By Sonja Horn, Data Science Lead, EQT Digital

Last week, we brought together more than 75 technology and AI leaders from across EQT’s global tech portfolio,  founders, CTOs, CPOs, and industry experts defining what comes next in Artificial Intelligence.

At EQT, our ambition is to build the most AI-literate investment organization in the world,  weaving intelligence into everything we do, from how we source and evaluate investments to how we help the companies we back grow and scale.

Our annual EQT AI Summit is where that ambition comes to life, a space to share learnings across our portfolio, explore what’s working, and reflect on how AI is transforming real businesses. You can read more about the event here. From the EQT Digital perspective, we work with our portfolio companies every day to help them adopt and scale the right AI solutions for their specific business, and this year’s Summit reinforced many of the success patterns we’re seeing across the portfolio.

EQT Digital Lessons from the Portfolio

From experimentation to scalable adoption. EQT Digital empowers portfolio companies to turn AI potential into lasting impact, by defining key opportunities, validating technical solutions, and building the capabilities needed to drive meaningful change and AI adoption.

Practical lessons from scaling AI across companies:

• Outcome focus. AI work should be business-led, not tech-first. The most successful companies link AI initiatives directly to strategic priorities and measure impact in business terms, not just technical metrics.
  
  

• Data-first. Start by identifying what data you need, how structured it needs to be, and who owns it.
  
  

• Build, test, scale. Shorten experimentation cycles to learn what works fast and scale with proven impact.
  
  

• Pair engineers with domain experts. Embed engineering talent directly within commercial and operational teams to surface automation opportunities faster, enable rapid prototyping, and expose data or platform gaps early.
  
  

• People & change. Identify needs for new skills, don’t underestimate change management, and measure and communicate AI impact clearly.

Founder / Leadership Lens - Do Now:

👉 Define impact clearly. Translate “impact” into 2-3 measurable business outcomes that reflect current strategic priorities (e.g. increased customer retention, faster delivery, higher utilization rates). Use these as your north star to anchor AI work and iterate continuously.

👉 Enable experimentation. Set up sandboxed environments where teams can safely and freely test new tools and workflows without risking operations or security. Encourage teams to spend time experimenting.

👉 Learn as a team. Share what worked and what didn’t openly; identify and give visibility to your champions and power users; document best practices.

What stood out most for me at this year’s Summit was the energy and openness in the room: founders, engineers, and product leaders sharing lessons and still-to-be-solved questions from real implementation journeys. That curiosity - the willingness to ask, test, and learn - is what’s moving this field forward. The companies that lean into it will be the ones that benefit most.