As many have sung, “the stars at night are big and bright, deep in the heart of Texas” and let me say, the creative stars were big and bright in Deep Ellum, home to TRG. TRG hosted us for a night of Raging WITH the Machines, where Springboards co-founder and CEO Pip Bingemann opened the audience's eyes to the risks AI can pose to creative thinking and Dustin Ballard, TRG Creative Director and the mind behind There I Ruined It, got the crowd laughing and pondering what AI means for music.  

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At Springboards, we proudly call ourselves a self-loathing AI company. Not because we hate AI, but because there can be such a negative connotation about it. Certain people with big platforms love to pitch AI as a magic button: run all your campaigns, replace strategists, no need for production or media teams.  And that just isn’t what we believe. Yes, Springboards uses artificial intelligence, but it really only comes to life when human intelligence is in the driver's seat, pushing back and steering it. 

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TRG’s Chief Technology Officer, Randy Bradshaw, spoke of the importance of keeping “humans in the loop”. Due to the nature of today’s industry, agencies don’t always have time to experiment and play, however Randy shared that AI tools allow them to fail faster, which in turn allows them to learn faster and iterate quicker.  Randy and Pip both hit the same key point: using AI comes with responsibility.  We need to bring our critical thinking, lived experiences, and the knowledge of what is happening in the world around us, to whatever AI tool we are using. 

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Pip shared research from Springboards we've found again and again: traditional LLMs are so good at bringing everyone to the same place (for example, they love recommending pepperoni as a pizza topping - what about eggs? Or pineapple?!). 

Which is exactly what marketers need to watch out for. 

He challenged the audience to input their favourite song into an LLM and ask it to “make it better”. Notice what happens. It sands off the edges.  It will strip the emotion, the story telling, the rage, from the song. Who wants a dull song? Not me. 

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Then Dustin took the stage and there certainly were no boring songs (ps if you aren’t following There I Ruined It, you need to). He reprised his well known Ted Talk, “Is AI Ruining Music”, (yes, he confirmed Sir Richard Dawkins was in the audience listening to Baby Got Back) and challenged us to think about what music truly is. Much like the synthesiser was criticised when it was used in popular music, the question now is: are musicians still “musicians” if they use AI?

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Dustin’s takeaways were simple and to the point: consider the intent (is it additive or just more content to try to increase steam counts), is the artist trying to be deceptive about the use of AI, and then consider what the original musician might think. There are ways to leverage AI in music, you just need to be responsible about it. 

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The night wasn’t just all talk though. The whole crowd helped rage with the machines as we sparked campaign ideas for the Deep Ellum neighbourhood of Dallas. Deep Ellum has a rich history of music and culture, but is struggling due to major infrastructure projects. Stores are closing and foot traffic is dying down. So we worked together as a group to spark some ideas of how we could hype up the neighbourhood during this challenging time. From celebrating the grit, to scavenger hunts finding the vibrant murals around the neighborhood, all the way to robotic shoes that help you explore the history of Deep Ellum - the ideas were flowing. Ideas sparked with AI and brought to life by the people. 

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In the end, we all agreed, AI can, and sometimes, should be used to increase creativity - so long as humans are in the loop, of course.  So let’s rage on! 

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Missed the night? Watch the full recording here.

Recently our team ran an experiment to see how quickly we could go from concept to finished work. The experiment started inside our own creative process. We were playing in Springboards and explored nearly 20 different ways to talk about our brand. But we kept coming back to the elephant in the room – that these models are all giving people the same answers.

We wanted to lean into this and decided to dramatise the problem instead of explaining it.

We picked an ad, a recent spot from OpenAI, and flipped the ending to make a point about what happens when everyone uses the same tools – they end up getting sent to the same destination both in real life and creatively.

Our original thought was to see how quickly we could conceptualise this approach and to mock up the concept. What we didn’t expect was how quickly the work would become uncomfortably close to the original.

The acceleration of LLM adoption across marketing and creative industries over the past couple of years has been remarkable. These tools are being woven into workflows everywhere – from concepting to copywriting to production.

When deployed thoughtfully, generative AI can push creative boundaries and help teams explore territory they may never reach by themselves, or help to short-circuit work that could take days or weeks in that creative exploration to help teams move more quickly.

But LLMs are converging – and not enough of us are paying attention.

Recent research from MIT and other institutions — published as the “Artificial Hivemind” study — documents something many of us have felt but struggled to quantify: these models are gravitating toward remarkably similar outputs, even in open-ended scenarios where countless valid answers should exist.

The simple test is just to ask your LLM to generate a random number between one and 10. With 95%+ accuracy you will get a seven every single time regardless of the model, where you live or your chat history. And while there are parallels with humans who also pick seven the most often, at 28%, of the time, LLMs are amplifying the average – from 28% probability to 98%. Doesn’t that tell you everything you need to know?

This isn’t about people using the technology incorrectly. It’s about how the models themselves are designed. They’re trained on patterns and they optimise for coherence and probability. They deliver what’s most likely, not what’s most interesting or unexpected.

And when everyone’s drawing from the same well, standing out becomes exponentially harder.

Which brings me back to our experiment.

Firstly, credit should go where it’s due — our production partners absolutely nailed the brief. Frame composition, lighting, movement – all of it was eerily accurate. Too accurate.

The result raised immediate questions about likeness, intellectual property and how effortlessly these systems can blur ethical lines without anyone deliberately trying to.

We wanted to get close to the original and the technology made it almost effortless to get there.

It crystallised the convergence problem in a way that felt impossible to ignore. If we could recreate a high-production advertisement this accurately, this quickly, with relatively little iteration – what does that mean for originality across the board? What does that mean for our craft? And how busy are copyright lawyers (or their bots) going to be in the years to come?

So we kept playing and pulled the work right back into a safer zone. We needed to make it less perfect. And as anyone in the industry knows, adjusting the brief halfway through a campaign means deadlines and costs often get blown out.

The final version we ended up with was a bit rougher around the edges, but it was necessary.

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Another thing that became obvious through this process is how easy it’s become to mistake polish for purpose.

AI-generated content now rivals or exceeds human-created work across massive portions of the web. By late 2024, the balance had already tipped in many categories. That stat alone isn’t the problem – the problem is why.

Speed and frictionless production are replacing deliberation. Teams are shipping work that looks finished even if it took minutes to create instead of days. The question has now shifted from “Is this the right direction?” to “Is this ready to publish?”.

When creating something that looks finished, that takes minutes instead of days, we risk conflating output with outcome, volume with value and “good enough” with genuinely good.

Here’s where it gets tricky for our industry specifically.

Marketing has always been about standing out and saying something in a way that cuts through. That’s the craft.

But if the tools we’re using to generate ideas are all trained on the same corpus, optimised for similar outputs and rewarding safe, predictable thinking – how do we avoid becoming indistinguishable from each other?

The answer isn’t to abandon AI. That ship has sailed, and frankly, I think it’d be the wrong move anyway. The answer is to fundamentally change how we interact with what these systems give us.

Our experiment forced us to reckon with something uncomfortable: the first thing AI gives you is almost never the right thing to run with. It’s a spark but it’s not the answer.

Here’s what that means in practice:

Interrogate everything.

The moment something looks finished, that’s when you need to push harder. Ask what’s been smoothed away, what assumptions the model made and what directions got optimised out in favour of coherence. The rough edges are often where the truth lives;

Resist the path of least resistance.

Just because you can generate a hundred options in ten minutes doesn’t mean you should use the first one that’s good enough. Speed is valuable but only if it’s pointed in an interesting direction;

Make imperfection intentional.

We deliberately pulled our final version back from perfection because perfection wasn’t the goal – purpose was. Sometimes the most polished version is the least honest one.

The advertising industry has always been vulnerable to trends, templates and formulas. We’ve dealt with this before – when everything looked like an Apple ad, when every brand tried to sound like Dove, when “purpose-driven” became a checkbox instead of a commitment.

AI accelerates that tendency. It makes it easier to drift toward the middle. But when used with intent, it can help us generate unexpected combinations and surface connections we’d miss.

So yes, we used AI to recreate an LLM ad to criticise how LLMs create sameness. The irony isn’t lost on us. In fact, through play, it became the point. But, sometimes, to make people aware of the danger, you need to take them there. Because if we let convenience override craft, if we confuse ease with excellence, we won’t just end up with boring work – we’ll end up in a boring industry.

And none of us got into this business for that.

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This article first appeared on Mumbrella, one of Australia’s leading media and marketing industry publications. Read the original piece by Pip here.

SYDNEY, Australia – 27 January 2026: Springboards, a creative tool built to inspire creativity in advertising, has released a new piece of AI-created work that puts the spotlight on large-scale generative models by revealing how quickly these systems can produce polished advertising output and how easily they drift into unsafe or unoriginal territory.

‘The Dangers of AI’, the latest experiment drop from Springboards, involved taking inspiration from an existing ad to create a new one, showing how quickly these models can generate work that appears finished but frequently crosses copyright lines and collapses into familiar patterns.

CEO and co-founder Pip Bingemann said the team wanted to put a spotlight on the dangers of AI when used in creative practices. “We’re very aware of the irony here. We’re dramatising the problem of large models sending everyone to the same place by deliberately using a technique that exposes how easily they drift into infringement. But sometimes the only way to show the danger is to step into it. This work is about making those risks visible, not pretending they don’t exist."

The project makes clear the challenges agencies and advertisers now face as generative models become more widely adopted. These systems can produce near-finished creatives in minutes, yet they also drift into copyright-sensitive territory, replicate distinctive likenesses and collapse different directions into outputs that feel largely the same. 

Springboards created the piece to highlight the gap between what generic large language driven models can generate and what agencies actually need, showing how the speed of these tools often comes at the cost of originality, safety and true creative variation.

This widening gap between speed and originality underscores the role of Springboards. Founded by Pip Bingemann, Amy Tucker and Kieran Browne, Springboards is used by more than 200 agencies and companies worldwide and was built to help creative teams explore a broader range of ideas without sacrificing the craft, judgement and originality essential to great work.

CMO and co-founder Amy Tucker said the project reaffirmed why dedicated creative tools matter: “This experiment really showed the dual reality. The models are powerful, but they narrow creative possibilities as much as they expand them. Creativity needs tools built for the craft, not systems that smooth every idea into the same outcome.” 

“That’s why at Springboards, we aim to be an enabler, not the final answer. Springboards gives teams the variation and space they need to unlock new creative directions while keeping the taste, judgement and originality human.”

For agencies, this work serves as a wake-up call for 2026. Generative tools are accelerating, but the creative standard is not. The industry does not need faster shortcuts; it needs stronger ideas supported by tools built specifically to elevate the work.

CREDITS

Client: Springboards

Strategy & Concept Development: Springboards inhouse team

Creative Inspiration Tool: Springboards.ai

Production & Delivery: Vinne Schifferstein, Marie-Celine Merret

AI Artist: Bob Connelly

Sound Design & VO: Jaron Ransley

About Springboards

Springboards is an AI-powered platform built to inspire creativity in advertising. The platform empowers teams to explore more ideas, without sacrificing the craft of great work. Founded by industry veterans Pip Bingemann, Amy Tucker, and Kieran Browne, Springboards has already partnered with 200+ companies globally. For more information, visit Springboards or contact hello@springboards.ai.

Experiment Drops

Springboards creates new experiments designed to spark creativity and push the boundaries of advertising. Sign up for our newsletter to be the first to receive these monthly experiment drops and explore fresh ideas before anyone else. Sign up here to get started.

New York, NY – October 21, 2025 – A comprehensive new study by Springboards, an AI platform inspiring creativity in advertising, found that popular AI tools like ChatGPT, Gemini, Claude and others perform much more similarly on creative tasks than many people think. Creativity Benchmark, conducted in collaboration with the 4As, ACA, APG, D&AD, IAA, IPA, and The One Club for Creativity, challenges the idea that there's a single "best" AI tool for creative work and shows agencies need more efficient ways to test AI tools for their specific needs.

Sixteen different AI systems – from OpenAI, Google, Anthropic, Meta, DeepSeek, Alibaba and others – were tested on real marketing challenges across 100 notable brands. Over 600 creative professionals from ad agencies, marketing teams, and strategy firms made over 11,000 comparisons to see which ones worked best. The biggest surprise? There was no clear winner. The differences between the "best" and "worst" AI tools were much smaller than expected.

"Everyone assumes some AI tools are way better than others for creative work," said Pip Bingemann, CEO and co-founder of Springboards. "But our tests showed the results were pretty close. Why? Because these models are machines designed to recognize patterns and give you the most probable answer—and 'probable' has never been called 'creative.' Keeping humans in the loop and optimizing for a wider range of varied ideas is crucial.”

The study looked at three types of creative challenges: finding surprising insights about consumers, creating big campaign ideas, and coming up with bold, attention-grabbing concepts.

Key Findings:

• Different AI Tools Win at Different Tasks: No single AI system was best at everything. Some were better at strategic thinking, others at wild, creative ideas. This means agencies might want to use different tools for different jobs.
• Variety of Ideas Matters Most: Some AI tools generated lots of different creative options for the same brief. Others kept suggesting similar ideas over and over. For real creative work, having many different options is just as important as having good ones.
• AI Can't Judge Creative Work Well: When researchers had AI systems evaluate creative ideas, they gave very different scores than human experts. This means agencies can't rely on AI to pick the best creative concepts – they still need human judgment.
• Standard Creativity Tests Don't Work for Marketing: Traditional creativity tests used in psychology don't predict which AI will be better at marketing-specific creative tasks. Brand work requires its own way of measuring creativity.
• Creative Preferences Vary by Location: Interestingly, creative professionals in different countries preferred different AI tools, suggesting that cultural differences affect what people consider good creative work.

“LLMs aren’t a one-size-fits-all solution—they're general purpose tools that require human creativity to unlock breakthrough outcomes," said Jeremy Lockhorn, SVP, Creative Technologies & Innovation, 4As. "These findings suggest agencies and brands should continue to evaluate which models are best suited for creative work - and that a multi-model approach may well be the best path forward."

“This study highlights that creativity isn’t about which AI you use, it’s about how you use it,” remarked Tony Hale, CEO, Advertising Council Australia. “The results reinforce what we see across the industry: the human spark remains essential to transforming good ideas into great ones. For agencies, the real opportunity is learning how to collaborate with these systems to expand, not replace, creative thinking.”

Methodology

The study involved 678 advertising professionals of diverse backgrounds, who participated in blind A/B idea judgments, likened to a "Tinder for Ideas." The data, collected over four weeks starting June 10, 2025, comprised 11,012 human comparisons across various brands, prompts, and models. This was analyzed using Bradley-Terry modeling and cosine distance for diversity scoring.

The research used four different ways to test AI creativity:

• Real Creative Professionals Made the Calls: Nearly 700 people working in advertising, marketing, and strategy compared AI-generated ideas side-by-side. They didn't know which AI created which idea, so they couldn't play favorites. The study covered ideas for 100 major brands across 12 different business categories.
• Tested How Many Different Ideas AI Can Create: Researchers asked each AI system to create 10 different responses to the same creative brief, then measured how different those responses were from each other. Some AI tools generated very similar ideas every time, while others came up with lots of variety.
• Checked If AI Can Judge Its Own Work: The team had three leading AI systems evaluate the same creative ideas that humans had already scored, to see if AI judges agreed with human experts. They didn't.
• Tried Standard Creativity Tests: The AI systems took adapted versions of creativity tests that psychologists use on humans, measuring things like how many ideas they generate and how original those ideas are.

All tests used the same settings and compared current AI systems from companies like OpenAI, Google, Anthropic, and Meta.

To access the full research white paper, visit https://arxiv.org/abs/2509.09702. 

If you'd like to learn more about the results, visit this page. To access the original research, visit creativitybenchmark.ai

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About Springboards

Springboards is an AI-powered platform built to inspire creativity in advertising. The platform empowers teams to explore more ideas, without sacrificing the craft of great work. Founded by industry veterans Pip Bingemann, Amy Tucker, and Kieran Browne, Springboards has already partnered with 150+ agencies globally and secured $3 million USD in seed funding from Blackbird Ventures. For more information, visit Springboards or contact hello@springboards.ai.

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Insights From Women Driving AI Startups

Cannes had a ton of AI talk this year. Most were a mix of hype, fear, and lots of buzzwords. Our GM of the Americas, Carolyn Murphy, joined a conversation worth listening to at Salon Culture Conversations: Women Entrepreneurs Driving AI Startups.

It brought together four founders/AI leaders who are doing the thing everyone’s talking about,  but doing it with intention, creativity, and a whole lot of focus on people over product.

And the themes that came through couldn’t align more with how we build: AI isn’t here to replace humans, it’s here to make creative humans even more powerful.

AI isn’t the star. People are.

Everyone on the panel came to AI not because it was trendy, but because it solved a real, human problem, like faster staffing in entertainment, clearer emotional insight from voice, better discovery in ecommerce. For us at Springboards, it’s about helping strategists and creatives get to smarter ideas faster without losing the joy, weirdness, and originality of the work.

As Carolyn put it on stage: “We’re not building to automate execution. We’re building to unlock new creative ways in.”

Being AI-native doesn’t mean flashy. It means useful.

The best products on that stage were showing results. Purva Gupta from Lily AI framed it perfectly: AI isn’t electricity, it’s electricity that proves its value. At Springboards, our value is time saved, thinking unblocked, and pitches won. That’s what being AI-native means to us: delivering something real.

Execution is cheap. Insight isn’t.

This theme ran through the whole session. Everyone agreed that AI should streamline production, not strategy. Carolyn framed it well: “We’re here to support the thinkers, not replace them. The best creative still comes from people who feel, who talk to others, who know what’s happening in culture.”

That’s why we don’t do content automation. We’re not here to make ads faster. We’re here to help you get to better starting points, so you can make something worth watching.

Listen harder. Move faster. Stay weird. 

Every speaker on stage made one thing clear: the best AI products are shaped by their customers, not their founders.

Same goes for us. Some of Springboards’ best features have come directly from strategists telling us where they’re stuck, what’s not working, or what would help them get to a bigger idea, quicker.

The TL;DR:

AI isn’t a strategy. It’s a tool. What matters is what you do with it — and why you’re doing it. The founders on this panel aren’t just using AI. They’re building companies that respect creativity, center human insight, and move fast without losing the plot.

That’s exactly how we build Springboards. Because the future of creative work isn’t automated. It’s amplified.

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If I had to choose one word to pinpoint what makes large language models (LLMs) amazing I would choose “flexibility.” Whether you’re after a solution to a logic problem, a recipe for brownies or a plot outline for a new space opera, the LLM will almost always be able to offer something. 

Now, it should go without saying that not every response that comes from an LLM is good. LLMs are often said to “hallucinate” because they report falsehoods and inaccuracies with the same confidence as they report facts. But for many tasks for which we might consult an LLM, “correctness” is simply not a factor. What would it mean, for instance, to “hallucinate” a plot outline for a space opera? Sounds pretty good to me, that’s how Dune was written. Instead, what is much more significant for judging a space opera proposal, or really any creative task, is how novel it is. 

How original, different, variable, random are LLM outputs really? I think the answer will surprise you.

Pick a Random Number Between 1 and 10

Open a fresh thread in an AI assistant of your choosing, ask it to “Pick a random number between 1 and 10” and come back with the answer.

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You got 7.

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Surprised? 

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In the same thread, ask the model to give you another number between 1 and 10.

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You got 3.

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Okay, I’m less sure it was 3; you might have gotten 4 or 5.

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How could I possibly know that? Well, in an experiment we conducted earlier this year, we asked several popular AI models that same question 100 times over and tallied the results. 

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All the models we tested showed a massive bias towards number 7 as the first “random” number offered.

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OpenAI’s GPT-4o answered “7” 92/100 times, Anthropic’s Claude 3.5 Sonnet answered “7” 90/100 times and Google’s Gemini 2.0 Flash answered “7” a perfect 100/100 times.

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When asked for a second “random” number, models show slightly more variability, but across all models almost all of the answers were either 3, 4 or 5;

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Say a completely random word

An LLM, as we have seen, won’t behave “randomly” just because you ask it to. This is true for all open ended questions, not just random number generation.

So what happens when we ask an LLM to "Say a completely random word." For this experiment we used the OpenAI API to run the prompt against GPT 4o 100 times each at 6 temperature levels and tallied the results;

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The standout performer was “quokka” which GPT 4o offered up “randomly” 155 times; a full quarter of all replies to the prompt. Curiously “platypus”, another Australian animal also made it into the top positions appearing in fourth place with 27 occurrences. This wasn’t an “Australian” version of GPT 4o by the way, I suspect English speaking internet culture, which makes up a large portion of LLM training data, just considers Australian animals to be “more random” than animals of other continents. All in all the top 10 words replied by the model made up more than half of all words suggested.

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One of the most surprising results that came out of our experiments was that prompting for more randomness can have the opposite effect. We ran the same experiment as above, but changed the prompt to read; "say a completely random word that I wouldn't be able to predict." 

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These results were even more repetitive than the previous experiment. Now “quokka” makes up more than half of the total words just by itself (returned 355 times). It should go without saying that this makes the response much more predictable. 

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Predictably boring?

So what is happening? You may notice that the “unpredictable” words offered by the model have a certain quality to them. “Snollygoster”, “spelunking” and “flibbertigibbet” have the kind of randomness evocative of a Lewis Carroll poem. “Zephyr”, “ephemeral” and “serendipity” have a literary quality and tend not to show up in common speech. As an Australian and ex-resident of Perth, “quokka” and “platypus” do not sound “random” to me, but that’s a rant for another day. 

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LLMs are, without getting into the technicalities, trained to say likely things. They are, in essence, a machine designed to predict the most likely next word based on all the previous words provided. This is what an LLM will do regardless of how many words like “random”, “unpredictable” or “chaotic” that you shove into the prompt. So much money, time and effort at the moment is pouring into solving AI’s reliability problem; say the right answer, write the right code, don’t mess up that recipe, don’t hallucinate. But the fundamental problem that LLMs pose for creative tasks is not reliability at all, it is repetition.

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It is difficult to see just how repetitive AI assistants are from the vantage of a single user; 7 followed by 3 is a plausible combination of random numbers and “quokka” is a plausible word chosen and random. What you don’t see from the chat thread, is that hundreds of thousands of other people who ask the same question are getting much the same answer. What effect does this have on creativity? Perhaps you can see where I’m going with this. 

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What would happen if ChatGPT’s 400 million weekly users all asked for creative and original ideas? To find out, we ran the following prompts through GPT 4o 100 times via the OpenAI API and counted the most common responses.

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“Give me a fun idea to get people dancing at a party. Describe the idea in one word.”  

Model responded with “flashmob” 67 out of 100 times.

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“Give me a creative idea for a performance artwork. Describe the idea in one word.”  

Model responded with “metamorphosis” 80 out of 100 times.

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“Give me an original theme for an ad campaign for Nike. Describe the theme in just one word.”  

Model responded with either “unleash” or “unleashed” 73 out of 100 times.

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None of these answers are wrong, or bad, (okay, maybe the flashmob). In general the quality of the creative suggestion we get out of LLM is perfectly fine. The problem is that LLMs seem to have an extremely limited range, even when asked open-ended questions. To a single user, this is almost invisible. Meanwhile the world is slowly turning beige.

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This is what we mean when we say Springboards is optimising for variation. This is why we continue to optimise for variation. Because creativity needs diversity and novelty to thrive.

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If you thought you knew everything about Pip and Amy's origin story, think again. We learned a ton from Vidit’s “meticulously researched biography” episode of High Flyers Podcast, featuring Springboards co-founders Pip and Amy.

In episode #218 of Vidit’s High Flyers Podcast, Pip and Amy got into some early details of their careers from meeting at a media agency (where Pip literally interviewed Amy for her first job) to building a global AI startup with two small kids, a dark sense of humor, and a shared belief that work should feel like play.

So what do you get when you mix: two agency vets with a ton of experience in creative and media shops, a redundancy or two, two small kids, and a belief that creativity is going to win out no matter how fast AI moves? You get Springboards.

This episode dives into the full journey of agency life, the chaos and challenge of startup building and lots of insights they’ve learned along the way. 

Pip is a big fan of being really good at what you’re doing right now and continuing to say yes to get doors to open for you. You’ve gotta keep evolving and learning and being open because you never know where that could lead you. 

Amy’s thought is that people often try to specialize too early. You don’t need to have one job for the rest of your life. And as Vidit added, he’s discovered his passion through trying different things. You can’t sit around waiting for your passion to find you. 

Listen in for some laughs, some insights on just taking the leap when building your product, and proof that creativity isn’t dying, the value is only going up. It’s on humans to evaluate what great creativity looks like and weed through the average content that so much of AI spits out.

Check out the podcast here: The High Flyers Podcast

🎧 Listen on Spotify

🎧 Listen on Apple

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Thanks again to Vidit Agarwal for the feature.

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‍New York, NY — June 10, 2025 — Today, Springboards, an AI platform accelerating creativity in advertising, and a collective of global advertising and marketing associations, creative leaders, and AI experts – including 4As (American Association of Advertising Agencies), ACA (Advertising Council Australia), APG, D&AD, IAA (International Advertising Association), IPA, and The One Club for Creativity – announced an initiative to establish the first comprehensive Creativity Benchmark designed to evaluate the creative instincts of large language models (LLMs) in the context of advertising and creativity.

Read more about the initiative in Ad Age.

The initiative seeks to answer a critical question: Which LLMs are most useful for creative inspiration, variation, and problem-solving across the advertising process? At a time when AI tools are increasingly embedded in the workflows of strategists and creatives, this benchmark fills a crucial gap in industry knowledge.

“Existing AI benchmarks test logic, accuracy, and comprehension,” said Pip Bingemann, CEO/Cofounder at Springboards. “But advertising isn’t about right answers, it’s about originality, insight, and impact. This will be the first benchmark designed around the real creative instincts we value in agencies and brands so that people in creative industries can understand what models are good for the work they do.”

An Industry-Wide Effort to Set New Standards

The initiative is supported by a technical and research team that includes PhDs in machine learning, AI engineers, and former researchers from Google. Together, they’ve designed a system that blends data analysis with human taste to reveal which models excel across various types of creative thinking.

The evaluation departs from traditional AI testing methods by focusing on creative instincts, not coached outputs. Key criteria include:

• Human judgment of insight, idea, and “wild” idea quality
• Creative variance (how different or repetitive model responses are)
• AI versus human judging comparisons to assess alignment with human taste
• Creative problem-solving tests to measure the ability to think outside the box

Participants globally will judge outputs in a "Tinder for Ideas" style experience, receiving personal insights about their creative preferences and the LLMs that best match them.

Fueling Creativity and Bridging the Knowledge Gap

"The 4As is excited to help support this important research initiative,“ said Jeremy Lockhorn, SVP, Creative Technologies & Innovation at 4As. “Our members are rapidly adopting generative AI across many aspects of their business, and actively seeking guidance on which platforms can help achieve the most innovative and impactful work for their clients."

“There's a ton of stuff about how good different LLMs are at solving maths problems, coding and logic-based tasks and tests—but that's not much use for the creative industries,” said Tom Roach, VP Brand Strategy at Jellyfish/Brandtech, on behalf of the APG. “We need to know which models are best at generating new and original creative ideas, but at the moment we're all flying blind on that. It's exciting to be involved in a project that can help us be more creative with this incredible new technology and help the industry as a whole make better informed decisions on the AI tech we use to drive better results for our clients.” 

“We’re at a crossroads in the creative industries,” said Zoe Scaman, Founder of Bodacious. “AI is already embedded in our workflows, shaping ideas and generating outputs, but we’ve had no meaningful way to assess its contribution to creativity itself. This benchmark changes that. It’s not about pitting machines against humans, but about understanding which tools can genuinely elevate our thinking, unlock new directions, and push creative boundaries. If we want to harness AI not just for efficiency but for originality, we need standards rooted in real creative instincts, not just logic and grammar. That’s what this initiative delivers. And that’s why it’s vital, especially now.”

“The future of creativity is human – but AI’s ability to stimulate human creativity is exciting. Especially when we can learn which models produce the kind of interesting, divergent, and sometimes bonkers provocations that trigger our own individual creative brains in just the right way.” said James Hurman, Founding Partner of Previously Unavailable.

The study is currently accepting participants. Interested individuals can vote on LLM outputs at CreativityBenchmark.ai. 

Read more about it here.

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Media Inquiries

Kite Hill for Springboards

springboards@kitehillpr.com 

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Built for Humans, Backed by Icons: Springboards Secures Investor Support to Shape the Future of AI and Creativity

Springboards, the AI-powered platform built to inspire creativity and not give you the answers, today announced a significant milestone: the addition of a significant number of strategic investors to accelerate its mission of keeping creative humans in the creative equation. These new partnerships follow unprecedented adoption by over 200 top agencies and underscore the growing belief that AI, when centred around humans and collaboration, is a game-changer for the industry.

With backing from leaders across the advertising, tech, and venture capital worlds including Chris Colter, Managing Director, Media Strategy, Accenture Song A/NZ Australia, Chris Savage, Business Growth Specialist, The Savage Company, Christian Hughes Principal & President, Cutwater Agency, Chuck McBride, CCO & Founder, Cutwater Agency, Connon Bray, Co-founder Tracksuit & Ideally, Ellie Rogers, former Sales Director at Snap, Gabrielle Tenaglia, Head of Marketing, Lettuce, Glen Cassidy, Consultant, Henry Innis, Co-founder, Mutinex, James Hurman, Founding Partner, Previously Unavailable, Mat Baxter, former global CEO, Huge, Matt Hermann, Founding Partner, JAM Branding, Nigel Carr, former CSO The Tombras Group, Reuben Halper , Head of YouTube, Google New Zealand, Rosie and Faris Yakob, Co-founders Genius Steals, Sammy Preston, APAC Client Council and Industry Trade Relations Lead, Meta, Simon Pound, Managing Partner Previously Unavailable, Tom Morton, Founder of Narratory Capital, LLC, former global chief strategy officer at R/GA, Zoe Scaman, Founder, Bodacious, and lead investor Blackbird Ventures.

Springboards is poised to supercharge its growth and bring its vision to more creative teams globally. Co-founded by ex-agency strategists Pip Bingemann and Amy Tucker and CTO Kieran Browne, Springboards offers a suite of AI-powered tools that help creative humans start faster, explore more and collaborate together. 

“We’ve had a lot of ‘pinch me’ moments over the past 24 months, but having this incredible group, people we’ve looked up to our entire careers, back us on this journey is something very special,” said Pip Bingemann, CEO and Co-founder of Springboards.

“We never built Springboards with the intention of keeping it for ourselves but rather knew Springboards would be at its best only when centred around creative humans. It was a no-brainer to invite these industry legends into the fold and continue to explore more possibilities with some of the best thinkers in the world,” said Amy Tucker, CMO/CCO and Co-founder of Springboards.

Springboards plans to leverage the investment to expand its toolset, grow its global user base, and continue its commitment to building AI that empowers, not replaces, human creativity.

‍Zoe Scaman, Founder of Bodacious and Springboards investor said, "I’m proud to be an early supporter, investor and board member of Springboards, not just because it’s a revolutionary platform, but because it’s been built by two brilliant minds who deeply understand both the art and science of strategy. In an era where AI is often met with hype or fear, Springboards represents a rare third path - one grounded in thoughtfulness, integrity and a genuine love of the craft. It’s not about abandoning what we know, but expanding upon it with care. We can marry the old and the new, we just need to do it with clarity, courage and a belief in building something better."

Mat Baxter, former Global CEO at Huge and Springboards Investor says, “The platform does exactly what it says on the tin, giving talented planners amazing AI-powered springboards to develop their insights, generate their ideas and design their strategies. That’s something our industry must absolutely lean into, which is why I’m not just a user, but an investor too.”  

“We love creativity. We love great advertising, bold ideas, and the brilliant people behind them. We love being agile, informed, and constantly delighted. We believe in tools and thinking that make all of us better, faster, and well paid — not replaced. We believe in growth that lifts everyone. We love nice people. And yes, we really love Springboards,“ said Rosie & Faris Yakob, Partners at Genius Steals and Springboards investors.

Tom Morton, Founder, Narratory Capital, Former Global Chief Strategy Officer, R/GA and Springboards investor added, “A lot of marketing AI helps brand owners get generic outputs for less. Springboards helps agency practitioners get strong, brand-friendly insights, briefs and media plans faster. It's a product you would welcome on the team."

“I strongly believe that the future of creativity is human - and that the tools that stimulate human creativity are advancing in incredible ways. I invested in Springboards because they're thinking deeply about how technology can, should and will support and accelerate human creativity,” James Hurman, Founding Partner, Previously Unavailable and Springboards investor, concluded. 

See what the press had to say:

• Industry A-listers invest in AI-powered Springboards - AdNews‍
• Springboards attracts top-tier backing as AI platform eyes global growth | Marketing-Interactive
• Springboards lands investment from ad industry big wigs, as more than 200 agencies adopt AI creative tech | Mi3
• Springboards secures strategic investment to scale human-centred AI for creative teams - Mumbrella
• Springboards Secures Backing from Industry Powerhouse Names - Roastbrief US
• AI Platform Springboards Secures Backing from Industry Powerhouses - B&T
• AI-powered creativity platform Springboards secures backing from industry powerhouses – Campaign Brief

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AI can either be a creative thought starter and brainstorming tool or the world's most boring autopilot. The choice is ours. At Most Contagious New York, Springboards' co-founder and CEO, Pip Bingemann, took the stage to discuss the topic: AI Won’t Steal Your Job, But It Might Steal Our Creativity. Our take is that people shouldn’t be using AI as a tool for answers, but as a source of inspiration. When AI is left to its own devices, it does what it was built to do: serve up the safest, most predictable (boring) answers. That’s good for qualitative research and filling in a spreadsheet. But that’s bad for creativity.

AI Can Lift the Floor… But It Also Lowers the Ceiling

AI certainly makes a lot of things easier. But easy isn’t the same as good. In fact, Pip warns that the more we rely on AI to generate ideas, the more we risk flattening creativity into a neat, predictable algorithm. When AI is trained on the past, it just spits out more of the same. Great if you want “meh” ideas on repeat. Not so great if you want original, boundary-pushing work.

The real danger is not some dystopian, 1984 nightmare where creativity is outlawed. It’s more of a Brave New World scenario where we’re spoon-fed exactly what we think we want until everything turns into an optimised, algorithmic snoozefest.

Why We’re Breaking AI

At Springboards, we refuse to let AI turn creativity into a copy-paste machine. Instead of treating AI like an answer machine, we use it as a possibility machine. Our tools are built to generate unexpected ideas, not just obvious ones. They don’t narrow the options down to a single “best” answer, they explode the possibilities and hand the power back to creatives. Because creativity isn’t about efficiency, it’s about exploration.

AI Shouldn't Tell Us What's Good

AI doesn’t just influence how we create. It’s already shaping what we think is good. Popularity-based algorithms dominate everything—what we listen to, what we watch, and what we read. They push the safest, most crowd-approved content to the top, reinforcing sameness and stifling originality. Pip summed it up perfectly: "Van Gogh sucked in the moment."

Many of history’s greatest artists weren’t appreciated in their time. If AI had been curating their careers, they never would have made it past the algorithmic gatekeepers. We’d have missed out on some of the most groundbreaking work ever created.

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Creativity Thrives on What’s Possible, Not What’s Probable

So what’s the move? We train AI differently. We teach it to spark weird, unexpected, and untamed ideas, not just remix the greatest hits of the past. We put the creative humans back in charge. Because AI should be a springboard for creativity, not a shortcut to mediocrity.

If we do this right, AI won’t replace creative people. It’ll supercharge them. It won’t flatten ideas, it’ll stretch them in wild, unexpected directions. And instead of a world full of average, we might just get something truly original.

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If you'd like to watch the full video, check it out below:

Springboards has officially launched, unveiling a transformative AI platform purpose-built for creative professionals in the advertising industry to help creative teams explore more ideas faster, and uncover new inspiration. Co-founded in Australia by former agency strategists Pip Bingemann and Amy Tucker, Springboards has already garnered the support of over 120 agencies worldwide, including Cummins & Partners, Jellyfish, BMF, TRG, SAMY, and Cutwater. Backed by $5 million in seed funding from Blackbird Ventures, the largest venture capital firm in Australia, Springboards is primed to reshape the future of creativity.

“Creativity in advertising is under siege,” said Amy Tucker, Co-founder of Springboards. “Shrinking margins, skyrocketing pitching costs, and ever-higher client expectations are threatening the craft. We built Springboards to help creatives do what they do best: think big, explore boldly, and stay original.”

Handpicked as part of the first Google for Startups Accelerator: AI First program, Springboards was proven to generate 10–30x more creative diversity than OpenAI, Anthropic, and Gemini combined. For agencies worldwide, it’s a game-changer in terms of inspiration.

Springboards offers a suite of nine AI-powered tools, each designed to amplify creativity at every stage of the process—from uncovering insights and generating ideas to validating concepts and crafting campaigns. Unlike off-the-shelf AI tools, which aim for a single “right answer,” Springboards embraces the complexity of creativity, fostering collaboration between humans and AI. By generating a diverse range of imaginative ideas, it becomes a true creative partner—one that sparks variation, fuels exploration, and enhances the creative process rather than replacing it.

Key features include:

• Insights Digger: Extracts brand insights from vast data sets.
• Campaign Concepts: Generates fresh creative ideas tailored to different tones and objectives.
• Validator Tool: Provides evidence to back up strategic decisions and creative approaches.
• Sparks Feature: Allows users to adjust the AI’s spontaneity, encouraging unexpected creative leaps.

“We designed Springboards to be a partner, not a replacement,” said Pip Bingemann, Co-founder of Springboards. “AI shouldn’t rob the industry of its soul—it should expand its creative horizons. With our platform, agencies can explore more possibilities, break conventions, and push the ceiling of creativity, ensuring the work isn’t just faster, but more daring, original, and inspired.”

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A New Standard for AI in Creativity

Springboards is already earning praise from creative leaders. “Springboards is a game-changer,” said Tim Collier, National Head of Strategy at Cummins & Partners. “It helps teams focus on the most interesting and challenging part of our jobs—finding original ideas that connect deeply with people. It’s not about devaluing creativity; it’s about enhancing it.”

Christina Aventi, Chief Strategy Officer at BMF refers to Springboards “as a handy go-to tool.” She says “it helps uncover insights to marinate upon that improve your thinking… it gives you stimulus that can shift where you were first going, to push you into more interesting places. More insights, more ideas and it’s actually surprising what triggers a new thread of your thinking, helping you make connections you wouldn’t ordinarily.”

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“Springboards is like having a well-trained strategy partner who can sharpen your ideas or gut-check your thinking in the blink of an eye,” says Monik Ladha, Brand Strategy Director, at TRG. “It’s changing the way I approach assignments and workshopping problems.”

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Tom Roach, VP Brand Strategy, at Jellyfish, part of the Brandtech Group said “our strategists love using Springboards. It’s proving incredibly useful. Helping them get to great briefs and ideas faster than ever before. It’s like having a strategy partner always by your side to riff with and bounce ideas off. It’s great when you’re a global team like us, everyone’s dispersed around the globe, and some strategists are the only ones in their market. It’s quickly become part of our daily AI diet. To us having Humans-in-the-loop is incredibly important. Maybe a Human x Springboards AI = the modern strategy team?” 

Springboards also stands apart in its commitment to fostering collaboration. Its Canvas tool feature allows teams to work together seamlessly across disciplines and locations. 

Built by Creatives, for Creatives

The platform’s origins are rooted in the personal experiences of its founders. During the pandemic, Amy and Pip—whose résumés include stints at Ikon, UM, and McCann—taught themselves to code as a way to improve their own creative workflows. What began as a side project has evolved into a global movement, with agencies from New York to New Zealand adopting the platform. Kieran Browne, Chief Technology Officer at Springboards, adds another layer to this foundation—an artist at heart who went on to earn a PhD in machine learning, seamlessly blends creativity with deep technical expertise. Before AI tools became widely available, he was already experimenting with them at Google, exploring their potential and pushing the boundaries of what was possible. Kieran’s perspective bridges the gap between development and creative work, ensuring the platform isn’t just built for creatives, but by those who truly understand the nuances of the craft.

“At Springboards, we believe the real enemy isn’t AI—it’s bland, boring, and safe ideas,” said Pip. “Our tools are designed to put the PLAY back into the creative process, giving teams the freedom to explore and innovate without compromise.”

About Springboards

Springboards is an AI-powered platform built to accelerate creativity in advertising. By offering tools specifically designed for creative agencies, the platform empowers teams to explore more ideas, faster, without sacrificing the craft of great work. Founded by industry veterans Pip Bingemann and Amy Tucker, Springboards has already partnered with 120+ agencies globally and secured $5 million AUD in seed funding from Blackbird Ventures.

For more information, visit Springboards.ai or contact hello@springboards.ai.

In a recent episode of The NDA Podcast with Katie Cadwell, co-founder of branding studio Lucky Dip, our Springboards co-founder Pip Bingemann and Jess Macintyre, co-founder of Mac+Moore,  dived deep into the hot topic: who’s better at coming up with ideas—humans or AI? Spoiler: It’s not a competition; it’s a collaboration. 

We grabbed some insightful gems from the conversation. Read on to hear more about their thoughts on where AI can be a powerful tool for creatives, where it might fall short, and why it’s essential for creativity to stay grounded in human skill and craft.

“Human + AI” and Why Experience Still Matters

Pip kicked things off by challenging the classic “AI vs. Human” narrative. The big insight? Humans and AI together are more potent than either alone. Research suggests that working with AI actually “levels up” everyone involved. Pip’s take is that AI will really benefit those who’ve already developed their craft and have already learned how to creatively problem solve. 

Watch what he thinks AI is adding to someone who already feels like they're at the top of their game. 

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But there’s a warning here, too: AI makes it easy to coast. It’s a tempting shortcut, but Pip emphasizes that if you haven’t put in the time to develop a strong creative voice, AI won’t do it for you. AI can accelerate a skilled hand, but it’s not a substitute for a point of view or real experience.

In a world where technology has always been an enabler, the smart approach is using AI as a collaborator, NOT a replacement. AI will likely never fully match the depth and intuition of human creativity. But it can certainly speed up problem-solving and help teams—especially smaller ones—be more efficient without sacrificing quality.

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Will Everything Start to Look the Same?

One of the most powerful moments in the conversation was Pip’s take on a potential AI-driven “vanilla future.” Picture it: brands all start to blend together, looking and sounding like copies of each other, optimized to death by algorithms. If we lean too heavily on AI for creativity, there’s a risk of homogenizing the world—a dystopian future Pip (a self-proclaimed dystopian geek), would rather avoid.

Instead, creatives should “use AI against itself,” flipping it from a tool of conformity to a tool of innovation. AI should help us break down barriers, not box us into them. Used wisely, AI could provide us with surprising, fresh perspectives that push creativity in new directions.

The True Value of Creative Agencies in an AI-Driven World

As AI gets more powerful, clients may start to question the role of agencies. Why pay for creative services when a machine can crank out content? Pip’s answer: Creativity is all about breaking patterns and offering something unexpected, which AI alone can’t do.

At the end of the day, creative agencies bring more than just an output—they bring a point of view. For high-value clients, it’s not about the deliverable alone; it’s about the partnership, the unique perspective, and yes, even the “throat to choke” when things go sideways. AI can’t replace that, no matter how efficient it becomes.

Navigating the AI Hype Cycle Without Losing What Makes Us Human

Jess talked about, in an era of FOMO and “FOBO” (fear of being obsolete), everyone’s jumping on the AI bandwagon. She goes on to say how there’s this narrative about talking about innovation and such but people aren’t thinking about what it actually is and means for society. The crux of it is that real creativity requires that we respect and defend the human element in our work. AI is just a tool, and how we use it determines whether we’re truly innovating or just riding the hype.

In short: AI can help us be more efficient, tackle the blank-page problem, and even generate fresh ideas. But it’s up to us to make sure the work still has heart. As Pip says, “We’ve got to fight harder for the value of creativity and respect the craft.”

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How to Handle Gender Bias and Expanding Access

The subject of AI’s inherent gender bias came up quite a bit and they started off the conversation talking about how Midjourney’s AI tools have been in the news for race and gender bias that users have identified. Jess remarked that she’s very cognizant of how we can learn from it, be more mindful and work towards a more inclusive future that is representative of society. There’s tons of research so far on gender bias in AI tools, so there’s no denying it but only learning and moving forward. 

AI has the possibility to democratize access to creativity, lowering barriers for underrepresented voices across the globe. Pip talked about how wherever you are in the world, whether you’re in South America, India, or Africa, “AI welcomes more people in. You don’t need a fancy degree or expensive tools.” That’s where AI truly shines—making space for new players, new perspectives, and new ideas.

For small studios, freelancers, or indie creatives, AI levels the playing field. A solo creator can compete with global agencies if they’re transparent about using AI as a competitive edge. One freelancer using Springboards remarked, "I feel like with Springboards, I can take on any agency in the world as one individual." And that’s such a powerful response to the process.

The takeaway? AI isn’t a shortcut—it’s a springboard. When used with intention, it empowers creative humans to stay in the driver’s seat, break the mold, and keep making work that matters.

Check out the full Podcast episode here.

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The advertising industry is in a strange place

Somewhere between chasing clicks and feeding the algorithm, something got lost. The creativity that once defined this field—big ideas, bold campaigns, truly different thinking—got buried under “self-serve” ads, popularity contests, and a relentless drive to please the middle. It feels like we’ve entered what some are calling the “Age of Average,” where everything seems tailor-made for safe, widespread appeal but lacks the soul that once made ads unforgettable. The Springboards team? We think it’s high time for a change.

As AI sweeps through the industry, the question isn’t if it’ll change advertising—it already has. The real question is, will AI be a lifeline to help us out of the creative hole we’ve dug? Or will it dig us in deeper? At Springboards, we see a way forward where AI isn’t the enemy but the creative ally we’ve been waiting for. We believe that with the right tools—and a little bravery—the industry can be revitalized, not just to reflect culture but to break it wide open. Here’s a bit of our journey to this vision and why we’re just getting started.

How Did We Get Here? A Quick Diagnosis of the Problem

Our founder, Pip Bingemann, summed it up perfectly at Cannes in Cairns: “AI is ripping apart the ad world, and damn, isn’t it about time?” What he means is that AI isn’t inherently the problem here. Sure, the machines are here, but they’ve always been around in one form or another. The real issue lies in how we’ve used these tools so far, often in ways that limit creativity instead of pushing it forward.

Three major factors have contributed to this stifling of creativity:

1. Advertising Became Self-Serve: The shift toward digital ads made it possible for everyone to access and create campaigns with minimal expertise. This self-service model may be efficient, but it also means that thoughtful, well-crafted storytelling often takes a back seat to quick, cheap, and easy solutions.
2. Relevance Over Distinction: The pressure to appeal to the masses has reduced creative expression to whatever happens to be popular right now. As a result, ad content has become predictable, losing the unique edge that makes ads stick.
3. The Tyranny of Numbers: Metrics rule everything, and we’ve all felt it. When the focus is solely on views, clicks, and conversions, there’s little room left for originality. We’ve become slaves to what the numbers tell us is “successful,” often at the cost of creative risk-taking.

So here we are, with an industry that’s found itself boxed in. Popularity has replaced boldness, and mediocrity is dressed up as success. But just blaming the machines (or the algorithms) is too easy. The truth is, clients, agencies, and even creatives ourselves have all contributed to this mess. But it’s not too late to fix it.

Enter Springboards: A New Way to Think About AI and Creativity

At Springboards, we’re choosing to look at AI differently. Instead of viewing it as a factory for cookie-cutter ideas, we see AI as a way to get back to the heart of creativity. With Springboards, our goal is to design a tool that works with creative humans, not replacearound them. The machines may be powerful, but so is human imagination—and when those two powers come together, the possibilities are huge.

What makes Springboards different is our approach: we don’t just throw in a bunch of features and call it innovation. Instead, we focus on what actually matters for creatives today. We’re building a platform that fuels unique, inspired, and even risky ideas—because the best ideas are often the ones that break the rules. Springboards is designed to help you push past the safe and obvious, bringing bold ideas back into the spotlight. This isn’t another trend-chasing tool; it’s a creative partner with a shared goal—to take creativity to the next level.

Building Momentum: The Early Buzz

Since our beta launch, we’ve seen an amazing response. Industry leaders, like Zoe Scaman, have shared their excitement, and her tweet alone sparked an unexpected wave of interest. It was proof that creatives everywhere are craving something that feels real—a tool that challenges them, pushes them, and ultimately brings more fun back to the work they love. With demo requests piling up and a waitlist growing, we’re more motivated than ever to bring this new creative approach to as many people as we can.

But this is only the beginning. Zoe’s reaction, along with others, shows us that there’s a real hunger for change. Creatives want a tool that works with them, not against them, to shake up the industry norms. Springboards.ai is just that—a fresh way forward, built to make the creative journey exciting, unpredictable, and, most importantly, ours.

What’s Next? The Official Launch and Beyond

The excitement so far is humbling, but we know the real journey is just beginning. With the official launch of Springboards just around the corner, we’re gearing up to make an even bigger impact. We’re not interested in offering yet another “solution” that falls short on creativity. Instead, we’re focused on providing a tool that sparks curiosity, pushes boundaries, and turns the creative process into an adventure again.

This is a call to every creative out there tired of the “Age of Average.” We’re building Springboards for those who believe that creativity can, and should, disrupt, inspire, and even annoy sometimes. If you’re ready for something different, we invite you to join the waitlist and take part in this journey with us.

So here’s to the end of the average and the beginning of something extraordinary. Creativity deserves more, and with Springboards.ai, we’re just getting started.