Centric IT Solutions Lithuania

A single cyberattack could cost your business far more than preventing one. But do you actually know where your systems are most vulnerable? Start with an IT assessment. Identify your biggest risks and learn what to fix first.

Most companies talk about AI. Few are actually ready for it. 67% are only basically digital. 32% haven’t even reached that. 👉 See where your company is on the curve. Watch the webinar “The Anatomy of Digitalisation.”

Full AI automation sounds good on slides. Real value starts before you get there. In a recent logistics project, the KPI wasn’t perfect data. It was less manual work and lower operational costs. Data came from multiple systems. Accuracy mattered, but not as much as removing repetitive human effort. Full automation wasn’t realistic at the start. But value was created long before that point. Manufacturing digitalisation without the BUTs. 👉 Let’s talk about getting the first step right.

An AI pilot is not a result. A result is when it runs in your day-to-day operations. The most common mistake? Starting with an AI pilot instead of a clear operating scenario. In manufacturing, this leads to: - long experimental phases - unclear ROI - solutions that never become real processes We take a different approach. AI only makes sense when it’s clear: - Where will it be used? - How will it be maintained? - What value must it deliver from day one? 👉 Manufacturing digitalisation without the BUTs. Only what you need. Exactly how you need it. Let’s talk about securing the first step.

Most AI projects follow the same three phases: preparation → development → production The problem? The first phase is usually chaotic and underestimated. This is where things are often missed: ➡️ Where will the AI run and integrate? ➡️ How will it be used day to day by real teams? ➡️ Who owns it after go-live? ➡️ Which KPIs define success? Even if development works, production never really starts. Manufacturing digitalisation without the BUTs. Plan first. Build the second. Use in production. 👉 Let’s talk about securing the first step.

AI is powerful. But it’s not an operating system you switch on and forget. AI works with complex, imperfect data. Mistakes can happen, just as they do with humans. That’s why people are essential: - to validate AI decisions - to spot gaps where automation falls short - to correct, guide, and improve the model over time Human oversight doesn’t slow AI down. It’s what makes AI usable in real operations. The goal isn’t replacing people. It’s reducing manual work, lowering costs, and improving reliability. 👉 Manufacturing digitalisation without the BUTs. AI works best when humans stay in the loop.