News and Articles

Prompt engineering is the skill of giving AI clear, structured instructions so it delivers accurate, useful and consistent results. From defining format and audience to using examples and system prompts, better prompting improves productivity across every AI tool. For businesses, it is one of the lowest-cost, highest-impact ways to improve AI adoption and output quality.

AI ROI is not guesswork, it is a measurable business discipline. This guide explains how to quantify AI returns through efficiency gains, revenue uplift, risk reduction and quality improvements, while tracking key metrics such as payback period, time-to-value and accuracy rates before signing any vendor contract.

Neural networks are the core technology behind modern AI, learning patterns from data rather than following fixed rules. From fraud detection to demand forecasting, they power many business applications. Understanding how they work helps leaders ask better questions, evaluate vendors, and unlock practical AI value without needing technical expertise.

Retrieval-Augmented Generation (RAG) allows AI systems to answer questions using your organisation’s own documents, policies and data. Instead of relying only on general training knowledge, the AI retrieves relevant information from your internal sources and generates accurate responses grounded in your business content.

Large Language Models (LLMs) power tools like ChatGPT, Claude and Copilot. These AI systems can read, write, summarise and analyse human language, helping businesses automate communication, improve productivity and unlock insights from documents and data. Understanding how LLMs work is essential for organisations adopting AI-driven workflows.

Artificial intelligence is rapidly reshaping how medical advice is accessed across the EU, driven by major generative AI providers and governed by a strict, risk-based regulatory framework. This article explores how the EU AI Act and GDPR are shaping medical AI, contrasts Europe’s approach with the UK and US, and examines what these developments may signal for the future of AI-powered financial advice, outlining benefits, risks, and unresolved questions without prescribing o

Automated interviewing platforms powered by AI combine the scale of surveys with the depth of human interviews. For Malta, they offer a new way to conduct voting surveys, public consultations, political research, and market insight, faster, cheaper, and with richer qualitative data. With strong governance and GDPR alignment, Malta could become an early European adopter of this next-generation research model.

Apple is integrating Google’s Gemini models into a revamped Siri, scheduled for release in Spring 2026. This hybrid approach uses Apple’s on-device processing for privacy and Google’s 1.2 trillion parameter cloud model for complex tasks. By paying Google $1 billion annually, Apple is prioritizing market speed and cost-efficiency over proprietary development. While the deal boosts Google’s market standing, it faces heavy regulatory scrutiny and complicates Apple’s ties with Op

Malta’s AI strategy, aligned with Vision 2050, positions education as a key driver of social equity and economic growth. By using AI for personalised learning, predictive analytics, and teacher support, the strategy aims to reduce educational disparities, prevent early school leaving, and raise standards in core skills. Parallel investments in AI literacy, higher education, and teacher training are designed to ensure students and the workforce remain future-ready.

Malta’s revised AI Strategy positions tourism, hospitality, and catering as a priority sector for artificial intelligence deployment. By leveraging data-driven decision-making, predictive analytics, and a national Digital Tourism Platform, the strategy aims to enhance visitor experiences, support sustainable tourism, protect heritage sites from over-tourism, and enable competitive, AI-powered operations across the industry.

The article summarises the EU's draft Code of Practice for AI transparency. It details the "mark and detect" technical requirements for providers and "label and disclose" rules for business owners using AI. Key highlights include the proposed common "AI" icon and the important exemption for content undergoing human review. The Code serves as a practical roadmap for businesses to achieve AI Act compliance by mid-2026.

TL;DR The first half of 2025 saw unprecedented investments and spending in AI, with companies like OpenAI, Anthropic, and xAI raising tens of billions and new startups securing multi-billion dollar seed rounds, fueling massive infrastructure build-outs. However, by the latter half of the year, a "vibe check" emerged, bringing concerns about an AI bubble, user safety, and the sustainability of current technological progress. Model advancements became more incremental, shifting

The festive peak season is a make-or-break period. Discover how integrating advanced AI, including machine learning for forecasting and generative AI for hyper-personalization, can transform your operations, protect margins, and elevate customer loyalty during the most critical sales period.

Measure your AI project's true ROI. Get the essential formulas, 9 high-impact metrics (Cost, Revenue, Risk), and the 5-step playbook for CFOs and Data Scientists to quantify value for 2026 budgeting

Artificial Intelligence (AI) is fundamentally reshaping the future of accountancy and finance . This transformation brings both exciting opportunities and critical challenges that finance professionals must address to stay ahead. The message is clear: Upskilling and adaptability are no longer optional, they are essential . 💡 Key Takeaways for the Finance Professional Automation is Freedom: AI is automating routine tasks, freeing up professional time for higher-value strateg