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AI represents one of the most significant economic opportunities in decades. According to a recent PWC study, AI is projected to increase global GDP by 14% by 2030. While the potential applications of AI seem limitless, there are also numerous challenges to navigate. Deloitte found that 79% of executives anticipate generative AI will drive substantial transformation within their organizations in under three years. However, only 25% of these leaders feel their organizations are highly prepared to address governance and risk issues related to AI.

Businesses today possess vast databases of customer information, but uncovering valuable insights within this data remains a significant challenge. Artificial intelligence (AI) now enables businesses to recognize emotions and sentiments within large datasets, offering transformative potential. However, to fully leverage this technology, businesses must commit to deeper investments. This discussion explores the current impact of AI on sentiment analysis and its future implications for business strategies. Traditional sentiment analysis relied on keyword detection and basic text processing. Mod

Large Language Models (LLMs) have become a transformative force in artificial intelligence, showcasing remarkable abilities in natural language processing and generation. Their capacity to understand, interpret, and produce human-like text has unlocked new possibilities across various sectors, including healthcare, finance, customer service, and entertainment. According to McKinsey, generative AI technologies like LLMs are expected to contribute trillions to the global economy. Despite their immense potential, building sophisticated LLMs necessitates a confluence of factors, including substan

Marketing communication has evolved dramatically over the past decade. As customer expectations rise, they now demand highly personalized, on-demand solutions at an organizational level. This is where artificial intelligence (AI), particularly conversational AI, comes into play. But is AI fully leveraging its potential to transform business-customer relationships? Let’s explore how Conversational AI is disrupting the landscape and why it’s rapidly becoming an essential tool across industries. Talking AI technologies include all the interfaces expanding from simple live chatbots to highly deve

Banks suffered an astounding $485.6 billion loss to fraud and scams last year, highlighting the urgent need for them to outpace criminals. Fraud analytics plays a crucial role in enabling banks to transition from merely reacting to fraud to proactively preventing it. Explore how fraud analytics helps detect and prevent various types of fraud, minimizing financial losses and improving customer trust and satisfaction. Fraud analytics blends artificial intelligence (AI), machine learning, and predictive analytics for advanced data analysis.

As systems grow increasingly complex and interconnected, the challenges facing DevOps teams become more intricate. Hybrid infrastructures, microservices, and real-time operations strain traditional tools, paving the way for artificial intelligence to revolutionize how DevOps operates. This evolution isn’t just about automation—it’s about reimagining how teams monitor and respond to issues in dynamic environments. AI promises smarter, faster, and more efficient DevOps processes, particularly in monitoring and incident response.

Feedzai, the world’s first RiskOps platform, has achieved two significant accolades from Chartis Research. We are proud to be recognized as the leading AI-driven anti-fraud platform and to rank among the top 5 overall in the prestigious RiskTech AI 50 2024 rankings. These achievements underscore Feedzai’s pioneering role in leveraging artificial intelligence and machine learning to advance financial risk management. With an AI-first approach, our technology is designed to swiftly adapt to emerging fraud and scam patterns.

Fraud is already a complex challenge, but merchants face an additional hurdle: first-party fraud perpetrated by their own customers. Unlike second- or third-party fraud, first-party fraud occurs when consumers use their legitimate payment credentials to commit dishonest acts for personal gain. This creates a significant challenge for acquiring banks and payment service providers (PSPs) in assisting merchants with fraud prevention. To effectively support merchants, acquiring banks must develop a thorough understanding of how first-party fraud operates. This article explores how acquirers and P

Acquiring banks often face the challenge of balancing merchant satisfaction with risk management. On one hand, they aim to keep merchants happy by enabling quick payouts. On the other, they must protect themselves from financial losses if a merchant's risk profile unexpectedly shifts. Dynamic risk assessment plays a crucial role in safeguarding acquirers while supporting businesses with the liquidity they need to operate smoothly. Here’s how Feedzai’s Dynamic Risk Assessment, available as an add-on to its Merchant Monitoring solution, helps acquirers mitigate risk while ensuring merchants mai

Delivering an improved digital employee experience (DEX) has become a top priority for many enterprise IT leaders, as it directly influences productivity, employee morale, and other critical aspects of business success. However, many organizations still lack the necessary visibility into their IT ecosystems to fully understand how digital tools impact employee experiences and productivity. This gap often hinders efforts to effectively manage the digital workplace and provide employees with an exceptional experience.

Having spent many years immersed in IT and information security, I can confidently say it has been a rewarding journey. Over time, I’ve observed a significant shift in how organizations perceive cybersecurity. It has gained prominence and relevance, with the role of the Chief Information Security Officer (CISO) evolving positively. CISOs are no longer seen as mere “blockers” but as agents of change who actively contribute to business decisions, enhance visibility, and drive impactful organizational outcomes.

In today’s digital era, cloud computing has become a cornerstone of application modernization and digital transformation. By 2025, it’s anticipated that over 85% of organizations will adopt a cloud-native approach for application development. Yes, you read that correctly! The primary goal of this approach is to streamline development processes, enhance scalability, and boost agility. Unlike traditional methods, cloud-native development doesn’t follow rigid rules. Instead, it focuses on addressing unique business challenges and leveraging the most suitable software solutions.

Netskope offers a unique capability to deeply inspect network packets (post-decryption) and understand the interactions between users and the SaaS applications they use. This enables the application of granular policy controls to regulate specific actions, such as downloading, uploading, editing, posting, or creating content within any application. However, it’s essential to avoid imposing such restrictions on critical business applications like corporate email or OneDrive that employees rely on for their daily tasks.

Augmented analytics represents a groundbreaking approach that integrates artificial intelligence (AI) and machine learning (ML) to unlock deeper insights from data. By automating data preparation and uncovering hidden patterns, it generates actionable recommendations that address the shortcomings of traditional BI systems. The driving forces behind this innovation include the explosion of data volumes, advancements in AI, and heightened customer expectations for faster, smarter decision-making.

In today’s fast-paced environment, it’s not about how much data you collect but how effectively you use it. Smart data is not just big data—it’s better data: focused, relevant, and actionable. By filtering out the noise from millions of data points, businesses can uncover insights that predict customer behavior, optimize processes, and reveal new opportunities. Companies leveraging smart data report a 20% increase in customer engagement and significant reductions in operational inefficiencies. The Smart Data Revolution isn’t a passing trend; it’s the future. And the first step toward embracin

The year 2024 has been marked by significant advancements in technology, particularly in AI, IoT, and cybersecurity. What once seemed like the stuff of futuristic movies has now become integral to our modern world. The convergence of these technologies has sparked creativity, collaboration, and caution, from developing ethical frameworks for AI to exploring how smart tech can enhance the holiday season. As AI continues to evolve, ethical concerns have moved beyond researchers and technologists, becoming a top priority for business leaders. Executives now face the challenge of integrating ethi

The healthcare system we inherited was a reflection of stagnation. Outdated systems and inefficient processes had become the norm, leaving healthcare professionals in a constant struggle to meet the ever-growing demands of modern medicine. This environment was not only challenging for providers but also frustrating for patients. Inefficient, archaic practices highlighted how far healthcare had fallen behind compared to industries that had readily embraced modern technologies. Over the past decade, we’ve seen a shift toward enhancing user experiences across industries.

Web3 technology has transitioned from being a buzzword and speculative trend to a transformative force shaping the digital landscape. As we approach 2025, Web3 is set to redefine business models, offering unprecedented security and transparency through decentralized platforms. But what does this future hold, and how can businesses, especially in the B2B sector, harness the power of Web3 for sustained success? Let’s explore the key trends, challenges, and opportunities Web3 will bring in 2025. Web3 technology has transitioned from being a buzzword and speculative trend to a transformative forc

For years, the concept of a “paperless office” has been a popular industry buzzword, envisioning a future where businesses replace physical paperwork with digital efficiency. Despite technological advancements, many organizations still rely heavily on paper-based processes, with bulky filing systems and stacks of documents central to daily operations. A truly paperless world has long seemed unattainable—until now. Enter optical character recognition (OCR), enhanced by artificial intelligence. By integrating OCR with AI and machine learning, businesses are experiencing a fundamental shift towa

As we approach 2025, the technological landscape continues to evolve at an unprecedented pace. The rapid development of emerging technologies is poised to revolutionize industries ranging from transportation to healthcare over the next decade. Innovations like causal AI and next-generation large language models (LLMs) are set to transform traditional methods, enabling businesses across sectors to make accurate, data-driven decisions derived from experimentation and insights. In this exclusive AITech Park article, we explore the perspective of Mridula Rahmsdorf, CRO at IKASI, on how the coming