This Week’s Top Five Stories in Technology

Lightwell: Securing Open Source with IBM and Red Hat

Open source code comprises up to 90% of enterprise codebases. With AI unleashing hidden exploits, traditional patch management simply cannot keep pace.

An average codebase today contains 581 vulnerabilities, according to IBM and Red Hat. To combat this, the pair have launched Lightwell, a platform designed to address this challenge through automated remediation and AI-powered dependency management.

The move builds on a US$5bn commitment to open source security announced in May 2026, supported by more than 20,000 engineers focused on scaling AI-powered remediation.

Ford Pro AI Saves Fleet Managers 20 Hours of Admin Monthly

Fleet managers – those who oversee a company’s commercial vehicles, drivers and related logistics – are struggling to keep on top of administrative tasks, according to telematics expert Jeremey Gould, who has been in the industry for 25 years, and serves as the Director of Ford Pro Solutions in Europe. 

“Only the largest companies have dedicated fleet managers and many of those are already multitasking, working on bits for HR, finance and marketing,” he explains.

“Smaller customers don’t have dedicated fleet managers and often in the field. It’s only in the evening that they have time to think about optimising their fleet operations. So anything they can do to improve their work is really welcomed by them.”

Oracle AI Studio Bridges Gap From No-Code to Pro-Code Tech

Oracle is helping both software engineers and non-technical business users to build and run their own agentic applications with Oracle AI Agent Studio for Fusion Applications, which integrate core functions like finance, supply chain, HR and customer experience into daily workflows. 

The new unified framework runs directly inside Oracle’s enterprise ecosystem to inherit existing security, governance and compliance controls without the need to add them later. 

Rather than acting as reactive conversational copilots that sit on top of software, Oracle’s new agentic applications are complete, outcome-driven systems. They employ specialised teams of AI agents to coordinate, reason, make decisions and execute complex workflows natively.

ABB and TCS sign multi-million AI network overhaul agreement

ABB and Tata Consultancy Services (TCS) have levelled up their 20-year relationship with a multi-million dollar, multi-year deal to rewrite how ABB’s global digital network runs.

ABB has more than 160 manufacturing sites with 111,900 employees working across them.

TCS’ software systems and cloud technology aims to better connect them all through a centalised, AI-powered network that can fix itself.

Global companies like ABB often suffer from fragmented networks where different systems run in different offices, which can create security blind spots and lag times.

Under this new deal, TCS will run ABB’s Future Network Model programme, bringing everything under a standardised Network-as-a-Service model.

Why Banking CRM is Overdue for an AI-Native Reinvention

Banks have spent the last two years experimenting with AI. The next challenge is far more  difficult: turning AI from an impressive novelty into a reliable part of everyday operations. 

While  the value of AI is no longer in question, many financial institutions are still working out how to deploy it consistently across customer interactions, compliance processes, relationship  management, and back-office operations without creating additional complexity or risk. 

While banks are investing billions in AI, many still face significant barriers to adoption  and scale. Creatio’s State of AI Agents and No-Code for Financial Services report identifies fragmented systems, siloed data, and regulatory, security, and legal concerns  as key obstacles preventing organisations from realising the full value of their AI  investments. 

At the same time, they face growing pressure to deliver even more personalised and seamless interactions, manage increasingly complex regulatory requirements, and improve operational efficiency in a highly competitive market.  

The question banks need to answer is no longer whether to adopt AI, but how to operationalise  it across the organisation.