Radu Pinzaru, Endava European Head of Data & AI: How an organization manages its data is often the strongest predictor of AI success

key standpoints and perspectives of Radu Pinzaru, Endava European Head of Data & AI
Core values: Open, Thoughtful, AdaptableThe AI-based technologies changing the company’s competitive edge in 2026
The AI era found us in a strong position, built on over 20 years of experience in Data Science and Machine Learning as a client services company working across many industries. When the hype accelerated, we already had the right expertise to guide clients effectively and form meaningful partnerships with major players in the market. Examples include Microsoft, Amazon and Google from a large cloud provider perspective as well as more AI specific partnerships with Open AI over 2 years ago and more recently what we announced with Miro and Cognition.
This allowed us to separate real value from noise early on. We proactively transitioned all of our workforce including our technical Endavans – developers, data engineers, testers – toward becoming more AI-native. After several years of sustained effort, we now have specialized capabilities across most relevant AI technologies, seamlessly integrated with software engineering. Another important thing to mention is how we have developed and now leverage our native AI methodology Dava.Flow to deliver for clients in this fast paced AI led world, more info on Flow can be found at www.endava.com/dava-flow . This combination gives us a significant competitive advantage: we can both advise strategically and deliver efficient, production-ready AI solutions.
Misconceptions about AI
One of the most common misconceptions is treating AI as a self-sufficient entity.
In reality, AI is part of a broader ecosystem that heavily depends on data. While AI receives most of the attention, there’s comparatively little discussion about data platforms, engineering practices, company readiness and governance.
How an organization manages its data is often the strongest predictor of AI success. That’s why any serious AI conversation must be anchored in the underlying data ecosystem.
AI-led business decisions this year
Today, most data informing our decisions is supported by using AI systems, always under the supervision of experienced engineers.
Over the past year, a growing share of decisions has been supported by supervised AI agents that continuously learn through feedback loops. However, final accountability remains with our people. We see AI as very much human in the loop (HITL) with our people working alongside AI to deliver business value.
Key examples include workforce allocation and RFP (Request for Proposal) handling – areas where AI enhances speed, consistency, and insight quality.
AI changing customers’ expectations
Initially, expectations centered around cost reduction and faster time to market. These perspectives have matured. Clients now seek a balanced approach – optimizing cost and speed while ensuring safety, ethical use, reliability, and trust. Our strong foundation in data, our partnerships and cloud technologies, combined with early AI adoption, enables us to meet these evolving expectations and deliver solutions that are both effective and responsible.
Staying differentiated in the market, leveraging tools and competitive advantages
Our key differentiator is efficiency – both in decision-making and delivery. Alongside that as referenced above is key partnerships and our own native AI delivery methodology Dava.Flow.
We combine deep expertise in cloud, data, and AI infrastructure with the ability to evaluate and select the right solution for each client’s context. This means not just delivering end-to-end systems, but delivering the right systems – optimized for cost, performance, and scalability that solve the well understood pain points for our clients
In addition, our strategic partnerships with major technology providers give us early access to new capabilities. By the time these tools reach the broader market, our teams are already experienced in applying them effectively.
Balancing rapid innovation with responsible and ethical AI use
Responsible AI is embedded in our foundation, not added as an afterthought.
We invested early in ethics training and governance, supported by colleagues with advanced academic expertise in the field. Our practices align with frameworks such as the EU AI Act, and we’ve established clear processes and guardrails for AI development and deployment. We have a company wide AI Policy alongside training for our teams. In addition we have a centralised AI Committee that has a strong focus on responsible and ethical AI.
This strong ethical baseline allows us to innovate rapidly and confidently, knowing that responsibility is already built into how we operate.
Technology trends emerging this year
While AI continues to dominate, its progress is accelerating adjacent fields. One area to watch closely is quantum computing. The momentum generated by AI could significantly speed up breakthroughs in this space, potentially triggering the next major technological shift.

In the near term, I would also highlight the rapid evolution of data platforms. We’re already seeing major advancements from partners like Databricks and Snowflake. This layer will be critical in enabling scalable, enterprise-grade AI.

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