AI Won’t Make A Bad Business Good: Interview with Daryl Cohen, Partner at Capital D
AI Won’t Make A Bad Business Good: Interview with Daryl Cohen, Partner at Capital D
AI is upending the media and marketing landscape, blurring the lines between creation and consumption and forcing companies to rethink where their true value lies.
For Daryl Cohen, Partner at Capital D, this brings both risk and opportunity. With 23 years’ experience in private equity investment, he’s looking for businesses that adapt quickly, differentiate through proprietary know-how and data, and use AI to sharpen their value proposition.
We spoke to Daryl about how Capital D assesses AI’s impact on investment, what makes a business’s value defensible and how media and marketing firms can navigate disruption.
Tell me Daryl, how do you view the evolution of AI and its impact on business models today?
AI in business isn’t new. “Rule-based decisioning” dates back to pre-2000, and “machine learning” based on “neural nets” became banker buzzwords during the Pandemic Era. At the time, those technologies represented major steps forward, enabling exciting product and business development. But they never brought seismic opportunity or disruption – or made the headlines. That all changed in 2022 with the explosion of interest sparked by human-like chat bots (ChatGPT, Claude etc.), powered by their awesomely powerful foundation models.
In that sense very few companies are truly AI companies – meaning they create their own foundation models – because building and training them remains extremely costly. I think what most people now see as an AI company is one where there is a deep integration of AI output into processes and products. Large Language Model “wrappers” are a first step in this direction, with significant value already being created in several verticals (e.g. copywriting, legal and financial). Given the enormous power of the foundation models, this new generation of AI enablement goes far beyond anything we’ve seen before and has the potential to fundamentally change how companies operate, develop and distribute products.
Has the latest wave of AI changed how you assess risk and value when looking at media and marketing businesses?
Definitely, and not just media and marketing businesses. LLM-based generative AI forces us to rethink what differentiates any business and whether that differentiation is still sustainable. As few businesses own the underlying AI, differentiation has to come from proprietary know-how applied in its use or from proprietary data used in curating its output.
In that sense I am a fan of businesses with deep verticalized knowledge that use AI to be better versions of their former selves. In media and marketing, AI is game-changing for creativity, targeting and personalisation. But the impact depends on having something proprietary to do the enhancing.
So, it’s the execution rather than the tech itself that determines which businesses succeed?
We’re in one of the most intense periods of disruption in a long time. But AI is still just a tool. Success depends on how well it’s used and how well a business can distribute.
In the media and marketing space, an early example of AI application is seen in enhancing how brands connect with audiences on a personal level, and then automating the content production. We already see this with short texts, static images and other high-frequency outputs. It’s less about replacing big human narratives, but more about enhancing and automating performance through smart execution. Think real-time personalised ads – a bus stop that knows you’re nearby and delivers content created for you in real time. That kind of applied AI is where the disruption gets real, and where execution becomes the differentiator.
BDO’s recent Economic Engine survey shows over half of mid-sized businesses are still hesitant about investing in AI. Does that reflect what you’re seeing?
Yes, we’re in a period of experimentation. Most firms are still exploring where and how AI adds value – some are trying to build, some are running proofs of concept, but most are not yet committing. Curiosity is high but major investments remain cautious.
It won’t take long though. Through 2025 and 2026, businesses will test, implement and determine where AI drives real gains. Some tasks will be automated quickly, others less so. The pace of adoption will depend on where those efficiencies emerge.
As AI tools become established, how do you predict content creation will evolve?
AI can generate huge volumes of content, but scale isn’t the only challenge, relevance is. The winners will be those who pair scaled real-time content generation with strong personalisation systems and the right data and distribution infrastructure.
Short-form and functional content (like emails and marketing copy) will see the first big gains but over time AI could generate entire content ecosystems shaped by platform incentives and personal data, blurring the line between media and experience. This shift won’t just transform entertainment, but how people perceive and engage with reality online.
Does that level of personalisation cause challenges in terms of data and ethics?
Definitely. Building the tech is one thing, but the regulation of privacy and consent, as well as IP rights in derived content, are also critical issues.
In that context, there’s also a debate around transparency. How much should users know about AI’s role? Without clear rules, businesses risk losing trust or crossing legal lines. Regulation will be key, both to protect personal data and set boundaries on AI’s use of creators’ work.
Where do you see the strongest positions forming in the AI-media value chain?
I see the greatest power emerging at the two ends of the value chain: among ad buyers and content creators whose work drives scale and engaged audiences. Middle layers like distributors and agencies are vulnerable because AI is making it easier for advertisers and creators to connect directly, cutting out the middleman.
That said, this growing creator economy adds another layer of complexity. While major ad platforms provide reach, many creators continue to want more direct, authentic relationships with their audiences and better control over monetisation – something that’s hard to achieve within closed ecosystems. So, while AI may drive consolidation, there’s also a countermovement toward openness and decentralisation. The winners will be those who balance access and scale with protecting creators’ rights.
What’s the sentiment right now among media and marketing businesses around growth?
There’s more hesitation than confidence. This year has been complex, shaped by domestic political shifts, changes in government and corporate investment priorities. The investors I’ve spoken to are approaching life cautiously. As a result, the focus has shifted toward conserving cash and protecting profitability, rather than pursuing aggressive growth.
If this level of uncertainty continues, at what point do businesses stop waiting for stability and start adapting to a new baseline?
The job of business leaders is to constantly adapt and evolve. And in that sense many already have by adapting to a baseline that includes greater risk. How deeply they embrace AI, and when, will depend more on each company’s individual risk-reward profile.
As that new normal takes shape, how is it changing what investors want to see in a business?
The fundamentals have shifted. In a world of heightened uncertainty and a real cost to capital, there’s greater emphasis on balancing profitability with growth. The “burn cash and quadruple quickly” mindset is gone – replaced by a focus on sustainable growth and value creation, all while keeping enough of a buffer in the bank for a rainy day.
Where do you see the biggest opportunity for investment firms right now?
For me the most pressing opportunity for private investors lies in evolving their approach to value creation. Differentiated returns come from genuinely improving businesses.
That’s why as a firm we constantly ask ourselves whether we have the best possible toolkit to add value, including the potential of generative AI. It means equipping businesses with the insight, capabilities and support they need to execute effectively and grow sustainably – resources they might not have had without our investment.
Is this hands-on value creation approach the future of private equity?
Yes, definitely. In most cases, the M&A and financing markets are too efficient to allow for sustained, differentiated returns. This means those returns must come from hard work in value creation – which itself continues to evolve.
Leaders need to move beyond an agenda of traditional operational improvements or consultancy-style support, and extend their focus into data, AI enablement and digital transformation.
How can businesses apply AI and digital transformation in a smart, effective way?
In our view you don’t need 100 people, but you do need the right ones. Our approach is to tap into a small group of highly skilled expert practitioners who bring sharp and differentiated insights continuously learned on the job. We then layer that over more traditional intelligence sources from across the consulting community. With the pace of change in AI, being well connected and agile is critical.
What’s the one piece of advice you’d give to businesses seeking investment right now?
AI won’t make a bad business good. It can amplify strengths, but it also exposes weaknesses fast. So ask yourself: which parts of your value proposition truly stand up in an AI world? What’s still defensible? What can be leveraged in product to create value? That’s the playbook. Know where your edge is and use AI to sharpen it. If you can’t find that edge, it’s time to rethink the fundamentals.
How can we help?
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As the UK’s leading provider of transaction advisory services in the media and marketing space, we have deep expertise in supporting innovative deals, from social content platforms to tech-enabled marketing solutions.
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