It’s been a while since we launched Above Trends, Beyond Insights. What started as an experiment in rethinking our editorial voice has now become a steady practice: every issue, we scan the signals that matter and translate them into business insight. Our commitment remains the same (less noise, more signal), with an even stronger focus on what executives need to navigate uncertainty: timely context, curated trends, and practical guidance.

How we recognise authenticity in an age of AI-written text

The rapid growth of machine generated content is changing how we read and evaluate what appears online. AI generated more online articles than human authors in November 2024, which makes the ability to recognise automated writing increasingly relevant.

Even Wikipedia now hosts a dedicated page, Signs of AI writing, that summarises the most frequent patterns. Some are obvious once pointed out, others are subtler, yet together they form a useful framework for understanding how AI tends to shape language.

• Tone is usually the first clue, because AI tends to favour a consistently smooth and balanced register that avoids personal angles, tension or sharper emotional shifts.

• Structure offers another useful signal, with long paragraphs built around a regular sequence of connectors that rarely allows digressions or irregular rhythms.

• About style: machine written text includes few specifics and relies on generic examples that could fit almost any context, and it often repeats certain ready made expressions that sound polished but indistinct. These markers are not definitive on their own, yet when several appear together they create a kind of linguistic uniformity that many editors have started to recognise.

Research also shows how easily this style influences human writers. A 2024 study by the MIT found reduced activity in the areas of the brain linked to creativity and memory when participants used AI to compose entire texts, and many struggled to recall what they had just produced. It is a reminder that convenience can quietly shape not only how we write, but how we think while writing.

What matters to me is keeping AI in the role of a tool rather than a substitute for the thinking that gives shape to a piece of writing. It can help getting started when the first lines feel slow, but the substance still needs to come from the choices and reflections that only a person can make. Using it this way keeps the process efficient without removing the part that makes the work genuine.

TREND TRACKER

Autonomous code remediation: from assistance to action

AI assisted development is moving into a new phase in which models do not just highlight a problem but can propose, apply and verify a fix.

GitHub Copilot Workspace and similar tools are experimenting with workflows where the system identifies a vulnerability or a bug, drafts the remediation and evaluates its impact before the developer intervenes. Efficiency is the driver, yet the implications reach beyond speed.

Automated remediation can reduce pressure on engineering and security teams, especially in large organisations with complex codebases, although it also raises questions about oversight, accountability and the risk of adopting corrections without fully understanding their context. Several industry analyses show that these models already perform reliably on routine issues, while more complex cases still require human judgment.

For companies, the current opportunity lies in adopting autonomous remediation as an incremental support rather than a replacement, especially in environments that must balance velocity and compliance.

Want to learn more?

• GitHub Blog – GitHub Copilot Workspace: welcome to the next generation of AI coding assistants

• GitHub Blog – GitHub Copilot: the agent awakens

• DigitalOcean – 10 AI code review tools that find bugs and flaws in 2025

• DEV Community – The future of AI assisted debugging: tools that fix bugs before you see them

QUICK INSIGHT

Preparing for 2025 cloud cost audits

Cloud spending reviews are becoming more frequent as organisations prepare next year’s budgets and assess the impact of expanded AI workloads, storage growth and multi cloud strategies. A few targeted actions can simplify internal audits and reduce oversights.

• Map resources that have remained idle or consistently underused during the last ninety days.

• Identify duplicated services across teams and consolidate them where appropriate.

• Review storage plans and retention policies that no longer match actual usage.

• Apply spending limits to testing and development environments to contain unexpected peaks.

• Request monthly reports with detailed breakdowns per business unit to improve transparency and forecasting.

WHO IS BABINI MAZZARI

Our Value Proposition

Babini Mazzari is the strategic IT partner for European companies looking to navigate digital transformation in a structured, pragmatic, and sustainable way.
We don’t just deliver technical solutions - we work as an extension of your internal team, helping you integrate systems, optimize processes, and lead change with clarity and competence.

Our approach is built on listening, transparency, and a strong results-driven culture. Whether you're scaling, modernizing, or rethinking your operating model, we support every client with the right tools, clear methodology, and long-term vision.
Above Technology. Beyond Solutions.

📎 [Our services]
📎 [Our Manifesto]