From AI in healthcare to breakthroughs in financial data, our Private Companies Showcase highlighted a clear and consistent theme: of growing demand for AI – powered solutions to support the rise of AI – empowered enterprises. This focus sparked a wide range of insights from founders, investors, and UBS leaders, each bringing deep and diverse experience to the table.

Christian Lesueur, Global Head of Coverage and Global Head of TMT Investment Banking, UBS, set the tone by highlighting the pace at which AI – native companies are emerging and reshaping industries, a clear signal that private capital is leaning into the tech transformation story.

With signs of stabilizing interest rates and improving investor confidence, many noted that capital is now flowing more confidently into enterprise ready AI solutions, moving from experimentation to execution.

From experiments to enterprise

The opening panel made one thing clear: we’ve moved beyond the “let’s try ChatGPT” phase. Enterprises are now building structured AI systems, often powered by AI – agents (or AI leads) that can execute real business tasks. Brian O’Reilly, General Manager at WRITER, the end-to-end platform for building, activating, and supervising AI agents that help enterprises automate work, improve decision making, and unlock the full potential of their workforce, described this shift as moving from ad hoc tools to agentic, where agents are embedded into workflows with clear objectives and measurable outcomes.

We’re seeing a shift from experimentation to execution, – Enterprises are fatigued from testing; they want agents that are secure, observable, tailored to their business context and production ready

- Brian O’Reilly, GM of International, WRITER

But while the technology is ready, many organizations are still catching up. Governance, supervision, and change management are now the biggest hurdles for implementation. Several panelists noted that many enterprises are still figuring out how to manage AI at scale, especially when it comes to data access, security, and compliance.

And in Europe the stakes are even higher. Regulatory complexity and cultural resistance are slowing adoption, but there’s growing momentum in sectors like healthcare with patient – facing tools and edge computer solutions that can operate safely within clinical environments.

From left: Brian O’Reilly (Writer AI), Sultan Saidov (Beamery), Katy Wigdahl (Speechmatics), Margarida Garcia (poolside), Bjoern Von Siemens (Caresyntax), Athena Theodorou (UBS)

AI across industries: From healthcare to financial infrastructure

Panelists explored how AI is transforming industries beyond software. In healthcare, companies like Cera, Europe’s largest HealthTech company, using technology and AI to shift healthcare services from hospital to home, delivering higher quality care at a fraction of the cost, and Oviva, who provide personalized dietetic and lifestyle coaching through a mobile app across Europe, are using AI to personalize treatment and bring care into the home in order to reduce hospitalizations.

Ben Maruthappu, Chief Executive Officer, Cera

Our AI tools have improved patient outcomes, reducing falls by 20% and cutting hospitalisations by up to 70%. We’re helping health systems reduce costs while improving the quality of care – contributing to a more sustainable future for healthcare.

– Ben Maruthappu, Chief Executive Officer, Cera

In financial services, firms like Taxfix, Moss, and Vertice are using AI to automate tax filings, optimize spend, and streamline procurement. The message was consistent: AI is no longer a back – office tool, it’s becoming central to how companies operate, serve clients, and manage risk.

Meanwhile, in HR and learning, platforms like CoachHub and LearnWorlds are using AI to personalize coaching and training at scale. CoachHub’s AI coach “Amy” is designed to make executive – level coaching accessible to all employees, not just senior leaders.

Building for scale: Security, specialization, and strategic clarity

As AI adoption accelerates, so does the need for control. Enterprises are demanding on – premises deployments, strict data governance, and clear boundaries around what tools can be used.

Margarida Garcia, COO, poolside, a startup focused on AI – assisted software development that helps developers write, understand, and maintain code more efficiently, emphasized that in high – consequence environments, like defense or finance, “security isn’t a feature, it’s the product.” Another theme that came through loud and clear, was that specificity wins. Both WRITER and Speechmatics, whose speech recognition technology understands diverse accents, dialects, and languages in real time, spoke about leaning into domain – specific models, tailored to enterprise needs. “We ensure everyone is understood, regardless of geography or background”, said Katy Wigdahl, Chief Officer, Speechmatics. The result? Better accuracy, faster adoption, and fewer surprises.

Sonia Boudier, Chief Product Officer at iBanFirst, a financial services provider offering payment solutions to small–medium enterprises operating internationally, echoed this sentiment from a user – centric perspective, "AI is already transforming financial services in very tangible ways. It’s not theoretical. We use AI every day: in onboarding automation, fraud detection, customer support, even in coding workflows. It’s not a new product – it’s become part of how we work. But the real shift is ahead: we’re entering a world where software agents, not humans, could initiate and manage financial activity."

Sonia Boudier, Chief Product Office, iBanFirst

What this signals to investors

The AI landscape is maturing, and with it, investor focus is evolving. As inflation moderates and the IPO market begins to reawaken, many investors are looking beyond generalized AI hype to assess true enterprise value. 

The key takeaways: 

  • Growing emphasis on data governance and security as foundational to scale 
  • Interest in domain-specific AI with measurable business impact 
  • A shift toward tangible evidence of productivity and cost efficiencies 
  • Demand for a clear roadmap for workforce transformation 

Rather than speculative excitement, there is a growing appetite for AI-native businesses that are execution-ready, with strategies aligned to long-term enterprise adoption.

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