CIO CIO

Large enterprises often struggle to integrate two beneficial technologies: virtualization for server infrastructure and containerization for application infrastructure. The reason is the differing needs of operational technology (OT) and information technology (IT) teams. These teams tend to see virtualization and containerization in terms of their own needs. That makes it difficult to mesh the two technologies. The OT case for VM infrastructure Virtualizing hardware architecture lets OT shift legacy operating systems and their mission-critical applications to modern, reliable, scalable hardware. “You can’t run your business on used hardware from eBay,” says Rudy de Anda, head of strategic alliances, Penguin Solutions. Virtualization offers other benefits for OT teams, such as workflow consolidation. “It also breaks up data silos and brings cybersecurity and other enterprise applications to the edge to reduce latency and improve user experiences,” says Ken Espiau, principal solutions architect at Penguin Solutions. The IT case for container infrastructure A main driver for containerizing applications is the rise of devops, an approach that adopts a microservices architecture to simplify and accelerate both software development and integration. A lightweight, portable container for each microservice simplifies software deployment. “This approach lends itself to continuous innovation by IT,” says Espiau. “You only have to update specific, small microservices. You can patch software in near real-time.” There is an inherent synergy between virtual machines (VMs) and containers that enables both teams to achieve success. Integration of VMs and containers is challenging Despite the benefits, as organizations try to integrate VMs and containers, they often run into business and IT issues that obstruct this natural synergy. Cybersecurity concerns remain surrounding legacy operating systems and applications that virtualization alone can’t address. Another issue is determining how to simultaneously facilitate and secure edge application access into corporate systems. Functions that had been neatly separated into OT and IT domains now urgently need to be integrated. For example, the industrial internet of things (IoT) is traditionally within the IT domain, yet industrial controls have caused it to become an OT responsibility. “These two organizations need to recognize, acknowledge, and resolve their respective differences and needs,” says Espiau. An opportunity for synergy Penguin Solutions recommends a four-pronged approach to resolving this disconnect: Enable both VMs and containers on a scalable, high-availability, fault-tolerant infrastructure, such as Stratus computing platforms. Establish an orchestration platform to automate deploying and managing containers. Eliminate or minimize application dependencies. Shift cybersecurity capabilities to the edge. A major oil and gas operator deployed the Penguin Solutions Stratus ztC Edge platform to host its legacy supervisory control and data acquisition (SCADA) applications in VMs. It also deployed a containerized, AI-based anomaly detection application for real-time pipeline monitoring. The VMs provided isolation and fault tolerance for critical OT workloads, while the containers enabled rapid deployment of predictive maintenance algorithms. The bottom line VMs and containers—properly designed and deployed—enable OT and IT teams to mesh their efforts for increased business value. Legacy applications run in high-availability VM networks, and containers enable new software functionality to deploy quickly in response to changing business needs. Delve further into the “Better Together” story of VMs and containers by watching this webcast. source

And organizations’ expectations of these IT teams have skyrocketed. IT teams must adapt quickly to these heightened expectations. IT is no longer simply about keeping the lights on; a highly effective and motivated IT team is now critical for organizational success. To add to this pressure, most seasoned CEOs and senior executives have not-too-distant memories of IT programmes gone bad, and of IT providing slow, siloed, inward-looking, bureaucratic, ineffective and lacklustre IT services and projects. Many CIOs running legacy IT teams have a big job to do to turn these perceptions around. They know that genuine trust in IT must be built to enable ongoing investment in IT. These CIOs want to be viewed as customer-focused, highly effective, trusted partners with the wider organization and its senior leaders. They also recognise that this requires structured, intentional IT transformation turnaround efforts. These efforts start with the actions of the CIO and the senior leaders of IT teams – those wholly responsible for shaping and leading the environment, behaviors and capabilities of IT teams to operate at their best. This requires engaging with the difficult people stuff — clarifying purpose, seeking feedback, building skills, resolving conflicts and refocusing the ways of working across the organization. Addressing these people-related challenges is, in some cases, not the natural forte of IT leaders. Many CIOs are technologists at heart, having built their careers on technical skills and not necessarily on people leadership skills. But technical credibility mixed with strong people leadership capability creates a powerful combination.  source

Finally, the Commission said, it is concerned that if a customer does manage to cancel its SAP maintenance and support contracts and subsequently returns to SAP, the company charges reinstatement and back-maintenance fees that, in some cases, “correspond to the amount customers would have paid if they had stayed with SAP all along.” User concern The managing director of German enterprise IT users association VOICE, Robin Kaufmann, said that many enterprises across Europe rely on SAP’s software and associated maintenance and support services to run their businesses. “We are concerned that certain SAP practices may limit competition and companies’ freedom of choice. For example, forcing all ERP instances to be maintained exclusively by SAP, preventing the cancellation of maintenance for unused licenses, or imposing automatic extensions and high re-entry fees. These practices not only increase costs but can potentially exclude competitors who also offer maintenance services,” he said via email. For VOICE members, it’s essential to have a real choice between suppliers, with fair pricing and clear contract conditions, he said. “Users must have the freedom to source maintenance and support flexibly and according to their needs from different providers.” source

The trial used trading data from Sept. 1, 2023, to Oct. 29, 2024, covering 1 073 926 requests for quotes (RFQs) relating to 5166 bonds and 747 associated tickers. It used IBM’s System 2 quantum machine with the latest Heron processors for the quantum computing involved. An ideal test market Jack Jacquier, Professor of Mathematics at Imperial College, London, agreed that it was an ideal market in which to test the technology. “For some time there has been a question of what we can do with quantum computing. This is ideal for quantum as they have big problems to solve.” Gartner research vice president Matthew Brisse endorsed this view. “The financial industry has been focusing on stochastic modeling, optimization, and machine learning for derivative pricing, risk analysis, portfolio/trade optimization, hedging, swap netting, and anomaly detection to see where quantum computing could have an impact. Adding quantum-enabled algorithmic trading with quantum computing on real industry data is a major step in quantum computing’s evolution to business value,” he said. source

Consider a single statistic: 85% of all work now happens in the browser. This represents a fundamental shift of the corporate workspace. While this shift has unlocked incredible productivity, it has also transformed the browser into the most critical — and most targeted — attack surface for the modern enterprise. This same redefinition of the workspace is now happening with artificial intelligence, but at a speed and scale that dwarfs previous shifts. AI is rapidly moving from a theoretical tool to an embedded, active participant in daily workflows, particularly in marketing, which has become a key arena for its adoption. Recent McKinsey research validates this trend, placing marketing at the forefront of AI implementation alongside IT and sales. For marketing leaders, this means AI is becoming as foundational as the browser itself. This new reality — where AI increasingly powers employee workflows — creates both immense opportunity and a new, urgent imperative to secure these powerful new capabilities. What if AI fails the brand? For marketing leaders, the unprecedented adoption of AI has created a new and complex risk environment for the brand. As noted by KPMG experts in an April 2025 study, this challenge stems from a potent combination — the speed of AI adoption, a widespread lack of AI literacy, and often weak internal governance. This new layer of AI risk is compounding the existing threats that already target the modern workspace. A recent Omdia report found that 95% of organizations experienced browser-based attacks like phishing and malware between 2023 and 2024. With the browser now being the primary interface for AI tools, these two threat vectors have become deeply intertwined. And attacks are already a top concern. This risk is taking hold across the entire marketing ecosystem, creating a new, three-front challenge for CMOs. It begins with the unsanctioned employee use of powerful tools like ChatGPT and extends to the AI models built directly into new products and services. It’s also deeply embedded in the AI capabilities of the core CRM and martech stacks that power our daily operations. A new threat to brand integrity: Shadow AI The appeal of AI tools within marketing teams is undeniable — they promise speed, convenience, and power. This widespread adoption, however, has a significant downside. The KPMG research highlights the scale of this challenge. That is, nearly half of employees admit to using AI in ways that contravene company policies, including uploading sensitive corporate information into public AI tools. This widespread, unsanctioned use has given rise to a new and significant threat — shadow AI. Much like the shadow IT of the past, this phenomenon creates a massive blind spot in an organization’s security posture. The scale of this risk is staggering. Gartner® predicts that through 2026, internal policy violations will be the root cause of at least 80% of unauthorized AI transactions, stemming from, for example, information oversharing and using unapproved tools. From brand steward to risk partner This new reality requires new accountability for marketing leaders. Our role must expand beyond stewarding the visual identity and voice of our brand; we must now become the stewards of its algorithmic integrity. This means forging a new, deeper, and non-negotiable partnership with our CIO and CISO. Traditional silos between marketing and IT have become a direct threat to the brand. The only path forward is to jointly architect an AI enablement framework that transforms shadow AI from a hidden risk into a managed engine for innovation. Forging an alliance between marketing and IT Managing the risks of a modern, AI-powered marketing department requires a new level of cross-departmental trust and collaboration. While the CMO must spearhead the effort to balance innovation with security, the technical nature of solutions, like browser controls and AI governance, means the CIO and CISO are essential partners. This has forced data security and access management to become a shared priority. CMOs and CIOs must now step outside of their traditional remits to build a unified strategy. This alignment enables teams to reimagine work with AI at its center to meet the marketing team’s needs for innovation while ensuring the enterprise remains secure. The work of alignment: A guide to CMO-CIO collaboration This alignment, though, doesn’t happen by accident; you must architect it with intention. You can build a successful partnership on three core pillars: Co-author an AI enablement framework. The first step is to move beyond ad hoc tool adoption. The CMO and CIO should jointly create a formal framework that establishes an approved list of AI tools, sets clear usage policies for sensitive data, and outlines a plan for ongoing employee education. This step transforms shadow AI from a risk into a managed asset. Establish a shared roadmap and cadence. True alignment requires a shared rhythm. This means that marketing and IT leadership must establish regular, strategic meetings to review roadmaps, anticipate challenges, and ensure that security is a design partner in new marketing initiatives, not a gatekeeper at the end. Run joint crisis simulations. The ultimate test of alignment is how the teams respond under pressure. The CMO and CISO should run joint tabletop exercises that simulate a brand-damaging AI incident, such as a compromised chatbot or a biased campaign. This test builds the muscle memory and trust required to effectively navigate a real crisis. Innovation demands a new operating model The traditional, siloed relationship between marketing and IT is more than inefficient; in the age of AI, it is a direct threat to the brand. The path forward requires more than occasional collaboration. Rather, it demands a new, deeply integrated operating model. This means moving beyond separate roadmaps to a single, shared vision for how to deploy AI securely to drive business outcomes. It means running joint crisis simulations to build the efficiency and accuracy required to navigate a brand-damaging AI incident. This transforms the relationship from a series of handoffs to a true partnership, where security becomes the foundation upon which marketing can safely innovate. This new alliance is the

Living Security, a global leader in Human Risk Management (HRM), today announced the full speaker lineup for the Human Risk Management Conference (HRMCon 2025), taking place October 20, 2025, at Austin’s Q2 Stadium and virtually worldwide. The announcement follows findings from the newly published 2025 State of Human Cyber Risk Report, produced by the Cyentia Institute in collaboration with Living Security, which reveals that on average, organizations detect only 19% of all human risk activity. That means the majority of risky behaviors — from credential misuse to insider threats — go unseen, leaving enterprises exposed to risks that technology or traditional awareness programs alone can’t solve. HRMCon is a one-day event focused on the people side of cybersecurity, offered this year both in-person in Austin and virtually worldwide. The program is designed for CISOs, security leaders, risk managers, and HR professionals who are responsible for building security culture and reducing human-driven risk. Sessions will explore how to extend risk ownership beyond traditional awareness programs and the security operations center, empowering managers and employees across the business to take accountability. Attendees will gain practical strategies they can apply immediately from executives, global analysts, and peers. Participants with confirmed attendance may also request a completion certificate for Continuing Professional Education (CPE) credits for the full conference. “Most organizations remain blind to the majority of human-driven risk, leaving gaps that technology or traditional awareness programs alone can’t solve,” said Ashley Rose, CEO and Co-Founder of Living Security. “Closing that visibility gap requires new strategies, proven frameworks, and collaboration across functions — which is exactly what HRMCon is designed to deliver. No matter where you are in your HRM journey, you’ll walk away with practical playbooks, proven strategies, and inspiring stories you can apply immediately. This isn’t just another security event—it’s a launchpad for making human risk a managed business function, all without pulling you away from your day-to-day responsibilities.” HRMCon 2025 will feature enterprise CISOs, Fortune 500 veterans, and leading analysts sharing research-backed strategies and real-world lessons on operationalizing human risk management. Speaker Highlights Opening Keynote – Brett Wahlin, CISO, Aurora – From Counterintelligence to Cybersecurity: Rethinking the Human Factor Across Industries. Risk frameworks have shaped enterprise security for decades but often overlook the human element. Drawing on his path from counterintelligence to the CISO seat, Brett Wahlin will show where traditional frameworks succeed, where they fall short, and how Human Risk Management can integrate people into the same disciplined approach that governs technology. Tim Taylor, VP of Security Education and Awareness, Mastercard – Creating Human Risk Visibility: Where to Start and How to Scale. Tim offers a step-by-step play for creating measurable human risk visibility in 90 days. Attendees will learn how to define goals, connect data sources, and build momentum toward sustainable risk reduction. Ashley Atiles, Director of Identity Risk, & Alfonso Mancuso, Director of Information Security, Labcorp – The Access Equation: Identity Meets Human Risk. Ashley and Alfonso will explore how identity and behavior intersect as the earliest line of defense. Attendees will learn how integrating IAM signals with human risk data creates a powerful new lever for stopping threats before they escalate. Kelly Harward, VP of Product & Mike Siegel, President, Living Security – Operationalizing HRM: From Frameworks and Playbooks to Goals for Adaptive Defense. Living Security leaders show how to translate frameworks into measurable outcomes. Attendees will see real-world playbooks and a preview of the new Goals feature, which ties behavior change directly to risk reduction. Jinan Budge, VP & Principal Analyst, Forrester – The Future of Human Risk Management: Market Landscape and the Role of Agentic AI. A market-level view of how Human Risk Management is evolving from compliance to strategy. Attendees will learn about the current state of the market, where it’s headed, and how autonomous AI agents are set to reshape HRM strategies in the years ahead. Closing Keynote – Larry Whiteside Jr., CISO Advisor & Co-Founder, Confide – Evolving the Role of the CISO: From Defense to Business Enabler. A concise look at how the CISO role is shifting from technical defense to strategic business leadership. Attendees will hear how Human Risk Management can help CISOs align security with culture, accountability, and measurable business outcomes. HRMCon 2025 Features Grounded in Research: Learning real-world strategies to close the 19% human risk visibility gap. Professional Development: Earning verifiable CPE credits with a completion certificate (confirmed attendance and upon request). Free and Flexible: Registering at no cost and choose to attending live in Austin or virtually from anywhere. Expert-Led: Hearing from leading CISOs, analysts, and security practitioners shaping the HRM market. Peer Insights: Seeing how organizations are operationalizing HRM through case studies and playbooks. Immediate Takeaways: Leaving with frameworks, tools, and strategies you can implement right away. HRMCon 2025, hosted by Living Security, comes at a pivotal time for organizations looking to transform security culture, reduce human-driven risk, and lead in an AI-enabled world. Users can register today at www.livingsecurity.com/hrmcon-2025 About Living Security Living Security is the global leader in Human Risk Management (HRM), providing a risk-informed approach that meets organizations where they are—whether that’s starting with AI-based phishing simulations, intelligent behavior-based training, or implementing a full HRM strategy that correlates behavior, identity, and threat data streams. Living Security’s Unify platform delivers 3X more visibility into human risk than traditional, compliance-based training platforms by eliminating siloed data and integrating across the security ecosystem. The platform pinpoints the 8–12% of users who pose the greatest risk and automates targeted interventions in real time—reducing exposure to human risk by over 90%. Powered by AI, human analysis, and industry-wide threat telemetry, Unify transforms fragmented signals into intelligent, adaptive defense. Named a Global Leader in Human Risk Management by Forrester and trusted by enterprises like Unilever, Mastercard, Merck, and Abbott Labs, Living Security helps security teams move from awareness to action—driving measurable behavior change and proving impact at every stage of the journey. Contact Living Security Media [email protected] source

The age of artificial intelligence (AI) isn’t defined by large language models alone. It’s defined by how enterprises use them—across customer journeys, internal operations, and revenue channels. As businesses experiment with GenAI, many face a fundamental decision: Should we build the underlying AI infrastructure ourselves, or should we partner? The instinct to build is strong. It offers perceived control, flexibility, and a bespoke experience. But the reality—as emerging data shows—is that building multi-agent AI systems from scratch introduces a level of technical and financial complexity that most enterprises underestimate. The hidden complexity of DIY On paper, in-house builds look strategic. You get to design the stack, control the data, tweak the orchestration logic, and select your preferred models. In practice, however, this control translates into responsibility across layers that your team may not be equipped to handle at scale: Data pipelines must be engineered to serve diverse context windows Retrieval-augmented generation (RAG) needs tight integration with structured and unstructured datasets Multiple agents—summarisation, search, reasoning, translation, and more—must operate in tandem with low latency Inferencing costs rise with concurrency and dynamic prompts Guardrails, monitoring, and feedback loops must be in place to avoid hallucinations, compliance risks, or performance drifts Each layer adds cost. Each interface introduces risk. And most critically, these aren’t one-time efforts. AI systems need continuous optimisation, governance, and infrastructure elasticity. The five phases where cost creeps in According to our latest three-year TCO study, the end-to-end cost of deploying multi-agent AI systems can be decomposed into five major blocks: Data preparation and pipeline engineering: Cleaning, annotating, and connecting data sources Model training or RAG integration: Fine-tuning LLMs or building hybrid architectures Agent design and orchestration: Setting logic, context flows, and inter-agent communication Inferencing infrastructure: GPU provisioning, concurrency management, latency optimisation Monitoring, security, and scaling: Real-time observability, prompt audits, compliance enforcement In a build-led model, each of these becomes an internal project. The TCO compounds quickly, especially when multiple use cases or geographies are involved. In contrast, partner-led models abstract much of this complexity, turning CAPEX-heavy experimentation into OPEX-optimised execution. A systems problem, not a model problem Too often, AI readiness is discussed in the context of model selection. But from what we see in the field, that’s rarely the real challenge. The bigger roadblock lies in stitching together a production-grade system: Vector databases that can handle hybrid search Real-time feedback loops for prompt evaluation Governance policies that keep LLM use auditable and secure Unified interfaces for prompt engineers, product teams, and compliance officers This is where a platform-led approach adds exponential value. Our recent collaboration with IDC outlines the anatomy of an AI-ready data value chain, from acquisition and enrichment to secure access and orchestration. Without this backbone, GenAI remains an expensive experiment. A smarter way to accelerate To better understand the economics of AI deployment, we conducted a detailed total cost of ownership (TCO) analysis using our own platforms: Tata Communications CXaaS and Vayu Cloud. The scenario modelled a multi-agent AI architecture for commerce applications over three years, simulating enterprise-scale deployments with varying levels of concurrency and agent complexity. The parameters included a typical commerce use case with agents for search, summarisation, translation, and decisioning, concurrency of 100+ sessions per second, integration with existing CRM, product, and inventory systems, and continuous fine-tuning and RAG-based orchestration. Some key findings from the study include: Build-led deployments were 2.4x more expensive over three years, primarily due to infrastructure sprawl and engineering overheads 45% of total cost in the build model was attributed to orchestration and system integration alone Partner-led models reduced time-to-launch by up to 6 months, enabling faster iteration and ROI realisation AI operations and governance costs were 3x lower in managed environments with built-in observability and compliance frameworks The results clearly highlighted the cost benefits and operational efficiencies of a platform-led approach. Enterprises can reduce costs, accelerate deployment, and scale AI initiatives without having to build every capability from the ground up. The decision to build or partner isn’t binary—it’s deeply contextual. Our analysis doesn’t suggest that building is always the wrong approach. In fact, for enterprises with highly specialised workflows, stringent data residency needs, or proprietary models and algorithms, a build-led path may provide the level of control and customisation required. However, for most organisations looking to scale GenAI capabilities across business units quickly, without reinventing the infrastructure wheel, partnering can offer speed, predictability, and lower risk. The critical takeaway is this: as multi-agent systems scale, so does the complexity. Whether you build or partner, it’s essential to have visibility into the hidden architecture of AI—and ensure that your strategy aligns not just with your technical vision, but with your business reality. Click here for more details on our study, Build vs. Partner: A three-year TCO analysis of multi-agent AI deployment. source

At Adobe, we believe in the power of technology to transform the way we work. As VP of Digital Employee Experience, I’ve seen firsthand how innovation can unlock human potential, foster collaboration and elevate business outcomes. In today’s hybrid environment, employees face an overwhelming amount of information, often buried in lengthy documents and scattered across disconnected tools. These challenges can slow down even agile teams, making it harder to focus on meaningful work. We know this struggle. When it comes to AI in Acrobat, we started with Acrobat AI Assistant — capable of summarizing lengthy documents, extracting key insights and comparing contracts in seconds. Now, Acrobat Studio takes how work gets done to the next level. Reimagining work with AI-powered tools Acrobat Studio isn’t just a refresh of our iconic platform — it’s designed to empower teams, unlock knowledge, streamline collaboration and create impactful content. Built for the age of AI, Acrobat Studio combines trusted PDF tools with innovative features like PDF Spaces and personalized AI assistants, helping our workforce turn static documents into dynamic, conversational knowledge hubs. Imagine a legal team centralizing contracts in PDF Spaces while AI quickly compares versions to flag risks. Marketing teams can transform briefs into polished presentations with Adobe Express. HR can create digestible summaries of policies and onboarding materials. And across all of it, Acrobat’s secure redactions and e-signatures streamline compliance. Visual communication is also central to this experience. With built-in Adobe Express Premium in Acrobat Studio, every employee can create professional-grade reports, infographics and posts — making complex ideas easier to share and remember. Drinking our own champagne We’re customer zero at Adobe, using Acrobat Studio to transform our work, helping us save time, reduce complexity and drive impact: Onboarding: PDF Spaces serve as centralized hubs for onboarding materials, including branding guidelines, training resources, and key contacts. Legal: Our legal teams use PDF Spaces to locate key clauses, compare contracts, and ensure compliance. Marketing & creative: From generating executive summaries of creative briefs to crafting branded presentations, Acrobat Studio streamlines content creation and enhances collaboration. HR: Summarizing policies, onboarding materials and benefits documents has never been easier. HR teams leverage AI to create digestible, employee-friendly content. Enterprise-grade trust and transparency Acrobat Studio is built with transparency, control and compliance at its core, making it a reliable partner for decision-making and collaboration: Secure AI-powered insights: The AI Assistant provides verifiable insights with clickable citations, ensuring accuracy in high-stakes workflows. Enterprise-grade encryption: Acrobat Studio leverages Adobe’s trusted infrastructure, safeguarding data with robust security measures. Commercially safe AI: Generative AI capabilities, powered by Adobe Firefly, ensure that all content is commercially safe and brand ready. Unlocking human potential Selecting the right technology, like AI in Acrobat Studio, is critical for businesses today. Now is the time to embrace AI-driven solutions to simplify complexity and amplify human creativity. For me, creating an environment to unlock human potential is about enabling our employees to do their best work. When you do this successfully, the true impact goes beyond numbers, helping foster a culture of innovation that empowers people, customers and your business to thrive. For more information, visit Acrobat Studio. source

Today’s new macro volatility We now face a new era of macro volatility. Inflation, geopolitical conflicts and supply chain disruptions are just a few of the forces at play. But today’s volatility goes beyond external factors — it’s internal as well. Many businesses are grappling with reduced budgets, shrinking headcounts and limited IT resources, all while trying to balance cost reduction with the need to innovate and grow. Simply investing in the latest technology is no longer enough to respond effectively. Companies must build foundational business agility and become smarter about where they invest their resources and how they measure success. In retail, I’ve seen plenty of companies build these monolithic, “do everything” platforms that were almost impossible to change once they were live. One large European retailer I spoke to had spent years building a custom ERP commerce system that was beautifully controlled, but when the COVID-19 pandemic hit and they needed new digital channels, they couldn’t move. Their competitors launched marketplaces in months. They were stuck. It wasn’t the technology that failed; it was the mindset of trying to control every detail. source

In today’s complex workplaces, building trust isn’t just a “nice to have.” It’s a strategic necessity. Research consistently shows that when trust thrives, so do collaboration, communication, decision-making, motivation, innovation, engagement, commitment, performance and employee satisfaction. Trustworthy leaders inspire loyalty and confidence. They create psychological safety that allows people to take smart risks, speak up with new ideas and embrace change. On the other hand, missteps by a single or a few leaders may erode trust in entire institutions, as demonstrated by the Cummings Effect in the UK during the COVID-19 outbreak. Trust is deeply context-dependent, shaped by experience, culture and communication, rather than “one-size-fits-all.” Overlooking trust influencers and nuances risks not only low trust levels, but also misalignment between employees, leaders, vendors and customers, leading to friction, frustration and additional adverse consequences. Communication Frontline employees’ trust in leadership is closely tied to how they perceive organizational communication. Research shows that Transparent and inclusive communication affects trust, and through it (and other factors) performance and satisfaction. Similarly, when managers actively listen and engage with employees through internal digital platforms, demonstrate they understand and address employee concerns promptly, trust improves. Consistent, transparent and empathetic messaging builds trust, which helps leaders earn buy-in and supports their sense-giving efforts. source