Over the last 30 years, David Parry-Jones has been at the forefront of major technological changes, including the advent of email, the internet, the cloud and SaaS. During that time, he led billion-dollar businesses at VMware and built Twilio’s international business across EMEA, APJ and LATAM.
David is currently the Chief Revenue Officer at one of Europe’s most valuable AI companies, DeepL, which was founded in Cologne in 2017. DeepL is an AI-native company specialising in high-quality language translation and has a multi-billion dollar valuation following significant investment from leading VCs including Atomico, ICONIQ, IVP, Benchmark, Index Ventures and b2venture. David joined DeepL as their first CRO in July 2023, and he kindly shares his perspectives on scaling an AI business and how it differs from previous technology cycles with our Global Technology and Software Partner, John Smith.
What are the unique opportunities & challenges of building an AI company?
Building an AI company is like a rollercoaster. The pace of what is happening both within your company and around you is like nothing you have experienced before. It is easy to get left behind, and you must stay tuned into market shifts; agility is key. You need to balance rapid innovation with the need to deliver now and be agile enough to respond to rapid changes in the market. One of the biggest challenges in AI is to stand out from the noise, but there is also an opportunity to create jaw-dropping moments for your customers, which is genuinely exciting to be a part of. My career has included several major technological shifts but nothing on the same scale as the opportunity for AI.
What is different about building the GTM for an AI company?
When it comes to GTM for an AI company, the traditional sales methodologies like MEDDIC and solution selling still have their place, but they do need some adapting. There is an underlying similarity across the previous companies I have worked for, but each period and each company evolved. One big difference in AI is catering to the needs of vastly different customer types. In DeepL’s case, this ranges from individual consumers using a freemium product to some of the largest companies in the world relying on us for critical legal document translation. There are also specifics relating to pricing and legal requirements, which can be very complex. Understanding traditional enterprise sales methodologies and product-led growth is an important skillset for AI companies. Many AI companies will evolve from a self-serve model to large-scale enterprise sales. That shift isn’t just about sales; it’s a cultural transformation for the whole business that requires alignment across product, engineering, marketing and the entire organization.
What makes a successful leader in an AI company?
The ability to pivot, grow and learn with the company is critical. Successful leaders will have a mix of adaptability, self-awareness, and a deep understanding of their market. Knowing who you are and what you’re good at is crucial. I also think having a breadth of experience is important. Having experience with different products and sectors, different buying sites and different GTM models will help with the need for agility that we talked about. It means you can draw upon a varied toolkit because change is going to happen to you whether you like it or not, and probably at a speed that you haven’t experienced before. Strong communication is also key for your leaders. Setting expectations and being predictable is critical in such a fast-paced environment.
How are you using AI within the GTM tech stack?
We are still early in our use of AI in the GTM tech stack. When I arrived, it was very traditional and we used the usual tools, Salesforce, HubSpot etc. But things are evolving quickly, and we are seeing some significant productivity gains with AI. For example, AI tools are helping our SDRs be twice as effective by driving insights with propensity analysis for customers and better predictability in the pipeline. For me, implementing AI is not about replacing people but about making them more productive. The goal is to have something like a co-pilot, not an autonomous replacement.
What are some of the best applications of AI that you have seen?
There are so many. Something we are currently working on is in partnership with Synthesia. They create some incredible AI-driven avatars which, in combination with our translation capability, have endless opportunities. Think about it: the ability to create exceptionally high-quality avatars that can seamlessly speak in 30 different languages at the push of a button. There is potential for some incredible use cases across sales, customer service and training in all industries.
As a consumer, I had my own ‘wow’ moment when I needed some legal documents translated, and my solicitor said that it would cost £1000 and take a week to do. Out of curiosity, I ran the document through DeepL, and almost immediately, I had a translated version of the document. The solicitor could not believe its accuracy and ability to understand context. I think it is a good example of how AI can do mundane tasks and allow humans to focus on higher-value work.
What advice would you give to Founders who are scaling AI companies?
I’ll come back to what I said earlier: stay close to your market and be agile enough to adapt quickly. Change happens so quickly across products, pricing, your ICP, use cases, buying sites and so on. It means doing proper discovery work with your customers to really understand how you can deliver value. Scaling sales teams is relatively straightforward when you have a clear product-market fit and well-defined ICP. However, most AI companies aren’t there yet, which makes it a risk to hire people who have only ever known well-defined products and customers. So, my best advice is to hire people who are good at discovery and have broad experience across different products and sales models.
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