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A sharp increase in cyberattacks is putting organizations across industries on high alert. In a recent Computer Weekly article, Jason Pyle, Managing Director of Harvey Nash USA & Canada, highlights new data from the 2025 Harvey Nash/Nash Squared Digital Leadership Report that shows 29% of global tech leaders experienced a major cyberattack in the past two years, up from 23% in 2023 and the highest level since 2019. This rise comes amid a growing and evolving threat landscape, with organized cybercrime, state-sponsored activity, and insider risks all becoming more prominent. Attacks are also becoming more sophisticated, leveraging tools like AI-driven phishing and deepfake impersonation, making detection and prevention more complex than ever. In the article, Jason outlines several ways organisations need to rethink their approach in response to the rise in cybercrime - from strengthening internal cyber capabilities to outsourcing specialized support for areas such as threat detection and incident response. He also addresses the growing talent shortages in cybersecurity, highlighting alternative hiring models that can help bridge the gap efficiently. Cybersecurity is no longer a back-office concern, it’s a business-critical issue. 👉 Read the full article on Computer Weekly

  Brett McMickell, CTO of Kubota, joins David Savage on a new episode of Tech Talks to explore purpose-driven technology that addresses the labor shortage crisis in agriculture. This young workforce siphoning itself towards urban careers makes this labor shortage worse, leaving dwindling numbers rurally.  Traditional mechanization can’t solve this growing crisis since large investments aren’t practical for struggling farmers, and skilled operators are still needed to run heavy equipment. This is where Kubota’s purpose-driven solutions come into play, harnessing machine learning, IoT, and artificial intelligence. Harvey Nash can supply qualified IT talent suited for ag tech jobs to bring these innovative solutions to life, blending artificial intelligence and agriculture seamlessly. Global food security and farm sustainability are at a critical juncture today, with a labor shortage putting the agriculture industry at a unique crossroads. From the earliest civilizations, humankind has taught itself to tend the soil and coax nourishment from nature. But now, fewer workers are available to plant, leaving farmers scrambling to meet productivity needs. This immense pressure has been the catalyst for innovative, newer ways to integrate technology—and more specifically, artificial intelligence—into agriculture and farming practices. In a recent episode of Tech Talks, David Sage welcomes the CTO of Kubota, Brett McMickell, to share how Kubota is reimagining solutions through automation-based solutions. It’s crucial to understand their transformative approach to the labor crisis and the pivotal role of ag tech jobs as we navigate the future of technology-driven agriculture.   A Growing Labor Shortage in Agriculture Agriculture is an industry that’s already plagued by tight deadlines, unpredictable weather conditions, and fluctuating market demands. Add to this mix a rapidly shrinking workforce, and it’s a whole new problem. But this labor gap is more than just a short-term inconvenience for farmers.  Young workers are becoming a rare sight on farms, with the average age of farmers rising as the youth head towards the metaphorical neon glow of urban careers. To compound losses, the manufacturing and service industries claim what little of the rural population remains. While reliable labor is scant, the larger battle of maintaining efficiency can only be won through the integration of artificial intelligence and agriculture.   Moving Past Traditional Mechanization While larger tractors and harvesters were a step forward for traditional agricultural societies, this isn’t a realistic solution for farmers who can’t make significant investments. At the end of the day, even a tractor needs a skilled operator. It’s not enough to simply scale up our existing tools, and Kubota recognized this. This is why they created smarter solutions that reduce our dependency on human labor by leveraging advanced technologies like machine learning, the Internet of Things (IoT), and artificial intelligence for agriculture.   Purpose-Built Technology: The Kubota Revolution   Kubota’s approach to technology solutions works because they avoid “bolting on” technology as an afterthought. Brett McMickell emphasizes how Kubota designs purpose-built solutions that are uniquely tailored to challenges in the sector. It starts with a deep understanding of farmers’ needs and how ag tech jobs can fill that gap. Only then can a successful blend of agriculture and artificial intelligence create effective technology that aligns with the end user’s reality. Kubota’s Autonomous Tractors: Reducing Human Oversight Use soil data to adjust planting patterns Optimize fuel efficiency Sensors and machine-learning algorithms make real-time decisions AI-Powered Crop Monitoring Analyze data from drones and IoT devices Deliver actionable insights on irrigation and fertilization schedules Innovations like these address the labor shortage by automating repetitive tasks. But they also enhance precision, which can have a lower environmental impact and improve yields. Something as rudimentary as spraying chemicals efficiently, when handed off to AI and precision tools, has resulted in a 20-40% reduction of chemical use.    The Critical Role of IT Expertise If Kubota’s mission for transforming agriculture is the doorway to a successful integration of agriculture and artificial intelligence, then IT expertise is the keystone holding it all together. A diverse set of tech talent is essential to run any innovative program successfully. Think of this as a Swiss knife of IT specialists, where everyone, from data scientists and software engineers to cybersecurity experts, has a role to play.   Recruiting IT Talent—Harvey Nash Can Help Harvey Nash plays a critical role in connecting companies like Kubota to tech talent. We understand the growing need for IT professionals specializing in artificial intelligence and agriculture. But understanding constraints is equally valuable; limited connectivity in rural areas and the need for weather-resistant hardware are just the tip of the iceberg.  We can support the industry’s shift towards smarter and sustainable practices by fostering a pipeline of skilled technologists for ag tech jobs who can marry artificial intelligence and agriculture. As McMickell succinctly puts it, “People need to eat”, and AgriTech can feed our future. Get Started

  Hybrid work is a flexible solution to maximize productivity and balance home life with work. But is it the most effective work model for tech talent? Insights from the Digital Leadership Report hint at many advantages, albeit not without some challenges. The hybrid model offers flexibility, reduces commute times, and can boost productivity for developers who get to work without distractions. Tech companies with hybrid models also hire more women and can reach beyond major tech hubs to access a bigger talent pool, remotely. But working hybridly can also create a work-life imbalance and affect chances of promotions. Tech professionals might struggle with mental wellness and be unable to collaborate effectively over remote networking tools. How tech companies address these challenges will affect the adoption of the hybrid setup across technology jobs in the future. The hybrid workplace model has been hailed as the future of work, blending remote and in-office setups to create a unique solution, particularly in the tech industry. It promises flexibility, work-life balance, and access to global talent unfettered by time and space constraints—what’s not to love? On the surface, hybrid work seems to check all the boxes, and this has tech companies embracing it left, right, and center.  But is it really that effective for tech professionals? We draw on insights from our Digital Leadership Report to examine the realities of a hybrid workplace in the tech sector and break down the benefits and challenges that come with adopting the hybrid model for tech jobs.   Hybrid Workplace Models: Structured Freedom The promise of hybrid models lies in the flexibility they offer. Although six in ten companies mandate at least one day in the office, this simply creates a modicum of structure and gives tech professionals the chance to collaborate in person while still retaining the autonomy to work remotely for the most part. Benefits of Hybrid Models for Technology Jobs No distractions: For tech professionals, working remotely means the freedom and space to code, design, and debug without distractions, in an environment of their choosing.  Eliminating commutes: A hybrid workplace model allows developers and engineers to avoid long commutes and channel their energy into more productive workflows at home, in a coworking space, or at their favorite coffee shop.  Improved diversity: According to the Digital Leadership Report, remote work has enhanced diversity for organizations. Those that limit office time to a few days a week showed 27% more female hires than other companies with typical 5-day mandates. Bigger talent pools: Hybrid models mean that companies aren’t limited by geographical bounds. This lets them tap into talent pools beyond major tech hubs, easily filling roles and getting past skill shortages. Find Hybrid and Remote Tech Jobs   Challenges of Hybrid Workplace Models   Despite its rosy benefits, the hybrid model comes with its fair share of pitfalls. Reduced collaboration: Collaboration is the cornerstone of innovation, but even more so in technology jobs. Hybrid setups may cause asynchronous communication among developers, causing delays or ineffectively communicated expectations. Lack of cross-functional dialogue: The spontaneous flavor of brainstorming in person can’t fully be replicated over video calls and chat tools.  Mental wellness challenges: Hybrid models can cause a dip in team collaboration and inclusivity with mental wellness challenges, as highlighted in the Nash Squared report. Leadership inequity: Many companies are worried that in-office workers might be given preference for promotions simply because they’re more visible to leadership. This makes it essential to develop thorough employee recognition strategies. Burnout: Working through tools like Zoom and Teams might lead to “always-on” expectations, which blur the lines between work and home for tech workers.   The Future of Hybrid Workplace Models in Tech The success of a hybrid setup for technology jobs depends on how tech companies handle the challenges of this model. A few prerequisites can make this a sustainable model: Investing in robust collaboration tools Clear protocols for communication Equitable career advancement opportunities Investment in employee wellness and mental health programmes Mandates driven by employee needs rather than policy Sadly, many tech companies lack this kind of strategic approach to hybrid work models, as revealed by the Nash Squared & Harvey Nash Digital Leadership Report. The hybrid workplace model is far from a one-size-fits-all setup, and it needs to be adapted and optimized to serve your organization and its people. Support the growth of your business

AI coding tools have reshaped the tech industry. Developers are leveraging AI tools for enhanced productivity, smoother workflow, and accelerated development cycles. This has led to a shift in the in-demand skills among developers, with a focus on problem solving and ethical use. Tech talent can stay ahead of the curve by treating AI as a partner and not a threat.  This means upskilling, joining AI developer communities, and actively showcasing their work. Employers need to encourage AI collaboration and train employees.   Gone are the days when artificial intelligence was just a fictitious entity in high-action thriller movies or an obscure fixture of the future in sci-fi flicks. Today, AI has permeated nearly every strata of our lives and is reshaping our interactions with not just the internet, but softwares as well.  This has left tech developers scrambling to leverage AI capabilities to gain an edge. Here’s everything you need to know about the application of AI in assisted software development and how it’s reshaping the tech market for IT professionals and tech leaders who are striving to get their workforce AI-ready. How AI Tools Are Transforming Coding Practices With AI tools like Claude and Copilot revolutionizing workflows, it’s led AI to become a collaborator in application development. While this has directly accelerated development cycles for businesses and software engineers, there are a few key ways these tools are changing key practices. Code Autocompletion & Generation Developers are relying on AI tools for assistance in writing boilerplate code, functions, and even entire modules, redefining the limits of AI assisted software development. Bug Detection & Optimization Since AI can review code, it’s often harnessed to suggest fixes and optimize performance of programs (like SonarQube AI plugins or DeepCode). Collaboration & Documentation Developers are using tools like ChatGPT to produce clear documentation or break down complex code logic in simpler terms. Natural Language to Code New developers can now even describe what they want their program to do in plain English, while AI tools turn these instructions into functional code. These transformations in application development using AI have meant lower barriers for new developers and a significant reduction in repetitive tasks. But over-reliance on these tools is a major concern due to the inconsistency of code quality. It’s crucial not to take AI-generated solutions at face value without human oversight. In-Demand Skills in an AI-Enhanced Development World This involvement of AI in application development has caused a shift in the demand for skills. AI-Augmented Programming Rather than fearing AI, developers need to learn how to work with it and harness it for better software development. Problem Solving When routine tasks are handed off to AI tools, humans are left free to think about logic, design thinking, and architecture. Basic Knowledge of AI/ML Concepts Even non-AI developers are required to understand the basics of how AI tools work. Ethical AI Use Tech talent is expected to exercise responsible use of AI tools. Fairness, security, and accountability are major concerns when using AI-generated code. How Tech Talent Can Prepare   Curiosity is Rewarding Keep experimenting with different tools to code small projects or troubleshoot bugs.  Continuous Upskilling As tools and tech hiring trends evolve, so should IT professionals. Take micro-courses on AI in software and application development. Portfolio Building If you’ve worked on projects with AI assisted software development, showcase your experience through a digital portfolio. Get Active in the Community Joining AI developer communities is a great way to learn from your peers and keep abreast of industry trends.  How Employers Can Leverage AI to Stay Competitive This new era of collaborative coding means tech employers need to adapt to stay competitive.  Streamlining Development Cycles: By adopting AI coding assistants, product delivery can be accelerated. Reskilling Teams: Bolster tech talent with internal training on AI in application development. Rethink Hiring Criteria: Work with a direct hire staffing agency to recruit candidates with AI literacy, critical thinking, and adaptability. Integration of AI into DevOps: Use AI for CI/CD optimization, predictive analytics, and automated testing. Encouragement of AI-Enhanced Collaboration: Create a space where developers can rely on AI for better communication of ideas, documentation, and cleaner code. The future of AI in application development is efficient, smart, and collaborative. And harnessing this potential of AI is crucial for developers hoping to stay ahead of the curve. Trust Harvey Nash for industry expertise and candidate sourcing. Get Tech Insights