Daily Tech Digest - September 16, 2025


Quote for the day:

“Too many of us are not living our dreams because we are living our fears.” -- Les Brown



Your employees are feeling ‘OK’ – and that’s a serious problem

At first glance, OK doesn’t sound dangerous. Teams aren’t unhappy enough to trigger alarms, nor are they burning out; they keep delivering at an acceptable level. But ‘acceptable’ is not the same as ‘successful’. Teams stuck in OK lack the energy, creativity and ambition to truly thrive. They’re passable, not powerful – and that complacency can quietly erode performance. ... In fact, the lifetime value of a happy employee is more than twice that of an OK one. This is not soft sentiment – it’s hard economics. By contrast, OK teams bring hidden costs. They are about twice as likely to miss targets as happy teams and have 50% higher staff turnover. They are also less collaborative, less creative and less resilient when challenges arise. ... First, reframe happiness as a serious business metric. It’s not vague or fluffy. It’s measurable, trackable and improvable. It connects directly to performance, retention and, ultimately, profit. Second, focus on the drivers of happiness. I’ve identified five ways to develop happiness at work: connect, be fair, empower, challenge and inspire. ... Third, embed a rhythm of measure-meet-repeat. Measure: Use light-touch weekly pulses and deeper quarterly surveys to gather data; Meet: Bring teams together to discuss results, identify blockers and celebrate progress; and  Repeat: Build momentum with regular reflection and action. This rhythm transforms data into dialogue, which helps organisations to improve.


Are cloud providers neglecting security to chase AI?

an unsettling trend now challenges this narrative. Recent research, including the “State of Cloud and AI Security 2025” report conducted by the Cloud Security Alliance (CSA) in partnership with cybersecurity company Tenable, highlights that cloud security, once considered best in class, is becoming more fragmented and misaligned, leaving organizations vulnerable. The issue isn’t a lack of resources or funding—it’s an alarming shift in priorities by cloud providers. As investment and innovative energies focus more on artificial intelligence and hybrid cloud development, security efforts appear to be falling behind. ... The dangers of this complexity are made worse by what the report calls the weakest link in cloud security: identity and access management (IAM). Nearly 59% of respondents cited insecure identities and risky permissions as their main concerns, with excessive permissions and poor identity hygiene among the top reasons for breaches. ... Deprioritizing security in favor of AI products is a gamble cloud providers appear willing to take, but there are clear signs that enterprises might not follow them down this path forever. The CSA/Tenable report highlights that 31% of surveyed respondents believe their executive leadership fails to grasp the nuances of cloud security, and many have uncritically relied on native tools from cloud vendors without adding extra protections.


The Future of Global A.I.

The accelerating development and adoption of AI products, services and platforms present both challenges and opportunities for regions like the Middle East and North Africa (MENA) and India that have ambitions of integrating AI into their economies. Data presented in the report suggests that the mobile user bases in India and MENA are primed for AI products and services on mobile platforms. For the Middle East, AI is a crucial enabler of economic diversification beyond its hydrocarbon industries, whereas for India, AI can be transformative for its world-leading digital public infrastructure, public service delivery, and digital payments platforms.  ... The BOND report notes that the current wave of AI development and adoption is unprecedented when compared to previous technological waves. It uses OpenAI’s ChatGPT as a benchmark to showcase the explosive growth of user adoption as the platform achieved 1 million users within five days, 800 million weekly active users within 17 months, and registered 90 percent of its users from non-US geographies by its third year. ... In an era of increasing geopolitical competition, countries are supporting efforts to achieve digital sovereignty. The BOND report notes a growing interest in Sovereign AI projects, as demonstrated by NVIDIA’s partnerships in countries like France, Spain, Switzerland, Ecuador, Japan, Vietnam, and Singapore.


Zero Trust Is 15 Years Old — Why Full Adoption Is Worth the Struggle

Effective ZT will not eliminate all breaches – there are simply too many ways into a network – but it would certainly limit the effectiveness of stolen credentials and inhibit lateral movement by intruders, and malicious activity by insiders inside the enterprise network. “Here’s the part most people miss: Zero Trust is just as important for reducing insider risk as it is for keeping out external threats.,” comments Chad Cragle. “Zero Trust is just as important for reducing insider risk as it is for keeping out external threats.” ... Putting people first is good people management and good PR, but bad security. It gives too much leeway to three basic human characteristics: a propensity to trust on sight, a tendency to be lazy, and a deep rooted curiosity. We have a natural tendency to trust first and ask questions later; to skirt security controls when they are too intrusive and hinder our work, and we are naturally curious. ... Technology first is becoming more essential in the emerging world of AI-enhanced deepfakes. We can no longer rely on people being able to recognize people. We are easily fooled into believing this entity is the entity we know and trust. ... Getting the technology ready for ZT is also hard, partly because many applications were not built with ZT in mind. “Many older programs just don’t play nice with modern security,” comments J Stephen Kowski, “so businesses end up stuck between keeping things secure and not slowing down the way they work.”


Crafting an Effective AI Strategy for Your Organization: A Comprehensive Approach

Without a deliberate strategy, AI initiatives might remain small pilot projects that never scale, or they might stray from business needs. A well-crafted AI strategy acts as a compass to guide AI investments and projects. It helps answer critical questions upfront: Which problems are we trying to solve with AI? How do these tie to our business KPIs? Do we have the right data and infrastructure? By addressing these, the strategy ensures AI adoption is purposeful rather than purely experimental. Crucially, the strategy also weaves in ethical and regulatory considerations ... An AI CoE is a dedicated team or organizational unit that centralizes AI expertise and resources to support the entire company’s AI initiatives. Think of it as an in-house “AI SWAT team” that bridges the gap between high-level strategy and the technical execution of AI projects. ... As organizations deploy AI more widely, ethical, legal, and societal responsibilities become non-negotiable. Responsible AI is all about ensuring that systems are fair, transparent, safe, and aligned with human values. ... Many AI models, especially deep learning systems, are often criticized for being “black boxes”—making decisions that are difficult to interpret. Explainable AI (XAI) is about creating methods and tools to make these models transparent and their outputs understandable.


Building security that protects customers, not just auditors

Good engineering usually leads to strong security, and cautions against just going through the motions to meet compliance requirements. ... Sadly, threat actors don’t need to improve, most of the market is very far behind and old-school attacks like phishing still work easily. One trend we’re seeing in the last few years is a strong focus on crypto attacks, and on crypto exchanges. Even these usually involve classic techniques. Another are “SMS abuse” attacks, where attackers exploit endpoints that trigger sending sms messages, which they send to premium numbers they want to bump up. Many such attacks are only discovered when the bill from the SMS provider arrives. ... Current Security Information and Event Management (SIEM) vendors often offer stacks and pricing models that just don’t fit the sheer scale and speed of transactions. Sure, you can make them work, if you spend millions! ... If you just check boxes, you are not protecting your customers, you are just protecting your company from the auditor. Try to understand the rationale behind the control and implement it according to your company’s architecture. Think of it philosophically, would you be happy being a box-ticker or would you prefer to have impact? ... Your goal is to find a way to collaborate with your QSA, they can be true partners for driving positive change in the company. 


Enterprise-Grade Data Ethics: How to Implement Privacy, Policy, and Architecture

Embedding ethics and privacy into daily business operations involves practical, continuous steps integrated deeply into organizational processes. Core recommendations include developing clear and understandable data policies and making them accessible to all stakeholders, regularly training teams to maintain updated awareness of ethical data standards, building privacy considerations directly into system architecture from inception, and collaborating with legal and technical teams on application programming interfaces (APIs) and data models to incorporate explicit privacy rules. ... An enterprise architecture framework creates fundamental support by outlining precise methods for data storage, transfer, and access permissions. Organizations use new and emerging technologies alongside other comprehensive tools to establish systematic policies while implementing strong encryption and data masking approaches for secure data management. ... Executive leaders who dedicate themselves to ethical data handling create profound changes in corporate cultural values. Organizations can demonstrate their strategic dedication to data ethics through executive-level visibility of privacy and ethics system design oversight, combined with employee training investments and performance accountability systems.


CIOs are stressed — and more or less loving it

Not surprisingly AI has upped the ante for stress — or in Richard’s case, concern over the quick adoption of AI tools by end users who may or may not know what to do with them. “I would say that’s probably the thing I worry about the most. I don’t know that it stresses me out,” but he constantly thinks about what tools employees are using and how they are using them. “We don’t want to suck away all the productivity gains by limiting access to great tools, but at the same time, we don’t want to let people run wild with [personally identifiable information] or data” by tools not managed by IT. ... Even with all the pressures on CIOs today and the need to wear many hats, most say the job is still worth it. Pressure, it seems, is not always a bad thing. “I’m still in it, so it must be worth it,’’ Grinnell says. “CIOs have a certain personality; we know you’re not getting into the job and it’ll be smooth sailing. We have to solve a challenge — whatever the challenge is.” … It’s tiring, it’s stressful, but I get up energized every day to go tackle that. That’s who I am.” Driscoll says she likes pressure and finds her role “worth it more now than ever because the job of CIO and CTO has evolved to where the expectation is you will be responsible for the technology, but also be a core partner in where the business is going. For me, that ability to help drive business outcomes, and shape wherever we go as a company makes my job more exciting and worth it.”


How AI and Machine Learning Are Shaping the Fight Against Ransomware

Machine learning algorithms can recognise and understand complex patterns within data sets. Analysing historical information facilitates the identification of behavioural patterns associated with ransomware attacks, enabling strategies to be developed to prevent these attacks in the future. One of the best examples is the use of AI tools that have proven successful in detecting and protecting against cyber threats, including ransomware, by examining and analysing network traffic and user behaviour. ... When it comes to ransomware, speed is everything. As noted by IBM, AI-enabled systems allow organizations to respond to threats 85% faster than traditional methods. This rapid response reduces the damage caused by an attack while also delivering cost savings of unimaginable value to enterprises.  ... Machine learning algorithms are given information about a user’s network activity that is considered normal. Any subsequent actions are deemed abnormal if they involve changes to files and data that are out of the norm for the user. These activities are flagged so that they can be pursued further. This level of automation allows the detection of the presence of ransomware prior to encryption, allowing for timely user intervention. With ransomware pre-encryption detection algorithms, 999 out of 1000 threats can be accurately identified. CrowdStrike also claims to have captured remarkable behaviour-based ransomware detection accuracy.


Navigating the new frontier: Data sovereignty, AI and the role of global infrastructure

Data centers, once mere warehouses of information, are now the backbone of AI-driven economies. In an ever-expanding universe of digital information and content, data center operators are now faced with the daunting task of balancing operational efficiencies against the stringent need for regulatory compliance. As governments worldwide tighten regulations around data residency, cybersecurity, and AI governance, multinational companies face a complex challenge: how to maintain seamless operations while adhering to diverse and often conflicting legal frameworks. ... The integration of programmable infrastructure and cloud-Edge capabilities into cross-border networks and operations further enhances flexibility, allowing customers to localize data processing without duplicating costly physical assets. This hybrid model, underpinned by scalable, region-sensitive architecture, positions compliance as an intrinsic design principle rather than an afterthought. As data sovereignty laws proliferate, governments must support these efforts through fundamental research, clear regulatory frameworks, and partnerships with industry leaders to avoid a fragmented digital landscape that could stifle innovation. ... The convergence of data sovereignty, AI governance, and critical infrastructure security demands a new model of digital governance - one where compliance, innovation, and resilience are seamlessly integrated. 

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