Cybersecurity’s Real Shortage: Strong Leaders Who Understand Tech

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If you’ve got your finger on the pulse of digital recruitment, you’ll know that the cybersecurity workforce shortage is a serious issue. Skills gaps are putting organizations at risk as increasingly sophisticated cyberattacks place a growing burden on already stretched cybersecurity teams. At least four million cybersecurity roles remain unfilled, while rates of cybercrime continue to soar.

Cybersecurity workforce development is one solution, but there could be another: investing in tech-savvy leaders who instill the importance of cybersecurity at all levels of their organization. 

Current Cybersecurity Workforce Landscape

Cybersecurity skills gaps continue to be problematic. Different sources give different figures for the size of the talent gap, but it’s at least four million, with USA-based organizations attempting to recruit over half a million new cybersecurity professionals in the last 12 months.

Challenges include rapidly advancing technologies, such as AI, and economic uncertainties that mean candidates are less likely to look for something new. Businesses may simply not have the budget to attract and retain top talent who can demand high salaries.

The Leadership Bottleneck

Cybersecurity talent acquisition has to be a top priority for leaders across all industries, yet some leaders are failing to take the right actions to bring cybersecurity talent to their organization. They’re creating a bottleneck — even where candidates are available, poor leadership is causing them to apply elsewhere.

Just look at some of these figures:

Organizational leaders who fail to address these issues could be creating their own internal security risks by driving away skilled talent.

Consequences of Leadership Deficiencies

Turning talent away isn’t the only issue. In cybersecurity, leadership challenges range from employing executives with zero tech experience to tech experts with minimal leadership skills. We recently discussed the importance of prioritizing tech fluency as a C-suite imperative. Cybersecurity workforce management requires leaders who understand the foundational concepts of the work their teams do. Similarly, tech leaders must have relevant leadership skills as well as technical know-how. 

Without this balance, organizations are at a much higher risk of data breaches and attacks. Research shows that 58% of cyber professionals believe that skills gaps place organizations at significant risk of cyberattack, while firms with significant cyber talent gaps are twice as likely to fall victim. Leaders not taking the right steps to address these skills gaps are effectively putting their entire organization at risk. This impacts overall morale and places existing cyber professionals under unreasonable amounts of pressure.

Strategies for Leadership Improvement

Cybersecurity leadership development can start with internal leadership development programs. Rather than hiring from untested talent pools, coaching and developing existing, loyal employees could create highly invested leaders with the know-how to quickly assess where more resources or personnel are required.

Investing in leadership development programs is more effective when organizations focus on formal training and transferable, strategic skills and certifications.

Key cybersecurity leadership skills should include: 

  • Communication

  • Collaboration

  • Cybersecurity-specific skills

  • Inclusivity

  • Strategic planning

  • Adaptability

Leaders should also be encouraged to be open to new ways of hiring. Cybersecurity leaders who sign off on social media-based hiring techniques, partnering with educational institutions, and working with specialist recruitment partners could ensure their organization stays secure while edging ahead of competitors.

Cybersecurity Leadership Development and Recruitment: Unlocking Success

Are you working on your cybersecurity workforce strategy? Investing in the right tech leadership team could be your first critical step. When leaders understand the importance of building, developing, and supporting a thriving cybersecurity workforce, it makes the whole organization more security aware — and could encourage competing organizations to change their approach to cyber hiring.

Connect with The Trevi Group and work with expert talent solutions specialists to upgrade your cybersecurity professional hiring strategy.

The Trevi Group | “Executive Search for Technology Professionals” | www.TheTreviGroup.com

#thetrevigroup #recruitingtrends #informationtechnology #employmenttrends #jobmarket #hiringtrends #cybersecurity

Cloud Cost Optimization in the Age of AI: Tools, Metrics, and ROI Strategies

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The cloud has become the backbone of digital innovation — especially as artificial intelligence (AI) continues to reshape how businesses operate, scale, and compete. Yet, as organizations expand their cloud footprint to support data-heavy AI workloads, one challenge has taken center stage: cost control.

Cloud cost optimization isn’t just about cutting expenses; it’s about maximizing performance, predictability, and return on investment (ROI) without compromising agility or innovation. In the age of AI, smarter cost management is a competitive advantage.

1. The AI Impact on Cloud Spending

AI workloads are data-intensive, compute-heavy, and often unpredictable. Training models, running analytics, and managing continuous inference pipelines can quickly inflate cloud bills.
A single generative AI deployment can consume thousands of GPU hours and terabytes of storage — and without proper oversight, cloud costs can spiral.

As enterprises scale AI adoption, they’re realizing that traditional cost governance no longer works. Optimization now requires real-time visibility, intelligent automation, and a deep understanding of how each workload drives business value.

2. Establishing Visibility: The Foundation of Cost Control

You can’t optimize what you can’t see.
Modern FinOps (Financial Operations) frameworks focus on giving finance, engineering, and operations teams shared visibility into cloud spend. By unifying cost data across AWS, Azure, and Google Cloud, companies gain the transparency needed to make data-driven decisions.

Key tools that enable visibility include:

  • CloudHealth by VMware – provides detailed spend analytics and governance dashboards.

  • AWS Cost Explorer & Savings Plans Advisor – tracks usage trends and recommends right-sizing or reserved instance purchases.

  • Google Cloud Cost Intelligence – connects usage data directly to projects and business units.

Clear visibility turns cloud cost management from guesswork into strategic decision-making.

3. Key Metrics That Matter

The right metrics are essential to identify inefficiencies and measure improvement. The most effective organizations monitor a mix of financial and operational KPIs, such as:

  • Cost per workload or application – isolates high-cost environments.

  • Cost per customer transaction – aligns spend with revenue performance.

  • Utilization rate – ensures resources aren’t underused.

  • Elasticity ratio – measures how effectively scaling matches demand.

  • Unit economics for AI models – tracks the cost of training and inference relative to output or accuracy.

These metrics reveal not just where money is going, but how it contributes to business outcomes.

4. Smart Tools for Cloud Optimization

In 2025, cloud optimization is powered by AI itself. Leading platforms now use machine learning to detect anomalies, predict demand, and recommend cost-saving actions automatically.

Top solutions include:

  • Apptio Cloudability – automates allocation and budget forecasting for complex multi-cloud environments.

  • Kubecost – provides real-time visibility into Kubernetes cluster expenses.

  • Harness Cloud Cost Management – integrates continuous delivery pipelines with cost controls.

  • Spot by NetApp – dynamically provisions and scales compute based on performance requirements and pricing models.

By combining automation with accountability, these tools help enterprises reduce waste and reinvest savings into innovation.

5. Rightsizing and Scaling Strategies

Rightsizing — adjusting compute, storage, and network resources to match actual needs — is one of the fastest paths to savings.
However, in AI-heavy environments, workloads fluctuate dramatically between training and production phases. Dynamic scaling policies and serverless architectures allow businesses to pay only for what they use, without sacrificing performance.

Additionally, reserved instances and spot instances remain effective cost levers when managed intelligently through automated policies.

6. Building a FinOps Culture

True optimization isn’t achieved through tools alone — it requires a cultural shift.
FinOps practices promote collaboration between finance and IT, ensuring every team understands how their cloud decisions impact profitability. Regular reporting, budget alerts, and ROI reviews create shared accountability.

By fostering this mindset, organizations transform cloud cost management from a reactive function into a strategic capability that drives innovation responsibly.

7. Measuring ROI and Continuous Improvement

Cost optimization is not a one-time project — it’s an ongoing discipline.
Track the return on every optimization initiative, whether it’s through reduced waste, improved utilization, or faster time-to-market. Reinvest those savings into AI innovation, product development, or digital transformation.

Continuous improvement is the hallmark of cloud maturity — and the key to turning cost efficiency into business agility.

Conclusion

As AI reshapes industries, cloud infrastructure will continue to expand — and so will the need for smarter, data-driven cost control.
Organizations that embrace visibility, automation, and financial discipline will not only reduce expenses but also strengthen their ability to innovate sustainably.

In the age of AI, cloud cost optimization isn’t just a technical exercise — it’s a strategic differentiator. By aligning cloud spending with business value, enterprises position themselves for long-term growth, efficiency, and innovation. Contact The Trevi Group if you need resources that will be able to handles these needs.

The Trevi Group | “Executive Search for Technology Professionals” | www.TheTreviGroup.com

#thetrevigroup #recruitingtrends #informationtechnology #employmenttrends #jobmarket #hiringtrends #cloud #AI

Rethinking Tech Leadership: Essential Skills for the Hybrid CIO/CTO of 2026

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Technology is no longer just a business function — it’s the foundation of every strategic decision. As we move toward 2026, the lines between the Chief Information Officer (CIO) and Chief Technology Officer (CTO) are blurring. Today’s tech leaders are expected to be visionaries, strategists, and change agents — all at once.

The modern CIO/CTO isn’t just managing infrastructure; they’re shaping innovation, driving digital transformation, and aligning technology with business value. To thrive in this new hybrid landscape, tech executives must combine technical fluency with human-centered leadership.

1. Strategic Vision Meets Business Acumen

In the past, CIOs focused on internal systems while CTOs drove external innovation. In 2026, those roles converge around a shared goal — creating technology that accelerates business outcomes.
The hybrid leader understands not only what technology can do, but why it matters. They speak the language of both code and commerce — translating technical complexity into business clarity.

Whether it’s optimizing cloud infrastructure or launching AI-driven customer experiences, the hybrid CIO/CTO must act as a strategic bridge between innovation and execution.

2. Digital Transformation as a Continuous Journey

Transformation is no longer a one-time project — it’s a cultural commitment.
The most effective tech leaders are those who see digital transformation as an ongoing evolution, not a milestone. They’re building adaptable systems, scalable architectures, and agile teams that can pivot quickly when markets shift.

In 2026, technology leadership will be measured not by how much software you deploy, but by how fluidly your organization adapts to change.

3. Human-Centered Technology Leadership

While automation, AI, and analytics are transforming business operations, the real differentiator lies in people.
Today’s hybrid CIO/CTO must balance innovation with empathy — fostering collaboration, inclusion, and trust across hybrid and remote teams. Emotional intelligence, communication, and mentorship are as vital as technical certifications.

The best leaders inspire engineers, data scientists, and business stakeholders alike to rally behind a shared purpose: creating technology that improves lives, not just systems.

4. Cyber Resilience and Risk Intelligence

In a world of increasing cyber threats, security is no longer just the CISO’s domain — it’s a shared leadership responsibility.
Hybrid CIOs/CTOs must adopt risk-aware mindsets, embedding security into every stage of development and decision-making. From data governance to AI ethics, tech leaders must ensure that innovation is both responsible and resilient.

Building a cyber-conscious culture means educating every employee — not just IT teams — about their role in protecting digital assets.

5. Data-Driven Decision Making

Data is the new competitive currency. The next generation of CIOs and CTOs must go beyond collecting information — they must turn insight into foresight.
 By leveraging predictive analytics, machine learning, and business intelligence tools, hybrid leaders can make smarter, faster decisions that align technology investment with measurable business outcomes.

The goal: create organizations where data drives direction, not confusion.

6. Collaboration Across the C-Suite

In 2026, no technology leader operates in isolation. The hybrid CIO/CTO must partner closely with the CEO, CFO, CHRO, and CMO to ensure technology supports every aspect of growth and culture.

This cross-functional collaboration demands diplomacy, communication, and strategic storytelling. The ability to influence peers — not just manage teams — defines the next wave of transformative tech leaders.

7. Future-Ready Mindset and Lifelong Learning

The pace of technological change means yesterday’s expertise can become tomorrow’s limitation. Successful hybrid leaders embrace continuous learning, staying curious about emerging technologies like quantum computing, generative AI, and edge intelligence.

They cultivate adaptive teams that thrive on exploration, not just execution — creating a culture where innovation is everyone’s job.

Conclusion

As organizations evolve toward digital-first business models, the CIO/CTO of 2026 must evolve too. The hybrid tech leader is no longer defined by their title, but by their impact — the ability to merge vision with action, data with empathy, and innovation with purpose.

The future belongs to those who don’t just manage technology, but lead transformation through it. Contact The Trevi Group if you need leadership that can do that.

The Trevi Group | “Executive Search for Technology Professionals” | www.TheTreviGroup.com

#thetrevigroup #recruitingtrends #informationtechnology #employmenttrends #jobmarket #hiringtrends #ITleadership

The Hidden Value of Lateral Moves in Leadership Development

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Promotions are traditionally seen as a symbol of success within an organization. 

In a standard career pathway, promoted employees take on broader job scopes and responsibilities, justified by higher salaries and additional staff benefits. Yet, career progression may come in subtler forms, such as lateral or sideways movements. 

These types of transitions could include…

  • Switching from a corporate role at the main office of an MNC to a smaller offshore branch

  • Moving from accounting to auditing at a financial institute

  • Assuming a cross-functional role for P&L exposure

While lateral movements may lack the prestige of promotions in terms of salary and benefits, they are more effective in keeping employees engaged in the long term. An MIT Sloan study showed that lateral transition opportunities at work are 12 times more effective than promotions in influencing talent retention.   

These lateral movements are more than title inflation. They offer talent golden opportunities to showcase their versatility and resilience, which qualify them for leadership roles further down the career pipeline. 

Thanks to decades of experience placing professionals across industries, The Trevi Group recruiters understand the value of lateral and their often-overlooked influence on leadership development. Read on to discover how decision-makers can enhance their executive talent search by identifying future leaders, no matter their path to career progression and professional development.

Identifying the Strategic Importance of Lateral Movements

Lateral movements present talent with unfamiliar and challenging territories, although they maintain the same job level. These transitions demand new functions and responsibilities that require individuals to adopt more resilient and adaptable workplace attitudes.

As such, lateral movements encourage the development of transferable soft skills crucial for leadership growth. These skills could include time management, calculated risk assessments, problem-solving, and communication. And perhaps more importantly, lateral movers have the advantage of experiencing different organizational areas without the pressures of a promotion. 

Exposure to different sides of company operations sharply improves an employee’s situational awareness to help them act practically and decisively when complex issues arise. Lateral movers could also develop a stronger sense of empathy through a deeper understanding of cross-departmental workflows. 

Through professional network expansions, talent can broaden their perspectives by appreciating their team and accepting diverse workplace dynamics. As future leaders, movers can effectively empathize with co-workers and foster a positive and supportive climate that advances a company’s employee retention techniques.     

How Lateral Moves Influence Leadership Development

Lateral movements broaden organizational perspectives, equipping talent with specialized skill sets for handling diverse workplace scenarios. Every deployment further diversifies the employee’s core competencies with informed choices, risk assessment, and resource management. 

Industry case studies show that lateral movers earn higher salaries than non-movers, even in scenarios where they do not demonstrate superior performance and despite the lack of promotion. These incentives could encourage employee engagement, retention, and organizational alignment to lead successfully by example. 

In fact, employees with lateral movement experience are more likely to be promoted in three to four years compared to peers who lack these skills. The interpersonal skills developed through a broader professional network could make these individuals more approachable as leaders. 

How The Trevi Group Recruiters Evaluate Lateral Moves in High-Impact Candidates

The experienced recruiters at The Trevi Group have developed a holistic approach to talent assessment, going beyond the limitations of traditional resumes. Lateral movements, for example, have become a standout factor for assessing job fits during interviews. Workforce research reveals that companies with established internal employee initiatives, like lateral transitions, boost employee intent and retention by 33%.  These transitory milestones shed valuable insights for predicting employee personas and career outcomes.

The Trevi Group team members also focus on key indicators such as problem-solving, risk-taking, and acquired competencies to achieve best practices in recruiting business leaders. By interpreting these indicators, employers can determine the talent’s long-term vision and career management. Recruiters can also increase awareness of red flags based on poor performance in these areas, which may suggest a cultural mismatch and a lack of leadership readiness. 

Strengthening Leadership Pipelines With Lateral Movements

The Trevi Group optimizes succession planning best practices by providing companies with access to the most qualified leadership candidates.

By incorporating hiring factors such as lateral transitions and cross-functional experience, employers can confidently attract astute individuals with diversified leadership skills. 

Visit The Trevi Group to discover how you can optimize organizational talent development with a comprehensive assessment of career movements. 

The Trevi Group | “Executive Search for Technology Professionals” | www.TheTreviGroup.com

#thetrevigroup #recruitingtrends #informationtechnology #employmenttrends #jobmarket #hiringtrends

Cybersecurity for Cloud-Native Environments: A Practical Framework

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Introduction

As more organizations across the United States transition to cloud-native architectures, cybersecurity has evolved from a technical concern to a strategic business priority. The flexibility and scalability of cloud-native systems — built on containers, microservices, and dynamic infrastructure — have unlocked new possibilities for innovation.

Yet, these same features introduce unique security challenges. Traditional perimeter defenses no longer suffice when workloads shift across hybrid and multi-cloud environments. To safeguard modern operations, companies must adopt a practical, adaptable, and continuous security framework designed specifically for the cloud-native world.

1. Rethinking Security for Cloud-Native Systems

Cloud-native environments are dynamic — workloads spin up and down within seconds, and components communicate through APIs across distributed networks. Security must therefore move from static defenses to dynamic, embedded protection.

Instead of securing the perimeter, forward-thinking organizations secure the workload itself.
 This means integrating security controls directly into the development pipeline, where every new container, function, or microservice is vetted for compliance and vulnerabilities before deployment.

2. The Zero-Trust Foundation

At the heart of modern cloud security lies the Zero Trust model — a philosophy built on one principle: never trust, always verify.
 Every connection, whether internal or external, must be authenticated and authorized.

In a cloud-native environment, this involves:

  • Strong identity and access management (IAM)

  • Multi-factor authentication (MFA)

  • Least-privilege access policies

  • Continuous monitoring of API and network activity

Zero Trust ensures that no single misconfiguration or compromised credential can jeopardize the entire system.

3. Secure the CI/CD Pipeline

Speed is the defining strength of cloud-native development — but it can also be a vulnerability. Automated pipelines accelerate innovation, yet they can push insecure code into production if not carefully governed.

Organizations should embed security testing throughout the DevOps cycle (DevSecOps) by:

  • Running vulnerability scans during build and deployment stages

  • Using container image signing and verification

  • Enforcing compliance gates before release

  • Monitoring dependencies and open-source libraries for risks

Security in CI/CD isn’t a checkpoint — it’s a continuous, automated safeguard that evolves with each iteration.

4. Container and Kubernetes Security

Containers and orchestration platforms like Kubernetes have revolutionized deployment, but they introduce complex layers of exposure.
Best practices include:

  • Regularly patching container images and base OS layers

  • Isolating workloads with namespaces and network policies

  • Using role-based access control (RBAC) for Kubernetes clusters

  • Scanning container registries for vulnerabilities

A secure Kubernetes environment should have visibility, control, and auditability across every node, pod, and API connection.

5. Observability and Incident Response

Cloud-native security doesn’t stop at prevention — it thrives on detection and response.
 By integrating observability tools that combine metrics, logs, and traces, organizations gain real-time visibility into performance and potential threats.

Advanced analytics and AI-driven insights can help teams detect anomalies early, trigger automated responses, and reduce dwell time — the window between breach and containment.

6. Shared Responsibility in the Cloud

A common misconception among enterprises is that cloud providers handle all aspects of security. In reality, security is shared.
 While providers like AWS, Azure, and Google Cloud secure the underlying infrastructure, the customer remains responsible for application-level, identity, and data protection.

This requires clear policies around:

  • Data encryption at rest and in transit

  • Backup and recovery strategies

  • Compliance mapping (HIPAA, SOC 2, ISO 27001, etc.)

  • Ongoing employee training on cloud security best practices

7. Building a Culture of Continuous Security

Technology alone cannot protect modern businesses — people and process complete the framework.
Organizations that embed cybersecurity awareness into their culture build stronger, more proactive teams. Cross-functional collaboration between developers, operations, and security leaders ensures that protection evolves alongside innovation.

Regular threat simulations, red team exercises, and security retrospectives help maintain readiness in an ever-changing environment.

Conclusion

Cloud-native technologies have transformed how American enterprises innovate, scale, and compete — but they also require a new mindset toward protection.
By embracing a Zero Trust architecture, integrating security into DevOps, and prioritizing observability and education, organizations can establish a practical cybersecurity framework built for today’s fast-moving digital landscape. Let The Trevi Group help you build your organization to make that happen.

In the modern economy, security is not a cost — it’s a catalyst for trust, resilience, and sustainable growth.

The Trevi Group | “Executive Search for Technology Professionals” | www.TheTreviGroup.com

#thetrevigroup #informationtechnology #cloud #cybersecurity #cloudsecurity

The Mid-Career Pivot: How Network Engineers Can Transition into Cloud Architecture Roles

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Introduction

For decades, network engineers have formed the backbone of enterprise IT — designing, securing, and maintaining the systems that keep organizations connected. But as cloud computing continues to reshape how businesses operate, many mid-career professionals are asking the same question: “How do I evolve my skills and move into a cloud architecture role?”

The good news? The transition from network engineering to cloud architecture is not only achievable — it’s a natural next step for those ready to embrace modern infrastructure design and hybrid environments.

Understanding the Shift: From Physical to Virtual Infrastructure

Traditional network engineering has focused on routers, switches, firewalls, and on-premises environments. Cloud architecture, by contrast, requires engineers to think in terms of virtual networks, automated scaling, and distributed systems.

In the cloud, your “data center” becomes software. Concepts like load balancing, network segmentation, and security still apply — but they’re executed through code and cloud services rather than physical hardware.

That’s why network engineers bring a huge advantage: they already understand the fundamentals of connectivity, security, and performance — the core of every cloud environment.

Step 1: Strengthen Your Cloud Fundamentals

Before diving into advanced cloud architecture, start by mastering the core principles of leading platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP).
Key areas to focus on include:

  • Virtual networks and subnets

  • Cloud storage and compute services

  • Identity and access management (IAM)

  • Load balancing and auto-scaling

  • Monitoring, logging, and cost optimization

Most professionals begin with certifications like AWS Certified Solutions Architect – Associate or Microsoft Azure Administrator. These credentials demonstrate both technical understanding and commitment to continuous learning — something employers highly value.

Step 2: Learn Infrastructure as Code (IaC)

In the cloud world, automation is everything. Tools such as Terraform, AWS CloudFormation, and Ansible allow engineers to build and manage environments programmatically.

For network engineers used to manual configuration, learning IaC might feel unfamiliar at first — but it’s a game changer. It ensures consistency, accelerates deployment, and allows cloud architects to manage large-scale systems with precision.

The more comfortable you become with scripting and automation, the faster you’ll bridge the gap between traditional networking and modern cloud architecture.

Step 3: Develop a DevOps Mindset

Cloud architecture sits at the intersection of development and operations. Understanding DevOps practices — CI/CD pipelines, containerization (Docker, Kubernetes), and observability — helps engineers design infrastructure that supports agile development and rapid innovation.

The key is to move from a “maintenance” mindset to a “continuous improvement” mindset. Cloud architects don’t just keep systems running — they design frameworks that enable teams to innovate faster, safer, and smarter.

Step 4: Build Real-World Experience

Certifications and theory are valuable, but nothing replaces hands-on practice.
Here’s how to gain experience even before landing a cloud architect title:

  • Set up personal labs using AWS Free Tier or Azure Sandbox environments.

  • Contribute to open-source projects focused on cloud networking or automation.

  • Volunteer for cloud migration initiatives within your current organization.

  • Shadow a cloud architect or collaborate on hybrid cloud implementations.

Each project builds credibility and confidence — two essentials when presenting yourself as a cloud-focused professional.

Step 5: Communicate Value Beyond Technology

Transitioning to a cloud architecture role isn’t just about technical expertise — it’s about understanding business strategy, cost management, and scalability.

Cloud architects work closely with executives and project managers to align technical decisions with business outcomes. Network engineers making the pivot should practice articulating how technology enables growth, resilience, and efficiency — not just how it functions.

Strong communication and presentation skills are as critical as technical mastery in these roles.

Step 6: Partner with Specialized Recruiters

Career transitions are smoother when you have the right guidance. Partnering with an experienced IT and cloud recruitment firm like The Trevi Group can help you navigate the market, identify roles that match your experience, and position your resume effectively.

Recruiters who specialize in network and cloud placements understand what hiring managers look for — and can help you highlight the transferable skills that make you a top candidate.

Conclusion

The journey from network engineer to cloud architect is not a leap — it’s a strategic evolution. Your experience designing secure, high-performing networks forms the foundation for success in the cloud.

By embracing new tools, expanding your cloud knowledge, and aligning your technical skills with business strategy, you can step confidently into a career that’s shaping the future of IT.

At The Trevi Group, we help talented engineers take that next step — connecting them with organizations that value innovation, expertise, and forward-thinking leadership.

Your next chapter in the cloud starts here.

The Trevi Group | “Executive Search for Technology Professionals” | www.TheTreviGroup.com

#thetrevigroup #recruitingtrends #informationtechnology #employmenttrends #jobmarket #hiringtrends

Preparing Your Manufacturing Plant For Edge Computing

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Edge computing in manufacturing has become popular as an Industry 4.0 technology solution. What was once the domain of cloud computing is now met by a competing force that redefines manufacturing operations. 

Today, decision-makers must anticipate the fresh roles and responsibilities created by these smart manufacturing systems.

In this guide, we take a close look at the tech trend by identifying the difference between edge computing and cloud computing, and their influence on plant floor operations.  

Edge Computing in Manufacturing

The primary difference between edge computing and cloud-based systems lies in their distributed structure. 

Cloud computing stores data on a centralized server, often located far from end users. In comparison, edge computing is located at the “edge” of a network, providing quicker access to sensors, machines, and devices in manufacturing plants.   

How Edge Computing Impacts Plant Floor Operations

The proximity of edge computing empowers plant floor teams with real-time data processing, unlike cloud computing, which continues to face network latency issues. As such, manufacturing teams have leveraged the new technology to expedite time-sensitive decisions critical to their plant operations. 

Implementing these solutions can enhance operational efficiency and consistency in predictive maintenance strategies. Industry reports indicate that manufacturing teams utilizing edge computing have seen operational efficiencies increase by 20% through automation and a decrease in downtime. 

Emerging Roles in Decentralized Manufacturing Operations

Edge computing has led to the rise of new industry standards in the manufacturing ops talent search. It is strategic for manufacturing leaders to focus on cross-skilling and upskilling in the following talent areas:

Data Analysts and Edge Computing Specialists

Hires may include cloud experts familiar with the latest analytical tools repurposed for edge systems. 

Cybersecurity Experts

Companies would need to gradually heighten cybersecurity in manufacturing. For instance, operational initiatives may include compliance and security controls and measures, as well as the development of edge-focused infrastructure.  

Maintenance Technicians

On-the-ground service teams may see a rising need for IoT in manufacturing to secure data transfers between edge servers and endpoint devices. Specialized Edge Computing Trainers – Facility leaders could witness an increased demand for edge-certified trainers. These learning and development (L&D) hiring trends would equip operational teams with the skills to adapt to the decentralized manufacturing climate. 

Best Practices for Recruiting in the Evolving Manufacturing Landscape

Experts project the growth of the global smart manufacturing market from $349.48 billion in 2024 to $998.99 billion by 2032, at a CAGR of 14.2%. Manufacturing employers can stay ahead of the ensuing workforce curve by optimizing their hiring strategies with multi-channel sourcing. 

For instance, employers should adopt a comprehensive hiring process that spans social media platforms, conventional job boards, and IT schools. These could attract the right job fit based on company culture and edge computing competencies.

It is also strategic for companies to enhance their employer branding during the technological shift toward decentralized manufacturing operations. Workforce trends suggest that structured onboarding in manufacturing can improve employee retention by 69% and raise productivity by 50%.

Recruitment campaigns could improve with standardized interview methods and job descriptions. Particularly, hiring teams could emphasize the long-term career fulfillment associated with edge computing roles.

For example, companies may craft JDs that promote clear edge computing-related progression pathways and training opportunities.   

Training and Development Strategies for Existing Workforce

Manufacturing employers can enhance employee management during tech adoption by integrating streamlined hiring processes with systematic training initiatives. Continuous learning programs can help encourage the existing workforce to stay confident and efficient through the operational overhaul.  

Employers could also collaborate with third-party technological institutions in overseeing company-wide upskilling. Expert-led partnerships during the adoption phase ensure that teams follow the latest industry standards. Management teams and new hires alike can acquire mentorship during these collaborations to maintain best practices for manufacturing hiring.

Preparing Your Manufacturing Plant For Edge Computing

Edge computing has reshaped manufacturing through the continuous advancement of 4.0 technologies. And now, hiring teams face a critical juncture where they need to update their workforce engagement techniques to achieve the best outcomes. 

The Trevi Group (MRINetwork)

Proactive manufacturing talent acquisition, which combines a comprehensive sourcing strategy, collaboration, and active learning, can attract top talent.  

Visit The Trevi Group to learn how your team can succeed in the edge computing era through strategic workforce development. 

The Trevi Group | “Executive Search for Technology Professionals” | www.TheTreviGroup.com

#thetrevigroup #recruitingtrends #informationtechnology #employmenttrends #jobmarket #hiringtrends #manufacturing #edgecomputing

Beyond the Code: Why Tech Leaders Must Now Hire for Ethics, Regulation, and AI Governance

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There is no denying the rapid integration of artificial intelligence into business operations. For many companies, AI technology is resulting in greater operational efficiency, enhanced customer experiences, and improved data analytics. 

However, there are also escalating ethical and regulatory challenges that accompany the advancements in AI. From concerns surrounding bias and discrimination to issues of accountability, these considerations are paramount moving forward—especially when hiring new talent. 

There is a necessity for technology leaders to incorporate ethics, regulation, and AI governance into their tech hiring strategies, starting today. Here’s why and how to get started.

The Current Landscape of AI in Business

AI adoption rates are growing exponentially across various industries. According to the latest McKinsey survey, 78% of respondents reported using AI in at least one business function. That figure is up from 72% in early 2024 and 55% the previous year. 

The applications of AI are far-reaching, which is why so many industries are leveraging AI technology. In healthcare, AI is utilized for a wide range of applications, from drug discovery to AI-powered diagnostics. In finance, it supports fraud detection and risk management. In retail, it enhances product recommendations and optimizes inventory management—and the list goes on. 

However, as these applications and use cases grow, so do the potential regulatory and ethical issues. 

Emerging Ethical and Regulatory Challenges

There are many ethical and regulatory challenges stacking up as AI becomes more commonplace in business settings, including the following:

  • The rapid evolution of AI is leading to challenges surrounding security risks, implementation costs, reliability, a widening skills gap, and more. 

  • Instances of AI-induced biases leading to public backlash. There are instances of AI systems learning and amplifying biases in their training data, which can lead to discriminatory or unfair outcomes if not properly managed. 

  • Data privacy concerns and breaches associated with AI systems remain high, and many companies have yet to develop ethical frameworks. 

The Business Imperative for Ethical AI Governance

AI governance is no longer something companies can put off—it is imperative. 

Based on what AI is capable of and what it’s already doing, it’s no longer about what you can do with AI; it’s more about how you can use it responsibly. This consideration is where AI governance comes into play—a framework that ensures AI is used ethically, safely, and transparently.

For those who do not remain compliant, financial repercussions are a reality. Legal penalties can be severe, including instances where the FCC has issued multi-million-dollar fines.

While it’s important to remain compliant, strong governance is now more than that. Having policies and practices in place is now a competitive advantage. It impacts everything from brand reputation and consumer trust to the ability to innovate and lead with confidence. 

It’s essential to be aware of the potential consequences so that you can take the appropriate action. Ethical AI, which fosters innovation and a competitive advantage, is a crucial area to focus on—especially when evaluating and addressing talent gaps.

The Talent Gap in AI Ethics and Governance

Even if companies have the strategies and policies in place, they need the right people to ensure success. 

There is a clear shortage of professionals in AI ethics and governance. In a recent survey, it was reported that 60% of public sector IT professionals cite a shortage of artificial intelligence skills as their top challenge to implementing AI. This figure is alarming, as companies may be implementing AI technology without the right people in place to manage ethical and regulatory concerns. 

Just some of the challenges organizations face in recruiting for these roles include a lack of qualified talent, the complexity of the systems they implement, and the need for specialized skill sets, which are in short supply. 

Strategic Approaches to Ethical Hiring in Tech Leadership

So, what are he next steps? Here are some tips. 

  • Develop comprehensive job descriptions emphasizing ethical and regulatory expertise.

  • Incorporate ethics and governance assessments into the hiring process.

  • Foster a culture that values and prioritizes ethical considerations in technology development..

Take Action Today

Today, those in tech leadership roles must prioritize ethics, regulation, and AI governance in their tech hiring practices.

Unsure where to begin?

The Trevi Group can help you develop the talent and recruitment strategies you need to fill critical positions. Learn more about our talent solutions and dive deeper into these resources:


The Trevi Group | “Executive Search for Technology Professionals” | www.TheTreviGroup.com

#thetrevigroup #recruitingtrends #informationtechnology #employmenttrends #jobmarket #hiringtrends

Hiring Your Next Executive? Why Tech Fluency Is Now a C-Suite Imperative

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Technology leadership is no longer about hiring an experienced Chief Technology Officer and letting them deal with all things digital.

Instead, evolving markets require tech-savvy executives in every C-suite position. Corporate innovation is only possible by balancing business acumen with an understanding of emerging technologies like artificial intelligence and machine learning, and their associated impacts on business strategy.

Read on to discover why organizational growth is dependent on digital literacy and embrace these tech-savvy executive search best practices.

The Rising Importance of Tech Fluency in C-Suite Executives

Executive competencies have always included aspects like leadership, honesty, transparency, courage, and innovation. Today, innovation comes in the form of digital advancement, from AI-powered customer service solutions to automated employee payroll tools. Tech fluency is the ability to understand these concepts and why they matter.

A recent study found that only a fifth of all executives were tech fluent. Slightly more CEOs met the benchmark for digital fluency at 23%.

These low fluency rates can be devastating to organizations large and small. Why? Research experts at Deloitte state that a tech-savvy board creates a “common language” between executives, managers, and technology professionals, opening up more tech-based opportunities for innovation and strategization.

Challenges of Tech Fluency in Executive Leadership

Growing demand for tech-fluent executives is outstripping the volume of qualified candidates. Leadership development can be one solution, as can working with an expert partner to hire directly from tech-focused talent pools.

Existing executives may be resistant to learning new tech skills, believing that others can take that responsibility or that it’s too difficult. Collaborative approaches to upskilling and highlighting the benefits of tech-first leadership, such as innovation, growth, and a competitive edge, can disrupt those objections.

Tech-Aware Hiring in the C-Suite

What tech-aware attributes should C-suite talent search experts look for in each type of executive?

  • CEO: Effective CEOS will have a clear digital vision, an understanding of AI strategy, and strive to foster a culture of innovation

  • CFO: Finance executives require relevant tech stack literacy and the ability to utilize technologies like automation for forecasting and budgeting

  • COO: Operational leaders need to understand workflow digitization, and in industries like manufacturing and engineering, may need to understand robotics and software connected to supply chain systems

  • CHRO: HR leaders should understand applicant tracking systems and other HR tools, be able to utilize workforce analytics, and be comfortable crafting hybrid working strategies

  • CMO: Modern marketing requires an understanding of AI-powered audience segmentation and targeting tools, knowledge on building martech (marketing technology) stacks, and the ability to utilize big data and business intelligence (BI) platforms

  • CIO/CTO: Chief information and technology officers are naturally tech fluent, and need to balance this with an understanding of business operational needs and people skills

Leadership development programs can help build your C-suite’s technical aptitudes, while strategic executive hiring initiatives ensure technological skills are a foundational requirement for your leadership team.

What Tech Fluency Actually Looks Like

Digital literacy isn’t just about knowing what AI means or how to use the company’s shared drive. Tech-savvy executives should understand the potential and limitations of the technologies they’re introducing. They should also have a grasp on the possible risks, such as the ethical concerns of bias in AI.

Ideally, your digitally minded C-suite team should have no problems communicating with your technical teams, such as IT support or DevOps.

Hiring Best Practices: How Executive Recruiters Assess Tech Fluency

So, how should recruiters assess tech fluency when hiring executives? They could employ interview questions such as:

  • Give us an example of when integrating a new technology impacted your previous team/business

  • Define tech terms such as AI, ML, analytics, and big data

  • Explain how business intelligence benefits your sales and marketing teams

Candidates who seem flustered when presented with technical terms may simply be unfamiliar with the concept. Consider explaining what the term means in brief and seeing if they immediately see the potential.

A tendency to brush off technical terminology as if it doesn’t matter, or insist that it’s the realm of the CTO/CIO could be major red flags. Tech-phobic executives won’t help your organization thrive in a digital-first landscape.

Tech-Savvy Executive Recruitment Support Via Talent Specialists

Executive recruitment is no longer about simply finding the best business leader. Digital transformation and continuous business growth require tech-focused leaders who keep their finger on the pulse of technological advancement.

Discover how to attract C-suite members who combine business and technology leadership. Connect with The Trevi Group to find out more.

The Trevi Group | “Executive Search for Technology Professionals” | www.TheTreviGroup.com

#thetrevigroup #recruitingtrends #informationtechnology #employmenttrends #jobmarket #hiringtrends #ITleadership #cio #cto

Vulnerability Management Reimagined: From Overwhelm to Operational Excellence

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The Hidden Struggle Behind Vulnerability Management

For many organizations, vulnerability management feels like an endless uphill battle. New threats appear daily, reports stack up, and security teams often find themselves drowning in alerts. Instead of driving progress, the process can become overwhelming—leaving IT and security leaders with more questions than answers. Where do we begin? Which risks matter most? How do we keep pace without burning out?

Shifting the Focus: From Volume to Value

The problem isn’t just the number of vulnerabilities—it’s the lack of prioritization. Not every patch, update, or warning carries the same weight. By reimagining vulnerability management as a value-driven process rather than a box-ticking exercise, organizations can shift focus from fixing “everything” to fixing what matters most. This means identifying vulnerabilities that pose the greatest business risk and addressing them first.

The Power of Smart Prioritization

Imagine walking into a room filled with hundreds of blinking alarms. The noise would be deafening, but not every alarm signals a crisis. Smart prioritization—through contextual risk assessment, asset criticality, and business impact—helps teams separate background noise from the real threats. This not only reduces overwhelm but empowers teams to act with confidence and clarity.

Automation: The Game-Changer

Manual tracking and remediation are no longer realistic. Automation brings order to the chaos. Modern vulnerability management platforms can scan, sort, and even initiate patching at speed and scale, freeing human teams to focus on high-level strategy. Automation doesn’t replace expertise—it amplifies it, ensuring teams can respond faster without sacrificing precision.

Building Collaboration Beyond IT

Vulnerability management is not just an IT issue; it’s an organizational challenge. True operational excellence happens when IT, security, and business leaders work together. Clear communication about risk, impact, and remediation timelines turns vulnerability management from a siloed headache into a shared responsibility that strengthens the entire business.

Measuring Progress, Not Just Activity

Too often, success is measured by the number of vulnerabilities “closed.” But the real measure of excellence lies in risk reduction, faster response times, and resilience against real-world threats. By redefining success metrics, organizations can ensure vulnerability management drives meaningful progress instead of busy work.

The Future: From Reactive to Proactive

The most effective organizations are those that evolve from firefighting to foresight. By embracing smarter tools, risk-driven prioritization, and collaborative culture, vulnerability management transforms from overwhelming chaos into a structured pathway toward operational excellence. The goal isn’t perfection—it’s progress, resilience, and the confidence to face whatever comes next.

Final Thought

Vulnerability management reimagined is about more than patching—it’s about empowering teams, protecting what matters, and creating a proactive security culture. When organizations move from overwhelm to operational excellence, they unlock not just stronger defenses but also greater peace of mind. Contact The Trevi Group if you need help find talent that can assist you with this challenge.

The Trevi Group | “Executive Search for Technology Professionals” | www.TheTreviGroup.com

#security #cybersecurity #thetrevigroup #recruitingtrends #informationtechnology #employmenttrends #jobmarket #hiringtrends