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This session aims to examine the impact of Generative AI on MSPs/MSSPs attempts to protect their clients. By offering a technical preview and discussing governance considerations, we'll navigate the complexities and opportunities of integrating AI into your security strategies for more robust protection.

Register for the event here: https://connect.comptia.org/events/view/comptia-anz-and-asean-committee-call---april

We're super lucky to have a couple of great presenters for you.

Kareem Tawansi, CEO of Solentive, is a director of 5 companies, a member of the executive council for CompTIA, and a graduate of the Australian Institute of Company Directors (GAICD). With a degree in Computer Science and Psychology and over 35 years of experience in the Digital/IT industry, Kareem is focused on where psychology & technology meet and is an expert in digital governance.

Ben Verschaeren, Director of Sales Engineering – Sophos. Ben is driven by a passion for innovation and technology. Based in Melbourne, Ben manages two teams – an inside presales team focused on global requests for proposals and a software development team building tools for internal and external use, with a recent focus on artificial intelligence and Large Language Models (LLMs).

In addition, Ben is responsible for researching the threat landscape and educating the Sophos team, customers and partners on the latest cybersecurity threats. This includes building demonstration and training tools, focusing on real-world exploits and malware. He often presents on behalf of Sophos at many events both in APJ and beyond including DEF CON and BlackHat in the USA.

The technology sector has long been at the forefront of innovation, driving changes that shape our world. However, when it comes to gender equality and pay equity, the tech industry, like many others, still has a long way to go. A recent 2024 report by Dice, a technology career website, sheds light on the current gender pay gap in tech, revealing both progress and persistent challenges.

The Current State of the Gender Pay Gap in Tech​

According to the report, women in tech earn, on average, about $15,000 less annually than their male counterparts, translating to approximately 87 cents on the dollar compared to men's earnings. This gap is narrower than the general population, where women earn about 78 cents on the dollar. While this indicates progress within the tech sector, the gap remains significant.

The report, which analyzed data from two separate surveys, also highlighted that 48% of women reported facing gender discrimination in the workplace, a stark contrast to the 15% of men who reported the same. This discrimination, however, does not fully explain the salary gap. Other contributing factors include:

• A lower percentage of women employed full-time in tech (80% of women vs. 86% of men)
• Fewer women in their current role for more than five years (22% of women vs. 31% of men)
• A smaller proportion of women with more than five years of experience in the tech field (66% of women vs. 80% of men)

Work-Life Balance and Compensation Satisfaction​

Interestingly, the research found that women in tech value their work but maintain a more balanced outlook on how work fits into their lives. This perspective has been supported by companies offering flexible work schedules, maternity/paternity leave, wellness programs, and childcare options. Despite these positives, there remains a slight difference in the percentage of women receiving raises and bonuses compared to men, contributing to 39% of women reporting dissatisfaction with their pay.

This dissatisfaction appears to be a driving factor for women in tech considering a change of employer, with 67% of women respondents indicating they are likely to change employers in the next year, compared to 57% of men.

Looking Forward​

The report's findings underscore the importance of continued efforts to bridge the gender pay gap in tech. While progress has been made, much work is still to ensure that women in tech are compensated fairly and equitably.

We invite you to join the discussion on this critical issue. What steps can further narrow the gender pay gap in tech? How can companies support women in tech more effectively? Share your thoughts, experiences, and suggestions in the comments below.

The journey toward gender pay equity in tech is ongoing, and it's a journey that requires the collective effort of individuals and organizations alike. Let's work together to create a more equitable and inclusive tech industry for everyone.

Read the article: https://www.bizjournals.com/bizwome...-what-your-job-is-worth-and-whe.html?page=all

The Internet of Things (IoT) era is not just upon us; it's evolving, maturing, and, more importantly, reshaping the future of our urban environments. As we stand on the brink of a new era, it's fascinating to see how technologies like Artificial Intelligence (AI) and IoT are spearheading the transformation of our cities into smarter, more efficient, and sustainable habitats.

The High-Tech Makeover of Urban Landscapes​

Our cities are transforming significantly, becoming smarter and more efficient thanks to regular technological innovations such as AI and IoT. These advancements are not just about enhancing the aesthetic appeal of urban landscapes but are fundamentally changing how cities operate and serve their inhabitants.

Connecting the Dots with IoT​

At its core, IoT is about connecting devices and sensors via the internet, enabling them to collect and share data in real-time. Imagine traffic lights, garbage cans, water pipes, and street lamps all interconnected, communicating with each other, and making decisions based on real-time data. This interconnectedness is revolutionizing urban management and operations, making cities more livable and responsive to the needs of their residents.

The Promise of Scalability and Adaptability​

One of the most compelling aspects of IoT in the context of smart cities is its scalability and adaptability. As cities grow and evolve, so too can their IoT infrastructure. This flexibility allows for the integration of new technologies and the ability to meet the ever-changing requirements of a dynamic urban population. The focus is not just on creating smart cities but on ensuring that these cities can continue to adapt and thrive in the face of future challenges and opportunities.

A Sustainable Future​

The adoption of IoT in urban development is not just about making cities smarter; it's also about making them more sustainable. By optimizing resource use and improving efficiency, IoT technologies can help reduce the environmental impact of urban living, paving the way for a more sustainable future.

Join the Discussion​

As we witness the transformative power of IoT in shaping our urban environments, it's clear that we are on the cusp of a new era in urban living. But what does this mean for us as individuals and communities? How can we ensure that the development of smart cities remains inclusive and beneficial for all?

We invite you to join the discussion and share your thoughts on the future of urban living in the age of IoT. How do you envision the role of technology in shaping our cities? What challenges and opportunities do you see on the horizon?

The future of our urban landscapes is being written now, and it's a story that we all have a part in shaping. Let's explore the possibilities together.

Read the article: https://www.techiexpert.com/how-iot-is-shaping-the-future-of-urban-living/

In the rapidly evolving business landscape, predictive artificial intelligence (AI) and machine learning (ML) stand out as transformative technologies capable of driving significant growth. However, the journey to successfully implementing these technologies is fraught with challenges, as many organizations struggle to realize their full potential. Drawing on insights from Eric Siegel's "The AI Playbook," this post outlines a strategic approach to deploying predictive AI and ML with minimal risk and maximum value.

A Six-Step Guide to Successful AI and ML Deployment:

1. Quantify a Positive Business Value Proposition: Begin by clearly defining the business improvements you aim to achieve, such as enhancing revenue through better ad response rates. Focus on the business outcomes rather than the technology to secure deployment approval.
2. Establish a Machine Learning Prediction Goal: Collaborate closely with both business leaders and technologists to define what your deployment will predict and how you will act on these predictions. This step is crucial for aligning business objectives with technical capabilities.
3. Define Specific Model Evaluation Metrics: Determine how you will measure the accuracy of your model's predictions. Consider the cost of correct predictions, the impact of false positives or negatives, and the model's learning potential over time.
4. Prepare the Data Sources for Learning: Quality data is the foundation of effective machine learning. Ensure your data includes positive and negative cases and any relevant supporting elements to facilitate comprehensive model training.
5. Generate and Train the Predictive Model: Develop your predictive model using suitable algorithms, such as decision trees or regression analysis. The training phase is critical for refining the model's ability to make accurate predictions.
6. Deploy and Evaluate the Machine Learning Model: Introduce the model to your operations, ensuring team buy-in at every level. Use a control group to assess the model's performance, make necessary adjustments, and mitigate risks.

Conclusion:

Implementing predictive AI and ML in your business requires careful planning, collaboration, and ongoing evaluation. By following the six steps outlined above, organizations can navigate the complexities of deployment and harness the power of these technologies to drive growth and innovation. Remember, the journey doesn't end with deployment; continuous maintenance, monitoring, and ethical considerations are essential for sustaining success in the long term.

Discussion Points:

• Have you encountered challenges in deploying predictive AI and ML in your organization? How did you overcome them?
• What strategies have you found effective for aligning business objectives with technical capabilities in AI and ML projects?
• How do you ensure the ethical use of AI and ML in your business practices?

Share your experiences and insights on deploying predictive AI and ML in the comments below. Let's learn from each other and navigate the path to successful implementation together.

Read the article: https://www.forbes.com/sites/martin...on-ai-in-your-business-today/?sh=1d819f257ff7

In the ever-evolving landscape of technology and finance, blockchain technology emerges as a formidable disruptor, reshaping industries and setting the stage for a revolutionary approach to global economic practices. With Bitcoin's resurgence and record-breaking price rallies, the spotlight on blockchain and its potential has never been brighter. Beyond the buzz of cryptocurrencies, the real game-changer lies in blockchain's capacity to revolutionize digital transformation across supply chain and vendor management sectors.

The Economic Impact of Blockchain: A Forecast of Growth

The trajectory of blockchain technology is on an unprecedented rise. According to a report by Fortune Business Insights, the blockchain landscape is poised to expand from $17.57 billion in 2023 to a staggering $469.49 billion by 2030. This represents a compound annual growth rate (CAGR) of 59.9%, signaling a seismic shift in how businesses operate and collaborate. The implications of this growth extend far beyond the confines of finance, promising to redefine inter-organizational collaborations and supply chain efficiencies on a global scale.

Reaping the Rewards of Blockchain-Backed Trust

At the core of blockchain's appeal is its ability to foster trust and transparency between trading partners. This technology offers a robust framework for resolving supply chain issues swiftly and forging stronger relationships among industry stakeholders. The consensus mechanisms inherent in blockchain ensure that any changes within the network are verified collectively, enhancing the immutability and transparency of transactions.

Smart Contracts: The Backbone of Blockchain Trust

Smart contracts, self-executing programs that automate contractual obligations, stand at the forefront of blockchain's transformative power. These contracts provide a transparent and irreversible record of agreements, ensuring compliance and uniformity across the board. Sunil Thomas, president and COO at TraceOne, highlights the practical applications of smart contracts in maintaining product specifications and managing quality control.

Blockchain in Action: Revolutionizing the Food Industry

One of the most compelling use cases for blockchain technology is in the food industry, where smart contracts serve as vital tools for quality control and waste management. The ability to trace food back to its source within seconds, rather than days, offers a significant advantage in addressing contamination issues and mitigating the impact of faulty products. This level of traceability empowers businesses and their supply chain partners to swiftly identify and recall compromised products, safeguarding public health and minimizing economic repercussions.

Conclusion:

As blockchain technology continues to evolve and expand its influence beyond the realm of cryptocurrencies, its potential to transform supply chain and vendor management becomes increasingly evident. The promise of enhanced trust, transparency, and efficiency presents a compelling case for businesses to embrace this technological revolution. With blockchain, the future of global trade and collaboration looks brighter than ever, offering a competitive edge to those ready to navigate this new frontier.

Discussion Points:

• How can businesses across different industries leverage blockchain technology to improve their supply chain and vendor management practices?
• What challenges might organizations face in integrating blockchain into their existing systems, and how can they overcome these obstacles?
• Share examples or experiences of blockchain technology making a tangible impact in supply chain management or vendor relations.

Join the conversation and share your insights on the transformative potential of blockchain technology in reshaping supply chain and vendor management.

Read the article: https://www.nasdaq.com/articles/why...-future-of-supply-chain-and-vendor-management

The key concepts covered in Module 2 of the Threat Management and Cybersecurity Resources:

1. Penetration Testing (Pen Test):
   • A penetration test (or pen test) is a security assessment technique where ethical hackers simulate attacks on a system or network to identify vulnerabilities. The goal is to uncover weaknesses before malicious actors exploit them.
   • Rules of Engagement: These define the scope, boundaries, and constraints of the pen test. They specify what can and cannot be tested, ensuring that the assessment remains controlled and safe.
   • Performing a Pen Test: During a pen test, security professionals use various tools and methodologies to probe for vulnerabilities. They attempt to exploit weaknesses, gain unauthorized access, and assess the system’s resilience.
2. Vulnerability Scanning:
   • Vulnerability scanning involves automated tools that scan networks, systems, and applications for known vulnerabilities. These tools identify security flaws such as outdated software, misconfigurations, or missing patches.
   • Regular vulnerability scans help organizations stay proactive by addressing vulnerabilities promptly.
3. Cybersecurity Resources:
   • Organizations have access to a variety of cybersecurity resources:
     • Bug Bounties: Monetary rewards given for uncovering software vulnerabilities. Crowdsourcing is often used for bug bounties, involving people from the internet in the testing process.
     • Adversary Tactics, Techniques, and Procedures (TTP) Database**: This resource catalogs threat actors’ behavior, attack patterns, and management strategies.
     • Exploit Acquisition Platforms: Examples include Zerodium, which acquires zero-day vulnerabilities and sells them to government organizations for defensive purposes.
     • Security Information and Event Management (SIEM): SIEM tools collect and analyze security event data to detect and respond to threats.
     • Incident Response Playbooks: These provide step-by-step instructions for handling security incidents.
     • Security Awareness Training: Educating employees about security best practices is crucial.