Enterprise artificial intelligence investment is unprecedented, with IDC projecting global spending on AI and GenAI to double to $631 billion by 2028. Yet beneath the impressive budget allocations and boardroom enthusiasm lies a troubling reality: most organisations struggle to translate their AI ambitions into operational success.The sobering statistics behind AI’s promiseModelOp’s 2025 AI Governance Benchmark Report, based on input from 100 senior AI and data leaders at Fortune 500 enterprises, reveals a disconnect between aspiration and execution.While more than 80% of enterprises have 51 or more generative AI projects in proposal phases, only 18% have successfully deployed more than 20 models into production.The execution gap represents one of the most significant challenges facing enterprise AI today. Most generative AI projects still require 6 to 18 months to go live – if they reach production at all.The result is delayed returns on investment, frustrated stakeholders, and diminished confidence in AI initiatives in the enterprise.The cause: Structural, not technical barriersThe biggest obstacles preventing AI scalability aren’t technical limitations – they’re structural inefficiencies plaguing enterprise operations. The ModelOp benchmark report identifies several problems that create what experts call a “time-to-market quagmire.”Fragmented systems plague implementation. 58% of organisations cite fragmented systems as the top obstacle to adopting governance platforms. Fragmentation creates silos where different departments use incompatible tools and processes, making it nearly impossible to maintain consistent oversight in AI initiatives.Manual processes dominate despite digital transformation. 55% of enterprises still rely on manual processes – including spreadsheets and email – to manage AI use case intake. The reliance on antiquated methods creates bottlenecks, increases the likelihood of errors, and makes it difficult to scale AI operations.Lack of standardisation hampers progress. Only 23% of organisations implement standardised intake, development, and model management processes. Without these elements, each AI project becomes a unique challenge requiring custom solutions and extensive coordination by multiple teams.Enterprise-level oversight remains rare Just 14% of companies perform AI assurance at the enterprise level, increasing the risk of duplicated efforts and inconsistent oversight. The lack of centralised governance means organisations often discover they’re solving the same problems multiple times in different departments.The governance revolution: From obstacle to acceleratorA change is taking place in how enterprises view AI governance. Rather than seeing it as a compliance burden that slows innovation, forward-thinking organisations recognise governance as an important enabler of scale and speed.Leadership alignment signals strategic shift. The ModelOp benchmark data reveals a change in organisational structure: 46% of companies now assign accountability for AI governance to a Chief Innovation Officer – more than four times the number who place accountability under Legal or Compliance. This strategic repositioning reflects a new understanding that governance isn’t solely about risk management, but can enable innovation.Investment follows strategic priority. A financial commitment to AI governance underscores its importance. According to the report, 36% of enterprises have budgeted at least $1 million annually for AI governance software, while 54% have allocated resources specifically for AI Portfolio Intelligence to track value and ROI.What high-performing organisations do differentlyThe enterprises that successfully bridge the ‘execution gap’ share several characteristics in their approach to AI implementation:Standardised processes from day one. Leading organisations implement standardised intake, development, and model review processes in AI initiatives. Consistency eliminates the need to reinvent workflows for each project and ensures that all stakeholders understand their responsibilities.Centralised documentation and inventory. Rather than allowing AI assets to proliferate in disconnected systems, successful enterprises maintain centralised inventories that provide visibility into every model’s status, performance, and compliance posture.Automated governance checkpoints. High-performing organisations embed automated governance checkpoints throughout the AI lifecycle, helping ensure compliance requirements and risk assessments are addressed systematically rather than as afterthoughts.End-to-end traceability. Leading enterprises maintain complete traceability of their AI models, including data sources, training methods, validation results, and performance metrics.Measurable impact of structured governanceThe benefits of implementing comprehensive AI governance extend beyond compliance. Organisations that adopt lifecycle automation platforms reportedly see dramatic improvements in operational efficiency and business outcomes.A financial services firm profiled in the ModelOp report experienced a halving of time to production and an 80% reduction in issue resolution time after implementing automated governance processes. Such improvements translate directly into faster time-to-value and increased confidence among business stakeholders.Enterprises with robust governance frameworks report the ability to many times more models simultaneously while maintaining oversight and control. This scalability lets organisations pursue AI initiatives in multiple business units without overwhelming their operational capabilities.The path forward: From stuck to scaledThe message from industry leaders that the gap between AI ambition and execution is solvable, but it requires a shift in approach. Rather than treating governance as a necessary evil, enterprises should realise it enables AI innovation at scale.Immediate action items for AI leadersOrganisations looking to escape the ‘time-to-market quagmire’ should prioritise the following:Audit current state: Conduct an assessment of existing AI initiatives, identifying fragmented processes and manual bottlenecksStandardise workflows: Implement consistent processes for AI use case intake, development, and deployment in all business unitsInvest in integration: Deploy platforms to unify disparate tools and systems under a single governance frameworkEstablish enterprise oversight: Create centralised visibility into all AI initiatives with real-time monitoring and reporting abilitiesThe competitive advantage of getting it rightOrganisations that can solve the execution challenge will be able to bring AI solutions to market faster, scale more efficiently, and maintain the trust of stakeholders and regulators.Enterprises that continue with fragmented processes and manual workflows will find themselves disadvantaged compared to their more organised competitors. Operational excellence isn’t about efficiency but survival.The data shows enterprise AI investment will continue to grow. Therefore, the question isn’t whether organisations will invest in AI, but whether they’ll develop the operational abilities necessary to realise return on investment. The opportunity to lead in the AI-driven economy has never been greater for those willing to embrace governance as an enabler not an obstacle.(Image source: Unsplash)

Outdated coding practices and memory-unsafe languages like C are putting software, including cryptographic libraries, at risk. Fortunately, memory-safe languages like Rust, along with formal verification tools, are now mature enough to be used at scale, helping prevent issues like crashes, data corruption, flawed implementation, and side-channel attacks. To address these vulnerabilities and improve memory safety, we’re rewriting SymCrypt (opens in new tab)—Microsoft’s open-source cryptographic library—in Rust. We’re also incorporating formal verification methods. SymCrypt is used in Windows, Azure Linux, Xbox, and other platforms. Currently, SymCrypt is primarily written in cross-platform C, with limited use of hardware-specific optimizations through intrinsics (compiler-provided low-level functions) and assembly language (direct processor instructions). It provides a wide range of algorithms, including AES-GCM, SHA, ECDSA, and the more recent post-quantum algorithms ML-KEM and ML-DSA.  Formal verification will confirm that implementations behave as intended and don’t deviate from algorithm specifications, critical for preventing attacks. We’ll also analyze compiled code to detect side-channel leaks caused by timing or hardware-level behavior. Proving Rust program properties with Aeneas Program verification is the process of proving that a piece of code will always satisfy a given property, no matter the input. Rust’s type system profoundly improves the prospects for program verification by providing strong ownership guarantees, by construction, using a discipline known as “aliasing xor mutability”. For example, reasoning about C code often requires proving that two non-const pointers are live and non-overlapping, a property that can depend on external client code. In contrast, Rust’s type system guarantees this property for any two mutably borrowed references. As a result, new tools have emerged specifically for verifying Rust code. We chose Aeneas (opens in new tab) because it helps provide a clean separation between code and proofs. Developed by Microsoft Azure Research in partnership with Inria, the French National Institute for Research in Digital Science and Technology, Aeneas connects to proof assistants like Lean (opens in new tab), allowing us to draw on a large body of mathematical proofs—especially valuable given the mathematical nature of cryptographic algorithms—and benefit from Lean’s active user community. Compiling Rust to C supports backward compatibility   We recognize that switching to Rust isn’t feasible for all use cases, so we’ll continue to support, extend, and certify C-based APIs as long as users need them. Users won’t see any changes, as Rust runs underneath the existing C APIs. Some users compile our C code directly and may rely on specific toolchains or compiler features that complicate the adoption of Rust code. To address this, we will use Eurydice (opens in new tab), a Rust-to-C compiler developed by Microsoft Azure Research, to replace handwritten C code with C generated from formally verified Rust. Eurydice (opens in new tab) compiles directly from Rust’s MIR intermediate language, and the resulting C code will be checked into the SymCrypt repository alongside the original Rust source code. As more users adopt Rust, we’ll continue supporting this compilation path for those who build SymCrypt from source code but aren’t ready to use the Rust compiler. In the long term, we hope to transition users to either use precompiled SymCrypt binaries (via C or Rust APIs), or compile from source code in Rust, at which point the Rust-to-C compilation path will no longer be needed. Microsoft research podcast Ideas: AI and democracy with Madeleine Daepp and Robert Osazuwa Ness As the “biggest election year in history” comes to an end, researchers Madeleine Daepp and Robert Osazuwa Ness and Democracy Forward GM Ginny Badanes discuss AI’s impact on democracy, including the tech’s use in Taiwan and India. Listen now Opens in a new tab Timing analysis with Revizor  Even software that has been verified for functional correctness can remain vulnerable to low-level security threats, such as side channels caused by timing leaks or speculative execution. These threats operate at the hardware level and can leak private information, such as memory load addresses, branch targets, or division operands, even when the source code is provably correct.  To address this, we’re extending Revizor (opens in new tab), a tool developed by Microsoft Azure Research, to more effectively analyze SymCrypt binaries. Revizor models microarchitectural leakage and uses fuzzing techniques to systematically uncover instructions that may expose private information through known hardware-level effects.   Earlier cryptographic libraries relied on constant-time programming to avoid operations on secret data. However, recent research has shown that this alone is insufficient with today’s CPUs, where every new optimization may open a new side channel.  By analyzing binary code for specific compilers and platforms, our extended Revizor tool enables deeper scrutiny of vulnerabilities that aren’t visible in the source code. Verified Rust implementations begin with ML-KEM This long-term effort is in alignment with the Microsoft Secure Future Initiative and brings together experts across Microsoft, building on decades of Microsoft Research investment in program verification and security tooling. A preliminary version of ML-KEM in Rust is now available on the preview feature/verifiedcrypto (opens in new tab) branch of the SymCrypt repository. We encourage users to try the Rust build and share feedback (opens in new tab). Looking ahead, we plan to support direct use of the same cryptographic library in Rust without requiring C bindings.  Over the coming months, we plan to rewrite, verify, and ship several algorithms in Rust as part of SymCrypt. As our investment in Rust deepens, we expect to gain new insights into how to best leverage the language for high-assurance cryptographic implementations with low-level optimizations.  As performance is key to scalability and sustainability, we’re holding new implementations to a high bar using our benchmarking tools to match or exceed existing systems. Looking forward  This is a pivotal moment for high-assurance software. Microsoft’s investment in Rust and formal verification presents a rare opportunity to advance one of our key libraries. We’re excited to scale this work and ultimately deliver an industrial-grade, Rust-based, FIPS-certified cryptographic library. Opens in a new tab

The Secure Government Email (SGE) Common Implementation Framework New Zealand’s government is introducing a comprehensive email security framework designed to protect official communications from phishing and domain spoofing. This new framework, which will be mandatory for all government agencies by October 2025, establishes clear technical standards to enhance email security and retire the outdated SEEMail service.  Key Takeaways All NZ government agencies must comply with new email security requirements by October 2025. The new framework strengthens trust and security in government communications by preventing spoofing and phishing. The framework mandates TLS 1.2+, SPF, DKIM, DMARC with p=reject, MTA-STS, and DLP controls. EasyDMARC simplifies compliance with our guided setup, monitoring, and automated reporting. Start a Free Trial What is the Secure Government Email Common Implementation Framework? The Secure Government Email (SGE) Common Implementation Framework is a new government-led initiative in New Zealand designed to standardize email security across all government agencies. Its main goal is to secure external email communication, reduce domain spoofing in phishing attacks, and replace the legacy SEEMail service. Why is New Zealand Implementing New Government Email Security Standards? The framework was developed by New Zealand’s Department of Internal Affairs (DIA) as part of its role in managing ICT Common Capabilities. It leverages modern email security controls via the Domain Name System (DNS) to enable the retirement of the legacy SEEMail service and provide: Encryption for transmission security Digital signing for message integrity Basic non-repudiation (by allowing only authorized senders) Domain spoofing protection These improvements apply to all emails, not just those routed through SEEMail, offering broader protection across agency communications. What Email Security Technologies Are Required by the New NZ SGE Framework? The SGE Framework outlines the following key technologies that agencies must implement: TLS 1.2 or higher with implicit TLS enforced TLS-RPT (TLS Reporting) SPF (Sender Policy Framework) DKIM (DomainKeys Identified Mail) DMARC (Domain-based Message Authentication, Reporting, and Conformance) with reporting MTA-STS (Mail Transfer Agent Strict Transport Security) Data Loss Prevention controls These technologies work together to ensure encrypted email transmission, validate sender identity, prevent unauthorized use of domains, and reduce the risk of sensitive data leaks. Get in touch When Do NZ Government Agencies Need to Comply with this Framework? All New Zealand government agencies are expected to fully implement the Secure Government Email (SGE) Common Implementation Framework by October 2025. Agencies should begin their planning and deployment now to ensure full compliance by the deadline. The All of Government Secure Email Common Implementation Framework v1.0 What are the Mandated Requirements for Domains? Below are the exact requirements for all email-enabled domains under the new framework. ControlExact RequirementTLSMinimum TLS 1.2. TLS 1.1, 1.0, SSL, or clear-text not permitted.TLS-RPTAll email-sending domains must have TLS reporting enabled.SPFMust exist and end with -all.DKIMAll outbound email from every sending service must be DKIM-signed at the final hop.DMARCPolicy of p=reject on all email-enabled domains. adkim=s is recommended when not bulk-sending.MTA-STSEnabled and set to enforce.Implicit TLSMust be configured and enforced for every connection.Data Loss PreventionEnforce in line with the New Zealand Information Security Manual (NZISM) and Protective Security Requirements (PSR). Compliance Monitoring and Reporting The All of Government Service Delivery (AoGSD) team will be monitoring compliance with the framework. Monitoring will initially cover SPF, DMARC, and MTA-STS settings and will be expanded to include DKIM. Changes to these settings will be monitored, enabling reporting on email security compliance across all government agencies. Ongoing monitoring will highlight changes to domains, ensure new domains are set up with security in place, and monitor the implementation of future email security technologies.  Should compliance changes occur, such as an agency’s SPF record being changed from -all to ~all, this will be captured so that the AoGSD Security Team can investigate. They will then communicate directly with the agency to determine if an issue exists or if an error has occurred, reviewing each case individually. Deployment Checklist for NZ Government Compliance Enforce TLS 1.2 minimum, implicit TLS, MTA-STS & TLS-RPT SPF with -all DKIM on all outbound email DMARC p=reject  adkim=s where suitable For non-email/parked domains: SPF -all, empty DKIM, DMARC reject strict Compliance dashboard Inbound DMARC evaluation enforced DLP aligned with NZISM Start a Free Trial How EasyDMARC Can Help Government Agencies Comply EasyDMARC provides a comprehensive email security solution that simplifies the deployment and ongoing management of DNS-based email security protocols like SPF, DKIM, and DMARC with reporting. Our platform offers automated checks, real-time monitoring, and a guided setup to help government organizations quickly reach compliance. 1. TLS-RPT / MTA-STS audit EasyDMARC enables you to enable the Managed MTA-STS and TLS-RPT option with a single click. We provide the required DNS records and continuously monitor them for issues, delivering reports on TLS negotiation problems. This helps agencies ensure secure email transmission and quickly detect delivery or encryption failures. Note: In this screenshot, you can see how to deploy MTA-STS and TLS Reporting by adding just three CNAME records provided by EasyDMARC. It’s recommended to start in “testing” mode, evaluate the TLS-RPT reports, and then gradually switch your MTA-STS policy to “enforce”. The process is simple and takes just a few clicks. As shown above, EasyDMARC parses incoming TLS reports into a centralized dashboard, giving you clear visibility into delivery and encryption issues across all sending sources. 2. SPF with “-all”In the EasyDARC platform, you can run the SPF Record Generator to create a compliant record. Publish your v=spf1 record with “-all” to enforce a hard fail for unauthorized senders and prevent spoofed emails from passing SPF checks. This strengthens your domain’s protection against impersonation. Note: It is highly recommended to start adjusting your SPF record only after you begin receiving DMARC reports and identifying your legitimate email sources. As we’ll explain in more detail below, both SPF and DKIM should be adjusted after you gain visibility through reports. Making changes without proper visibility can lead to false positives, misconfigurations, and potential loss of legitimate emails. That’s why the first step should always be setting DMARC to p=none, receiving reports, analyzing them, and then gradually fixing any SPF or DKIM issues. 3. DKIM on all outbound email DKIM must be configured for all email sources sending emails on behalf of your domain. This is critical, as DKIM plays a bigger role than SPF when it comes to building domain reputation, surviving auto-forwarding, mailing lists, and other edge cases. As mentioned above, DMARC reports provide visibility into your email sources, allowing you to implement DKIM accordingly (see first screenshot). If you’re using third-party services like Google Workspace, Microsoft 365, or Mimecast, you’ll need to retrieve the public DKIM key from your provider’s admin interface (see second screenshot). EasyDMARC maintains a backend directory of over 1,400 email sources. We also give you detailed guidance on how to configure SPF and DKIM correctly for major ESPs.  Note: At the end of this article, you’ll find configuration links for well-known ESPs like Google Workspace, Microsoft 365, Zoho Mail, Amazon SES, and SendGrid – helping you avoid common misconfigurations and get aligned with SGE requirements. If you’re using a dedicated MTA (e.g., Postfix), DKIM must be implemented manually. EasyDMARC’s DKIM Record Generator lets you generate both public and private keys for your server. The private key is stored on your MTA, while the public key must be published in your DNS (see third and fourth screenshots). 4. DMARC p=reject rollout As mentioned in previous points, DMARC reporting is the first and most important step on your DMARC enforcement journey. Always start with a p=none policy and configure RUA reports to be sent to EasyDMARC. Use the report insights to identify and fix SPF and DKIM alignment issues, then gradually move to p=quarantine and finally p=reject once all legitimate email sources have been authenticated.  This phased approach ensures full protection against domain spoofing without risking legitimate email delivery. 5. adkim Strict Alignment Check This strict alignment check is not always applicable, especially if you’re using third-party bulk ESPs, such as Sendgrid, that require you to set DKIM on a subdomain level. You can set adkim=s in your DMARC TXT record, or simply enable strict mode in EasyDMARC’s Managed DMARC settings. This ensures that only emails with a DKIM signature that exactly match your domain pass alignment, adding an extra layer of protection against domain spoofing. But only do this if you are NOT a bulk sender. 6. Securing Non-Email Enabled Domains The purpose of deploying email security to non-email-enabled domains, or parked domains, is to prevent messages being spoofed from that domain. This requirement remains even if the root-level domain has SP=reject set within its DMARC record. Under this new framework, you must bulk import and mark parked domains as “Parked.” Crucially, this requires adjusting SPF settings to an empty record, setting DMARC to p=reject, and ensuring an empty DKIM record is in place: • SPF record: “v=spf1 -all”. • Wildcard DKIM record with empty public key.• DMARC record: “v=DMARC1;p=reject;adkim=s;aspf=s;rua=mailto:…”. EasyDMARC allows you to add and label parked domains for free. This is important because it helps you monitor any activity from these domains and ensure they remain protected with a strict DMARC policy of p=reject. 7. Compliance Dashboard Use EasyDMARC’s Domain Scanner to assess the security posture of each domain with a clear compliance score and risk level. The dashboard highlights configuration gaps and guides remediation steps, helping government agencies stay on track toward full compliance with the SGE Framework. 8. Inbound DMARC Evaluation Enforced You don’t need to apply any changes if you’re using Google Workspace, Microsoft 365, or other major mailbox providers. Most of them already enforce DMARC evaluation on incoming emails. However, some legacy Microsoft 365 setups may still quarantine emails that fail DMARC checks, even when the sending domain has a p=reject policy, instead of rejecting them. This behavior can be adjusted directly from your Microsoft Defender portal. Read more about this in our step-by-step guide on how to set up SPF, DKIM, and DMARC from Microsoft Defender. If you’re using a third-party mail provider that doesn’t enforce having a DMARC policy for incoming emails, which is rare, you’ll need to contact their support to request a configuration change. 9. Data Loss Prevention Aligned with NZISM The New Zealand Information Security Manual (NZISM) is the New Zealand Government’s manual on information assurance and information systems security. It includes guidance on data loss prevention (DLP), which must be followed to be aligned with the SEG. Need Help Setting up SPF and DKIM for your Email Provider? Setting up SPF and DKIM for different ESPs often requires specific configurations. Some providers require you to publish SPF and DKIM on a subdomain, while others only require DKIM, or have different formatting rules. We’ve simplified all these steps to help you avoid misconfigurations that could delay your DMARC enforcement, or worse, block legitimate emails from reaching your recipients. Below you’ll find comprehensive setup guides for Google Workspace, Microsoft 365, Zoho Mail, Amazon SES, and SendGrid. You can also explore our full blog section that covers setup instructions for many other well-known ESPs. Remember, all this information is reflected in your DMARC aggregate reports. These reports give you live visibility into your outgoing email ecosystem, helping you analyze and fix any issues specific to a given provider. Here are our step-by-step guides for the most common platforms: Google Workspace Microsoft 365 These guides will help ensure your DNS records are configured correctly as part of the Secure Government Email (SGE) Framework rollout. Meet New Government Email Security Standards With EasyDMARC New Zealand’s SEG Framework sets a clear path for government agencies to enhance their email security by October 2025. With EasyDMARC, you can meet these technical requirements efficiently and with confidence. From protocol setup to continuous monitoring and compliance tracking, EasyDMARC streamlines the entire process, ensuring strong protection against spoofing, phishing, and data loss while simplifying your transition from SEEMail.

Rene Byrd did IVF to have her baby. Courtesy of Rene Byrd 2025-06-14T21:23:01Z Save Saved Read in app This story is available exclusively to Business Insider subscribers. Become an Insider and start reading now. Have an account? Rene Byrd is a 49-year-old singer-songwriter in London who had her first baby at 48. She had held on to hope for a baby throughout her 40s, undergoing IVF for over two years. Being an older mom has had several benefits, like financial security and contentment. This as-told-to essay is based on a conversation with Rene Byrd. It has been edited for length and clarity.When I turned 40, I went on a seven-day retreat full of meditation and massage to fall in love with myself. I'm a strong believer that to find love, you first have to love yourself.I had wanted to settle down with someone and build a family, but it just hadn't happened. Three years prior, I had frozen my eggs because I knew that I wanted a family someday.On the retreat, I felt deep in my spirit that I would one day find my person and hold my child in my hands. I wouldn't give up hope.I met someone at a barReturning home, I continued dating, but it wasn't until a chance meeting at a bar that I finally found the man who would become my husband. I hadn't quite turned 41, and he was 34.I remember not wanting to scare him off by talking too much about my desire for kids, but we did have discussions about the future. When love started to bloom between the two of us, we started looking at what our options were for having a child together.After trying holistic methods to no avail, we decided to go down the IVF route. I'd heard horror stories about IVF — that it was never straightforward — but as I already had my eggs frozen, it was the best option for us at the time.I felt guilty for waiting so longTwo-and-a-half long years later, I was given the news from the IVF clinic — I was pregnant. I fell apart, phoning my husband to tell him we would be having a baby. Rene Byrd got pregnant at age 48 thanks to IVF. Courtesy of Rene Byrd Throughout my pregnancy, I remember being scared of what this new life as a mother would look like. I had little panic attacks considering how different life would be, as compared to the decades of life without a child. And then I felt guilty, telling myself I had waited so long for this. There was a lot of grappling with these thoughts until I realized my child would just be an extension of me.Once our little boy, Crue, was born in November 2024, I felt ready for his arrival in theory. Having spent years hearing from friends with children, I had an idea of what to expect. Even still, those early days were a lot to deal with. All these things were being thrown at me about what I should and shouldn't do with a baby.Being a mom in my late 40s has so many beautiful benefitsI joined online mother and baby communities and in-person baby groups, finding my tribe of mothers like me, ones that were "older."There is a stillness within me that grounds me as I take care of Crue. I have this playbook of mothering, developed from years of research and observation, that has given me assurance that even when things don't seem to be going to plan — like breastfeeding or sleeping — I was OK, and so was he.Having built up financial security, I didn't worry about how I was going to provide for a baby. Established in a career, I could plan for all baby-related expenses, including IVF.And since I had gotten so much out of my system in my younger years — corporate working, parties, nice restaurants — I felt content to settle in at home with my baby and husband. I never feel like I'm missing out.The only concern I've heard quietly whispered in different circles is that of my health. I know that as I get older, little issues with my body could pop up — issues that I might not have had as a younger mother. This has forced me to look after my body more than I ever have so that I can fully enjoy time with Crue as he gets older.Becoming a mother had always been a dream of mine. I trusted the process, holding on to hope, and although delayed, my dream finally came true.