{"id":15205,"date":"2026-03-10T10:24:52","date_gmt":"2026-03-10T10:24:52","guid":{"rendered":"https:\/\/outsourcing-today.ro\/?p=15205"},"modified":"2026-04-09T09:26:58","modified_gmt":"2026-04-09T09:26:58","slug":"alexandru-lapusan-co-founder-ceo-zitec-data-access-and-data-governance-are-the-foundation-on-which-every-technology-including-ai-depends","status":"publish","type":"post","link":"https:\/\/outsourcing-today.ro\/?p=15205","title":{"rendered":"&#x1f399;&#xfe0f;Alexandru L\u0103pu\u0219an, Co-founder &#038; CEO Zitec: Data access and data governance are the foundation on which every technology, including AI, depends"},"content":{"rendered":"\n<p><strong><span class=\"has-inline-color has-vivid-cyan-blue-color\">Outsourcing Today, the business services industry\u2019s integrated networking and news platform, continues its interview series with leaders shaping the future of business services and related sectors. We explore key perspectives on the year ahead, strategic priorities, and growth opportunities.<\/span><\/strong><\/p>\n\n\n\n<p><span class=\"has-inline-color has-black-color\"><strong>Read below the key standpoints and perspectives of&nbsp;<\/strong><\/span><span class=\"has-inline-color has-vivid-cyan-blue-color\"><strong>Alexandru L\u0103pu\u0219an, Co-fondator &amp; CEO Zitec<\/strong> <\/span><\/p>\n\n\n\n<p><strong>Three-word motivational core belief for 2026: <span class=\"has-inline-color has-vivid-cyan-blue-color\">Build. Impact. Partner.<\/span><\/strong><\/p>\n\n\n\n<ul><li><em><span class=\"has-inline-color has-vivid-cyan-blue-color\">We build technology that solves real problems, and we are selective about which problems we take on. We pursue projects that create genuine impact, and we turn down those that do not add value or change something meaningful in society. And we partner with top technology providers for long-term outcomes.<\/span><\/em><\/li><li><em><span class=\"has-inline-color has-vivid-cyan-blue-color\">Human oversight is a must. With regulations like the EU AI Act, companies can no longer postpone mature governance frameworks.<\/span><\/em><\/li><\/ul>\n\n\n\n<p><strong><span class=\"has-inline-color has-vivid-cyan-blue-color\">How is the AI-based technologies changing your company&#8217;s competitive edge in 2026?<\/span><\/strong><\/p>\n\n\n\n<p>AI is a technology whose magnitude can be compared to the rise of the internet, and there\u2019s no doubt about it. But technology alone is not the competitive edge. The edge comes from pairing AI with a prepared organization.<\/p>\n\n\n\n<p>For example, internally, our software development teams recorded a 15% productivity increase on average by integrating AI into our processes. Think code reviews, documentation, testing, and knowledge transfer. But this did not happen by simply giving people access to tools. We built a healthy organizational culture based on autonomy and ownership. This foundation helped generate organic interest across departments to explore scenarios where they could improve their own processes, including business partners and support functions, not just core business teams. The adoption came from genuine curiosity and empowerment.<\/p>\n\n\n\n<p>\u00cen 2025 we invested heavily in our organization\u2019s development, with over \u20ac2 million dedicated to growth and learning. Some of the investments included AI training for teams, change management for executives who will help carry change forward, and many more.<\/p>\n\n\n\n<p>Our internal investments went into building an AI-ready culture for practical literacy. Our teams know what AI can and cannot do. They understand when to trust AI-generated outputs and when to verify. This sounds basic, but it is the difference between companies that get value from AI and companies that accumulate technical debt from AI.<\/p>\n\n\n\n<p>For our clients, AI has become a solution for solving problems at scale. For example, in our collaboration with the Ministry of Environment, we deployed a solution based on Google Vertex AI and Gemini PRO that proved time savings of 99% and cost savings of 97%. Another example is a global healthcare provider processing customer support tickets. Before our collaboration, they handled 14,000 tickets monthly with a team of 13 people. After deploying agentic workflows to automate routine operational tasks, they now process over 30,000 tickets monthly, a 114% volume increase, while saving 74% of costs.<\/p>\n\n\n\n<p>This combination of AI for internal efficiency and AI as a client-facing capability, supported by a culture that knows how to adopt change, creates our compounding competitive edge.<\/p>\n\n\n\n<p><strong><span class=\"has-inline-color has-vivid-cyan-blue-color\">What&#8217;s the biggest misconception business leaders still have about AI?<\/span><\/strong><\/p>\n\n\n\n<p>There are three that I repeatedly encounter. The first one is that AI is primarily about replacing people.<\/p>\n\n\n\n<p>The projects that deliver value are those where AI augments human capabilities, not replaces them. In our financial services sector, where our revenue grew by 83% in 2025, AI allowed us to significantly scale operations for a client, processing 3x more requests with the same team. This threefold increase happened in just under three months, and our client&#8217;s team is now able to process over 2000 financing requests daily, with the help of the SME Lending Origination Accelerator Agent developed with our teams. But the strategy and execution still require experienced teams.<\/p>\n\n\n\n<p><strong>Secondly, the misconception that AI causes internal friction and operational debt.<\/strong><\/p>\n\n\n\n<p>I hear this increasingly from business leaders who started implementation and now feel stuck. They perceive AI as a source of complexity, adding more tools to manage, more integrations to maintain, and new workflows that clash with existing ones. But this perception exists precisely because many organizations do not yet know how to implement this technology properly.<\/p>\n\n\n\n<p>The famous MIT study published in 2025, &#8220;The GenAI Divide&#8221;, found that 95% of enterprise AI pilots deliver no measurable P&amp;L impact. But it\u2019s all due to how it is being implemented. No one talks about how the same study found that vendor partnerships succeed about 67% of the time, while internal builds succeed only 33% of the time. The companies extracting value start with clear scoping, run focused proof-of-concepts tied to business metrics, and scale what works, backed by trustworthy partners. The friction leaders experience is not inherent to AI, but a symptom of skipping important steps.<\/p>\n\n\n\n<p>Thirdly, the assumption that you can &#8220;vibe code&#8221; your way to AI. &#8220;Vibe coding&#8221;, which involves describing what you want and letting AI generate the code without deep review, actually became Collins Dictionary&#8217;s Word of the Year in 2025.<\/p>\n\n\n\n<p>For prototypes and weekend projects, it works. For enterprise systems, it creates problems that far outweigh the speed gains. Just in December 2025, CodeRabbit found that AI co-authored code contained 1.7 times more major issues than human-written code, including 2.74 times higher security vulnerabilities.<\/p>\n\n\n\n<p>Enterprise software requires architecture, governance, and accountability. You cannot prompt your way to that.<\/p>\n\n\n\n<p><strong><span class=\"has-inline-color has-vivid-cyan-blue-color\">Which business decisions in your company are AI-led?<\/span><\/strong><\/p>\n\n\n\n<p><strong>None. And that is intentional.<\/strong><\/p>\n\n\n\n<p>AI informs decisions, but it does not make them. We use AI-driven insights for resource allocation, project scoping, and identifying patterns in client data. But the accountability for decisions remains with our people: our project managers, our technical leads, our delivery teams.<\/p>\n\n\n\n<p>We have integrated AI across multiple internal processes. In software development, we use it for code reviews, automated testing, documentation generation, UI, and knowledge transfer between teams. In ideation and scoping, we use generative AI to accelerate the exploration of technical approaches and to stress-test requirements. The technologies vary by use case, but always with humans involved at every step. That is how we build trust with our clients, and that is how we ensure quality.<\/p>\n\n\n\n<p><strong><span class=\"has-inline-color has-vivid-cyan-blue-color\">How has AI changed what customers expect from your products or services?<\/span><\/strong><\/p>\n\n\n\n<p>For starters, speed, as clients expect faster delivery. AI-assisted development has reduced certain phases of our projects, and clients now calibrate their timelines accordingly.<\/p>\n\n\n\n<p>Clients are more sophisticated about what AI can and cannot deliver. They ask more questions about the total cost of ownership, maintenance requirements, and measurable outcomes.<\/p>\n\n\n\n<p>On the flip side, some clients come to us with unrealistic expectations shaped by AI. We occasionally receive briefs written with AI where clients believe they are saving time and covering all bases. But more often than not, AI-generated briefs complicate the situation. They sound comprehensive but miss the strategic nuance, or they ask for things that do not align with actual business goals.<\/p>\n\n\n\n<p><strong><span class=\"has-inline-color has-vivid-cyan-blue-color\">How do you stay differentiated in your market, what tools and competitive advantages do you leverage in 2026?<\/span><\/strong><\/p>\n\n\n\n<p>Several differentiators define our position, and they compound over time. We are consultants, focused on adding value to the products we are involved with. Every engagement starts with understanding the client&#8217;s real problem. We challenge assumptions, suggest improvements, and stay involved from scoping through post-launch and maintenance phases. As a result, our average client relationship exceeds five years.<\/p>\n\n\n\n<p>We have strong expertise across retail, logistics, financial services, healthcare, and the public sector. We also maintain strategic partnerships with both major cloud providers. With Google Cloud, we hold specializations in areas such as cloud architecture, data engineering, and network engineering. Our long-standing collaboration was recognized in 2025, when our Ministry of Environment project received the AI for Good Award. With Microsoft Azure, we are a Gold Partner with experience in cloud infrastructure and application modernization.<\/p>\n\n\n\n<p>Both partnerships provide additional advantages, including access to vendor engineering teams, early visibility into new technologies, and co-funded training for our engineers.<\/p>\n\n\n\n<p>When it comes to our software development methodology,&nbsp; we have mature processes for selecting technical solutions and extensive automation that allows us to deliver predictably at a high quality level. We don\u2019t use untested technologies and processes with our clients, resulting in a 90% on time and on-budget delivery in an industry where McKinsey reported that, on average, large IT projects run 45% over budget and 7% over time.<\/p>\n\n\n\n<p>We ended the year with a 95% employee loyalty rate. 63% of our team are seniors or directors, so in an industry where talent churn is constant, this stability translates directly into delivery quality. Our recent acquisition of Equilobe further strengthens this, as we now have one of the strongest .NET capability hubs in Romania.<\/p>\n\n\n\n<p><strong><span class=\"has-inline-color has-vivid-cyan-blue-color\">How do you balance rapid innovation with responsible and ethical AI use?<\/span><\/strong><\/p>\n\n\n\n<p>By starting with the problem, not the technology. To be clear, we do not do AI for the sake of AI.<\/p>\n\n\n\n<p>If AI does not solve a real business problem, we do not implement it. This sounds obvious, but in a market flooded with AI hype, it is rare. We have dedicated Data Analytics &amp; AI, Technology Consulting departments, and Digital Product Analyst departments that handle scoping, consulting, and staying current with the landscape. Their job is not to push AI into every project, but to identify where it creates genuine value and where it does not.<\/p>\n\n\n\n<p>Before any AI implementation, we ask about the business outcome and analyze the risks. We are also paying close attention to the EU AI Act and its implications for how AI systems are designed, deployed, and governed. For our clients in regulated industries, like financial services, healthcare, public sector, compliance is vital. Our approach already aligns with the Act&#8217;s requirements of human oversight, transparency about AI decision-making, and documentation of how systems work.&nbsp;<\/p>\n\n\n\n<p>Lastly, it is very important for us to have a moral compass as a company, and that translates into everything, including how we adopt and implement new technologies like AI.<\/p>\n\n\n\n<p>We are working to become the first B Corp-certified tech company in Romania. B Corp (Benefit Corporation) is an independent audit that evaluates criteria like governance, worker treatment, community impact, and more. We feel this certification aligns with how we\u2019ve been running Zitec since the beginning, and also guides us to steer it in the right direction going forward. We\u2019ve always turned down projects that conflict with our values, but B Corp formalizes this into legal commitment and public accountability.<\/p>\n\n\n\n<p><strong><span class=\"has-inline-color has-vivid-cyan-blue-color\">What technology trend beyond AI should businesses be paying attention to now?<\/span><\/strong><\/p>\n\n\n\n<p>Data access and data governance. It is not a technology per se, but it is the foundation on which every technology, including AI, depends.<\/p>\n\n\n\n<p>Last year, at Romanian Digital Day in Brussels, I spoke about a challenge that is often overlooked, which is that AI cannot be built without access to data. In Romania, most companies do not have datasets large enough to train meaningful models. The public sector holds vast amounts of data that could fuel innovation, but much of it remains locked. These are not the institutions&#8217; data, but citizens&#8217; data. When this changes, everyone will be able to fine-tune their AI models and develop new products that benefit everyone.<\/p>\n\n\n\n<p>The businesses and institutions that solve the data access problem will be the ones that capture the most value from AI. This is not glamorous work. It involves data architecture, governance frameworks, and interoperability standards, but it is foundational.<\/p>\n\n\n\n<p>The second trend is AI governance. When everyone is implementing AI and trying out various models, the differentiator becomes how well you govern it inside the organization.<\/p>\n\n\n\n<p>We see that in order to extract sustainable value from AI, you need frameworks for how AI systems are designed, deployed, and maintained. This means establishing who has authority over AI decisions, what review processes exist before deployment, how models are monitored after launch, what happens when systems behave unexpectedly, etc.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Outsourcing Today, the business services industry\u2019s integrated networking and news platform, continues its interview series with leaders shaping the future of business services and related sectors. We explore key perspectives on the year ahead, strategic priorities, and growth opportunities. 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