Categoria: Management

Chase, please tell us about your background and what brought you to your role as Principal Strategist at JumpCloud.

I’ve spent over a decade in the tech industry, in cloud computing and cybersecurity. Over that time, I’ve been able to indulge my passion for all things identity-related and JumpCloud has been a perfect fit.  JumpCloud’s mission to simplify and secure IT management for businesses of all sizes— especially for the traditionally overlooked small and medium-sized enterprises (SMEs)—is unique, and I’d argue we’re uniquely good at it. My role is to help shape our product vision to ensure we’re meeting the evolving needs of our customers in an increasingly complex IT landscape.

How is AI currently impacting cybersecurity for small and medium-sized enterprises (SMEs)?

JumpCloud conducts a twice-yearly survey of IT admins (our most recent edition of the survey just came out in July), so we’ve been able to get a real-time pulse on how SMEs are adapting to AI.

The first time we asked about AI six months ago, there was a lot of excitement but also a lot of fear. What we’re seeing now is that while the optimism has faded a little, it’s still pretty strong. Most organizations – 67% –  have plans to implement AI initiatives and about the same number of folks have actually developed an AI policy–  a great first step toward a robust, intentional approach to AI in the workplace.

As to how AI is impacting cybersecurity for SMEs, it’s both positive and negative. On the positive side, AI-powered tools are enhancing threat detection and response capabilities, allowing SMEs to identify and mitigate potential security risks much more quickly and accurately than before. This is particularly beneficial for SMEs that lack the resources for large security teams. However, AI is also being used by bad actors in more sophisticated attacks. We’re seeing an increase in AI-generated phishing emails and adaptive malware that can evade traditional security measures. This duality around AI won’t be going away anytime soon, so SMEs need to embrace AI while developing protections against it.

Based on your recent survey, what best practices would you recommend for SMEs to enhance their cybersecurity in light of AI developments?

First and foremost, implementing strong identity and access management is crucial. This includes using multi-factor authentication (MFA) and adopting a least-privilege access model. We also found that employee training is more important than ever, given the increasing sophistication of AI-powered phishing attempts. SMEs are also responding by partnering with managed service providers (MSPs) to access expertise and capabilities that might otherwise be out of reach.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-chase-doelling/

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In 2024, the cybersecurity realm has opened new doors to new vulnerabilities and attack techniques. As attacks become more sophisticated and dynamic, traditional defense mechanisms fail to provide protection. Therefore, to effectively combat these challenges, CISOs and IT leaders need to analyze the current situation and mitigate threats in real-time.

As we look ahead to 2025, likely, the concerns faced by CISOs and IT leaders in 2024 will potentially worsen.

However, for a handy deep dive into tackling cyber attackers, this roundup of AITech Park articles on the cybersecurity topic offers guidance in creating good cyber awareness strategies, insights, and recommendations that will aid in embedding privacy compliance into your culture.

The Rise of Cybersecurity Careers

As cyberattacks become increasingly sophisticated, organizations are prioritizing the hiring of certified cybersecurity professionals to enhance their security measures. Therefore, to excel in this ever-evolving competitive field, it is crucial to pursue the right certification courses. In 2024, the top popular cybersecurity certifications include CompTIA Security+, OSCP, CISA, CISSP, and CISM. Each certification course offers valuable skills and knowledge catering to numerous roles within cybersecurity.

Understanding the Third-Party Risk Management Strategies

In this new-age world, third-party risk management strategies have become quite essential in this modern interconnected business environment. As businesses no longer rely solely on an organization’s security, CISOs require external connections to manage security strategies. Therefore, implementing robust third-party cyber risk management so you can continuously focus on due diligence, monitoring, deception, and incident response plans can help limit your exposure and defend against growing threats.

Preparing for Data Center Security Threats in 2024

Most organizations have data centers that are rich in critical information, and for cybercriminals, this center is the prime target. Therefore, IT leaders must prioritize building the defenses around to eliminate the increasing ransomware and cyberattacks. This also implies that hardware-based root-of-trust (RoT) systems should be combined with AI technologies that will ultimately enhance zero-trust practices beyond current capabilities.

The need of the hour is a comprehensive cybersecurity strategy that will secure the organization’s digital assets and reduce the risk of loss, theft, or destruction of company data or systems. Hence, by reading the recommended articles, you can create a robust strategy that will protect your brand from reputational harm and create a safe environment for employees, stakeholders, and the organization.

To Know More, Read Full Article @ https://ai-techpark.com/top-cybersecurity-articles-in-2024/

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Picture a world where your professional services business operates like a well-oiled machine, effortlessly balancing resources, predicting project outcomes, and communicating with precision. This isn’t a far-off dream—it’s the reality that Artificial Intelligence (AI) is bringing to the professional services industry right now. As the lines between human expertise and technological capabilities blur, AI is emerging as the secret weapon for firms looking to surge ahead in a fiercely competitive market.

By leveraging AI-powered Professional Services Automation (PSA) software, firms can optimize resource allocation, enhance governance, and streamline communication processes. Let’s explore how AI can revolutionize three key areas of professional services operations.

Intelligent Resource Management

One of the most significant challenges faced by professional services firms is effective resource management. AI-powered solutions can provide unprecedented insights and automation in this critical area:

Optimizing Team Utilization

AI algorithms can analyze historical project data, current workloads, and upcoming commitments to balance the workload across team members. This ensures that no individual is overworked while maximizing overall team productivity. By continuously monitoring utilization rates, AI can alert managers when team members are approaching burnout or when there’s capacity for additional projects.

Forecasting and Capacity Planning

Predictive AI models can forecast resource requirements for upcoming projects based on past performance data and project characteristics. This allows firms to anticipate staffing needs, plan for hiring or training, and make informed decisions about taking on new projects. AI can also help identify potential resource conflicts well in advance, giving managers time to reallocate resources or adjust timelines.

Skill Matching and Project Staffing

AI can analyze the skill sets of available resources and match them with the requirements of incoming projects. This ensures that the right people with the right expertise are assigned to each project, improving project outcomes and client satisfaction. Additionally, AI can identify skill gaps within the organization and suggest upskilling opportunities to prepare teams for future high-stakes projects.

Profitability Analysis and Pricing Optimization

By analyzing PSA tool data, AI can uncover patterns in project profitability across different types of engagements, clients, or project phases. This insight allows firms to identify which areas of their business are most profitable and which may be losing money. AI can then suggest optimal pricing strategies for different types of projects or clients, helping firms maintain a healthy balance between competitive pricing and profitability.

To Know More, Read Full Article @ https://ai-techpark.com/revolutionizing-professional-services-with-ai/

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In today’s fast-paced business landscape, data is not just an asset; it’s a cornerstone of strategic decision-making. For B2B companies, leveraging data effectively can create significant competitive advantages, enabling them to understand their customers better, streamline operations, and drive innovation. This article explores the importance of a robust data strategy and how businesses can harness data to outpace their competition.

The Value of a Strong Data Strategy in B2B

Why Data is the New Competitive Currency

As businesses increasingly rely on data to inform their decisions, it has become the new competitive currency. Companies that effectively harness data can unlock valuable insights that guide product development, enhance customer experiences, and optimize operational efficiency. For instance, consider how a leading B2B SaaS company used data analytics to analyze customer usage patterns, which led to the development of new features that directly addressed user needs, resulting in a significant boost in customer retention.

Aligning Data Strategy with Business Goals

A successful data strategy must align with the overarching business objectives. Organizations should ensure that their data initiatives are not just about collection but are focused on measurable outcomes. For example, a manufacturing company may set specific targets for reducing downtime by analyzing equipment performance data. By aligning data strategy with business goals, companies can demonstrate clear ROI and reinforce the value of data initiatives across the organization.

Key Components of a Robust Data Strategy

Data Collection and Management

Effective data collection is the foundation of any data strategy. B2B organizations must prioritize collecting relevant and high-quality data from diverse sources, such as customer interactions, market research, and internal processes. Additionally, centralized data storage solutions, such as data lakes or warehouses, can streamline data management and improve access across departments.

Implementing robust data governance is equally essential. Establishing clear policies on data usage, ownership, and security ensures that data remains accurate, reliable, and compliant with regulations. This not only enhances decision-making but also builds trust among stakeholders who rely on data for strategic insights.

In an era where data is a vital asset, developing a robust data strategy is crucial for B2B organizations seeking a competitive edge. By aligning data initiatives with business goals, implementing best practices, and leveraging advanced tools, companies can harness the power of data to drive growth, enhance customer experiences, and remain agile in a dynamic marketplace. Embracing a culture of data-driven decision-making will not only empower organizations to thrive but also position them as leaders in their industries.

To Know More, Read Full Article @ https://ai-techpark.com/data-strategy-competitive-advantage/

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Sebastian, can you start by sharing your background and what led you to your current role as VP of Engineering at Storyblok?

My journey in the tech industry began with a deep interest in software development and a passion for creating innovative solutions. Over the years, I have held various roles in engineering and management, which have provided me with a broad perspective on technology and its applications.

Before joining Storyblok, I worked with several startups and established companies, focusing on building scalable and secure software solutions. My experience in these diverse environments has been instrumental in shaping my approach to engineering and leadership. With Storyblok, I was drawn to the company’s vision of transforming content management and the opportunity to lead a talented team in driving this innovation forward.

In what ways can generative AI be utilized to create malicious content such as phishing emails and social engineering attacks?

Generative AI can produce highly realistic and personalized phishing emails by analyzing vast amounts of publicly available data about potential targets. This allows attackers to craft messages that are more likely to deceive recipients into divulging sensitive information. Similarly, AI can generate fake social media profiles or impersonate trusted contacts, enhancing the effectiveness of social engineering attacks. The ability to produce high-quality, contextually relevant content at scale means that these AI-generated threats can bypass many traditional security filters designed to catch generic phishing attempts.

The current cybersecurity measures seem adequate. What specific measures do you believe are most effective against AI-driven attacks?

While current cybersecurity measures provide a foundation, they need to be enhanced to effectively counter AI-driven attacks. Key measures include advanced threat detection where AI and machine learning are used to detect and respond to threats in real-time, behavioral analytics, which is the monitoring of user behavior to identify deviations that may indicate compromised accounts. Zero Trust Architecture is also important which involves implementing a model where verification is required for every access request, regardless of its origin.

Keeping staff informed about the latest threats and best practices to mitigate human error are also key measures in reducing the threat of AI-driven cyber attacks as is Multi-Factor Authentication (MFA) where an extra layer of security is added to verify user identities.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-sebastian-gierlinger/

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Chief Information Security Officers (CISOs) have some serious responsibilities on their shoulders as they single-handedly carry the security policies and enforcement, which are directly proportionate to an entire company’s success or downfall.

CISO’s insights and knowledge allow a company to balance out supporting its internal team while guarding the organization’s data and infrastructure.

However, in recent years, CISOs have witnessed shifts in the cybersecurity realm; especially with the technological advancements, cyberattacks such as phishing have increased by 58%, consisting of 90% data and 42% malware and ransomware attacks, affecting millions of users yearly (Cisco).

Even with the latest security protocols and software, it is only possible to fully protect against cyber threats with proper security awareness and strategies.

Therefore, to protect your company from an avoidable phishing attempt, AITech Park brings you a comprehensive guide on the different types of phishing attacks and how CISOs and their internal teams can handle them.

For a better understanding, let’s dive into the different types of new-age phishing attacks:

Email Phishing

Email phishing is the oldest and most common form of phishing, where scammers send spam emails to as many people as possible, hoping that a fraction of the targets fall for the attack. As per a recent study by Deloitte, it was witnessed that 91% of cyberattacks begin with email phishing and 32% of successful breaches involve the use of phishing techniques.

Cyberattackers often impersonate any well-known or legitimate brands and target their victim through those brands.

How to Spot Spam Emails?

Scammers often write email subject lines that are more appealing with strong emotions or create a sense of urgency. The body of the email instructs the recipient to take reasonable actions that deal with sensitive information or downloading malware. For instance, a phishing link might read, “Click here to update your profile.” When the victim clicks that malicious link, it takes them to a fake website that embezzles their login credentials.

Deepfake Scams

With rapid development in AI technology, deepfake has become more accessible to users. In recent research by Egress, 63% of cybersecurity personnel surveyed were worried about the cyber attacks introduced by deepfakes. To battle these types of attacks, CISOs can use deepfake detection tools that are available on the internet. These tools can point out synthetic images generated by AI and ML technologies, leaving unique traces that are invisible to the human eye. For instance, in recent years there have been modified videos of popular dignitaries that are common on social media platforms; these videos can be with a fun intention or sometimes defaming them through manipulated speeches or actions.

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How AI avatars are transforming customer service in business

What hasn’t AI transformed? Many business fields have evolved in recent years thanks to the tools that Artificial Intelligence has provided, one of them is customer service, through the use of AI avatars.

This is a new way in which companies are interacting with their public, trying to be more efficient and sophisticated in their processes. AI avatars are a very interesting figure in this transformation of customer service, as they have allowed companies to interact with their customers in a more personalized and efficient way than ever.

These virtual assistants are equipped with natural language processing and machine learning technology, which has redefined the customer experience by providing faster responses, solving problems more accurately, and even anticipating potential customer needs.

In this article we will delve deeper into the topic of AI avatars, how they are changing the rules of the game in customer service and what they bring to today’s modern companies.

Let’s start with the basics: What is an AI avatar?

When we talk about an AI avatar, we refer to the virtual, dynamic and animated representation of a person through Artificial Intelligence to interact with users in an automated and personalized way.

These avatars have the ability to simulate a human conversation, answer questions, provide assistance and solve problems, without the need for direct human intervention.

The digital avatar market is growing considerably

Everything indicates that the strategy of digital avatars is not a passing fad but is here to stay and grow constantly. According to a report by Spherical Insights, the global digital avatar market size is expected to reach $283.47 billion by 2032, a clear sign that businesses are increasingly investing in this tool.

“Technological advances in 3D modeling, animation and rendering result in increasingly realistic and visually appealing digital humans. Conversations become more attractive and closer because these avatars can look very similar to humans,” they noted in another report from the Market Research Future portal.

In this report they also indicate that the main market that uses AI avatars is North America, driven by the launch of new products and expansions of others, which has increased the need for this virtual assistance. Likewise, the Asia-Pacific region is the fastest growing region in terms of AI avatars, which is very promising for the immediate future.

To Know More, Read Full Article @ https://ai-techpark.com/transforming-customer-service-with-ai-avatars/

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There is growing concern over deepfakes, which are videos and audios that are highly realistic yet fake across various industries, but perhaps more pertinent in the B2B context. These synthetic media can mislead society and create negative impacts on reputation and financial aspects. However, it is evident that social media platforms have an essential role in addressing the fake problem and enhancing the credibility of online interactions as enterprises operate in this challenging environment. This article looks at the rise of deep fakes and also explores how popular social media companies are responding to this problem.

Understanding Deepfakes

Deepfakes are a form of synthetic media that apply artificial intelligence and machine learning to generate hyper-realistic fake audiovisual data. This technology relies on neural networks, and particularly on generative adversarial networks (GANs), to create realistic modifications of existing media.

The first step involves the accumulation of massive data sets that include images, videos, and even voice clips of the targeted person. These datasets enable AI to capture the details of the person’s gestures, voice, and even their tone. For example, GANs are composed of two neural networks, including a generator and a discriminator. The generator thus generates fake content, and the discriminator compares it with real media. This process is carried out in a cycle where the generator generates outputs until the results are as real as the original content being emulated.

Deepfakes can accommodate a range of manipulations based on simple swaps of facial images in videos to advanced ways of forgery where a person looks and acts like doing something they never did. It can also be applied where someone’s voice is changed to say sentences he has never said. This level of realism presents some problems in differentiating between real media and fakes, which could perpetuate skepticism and distrust of digital media.

Social media platforms are at the forefront of the fight against deepfakes, serving as essential gatekeepers to maintain the integrity of online communication. As the sophistication of deepfake technology rapidly evolves, these platforms face the growing challenge of detecting and mitigating manipulated content before it spreads. Their role is critical, not just in protecting users from deception but also in preserving trust across digital spaces where businesses interact with clients, stakeholders, and the public.

For companies, the stakes are equally high. Deepfakes can significantly damage brand reputation and sow confusion, eroding the trust that is central to B2B relationships. Businesses must be vigilant, ensuring they remain informed about the latest developments in deepfake technology and taking proactive steps to defend against its potential harms. By adopting a strategy that includes close collaboration with social media platforms, regular updates to security protocols, and internal training on identifying manipulated content, companies can safeguard their reputation and maintain the trust of their audience.

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Paige, kindly let our readers know how Seismic perceives the role of AI in evolving customer experiences and go-to-market (GTM) processes based on recent data.

At Seismic, we believe enablement is a mission-critical function that turns strategy into reality, and generative AI is creating an industry-defining moment for GTM and enablement teams. It is changing everything about the sales process, from prospecting to meeting preparation, content and presentation development, follow-up, training and performance tracking.

In fact, an overwhelming majority (93%) of enablement tech users acknowledge AI as the driving force behind their future investments. Based on this data, it’s evident that organizations neglecting to integrate AI into their GTM processes risk lagging behind and losing competitiveness in today’s industry, a sentiment echoed by 73% of respondents in our research.

What’s more: our customers know this to be true. In a Seismic customer survey, 65% of respondents cited AI as a primary reason for increased enablement investment. Specifically, they view Sales Content Generation & Optimization as the most valuable use cases to explore and implement for their teams. Over half (52%) are currently using or evaluating AI-powered tools within sales enablement processes, with 61% sharing that they are familiar with these tools to varying degrees.

Your report suggests a significant impact on both internal processes and customer experiences for businesses leveraging AI. How does Seismic observe this impact in terms of tangible ROI and enhanced customer engagement?

In addition to the clear revenue growth teams have witnessed, GTM leaders predict an average of 23% of that growth will be directly attributed to AI utilization over the next five years. In fact, 63% believe that AI is the primary force behind evolving customer experiences today. AI solutions are poised to touch nearly every corner of customer engagement.

For context, GTM leaders in the United States are leveraging AI-powered enablement tools for three primary functions: 53% utilize them for content analytics, 50% for content distribution, and 48% for learning and coaching. Businesses are experiencing significant benefits, with 91% of those who have implemented AI tools reporting an increase in customer satisfaction since integrating AI into their enablement processes.

How is Seismic addressing the gap in understanding how AI is used in GTM processes, and what educational initiatives or tools are being introduced without delving into specific numbers?

At Seismic, we work to consistently update our AI product offerings and tools to ensure they are meeting the needs of our customers and empowering them to build more strategic relationships, effectively engage with buyers, and speed up the entire buying process.

In fact, just last year we introduced an AI customer community, which is dedicated to sharing best practices, knowledge and strategies to seamlessly integrate AI into revenue teams’ operations. Additionally, we offer both the Seismic Advocacy Program and Seismic Community – two spaces for our customers to hear more directly from Seismic leadership about our products, as well as share with each other what they’re learning and doing with AI-powered enablement at their company.

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In recent years, computer vision (CV) has appeared as a transformative technology that reshapes the landscape of numerous industries by allowing machines to analyze and understand visual information around them.

According to tech leaders, computer vision is often referred to as the eyes of artificial intelligence (AI), which makes it a transformative technology that not only revolutionizes the industries that adapted it but also becomes a cornerstone for the advancement of AI. With more technological advancements, the convergence of CV with IoT, big data analytics (BDA), and automation has given rise to smart work that remains competitive and improves productivity and efficiency.

In this blog, we will learn about the critical role that computer vision plays in pushing the boundaries and creating new avenues for different industries in this digital world.

The Core of Computer Vision

Computer vision is a field of study that enables computers to replicate human visual systems and is often considered a subset of artificial intelligence that collects information from digital images and videos and further processes it to define different attributes. CV relies on way recognition approaches to self-train and comprehend visual data. Earlier ML algorithms were used for computer vision applications; now deep learning (DL) methods have developed as a better solution for this domain. Therefore, with more training with data and algorithms, CV now works much the same as human vision.

These capabilities make computer vision more useful in different industries that range from healthcare and logistics to manufacturing and financial services.

Computer Vision Use Cases

Computer vision technology has tremendous potential to revolutionize numerous industries by providing an automated technique to identify minute defects in products. With the help of ML algorithms, computer vision systems can detect slight variations in outcome quality that may not be observable by the human eye.

The healthcare industry has already advanced with new-age robotic surgeries, but computer vision has quite a multifold effect that can help in performing even delicate and complex procedures. According to a recent report by Statista, more than 20.21% of healthcare institutions and hospitals are implementing CV in their daily processes. This technology can be improved by real-time, high-resolution photographs of the surgical site, allowing the surgeon to have a better idea and acquaintance with the procedure.

Computer vision is an area that tech researchers are still researching and looking for further development in. As we navigate into the future of intelligent technologies, computer vision can redefine boundaries that machines can archive and further open new doors to new possibilities that will reshape the way we interact with the world around us.

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