AI is the next logical evolution of the cloud. Google’s Gemini realized 34% YoY (Q3 2025) and 650 million users, while Microsoft’s Copilot/Azure) realized 39% YoY (FY Q4 2025) and 150 million Copilot users. The buildout has begun and will not slow down anytime soon. Meanwhile, in 2025, AI adoption transitions from experimental curiosity to essential operational infrastructure, with roughly 1 in 6 people worldwide using generative AI tools. 

BridgeView’s PR Services knows you can’t have AI without the cloud, and you can’t have the cloud without datacenters. That’s why we brought hi-tequity’s Ryan Friedman, who builds data centers, to the Data Center Post.  He is in a unique position to witness this AI transition. Anyone who has experienced the rise of the internet can certainly attest to this perspective and AI’s longevity. 

Enjoy Ryne’s insights, originally posted by Data Center Post at: https://datacenterpost.com/its-not-an-ai-bubble-were-witnessing-the-next-cloud-revolution/

Alphabet, Amazon, and Microsoft; these tech giants’ cloud services, Google Cloud, AWS, and Azure, respectively, are considered the driving force behind all current business computing, data, and mobile services. But back in the mid-2000s, they weren’t immediately seen as best bets on Wall Street. When Amazon launched AWS, analysts and investors were skeptical. They dismissed AWS as a distraction from Amazon’s core retail business. The Wall Street wizards did not understand the potential of cloud computing services. Many critics believed enterprises would never move their mission-critical workloads off-premises and into remote data centers.

As we all know, the naysayers were wrong, and cloud computing took off, redefining global business. It turbo-charged the economy, creating trillions in enterprise value while reducing IT costs, increasing application agility, and enabling new business models. In addition, the advent of cloud services lowered barriers to entry for startups and enabled rapid service scaling. Improving efficiency, collaboration, and innovation through scalable, pay-as-you-go access to computing resources was part of the formula for astounding success. The cloud pushed innovation to every corner of society, and those wise financiers misunderstood it. They could not see how this capital-intensive, long-horizon bet would ever pay off.

Now, we are at that moment again. This time with artificial intelligence.

Headlines appear every day saying that we’re in an “AI bubble.” But AI has gone beyond mere speculation as companies (hyperscalers) are in early-stage infrastructure buildout mode. Hyperscalers understand this momentum. They have seen this movie before with a different protagonist, and they know the story ends with transformation, not collapse. The need for transformative compute, power, and connectivity is the catalyst driving a new generation of data center buildouts. The applications, the productivity, and the tools are there. And unlike the early cloud era, sustainable AI-related revenue is a predictable balance sheet line item.

The Data

Consider these most recent quarterly earnings:

• Microsoft Q3 2025: Revenue: $70.1B, up 13%. Net income: $25.8B, up 18%. Intelligent Cloud grew 21% led by Azure, with 16 points of growth from AI services.
• Amazon Q3 2025: Revenue: $180.2B, up 13%. AWS grew 20% to $33B. Trainium2, its second-gen AI chip, is a multi-billion-dollar line. AWS added 3.8 GW of power capacity in 12 months due to high demand.

• Alphabet (Google Parent) Q3 2025: Revenue: $102.35B, up 16%. Cloud revenue grew 33% to $15.2B. Operating income: up nearly 85%, backed by $155B cloud backlog.
• Meta Q3 2025: Revenue: $51.2B, up 26%. Increased infrastructure spend focused on expanding AI compute capacity. (4)

These are not the signs of a bubble. These are the signatures of a platform shift, and the companies leading it are already realizing returns while businesses weave AI into operations.

Bubble or Bottleneck

However, let’s be clear about this analogy: AI is not simply the next chapter of the cloud. Instead, it builds on and accelerates the cloud’s original mission: making extraordinary computing capabilities accessible and scalable. While the cloud democratized computing, AI is now democratizing intelligence and autonomy. This evolution will transform how we work, secure systems, travel, heal, build, educate, and solve problems.

Just as there were cloud critics, we now have AI critics. They say that aggressive capital spending, rising energy demand, and grid strain are signs that the market is already overextended. The pundits are correct about the spending:

• Alphabet (Google) Q3 2025: ~US $24B on infrastructure oriented toward AI/data centers.
• Amazon (AWS) Q3 2025: ~US $34.2B, largely on infrastructure/AI-related efforts.
• Meta Q3 2025: US $19.4B directed at servers/data centers/network infrastructure for AI.
• Microsoft Q3 2025: Roughly US $34.9B, of which perhaps US $17-18B or more is directly AI/data-center infrastructure (based on “half” of capex).

However, the pundits’ underlying argument is predicated on the same misunderstandings seen in the run-up to the cloud era: it confuses infrastructure investment with excess spending. The challenge with AI is not too much capacity; it is not enough. Demand is already exceeding grid capacity, land availability, power transmission expansion, and specialized equipment supply.

Bubbles do not behave that way; they generate idle capacity. For example, consider the collapse of Global Crossing. The company created the first transcontinental internet backbone by laying 100,000 route-miles of undersea fiber linking 27 countries.

Unfortunately, Global Crossing did not survive the dot-com bubble burst (1990-2000) and filed for bankruptcy. However, Level 3, then CenturyLink (2017), and Lumen Technologies knew better than to listen to Wall Street and acquired Global Crossing’s cables. Today, Lumen has reported total 2024 revenue of $13.1 billion. Although they don’t specifically list submarine cable business revenue, it’s reasonable to infer that these cables are still generating in the low billion-dollar revenue figures—a nice perpetual paycheck for not listening to the penny pinchers.

The AI economy is moving the value chain down the same path of sustainable profitability. But first, we must address factors such as data center proximity to grid strength, access to substation expansion, transformer supply, water access, cooling capacity, and land for modern power-intensive compute loads.

Power, Land, and the New Workforce

The cloud era prioritized fiber; the AI era is prioritizing power. Transmission corridors, utility partnerships, renewable integration, cooling systems, and purpose-built digital land strategies are essential for AI expansion. And with all that comes the “pick and shovel” jobs building data centers, which Wall Street does not factor into the AI economy. You need to look no further than Caterpillar’s Q3 2025 sales and revenue of $16.1 billion, up 10 percent.

Often overlooked in the tech hype are the industrial, real estate, and power grid requirements for data center builds, which require skilled workers such as electricians, steelworkers, construction crews, civil engineers, equipment manufacturers, utility operators, grid modernizers, and renewable developers. And once they’re up and running, data centers need cloud and network architects, cybersecurity analysts, and AI professionals.

As AI scales, it will lift industrial landowners, renewable power developers, utilities, semiconductor manufacturers, equipment suppliers, telecom networks, and thousands of local trades and service ecosystems, just as it’s lifting Caterpillar. It will accelerate infrastructure revitalization and strengthen rural and suburban economies. It will create new industries, just like the cloud did with Software as a Service (SaaS), e-commerce logistics, digital banking, streaming media, and remote-work platforms.

Conclusion

We’ve seen Wall Street mislabel some of the most significant tech expansions, from the telecom-hotel buildout of the 1990s to the co-location wave, global fiber expansion, hyperscale cloud, and now, with AI. Just like all revolutionary ideas, skepticism tends to precede them, even though there’s an inevitability to them. But stay focused: infrastructure comes before revenue, and revenue tends to arrive sooner than predicted, which brings home the point that AI is not inflating; it is expanding.

Smartphones reshaped consumer behavior within a decade; AI will reshape the industry in less than half that time. This is not a bubble. It is an infrastructure super-cycle predicated on electricity, land, silicon, and ingenuity. Now is the time to act: those who build power-first digital infrastructure are not in the hype business; they’re laying the foundation for the next century of economic growth.

The post It’s Not An AI Bubble — We’re Witnessing the Next “Cloud” Revolution appeared first on Bridgeview Marketing.

This article delivers an essential wake-up call to business leaders about the urgent need for robust data governance frameworks before the wild west of unsecured AI development becomes a playground for cybercriminals. 

By helping CIOSO Global articulate these complex security challenges in accessible terms, BridgeView has enabled an important conversation about balancing innovation with protection—a message that couldn’t be more relevant as cybercrime costs are projected to reach $10.5 trillion by 2025. The piece provides actionable guidance for implementing security-first AI strategies, making it an invaluable resource for organizations navigating this new frontier.

Thank you, AI Journal, for originally posting this article: https://aijourn.com/citizen-developers-ride-unbridled-llm-coding-ai-manifest-destiny/

Every new frontier brings both pioneers and peril. Artificial intelligence is no different. Its  rapid democratization is allowing this profound, paradigm-shifting technology to be used by a wider audience well beyond the data scientists and trained coders. 

As AI tools trickle down into more untrained hands, large language models (LLMs) now guide untrained individuals through complex coding processes at blinding speed, ushering in the age of the citizen developer. However, these Python-slinging developers create a lawless cloud zone of half-baked or abandoned coding projects. Unchecked, these projects dramatically increase the number of available attack vectors and expose corporations to a new host of vandals who can ride in and hold corporate data hostage.   

Reports describe this growing data governance problem and how it has already increased cyberattacks: 13% of organizations have reported breaches of AI models or applications, and among those breached, 97% lacked proper AI access controls. What’s even more concerning is that 63% of breached organizations either don’t have an AI governance policy or are in the process of developing one. All this is unfolding as cybercrime is projected to cost businesses up to $10.5 trillion by 2025. 

The Expanding Attack Surface  

The rise of citizen developers, non-engineers using AI-powered tools to build applications and conduct analyses, is spreading organizational data across previously controlled boundaries. From a cybersecurity perspective, this new trend widens the attack surface area.  

AI tools require data; without it, they are ineffective. When business users feed sensitive datasets into unsecured AI environments, they will unknowingly increase the organization’s overall attack surface area by lowering the walls around their fort, leaving their organization vulnerable beyond traditional IT perimeters. The result is a two-tier problem: rapid AI development and inadequate AI governance. 

The Governance Imperative 

Before allowing AI-based analytics access to any dataset, organizations must first ask: 

1. Do we have the correct security in place to process data in this manner?  
2. Has the data been appropriately cleansed for the specific analyses being conducted? 

These questions are not mere formalities but the foundation of responsible AI deployment. Any outliers must be evaluated for their potential usefulness in modeling rather than automatically discarded. Each of these decisions has implications for the integrity of AI outputs and underlying data security. 

The framework connecting exploitability, vulnerability, and probability of exposure becomes critical when considering AI workflows. Threat actors more readily breach systems where sensitive data flows freely, and even more enticing are citizen developer environments that lack the security controls present in traditional IT systems. Increased access points and inadequate governance surrounding valuable data are exactly the combination of factors that get the attention of cybercriminals. 

Building a Security-First AI Strategy 

Security-first goes beyond maintaining compliance. Effective AI deployment requires key operating principles. These principles must be executed, managed, and tracked against compliance requirements and organizational policies. A formal management program is key to this approach; the program must be well-governed, systematically tracked and built for managing exceptions. In this manner, organizations can maintain visibility into where their data flows through AI, who has access to it, and how it’s being used. 

The challenge extends beyond access control. There is a risk when retaining data and allowing for necessary data replication through citizen developer programs. Frameworks must be implemented that appropriately protect data for confidentiality and compliance while allowing business-user AI tool access. 

Success requires a combination of security engineering and data governance disciplines anchored in clearly defined risk tolerance, transparency, and shared responsibility guidelines. Security teams must work in tandem with the organization’s data stewards, and citizen developers cannot operate without understanding the implications of their data usage. 

The Path Forward 

The democratization of coding is AI’s manifest destiny. However, this migration comes with risks, and organizations must implement robust data governance frameworks. Otherwise, they may find themselves open to hostile attacks perpetrated by the weaponization of their coding projects. The fact remains, data becomes ammunition for threat actors exploiting inadequately secured AI-based projects. 

The solution does not restrict innovation; instead, it installs guardrails that enable secure AI deployment at scale. Governance policies must clearly define ownership, accountability, and escalation paths. Training programs must also teach citizen developers the fundamentals of security. This establishes clear policies for AI governance and implements technical controls that enforce data protection requirements without stifling creativity. 

The data in AI pipelines must be checked for accuracy, compliance and biases, as well as for lawful processing rights, cleansing integrity, and proper outlier treatment. Organizations should implement automated tools, combined with manual oversight, for proper vulnerability assessments. Code reviews should examine both algorithms and software for potential security flaws. 

As untrained coders leverage AI on a journey to application boomtown, the question is: How do you mitigate risk while cultivating enthusiasm? Those organizations that succeed will be the ones that see data governance as the sheriff of AI security. Without established guidelines, democratized AI will become the lawless wild west ruled by black-hatted hackers. 

The post Citizen Developers & LLM Coding appeared first on Bridgeview Marketing.

Equally important is the strategic placement of client stories on high-quality online news sites that include authoritative backlinks. These backlinks not only enhance credibility and trust with readers but also deliver measurable business value by improving search visibility, domain authority, and long-term discoverability of client expertise.

Originally posted by Cyber Security Intelligence at https://www.cybersecurityintelligence.com/blog/ai-has-enabled-cyber-crime-to-become-industrialised-9100.html

Quorum Cyber has published its 2026 Global Cyber Risk Outlook report, detailing a significant evolution in cyber threats driven by Artificial Intelligence (AI) and Ransomware-as-a-Service (RaaS) platforms. The analysis, based on incidents across more than 350 organisations worldwide in 2025, indicates that cyber crime has entered a more industrialised phase. This development allows even poorly skilled attackers to launch sophisticated operations, with nation-state actors automating up to 90% of intrusions using AI tools.

The report highlights how AI-enabled tooling and accessible RaaS platforms have lowered entry barriers for criminals, expanding their reach and accelerating attack speeds. Organisations now confront shorter detection windows and heightened risks, as attackers move beyond traditional methods.

Rising Ransomware Groups & AI Integration

The number of newly formed ransomware groups rose by 30% in the 12 months to October 2025, fuelled by the emergence of white-label RaaS platforms that enable quick branding of criminal operations. This trend has professionalised cyber crime, allowing groups to operate like businesses. Early evidence points to a nation-state-backed group employing AI agents, such as those from Claude, to handle up to 90% of intrusion activities, marking a notable escalation in automated threats.

Quorum Cyber’s Chief Executive Officer, Federico Charosky, commented, “Over the past year, we have witnessed a marked acceleration in the capability and ambition of threat actors. The proliferation of AI-enabled tooling, combined with an increasingly professionalised cybercriminal economy, has lowered barriers to entry and expanded the reach of even modestly skilled actors.” The report draws from intelligence, incident response, and counter-extortion efforts to provide guidance on mitigating these risks.

Surge in Vulnerabilities & Tactical Shifts

Global vulnerability disclosures increased by 21%, exceeding 35,000 for the year to October 2025, amplifying opportunities for exploitation. Cybercriminals are increasingly abandoning slow encryption tactics in favour of faster, lower-cost data exfiltration attacks, which allow quicker monetisation of stolen information.

Average ransom demands have escalated sharply across sectors, with a 179% increase in financial services and a 97% rise in manufacturing. Nation-state actors linked to Russia, China, and Iran continue to pose major threats to the public sector through sustained espionage campaigns, while North Korea-associated groups are estimated to have generated over $2 billion from cyber crime in 2025.

Sector-Specific Impacts

The outlook includes companion reports for nine industries, tailoring insights to specific risks. In financial services, high-value data attracts financially motivated and state-linked actors. Healthcare and pharmaceuticals saw a 26% rise in cyber activity, driven by ransomware and access brokers targeting operational disruptions. Manufacturing faces vulnerabilities from operational technology and supply chains, with ransomware demands nearly doubling.

• Higher education experienced a 73% increase in data breaches, pressured by open networks and valuable research data.

• Professional services, including legal, noted a 43% uptick in ransomware targeting and 20% more data breaches.

• Energy and utilities contend with geopolitical tensions, while public sector threats stem from service disruptions.

• Housing and construction deal with sensitive tenant data, and retail faces risks from digital sales and customer information.

Nation-State & Broader Threats

Threat actors from Russia, China, and Iran remain dominant in public sector attacks, supplemented by North Korean groups, organised crime, and hacktivists adapting their methods. Governments in the UK, US, Canada, and Australia have updated cybersecurity legislation to bolster national defences.

Quorum Cyber advises shifting to proactive resilience, leveraging intelligence-led security. Defensive AI is maturing, aiding early anomaly detection and efficient investigations. This report emphasises the need for organisations to anticipate threats through enhanced collaboration and managed services. 

The post AI Has Enabled Cyber Crime To Become Industrialised appeared first on Bridgeview Marketing.

Portsmouth, NH — February 10, 2026 — BridgeView Marketing, an innovative digital agency integrating tech PR and marketing, today announced the launch of PR Rosetta Stone™, a proprietary, AI-enabled PR reporting and intelligence system designed to show executives exactly how earned media drives their company’s website traffic, search visibility, AI discoverability, and revenue-relevant engagement.

Search now extends beyond Google, with AI platforms playing an increasingly important role in brand discovery. These platforms value authority, quality backlinks, editorial credibility, and consistent earned media. Holistic reporting standards are lagging, as legacy PR agencies rely solely on metrics such as impressions and outdated advertising value equivalency (AVE) figures. 

These vanity metrics do not link press coverage to website visits or traffic sources, nor do they provide ROI per media placement. Without placement-level ROI, marketing leaders and executives lack a clear understanding of PR impact when making budget decisions or comparing success to monthly retainers.

PR Rosetta Stone applies a decision-grade framework that assigns placement-level value to each earned media placement using a weighted model of authority, reach, and website credibility. The automated report correlates coverage timing with Google Analytics (GA4) referral traffic and on-site engagement, making PR impact easier to validate and communicate while uncovering potential sales leads.

“The way PR Rosetta Stone hierarchically weights MOZ authority, audience reach, and follower credibility is both unique and highly valuable, with the calculation framework itself serving as a clear differentiator. Even more powerful is the aggregated correlation of referral traffic and media coverage spikes, which finally answers the question executives care about most—how press coverage actually drives awareness, engagement, and website traffic,” said Miranda McCurdy, Head of Brand and Inbound Demand, Quorum Cyber. 

C-Level Visibility at AI Speed

PR Rosetta Stone was built to finally close the visibility gap. Unlike traditional PR reporting, its push-button analysis unifies the following data into a single dashboard reporting structure:

• Earned media performance.
• Backlink quality. 
• Google Analytics 4 (GA4) traffic intelligence.
• Large Language Model (LLM) visibility signals.
• Sales-relevant web traffic insights. 

The resulting report provides a decision-grade framework that replaces legacy vanity metrics with verifiable impact.

Pricing and Availability

Designed for the AI era, the reporting system is part of BridgeView Marketing’s PR services and is currently available to retainer-based clients.

“With the introduction of PR Rosetta Stone, BridgeView Marketing is redefining how PR value is measured—transforming earned media from a subjective exercise into a measurable, revenue-aligned business function,” said Michael Emerton, CEO and Founder, BridgeView Marketing.

For more information on Rosetta Stone, please visit https://www.bridgeviewmarketing.com/marketing-consulting-services/pr-rosetta-stone/

About BridgeView Marketing

For over two decades, BridgeView Marketing has specialized in technology-driven PR and communications. Formed as a nimble, boutique partner without the bloated overhead of agency pricing, its members leverage their technology training to deliver earned media strategies and measurable outcomes, while the company’s webmasters produce SEO-compliant websites. For more information, please visit: bridgeviewmarketing.com.

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The post BridgeView Marketing Launches PR Rosetta Stone™, an AI-Enabled System for Decision-Grade PR ROI appeared first on Bridgeview Marketing.

Victoria Durgin’s conversation with Quorum Cyber’s CEO, Federico Charosky paints a vivid, but alarming picture of the 2026 cybersecurity landscape while pointing out MSSPs must focus on the fundamentals of cybersecurity and augment with AI where it makes sense. 

Enjoy this enlightening and informative piece of journalism captured by Channel Insider: https://www.channelinsider.com/security/managed-services/quorum-cyber-security-outlook-2026/

As AI enables faster phishing, identity abuse, and automated attacks, Quorum Cyber expects cyber risks to intensify in 2026.

CEO Federico Charosky says providers that prioritize operational security fundamentals and measurable outcomes will be better positioned to deliver value as threat volumes rise.

AI is scaling phishing, identity abuse, and supply chain risk

To Charosky, much of what drove security conversations in 2025 will do the same this year, and he expects similar conversations taking shape throughout much of the next 12 months.

“I don’t think trends really have a yearly cut off,” Charosky said.

In particular, he expects the following to remain priorities for his team and its customers this year:

• AI is fueling the industrialization of existing threats, meaning things like sophisticated phishing attempts and other attacks can now be carried out a larger scale than ever before.
• Third-party supply chains remain vulnerable to threats and open businesses to a variety of risks they might not be prepared for.

“2025 was the year that threat actors scaled identity abuse and social engineering, for sure,” Charosky said. “It’s a lot harder to trust what you see now.”

To address this, Charosky says, organizations need to stop chasing tools and start understanding the processes and operations that build a stronger security posture.

“Security is now a managed operating system,” added Charosky. “Customers are adjusting to this and prioritizing outcomes, not dashboards. It’s not about buying more things, it’s about operationalizing things moving forward.”

Why Quorum Cyber is cautious about AI-led security strategies

While AI is widening the attack surface and scaling the sheer amount of potential attacks, Charosky does not see it as the only pathway to success for MSSPs and other provider businesses.

“Everybody is running to AI, but I haven’t really seen anyone make it valuable yet,” Charosky said.

Charosky isn’t anti-AI; he says Quorum Cyber has continued to experiment with where to best apply it in workflows and has found value within the technology.

Still, the provider is deliberately not promising a full-spin shift that others in the industry have focused on as the only opportunity for growth this year.

“Our core strategy isn’t changing. We are threat-led and action-based in everything we do. We’re going to consider how we can use AI to do that better, of course, but we’re not changing course entirely,” Charosky added.

Emphasizing the fundamentals remains key to Quorum Cyber and its clients

When considering both the widening attack surface brought by AI and the ongoing gaps in third-party risk management, Charosky stresses the basic truths of security are still the most important.

“I think the way to do this right is still in the fundamentals. We can navigate the new landscape if we do the core things right,” said Charosky.

Those fundamentals, Charosky says, return the focus to understanding the threats approaching a business and building the best possible set of actions to address them.

While areas like MDR are now what Charosky considers table stakes for providers to offer, they are still a crucial part of a holistic security posture.

Quorum Cyber research shows ransomware and vulnerability spikes

The provider also recently released its own security research. The 2026 Global Cyber Risk Outlook was derived from incidents and investigations observed across over 350 global organizations ranging in staff size from 10 to 10,000 throughout 2025.

The findings point to faster, more automated attacks that will challenge MSSPs relying on static tooling models.

Key findings from that outlook include:

• The number of newly formed ransomware groups increased by 30% in the year to October 2025
• Global vulnerability disclosures rose 21%, surpassing 35,000
• Early evidence of a nation-state group using AI agents to automate up to 90% of an intrusion
• Cybercriminals are increasingly shifting away from encryption toward faster, lower-cost data exfiltration attacks
• New white-label RaaS platforms enabling rapid launch of branded criminal operations
• Average ransom demands surged across multiple sectors, including 179% in financial services and 97% in manufacturing
• Nation-state threat actors associated with Russia, China, and Iran remain the top threats to the public sector, while North Korea-linked actors likely earned over $2 billion from cybercrime in 2025

The outlook also includes companion reports focused on nine industry sectors, including energy, financial services and insurance, healthcare and pharmaceuticals, higher education, housing and construction, legal and professional services, manufacturing, public sector, and retail.

Each companion report outlines sector-specific threat dynamics and practical considerations for strengthening cyber resilience.

How MSSPs can demonstrate value as threats intensify

Quorum Cyber was recognized as the 2025 Microsoft Security MSSP of the Year, as well as a 2025 Microsoft Security Partner of the Year Award finalist. The provider continues to focus its portfolio on quality, not necessarily quantity, of services offered.

Charosky is confident the moves made by his team over the past year have strengthened how Quorum Cyber goes to market for existing and new clients.

He is also confident the rise in sophisticated threats, paired with higher demands from customers, is beginning to highlight the types of partners actually equipped to offer managed security services.

“There was a lot of noise in the market, frankly. If we can parse that out, I can define and defend my value to clients,” Charosky said. “I think what’s exciting is that customers are starting to get it and understand what we can really bring them in terms of value.”

Charosky says the differentiator for Quorum Cyber remains its focus on continuous improvement for clients. As he notes, clients want to see how a provider can help them continuously become more secure over time.

“Our customers, we’ve seen, will pay for value. As long as we can demonstrate to them what the outcomes are that we’re helping them achieve, they see how we provide that value,” Charosky said.

The post Quorum Cyber CEO on AI Threats and Security Outcomes in 2026 appeared first on Bridgeview Marketing.

We brought Jephy Pothen of SecurityBridge forward and helped him produce this article to underscore the value of SAP GRC. He knows that advantage matters because SAP environments remain some of the most targeted systems in the enterprise, yet many organizations still confuse audit-readiness with security: SAP GRC supports governance and compliance, but it does not provide real-time threat detection, continuous monitoring, technical vulnerability visibility, or ABAP custom-code scanning. 

Originally posted by the GRC Report at https://www.grcreport.com/post/why-governance-tools-miss-what-hackers-exploit, this is a must-read for anyone concerned with SAP.

Key Takeaways

• Compliance Does Not Equal Security: SAP GRC supports audits and controls but does not protect against live cyber threats.
• Lack of Real-Time Detection Creates Exposure: Without continuous monitoring, attackers can operate undetected for extended periods.
• Periodic Risk Assessments Are Insufficient: Scheduled reviews leave gaps that attackers can exploit between cycles.
• Integration Gaps Weaken Security Posture: Poor connectivity with SIEMs, endpoint tools, and scanners creates blind spots and slows response.
• Technical Vulnerabilities Go Unseen: SAP GRC does not identify misconfigurations, missing patches, or custom code flaws.
• Custom ABAP Code Is a Major Risk Vector: Unscanned custom code introduces exploitable weaknesses such as SQL injection and hardcoded credentials.

Deep Dive

SAP systems store sensitive business data, run mission-critical processes, and ensure that operations continue uninterrupted. However, having the SAP GRC product suite or similar governance, risk, and compliance tools does not cover all aspects of system security. Relying on them to keep you safe is a recipe for infiltration.

Relying on compliance with audit requirements doesn’t mean that you are protected against cyberattacks. In addition, governance tools (such as GRC) do not detect cyber threats as they occur, and ensuring you are ready for a scheduled audit does not guarantee immunity from attacks. Poor integration with other components of your security ecosystem, inability to real-time scan for lateral movement vulnerabilities, and overlooking the regular scanning of ABAP (advanced business application programming) code are all problems that need addressing.

This article will explain these inadequacies, omissions, and how to address them.

Compliance ≠ Security

The first thing to understand is that compliance does not necessarily equate to security. SAP GRC can help manage risk and ensure compliance with internal controls and regulations. However, as stated earlier, merely meeting audit requirements does not guarantee protection against cyberattacks. Locking your front door may satisfy stipulations in your insurance policy, but if you leave the windows open, burglars can still gain entrance. Compliance will not prevent cyberattacks.

No Real-Time Threat Detection

The second element to understand follows logically from the first: you must have real-time threat detection. Tools such as GRC are not designed to detect cyber threats as they happen. Notifications of attack will not be delivered if someone is attempting to log in with false credentials or accessing sensitive data at unusual times of the day (ie, outside regular business hours). If you do not have real-time detection, hackers may have already infiltrated your system days or even months ago.

Reactive Risk Models

It’s common for GRC tools to put risk assessments on a periodic schedule—say monthly, quarterly, or annually. If you’re delaying evaluation of risks for weeks or months, then you’re leaving your organization exposed. Itś essential to adhere to these schedules to avoid elevated risk exposure.

Poor Integration = Blind Spots

It’s common for GRC tools to have difficulty integrating with other components of your security ecosystem. For example, suppose these tools are not connected to SIEM systems, endpoint tools, or vulnerability scanners. In that case, you will have blind spots in your overall security posture and slower incident response times.

Lack of Vulnerability Management

Many organizations are unaware that SAP GRC does not scan for technical vulnerabilities. This results in problems such as outdated kernel patches, insecure transport, or misconfigured parameters that are not detected. These are just a few areas it misses. Vulnerabilities in custom code can also be exploited, and transport layers can become areas of risk, as well. Without automatic scanning and prioritization, your team may remain unaware of these weaknesses.

Too Narrow a Focus

GRC platforms have too narrow a focus. They primarily concentrate on identity and access management. What they do not concentrate on is determining who has access to specific resources and whether that access aligns with your policies. Once hackers penetrate your systems, they can move laterally, exploit vulnerabilities, or deploy malware—none of which is addressed by identity management tools.

Custom Code: The Silent Risk

And lastly, custom code is a silent risk. Most SAP environments rely heavily on custom ABAP code. However, custom code is often overlooked during standard security reviews. If you’re not scanning this code regularly, you render yourself susceptible to significant issues such as SQL injection, hardcoded passwords, and insecure integrations. These are some of the hackers’ favorite weaknesses; attackers love them because they’re hard to detect and easy to exploit.

Your SAP Landscape Requires a Strategy

The ability to detect threats as they occur is crucial. Real-time monitoring gives you immediate visibility into suspicious activities, policy violations, and unauthorized changes. Continuously scanning your SAP environment for vulnerabilities and ranking them based on severity is paramount for prioritizing fixes. And when your SAP alerts are connected to your SIEM, you can respond to threats in context and act quickly and effectively.

Additionally, automated code scanning tools enable you to identify vulnerabilities before they are exploited. Embedding security checks into your development process (also known as DevSecOps) will help ensure that every new release is thoroughly vetted and secured. This will reduce attack surfaces and create a culture of security in your SAP lifecycle.

Conclusion

System governance, proper detection, and reliable vulnerability management, along with an integrated system that covers the entire SAP stack, are optimal protection. GRC tools have importance, but they do not provide complete protection. A strong SAP security posture requires:

• Real-time monitoring and threat detection
• Automated scanning for vulnerabilities and misconfigurations
• Integrated response and visibility across systems
• Custom code analysis and DevSecOps practices

When these pieces work together, you can be assured that you have proactive security, as opposed to reactive.

The post Why Governance Tools Miss What Hackers Exploit appeared first on Bridgeview Marketing.

Originally posted by CIO Influence at https://cioinfluence.com/security/securitybridge-announces-ceo-transition-to-accelerate-global-expansion/

SecurityBridge, a leading provider of cybersecurity solutions for SAP, announced the appointment of Jesper Zerlang as Chief Executive Officer, effective January 1, 2026. Zerlang transitions from his role as Chairman of the Board, a position he has held for the past 12 months, as the company enters its next phase of international expansion, backed by funds advised by BU Bregal Unternehmerkapital (BU).

SecurityBridge protects SAP environments for large enterprises by reducing cyber risk across mission-critical SAP landscapes. The company is trusted by global customers to safeguard systems that power core operations, financial processes, supply chains, and digital transformation programs.

“SecurityBridge is uniquely positioned at the intersection of cybersecurity and SAP – a domain I know deeply and care about profoundly,” said Jesper Zerlang, CEO of SecurityBridge. “Over the past year, as Chairman, I have seen firsthand the strength of the team, the technology, and the outcomes we deliver for customers. With BU’s support and a clear ambition to scale internationally, I am excited to step into the CEO role to accelerate global impact while raising the bar on trust and customer outcomes.”

Leadership Transition and Founder Roles

SecurityBridge founders Christoph Nagy and Ivan Mans will transition out of their day-to-day operational roles as CEO and CTO, respectively. They will remain strategically central to the business in pivotal roles focused on product evangelism and high-impact, customer-driven initiatives, leveraging their SAP engineering depth, credibility, and long-term product vision.

“SecurityBridge has grown into a remarkable company with a strong foundation and a clear mission,” said Nagy, Co-Founder of SecurityBridge. “This transition strengthens the company’s ability to scale globally while allowing us to focus where we create the greatest value for customers: product leadership, innovation, and engagement with the SAP ecosystem.”

“We are fully supportive of this exciting transition and look forward to contributing in roles that amplify our technical focus and customer impact. SecurityBridge’s opportunity ahead is significant, and this step positions the company strongly for the next stage,” added Ivan Mans, Co-Founder of SecurityBridge.

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Originally posted by VMblog.com at https://vmblog.com/archive/2025/12/15/cybersecurity-platform-consolidation-in-2026-the-ai-imperative.aspx

By 2026, organizations will defend against AI-powered threats that adapt in real-time, forcing a fundamental shift from fragmented security tools to consolidate platforms. This isn’t about cost savings – it’s about survival.

The majority of advanced cyberattacks will employ AI to execute dynamic, multilayered attacks that adapt instantaneously to defensive measures. Organizations with fragmented security stacks simply cannot respond at the speed these threats demand.

The Breaking Point: Why Consolidation Is No Longer Optional

Seventy-five percent of organizations have already pursued security vendor consolidation to address a critical problem: security teams are drowning in complexity. The average enterprise deploys dozens of security tools, each generating alerts, requiring integration, and creating dangerous gaps in visibility.

The real cost isn’t licensing fees – it’s operational paralysis. When threats move through networks in minutes, security teams switching between disparate tools, manually correlating data, and managing failed integrations cannot keep pace. The benefit of consolidation becomes key to centralizing data streams to reduce mean time to detect and respond to minutes rather than hours or days.

The AI Threat Revolution

By 2026, AI will fundamentally change what organizations defend against:

Adaptive attacks that learn: AI-powered threats probe defenses, identify weaknesses, and modify their approach in real-time during the attack itself. Traditional signature-based detection and behavioral analysis fail against adversaries that operate at machine speed and generate novel attack vectors on the fly.

Agentic AI breaches: Research predicts that in 2026, agentic AI will cause a public breach. These autonomous agents navigate networks, escalate privileges, and exfiltrate data without constant human control, making them exponentially harder to detect and stop.

The speed differential: Organizations defending against AI threats require AI-powered defenses. This necessitates comprehensive data visibility and real-time analysis across the entire attack surface – requirements that fragmented architectures cannot meet.

Why Platforms Win in the AI Era

Unified platforms provide decisive advantages against AI threats:

Comprehensive visibility: When security data flows through a single platform, AI models correlate events across previously siloed domains. An unusual authentication combined with anomalous network traffic and suspicious file access reveals attack patterns invisible in fragmented systems.

Centralized risk management: Organizations gain both a centralized view of risk across the organization and mechanisms to remediate that risk, enabling security leaders to prioritize based on actual business impact rather than tool-specific alerts.

AI-powered defense at scale: Platform architectures enable AI systems to understand context across the entire security stack, powering automated response workflows that contain threats before they achieve objectives.

2026: Key Predictions and Trends

Accelerated Consolidation

By 2026, missed SLAs, spiraling overheads, and dangerous security drift will push 55% of enterprises to accelerate technology consolidation. This reflects market maturity -early adopters have demonstrated benefits, creating competitive pressure on organizations still struggling with fragmented architectures.

GenAI Integration Impact

Enterprises combining GenAI technology with integrated platform-based architecture will experience 40% fewer employee-driven cybersecurity incidents by 2026. GenAI provides personalized, context-aware security guidance – but only when integrated platforms provide the comprehensive user and risk context required.

Executive Accountability

By 2026, 45% of Fortune 500 enterprises will appoint a Chief AI Security Officer to the board. This signals that security is no longer a technical concern delegated to IT – it’s a board-level risk management priority.

Quantum Security Investment

Quantum security spending will exceed 5% of overall IT security budgets by 2026 as organizations prepare for the quantum computing threat to current encryption. Platform consolidation simplifies deploying quantum-resistant cryptography across the enterprise.

Critical Implementation Guidance

Balance Platforms and Point Solutions

Security leaders are shifting focus to tool optimization rather than pure vendor consolidation, finding the right mix to balance reducing complexity with providing flexibility. No single platform addresses every need – specialized tools remain valuable when they integrate effectively with the core platform.

Manage Consolidation Risks

Organizations must navigate inherent risks:

• Vendor lock-in: Maintain relationships with multiple providers; ensure contracts include data portability provisions

• Innovation constraints: Retain strategic point solutions in areas where platform capabilities prove insufficient

• Exit planning: Ensure security data can be exported in standard formats if vendor relationships change

In summary, the cybersecurity landscape of 2026 will be defined by AI-powered threats versus consolidated platform defenses. Organizations that embrace consolidation position themselves to defend effectively. Those clinging to fragmented architectures face mounting vulnerability to threats that exploit gaps, delays, and blind spots inherent in tool sprawl.

This transformation is not optional. AI-powered attacks leave no room for the inefficiencies of fragmented security stacks. Organizations must simplify architectures, centralize data streams, and deploy AI-powered defenses capable of matching intelligent adversaries.

The question is not whether to consolidate but how quickly organizations can execute while managing risks. Those who move decisively will emerge with resilient security postures. Those who hesitate will defend 20th-century architectures against 21st-century threats – a battle they cannot win.

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Originally Posted by Cyber Defense Magazine at https://www.cyberdefensemagazine.com/mastering-multi-cloud-security/

Multi-cloud computing has benefits and challenges. With flexibility, innovation, and cost control as some of its advantages, the most significant challenges it presents are in the realm of cybersecurity. Each cloud provider has its own architecture, tools, software componentry, and telemetry. This creates a fragmented ecosystem where vulnerabilities can lurk and threat actors can exploit gaps.

CISOs today recognize that multi-cloud environments pose this kind of risk, and the solution is to ensure visibility across environments, maintain consistency in policy enforcement, exception governance, and implement a layered approach to threat detection and response. Single-cloud rules no longer apply.

The Multi-Cloud Challenge: Complexity Without Consistency

Multi-cloud ecosystems can present inconsistency in how data, logs, and events are captured and managed. Whether it’s AWS, Azure, Google Cloud, or a niche SaaS vendor, each employs different formats and nomenclature for security events. This creates a challenge for centralizing monitoring, correlation, and response. In turn, this multiplies our operating costs for managing multiple cloud platforms.

Vendor-native tools, unfortunately, do not offer the consistent coverage that is necessary. They can provide value, but they are often limited in scope and lack the needed interoperability across providers. Therefore, relying solely on vendor-native tooling or open-source community edition tools results in blind spots, which are factors in detecting threat patterns and coordinating policy deviations across environments.

The imperative is for organizations to adopt vendor-agnostic policies and complement vendor-native security capabilities with third-party tools. Event logs should be normalized into a common format, thus allowing consistent monitoring, detection, and policy enforcement across cloud platforms.

Why Consistency Beats Convenience

Multi-cloud security requires both visibility and cohesion. With consistent capabilities across all cloud providers, it becomes easier to:

• Apply uniform security controls.
• Monitor for, and properly track, policy deviations.
• Detect anomalies across services and workloads.
• Prioritize risk based on real context.

Many fear that consistency and uniformity will negatively impact flexibility. However, flexibility will be maintained by designing and enforcing baseline security expectations across the multi-cloud landscape, and by utilizing Security Information Event Management (SIEM), Extended Detection Response (XDR), SBOM, observability, and third-party tools to monitor against that standard.

Logs Tell the Truth—If You Know How To Read Them

Cross-referencing operational logs and metadata across providers is wise. Doing this will uncover misconfigurations, timing anomalies, and coverage gaps that would otherwise go unnoticed.

By aligning log data from Azure and AWS for the same application, a CISO can discover issues such as one environment not capturing failed login attempts or unusual time gaps in log ingestion across platforms, which may be indicative of performance issues or malicious tampering.

These insights help security teams prioritize based on real risks, as opposed to a vendor dashboard that does not show a complete picture.

Avoid the Single Tool Fallacy

Having a single platform—especially a vendor-native or free tool—is unlikely to provide the holistic multi-cloud security required for optimal defense. These tools can be helpful in their native environments, but they can fall short when it comes to supporting interoperability. Real-time correlation or enterprise-grade support is often not available.

A layered, overlapping security approach, combining the following, is best:

• Vendor-native tools for baseline protection.
• Enterprise-grade third-party tools for unified visibility.
• Cross-platform log aggregation and normalization.
• Automation and AI-driven correlation across all environments.

If open-source tools are in use, it’s imperative to make sure that they are enterprise editions, with support, updates, and verified integrations.

The CISO’s Role In Multi-Cloud Security

Multi-cloud security is the domain of the CISO and their team – even for shadow IT. Securing the cloud assets is the goal, and that requires aligning policies, prioritizing remediation, and maintaining executive visibility into risks and compliance. This means that the CISO must proactively advocate for a budget, staffing, and the necessary tooling that a multi-cloud environment requires, as the severity of a breach can be significant. The CISO must also ensure that vendors have transparency, that security standards are enforced across procurement, and that third-party software aligns with internal risk frameworks.

Clarity Is Security

In 2024, the number of Common Vulnerabilities and Exposures (CVE) surged more than 38 percent compared to 2023. Many of these vulnerabilities were discovered in third-party software used by organizations that lacked visibility into their exposure until it was too late.

For CISOs managing multi-cloud environments, reacting to and recovering from breaches is far more painful than proactive visibility. The CISO must ensure that the organization they work for has a proactive and strategic approach when managing the complexities of the cloud.

The time to normalize logs, layer defenses, and demand more from providers is now, because in a multi-cloud world, clarity is security.

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Originally posted by Tech News World at https://www.technewsworld.com/story/quenching-data-center-thirst-for-power-now-is-solvable-problem-180031.html

With energy demand soaring — largely due to the growth of data centers supporting a burgeoning AI industry — concerns have arisen about where the nation will find the energy capacity to meet its power needs.

A new report by the Information Technology and Innovation Foundation (ITIF) argues that capacity can be found in the near- and medium-term, giving power providers the time they need to add infrastructure to the existing grid and meet longer-term electricity demand.

“However, such a solution will not arrive on its own,” wrote the author of the report, Robin Gaster, research director for ITIF’s Center for Clean Energy in Washington, D.C. “Without significant action across multiple fronts and at substantial scale, the existing grid will come under increasing pressure — and we can expect a massive struggle for access.”

“Regulators will be caught between the sudden growth in demand and political pressure to service existing commercial and residential customers first, while keeping a lid on prices,” he explained.

One of the significant drivers of the growing electricity demand appears to be data centers, the report noted, prompting calls to slow their growth or even prevent them from connecting to the grid altogether.

“Slowing data center growth or prohibiting grid connection is a short-sighted approach that embraces a scarcity mentality,” argued Wannie Park, CEO and founder of Pado AI, an energy management and AI orchestration company, in Malibu, Calif.

“The explosive growth of AI and digital infrastructure is a massive engine for economic, scientific, and industrial progress,” he told TechNewsWorld. “The focus should not be on stifling this essential innovation, but on making data centers active, supportive participants in the energy ecosystem.”

“Data centers are the engine of the AI economy, but they can’t be passive loads anymore,” he said. “Data centers can and should be active partners that contribute to grid stability and resilience, not just consume power. Prohibiting growth would simply limit the innovation needed to solve the power crunch in the first place.”

Smart Integration Needed

The reality is the U.S. has dramatically underinvested in long-term grid upgrades and planning, maintained Scotty Embley, an associate with Hi-Tequity, a data center development and investment firm, in Melbourne Beach, Fla. Slowing data center builds equates to slowing vital applications such as banking, federal, health care, and transportation, he told TechNewsWorld.

However, he acknowledged that early coordination with utilities is necessary to ensure new facility locations are strategically planned and responsibly powered, where adequate grid support is available.

Instead of restricting data center development, the focus should be on smarter integration with the grid, added Allan Schurr, chief commercial officer at Enchanted Rock, a provider of natural gas-powered microgrids, in Houston.

Planning for the full lifecycle of a data center’s power needs — from construction through long-term operations — is essential, he continued. This approach includes having solutions in place that can keep facilities operational during periods of limited grid availability, major weather events, or unexpected demand pressures, he said.

Schurr explained that on-site generation, including natural gas microgrids, can provide bridge power during interconnection delays, flexible capacity to support grid-constrained regions, and dependable backup power when the grid is stressed or offline. With this type of coordinated approach, data centers can continue to grow while strengthening, not straining, our power infrastructure, he contended.

Data centers are the source of the information for anything we do on the internet, added Arie Brish, a business professor at St. Edward’s University in Austin, Texas. They must be up 24/7. These facilities are not like a laundry operation that can be limited to off-hours.

He also noted that the importance of continuity in data center operations requires that they have backups of local generators. These local generators can indeed be used to feed the facilities during peak hours, thus balancing grid demand, he told TechNewsWorld.

Getting More From Existing Infrastructure

Rick Bentley, CEO of HydroHash, a crypto-mining company focused on clean energy and high-efficiency operations, in Albuquerque, N.M., recommended that data center operators avoid the grid entirely. That saves the data center massive costs in both regulations and fees, he told TechNewsWorld.

Once they are on the grid, their power can be curtailed during times of high demand to make sure the heat stays on in people’s homes during a cold snap, hospitals stay operational, and A/C works during a heat wave, he explained.

The ITIF report also called for the United States to squeeze more power from the existing grid without negatively impacting customers, while also building new capacity.

New technology can increase supply from existing transmission lines and generators, the report explained, which can bridge the transition to an expanded physical grid.

On the demand side, it added, there is spare capacity, but not at peak times. It suggested that large users, such as data centers, be encouraged to shift their demand to off-peak periods, without damaging their customers. Grids do some of that already, it noted, but much more is needed.

Up to 40% of data centers’ needs are not highly time sensitive, so they can be partners in managing peak demand by proactively shifting some of their use to different times and even different geographies, it reasoned.

AI’s Strain on the Grid

Ironically, AI, a significant driver of data center power usage, can also help squeeze more electricity from the existing grid.

We need to map energy delivery with the same supply chain visibility we apply to national defense — using AI to map where power is wasted, where infrastructure is stalled due to fragile supply chains and where capacity is trapped behind inefficient legacy systems, Brandon Daniels, CEO of Exiger, a developer of AI-powered risk, compliance and supply chain management solutions, in McLean, Va., told TechNewsWorld.

Pado’s Park agreed that one of the best ways to maximize existing grid capacity is to leverage software and AI/ML to balance power supply and demand better. Implementing orchestrated demand through advanced software for demand-side flexibility can intelligently coordinate large, flexible loads — like data centers — with grid signals, he noted.

The primary challenge is the speed of deployment and regulatory lag, he said. Data center growth is moving at an unprecedented pace, and traditional utility planning and regulatory approval processes struggle to keep up, for good reasons.

Additionally, he continued, data centers operate under stringent reliability requirements, aka “five nines,” which create technical and contractual hurdles to integrating load flexibility at scale.

Embley, of Hi-Tequity, asserted that the U.S. can squeeze more capacity from the existing grid by putting underutilized or stranded power to work — whether through repurposing industrial sites that already have heavy electrical infrastructure or tapping idle substations and interconnects built for past manufacturing loads.

These approaches deliver relief far faster than building new transmission, he explained. The challenge is that grid stress is already the top obstacle utilities cite, and major upgrades move on decade-long timelines. Interconnection queues continue to grow, and even when capacity exists on paper, critical equipment like transformers and switchgear carry 12- to 24-month lead times, which often slow projects more than construction itself.

He added that computing density has changed dramatically as the use of artificial intelligence continues to soar. Today’s AI clusters draw 30 to 60 kilowatts per cabinet, two to three times the load of legacy CPU racks, overwhelming the electrical and thermal systems built for a different era, he explained.

At the same time, grid expansion, interconnection, and long-lead electrical equipment operate on decade-long timelines, while AI demand is rising on year-long timelines.

That mismatch, he said, not a lack of ambition or innovation, is what’s driving the current power crunch.

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