TeraSky Europe ads

12 real AI use cases across HR, Finance, Legal, and more, already saving teams hours every week. See how they work and where to start.

❓Can AI reduce public procurement workloads without compromising legal and security requirements? At Altra, early results suggest it can. Altra is responsible for one of Europe’s largest and most complex nuclear decommissioning projects. Before a tender can be published, its teams must prepare detailed technical specifications, contract conditions, and supporting documents in line with Lithuania’s Public Procurement Law and the organisation’s internal procedures. To make this process more efficient, Altra partnered with TeraSky Europe to implement Gemini Enterprise and develop a specialised AI agent for procurement documentation. Built around the legislation and internal rules governing the process, not around shortcuts, the agent can independently prepare and format complex documentation. Early testing indicates that it can reduce preparation time by up to 80% while maintaining the required legal and security standards. This means less administrative work and more time for engineers and procurement specialists to focus on tasks that require their expertise. “Public procurement in the public sector often becomes a barrier to innovation because of its complexity and strict regulation. We wanted to change that, and we have succeeded.” - Mindaugas Bereiša, Head of Information Technology Development at Altra Which other highly regulated processes could benefit from this approach? See how Altra and TeraSky Europe are setting a new benchmark for AI adoption in the public sector. Read the full case study: https://lnkd.in/d96KpB6P

Can AI accelerate public procurement without weakening legal or security requirements? Altra partnered with TeraSky Europe to implement Gemini Enterprise and to build a specialised AI agent focused on Lithuania’s Public Procurement Law and its internal procedures. Early testing indicates 70–80% less time spent preparing procurement documentation, giving engineers and procurement specialists more time for work that requires their expertise. See how Altra is setting a new benchmark for AI in the public sector. Read the case study.

SME Bank didn’t just move to a new email system. They moved to a new way of working. Migrating from Microsoft 365 to Google Workspace involved far more than transferring email. Working with TeraSky Europe, SME Bank migrated calendars, contacts, SharePoint content, OneDrive files, permissions, and device management as a single, coordinated project without slowing day-to-day operations. “Every step of the migration was planned to keep day-to-day work running as usual. People could continue working without major interruptions while the move was taking place.” — Tomas Smalakys, CIO, SME Bank But the real story is not the platform switch. It is what the move enabled: an AI-first workplace. Today, more than 110 SME Bank employees use Google Workspace, with Gemini integrated into the tools they use every day, all while maintaining the governance and security standards required in financial services. Teams collaborate differently. Information moves more freely. AI is part of the daily workflow, not an added layer on top. See how SME Bank delivered an AI-first workplace transformation while maintaining compliance, security, and business continuity. 👉 Read the full case study: https://lnkd.in/d_ffWzBe

SME Bank migrated its entire Microsoft 365 environment, including email, files, and device management, to Google Workspace. Daily operations continued without disruption, financial-sector compliance was maintained, and more than 110 employees now use Gemini in their daily work. See how TeraSky delivered the transformation.

88% of organisations use AI in at least one business function. Only 6% call themselves AI high performers. That gap is the real story of Applied AI in 2026. Adoption stopped being the hard question a while ago. The harder one: can what you've deployed actually run in production, not just survive a pilot? Access to models was never the constraint. The constraint is everything around it: governed data, identity controls, security built in from the start rather than bolted on after. Agentic AI raises the stakes further. Gartner expects up to 40% of enterprise apps to include task-specific AI agents by the end of 2026, up from under 5% last year. At the same time, Gartner projects over 40% of agentic AI projects will be cancelled by 2027. Both can be true in the same organisation at once. "Every client conversation now starts the same way: they've already experimented with AI, and they want to know why it isn't paying off yet," says Greta Mieliauskaitė, Account Executive at TeraSky Europe. "Adoption was never going to be the hard part. We built our practice around the harder work of making AI safe enough to run without someone watching it every hour." Full article, including where the scaling gap comes from 👇