:

Even the world of foresight is embracing creative shifts. Diageo created a Foresight System that implements an AI and human monitoring framework. Their recent Distilled report describes trends surfaced from 160,+ online conversations across 180 markets that were tracked from 2021 and 2024. 

It found that consumers are comfortable chatting with bots for simple tasks but increasingly want real human interaction for sensitive and complex issues, and people are discerning about who and what brands they trust. 

In an information-saturated environment, trust and transparency are the scarce resources.

Horizon 3: The future

Signals and speculations about transformative or visionary changes.

Looking ahead, a transformative shift is taking shape. In this horizon, AI is no longer a tool for efficiency but a collaborator in creativity. As more teams become fluent in its use, AI is expected to amplify ingenuity, open new business models, and enable personalized consumer experiences on a scale that was previously unimaginable.

This future is contested. Legal and regulatory frameworks lag behind. Questions of copyright and intellectual property remain unresolved: can AI-generated work be protected, and will artists’ content continue to be ingested without consent? 

Campaigns like Elton John’s 2025 protest against UK copyright policy highlight the intensity of this debate. In response, some companies are experimenting with “walled garden” models, training AI only on cleared, proprietary datasets – for example, the partnership between Lions Gates and Runway AI. 

The EU AI Act, which came into force in 2025, is one attempt to create guardrails, but divergence between the EU, UK, and US means uneven adoption and regulatory uncertainty.

Cultural signals also point to dual trajectories. On one side, experts predict up to 90% of internet content could be AI-generated within a few years, raising profound concerns about trust, authenticity, and manipulation – particularly in elections and conflicts.  

On the other, consumers are pushing back with a desire to “escape the algorithm” – seeking exclusive, local, and craftsmanship-driven experiences that feel unmediated and authentic. 

The governance agenda for this horizon centers on accountability, fairness, and transparency. That means diverse oversight bodies, bias mitigation in model training, disclosure and labeling of AI content, and technical solutions such as watermarking, provenance, and blockchain rights management. 

Yet even in an AI-saturated world, human qualities – emotional resonance, cultural nuance, moral judgment – remain irreplaceable. The long-term future of creativity depends not only on what AI makes possible, but on multistakeholder collaboration across industry, governments, civil society, and creators to shape the boundaries of what is desirable.

Horizon 2: The transition

Signals and observations about shifts, experiments, or adaptations underway.

The creative industries are in the middle of a volatile and uneven transition. AI is no longer just an experimental tool on the margins, it’s weaving itself into production cycles, often pitched as an efficiency gain, but already triggering deeper structural shifts.

In film and music, generative tools are speeding up workflows, while in post-production, dubbing and subtitling platforms like ElevenLabs and Panjaya.ai are unlocking markets that were once prohibitively expensive to reach. Anime studios in Japan are reshoring production, investing billions of yen in domestic AI firms to bring work back in-house.

These shifts are reshaping roles and exposing new vulnerabilities. Creative jobs are being redefined rather than eliminated, but the skills gap is widening. Demand for AI-fluent creatives already outpaces supply. And companies worry about fragility: integrating new tools into pipelines without creating single points of failure is proving difficult.

Culturally, people are negotiating what AI means for connection. The COVID-era boom of independent creators has some-what faded, replaced by AI-enabled relationships as a new medium of connection. Education signals the mainstreaming of this shift, where global GenAI course enrollments grew more than 1,000% in 2024. 

Consumers, however, are drawing hard lines. They demand transparency in AI-generated imagery and media, guarantees of data privacy, and sensitivity toward traditions already under pressure from climate change, demographic shifts, and cultural globalization. 

Bias, hallucinations, and IP infringement are widely cited concerns. And disinformation is spreading fast: deepfake tool exchanges grew more than 200% on the dark web in 2023-24, and AI-generated images exploded into the billions. 

Environmental concerns follow suit. Large-scale AI deployment relies on energy- and water-intensive data centers, drives up e-waste, and already consumes close to 2% of global electricity. One AI prompt is estimated to use nearly ten times the electricity of a standard Google search. As creative tech adoption scales, the tension between creative opportunity and environmental cost will shape both public perception and policy response.

One of the loudest signals this month has been the MIT study claiming that “95% of enterprise AI pilots fail.” It’s a striking number, but worth unpacking. The study defines success very narrowly, as sustained productivity and/or P&L impact. By that metric, anything less is called failure, even if the project delivered learning, cultural change, or early creative benefits. In reality, most pilots are still in flux, and their impact doesn’t show up on a balance sheet yet.

A 2023 Gartner survey offers a useful counterpoint. Their survey of 822 business leaders shows that while many proofs of concept stall, earlier adopters are already reporting measurable gains: on average 15.8% revenue growth, 15.2% cost savings, and 22.6% productivity improvement. They also predict at least 30% of GenAI projects will be abandoned after proof of concept by the end of 2025.

The difference is one of framing. Gartner emphasizes that GenAI requires tolerance for indirect and delayed value, whereas MIT’s framing inflates “failure” by only counting immediate P&L impact. Both point to the same messy middle, but Gartner reminds us that adoption is incremental, costly, and highly context-specific, not fruitless.

This is classic messy middle: early investments feel like failure because they’re slowed by organizational friction, redesign, and learning curves. But those are necessary precursors to transformation. In system dynamics, the delay between investment and payoff isn’t failure at all, it’s the hidden work of adaptation. 

For creatives, this highlights the need to measure success in broader ways: customer satisfaction, cultural shifts, and innovation potential, not just near-term margin.

Seen in this light, the “failure” headlines aren’t the end of the story. They’re signals of where systems are straining, and where governance, oversight, and new skills are most urgently needed. 

Emphasis on skills. The real creative advantage will belong to those who can bridge this gap, experimenting with new tools while holding fast to trust, values, and human voice.

Actionable takeaways & closing

Looking across the three horizons, a few things stand out.

What you can do now

Closing

Right now, the ground is shifting faster than we can always keep up. We’re bound to get some things wrong along the way. But that’s the point of foresight: it’s less about certainty and more about holding space for curiosity, adaptation, and conversation.

If you’ve spotted signals in your own work, have thoughts to add, or want to feature in a future foresight post, please reach out.

For more on these themes, check out the latest episode of our podcast: “Infinite Content: Doug Shapiro on Media in the Age of Disruption.” 

Orlando sits down with Doug – former Wall Street analyst, Time Warner strategist, and one of the most respected media futurists in the business.

From the collapse of cable bundles and Hollywood’s old playbook to the rise of the creator economy, YouTube, and GenAI, Doug makes the case that the future of media isn’t just about efficiency, but about inventing entirely new forms of storytelling.