As AI reshapes industries and drives global innovation, the UK must urgently address its AI skills gap to remain competitive. Nations investing in AI education and training are gaining a clear advantage, leaving others at risk of falling behind. By equipping the workforce with essential AI expertise, the UK can strengthen its position as a leader in innovation and secure its economic future.Developing AI skills isn’t just about maintaining a competitive edge—it’s about creating opportunities. This dual approach ensures that experts can drive technological advancements while a broad understanding of AI empowers diverse sectors to integrate its potential. Investing in education, upskilling, and industry partnerships will ensure the UK workforce is ready to meet the demands of an AI-driven world. In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to James Kuht, CEO and Founder of Inversity, about integrating AI into education and the collaborative effort required from government and society to achieve this goal.Key Takeaways: The UK has a strong AI talent pipeline concentrated in key areas.Specialist and generalist AI skills are both important.AI can significantly boost productivity in knowledge-based tasks.Teachers need training to effectively integrate AI into education.AI skills will be a baseline requirement for future jobs.Government and society must collaborate on AI education initiatives.AI has the potential to reduce economic inequality.Most jobs will evolve rather than disappear due to AI.Chapters: 00:00 - The Importance of AI Skills for the UK03:01 - James Kuht’s Journey in AI05:57 - Building a Competitive AI Workforce08:45 - Integrating AI into Education12:07 - The Role of Government and Society in AI Education15:01 - Addressing Inequality in AI Access17:58 - Future-Proofing the Workforce with AI Skills21:10 - The Impact of AI on Global Industries

AI operates in two primary environments: on-device and cloud-based. On-device AI processes data locally, ensuring privacy and speed by eliminating the need for internet connectivity. Cloud-based AI, on the other hand, leverages powerful remote servers to handle complex computations and large-scale data analysis, enabling more robust capabilities but often at the cost of latency and potential privacy concerns. Apple Intelligence exemplifies the strengths of on-device AI, with innovations like Siri, Face ID, and real-time photo enhancements all designed to prioritise user privacy while delivering seamless, responsive experiences.  Unlike cloud-based AI, which may send sensitive data to external servers for processing, Apple’s approach ensures that personal information stays on the user’s device and is protected by advanced encryption. This difference builds trust and empowers users with faster, more reliable interactions. In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Karel Callens, CEO at Luzmo, about best practices for developers integrating AI into their products. Key Takeaways:Apple Intelligence operates on-device but can access cloud resources.Developers must implement robust security measures for user data.Clear data policies enhance user trust in AI solutions.Opt-in and opt-out options empower users regarding their data.Education on AI usage is crucial for consumer confidence.Shared security standards can mitigate AI misuse.Regulation is necessary to keep pace with AI advancements.Big tech companies have a responsibility to ensure ethical AI use.Chapters:00:00 - Introduction to AI: On-Device vs Cloud-Based02:54 - Understanding Apple Intelligence and Its Benefits05:47 - Security Measures in AI Integration09:03 - Building Trust Through Transparency and Regulation11:50 - Best Practices for Developers in AI Implementation15:04 - The Role of Education in AI Trust and Security17:47 - The Future of AI: Regulation and Responsibility

AI Personas are the cornerstone of how these systems interact with users, delivering tailored and engaging experiences. These personas—crafted from user research, behavioural insights, and cultural contexts—help define an AI's tone, style, and decision-making approach. Whether it’s a friendly virtual assistant or a professional customer service bot, personas ensure that AI systems resonate with their audiences while maintaining a consistent identity. However, developing personas for AI isn’t without its challenges. Ensuring that AI responses remain appropriate, ethical, and unbiased while preserving a unique persona requires careful consideration. From avoiding stereotypes to addressing edge cases, the process demands robust testing and a clear understanding of how diverse user interactions can unfold. When personas fail to account for the complexity of real-world scenarios, the risk of inappropriate or harmful responses increases. By combining creative storytelling with ethical AI design principles, organisations can navigate these challenges and build AI systems that are engaging and responsible in their behaviour.In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Cobus Greyling, Chief Evangelist at Kore.ai, about the influence of cultural norms and value systems on AI and strategies for maintaining control over AI behaviour. Key Takeaways: Personas in AI shape user interactions and trust.Cultural norms influence AI decision-making processes.Balancing control and agency is crucial for effective AI.Adversarial attacks can undermine AI reliability.Transparency is essential for user confidence in AI.Organisations should not offload too much responsibility to AI.AI should enhance human creativity, not replace it.Proof of value is necessary for AI technology implementation.Chapters:00:00 - Introduction to AI Personas and Their Impact02:34 - The Role of Personas in AI Behavior05:51 - Challenges in Ensuring Appropriate AI Responses09:07 - Cultural Norms and Value Systems in AI10:30 - Balancing Control and Agency in AI14:14 - Strategies for Maintaining Control Over AI Behavior21:24 - The Importance of Responsibility in AI Usage

Low-code and no-code platforms are revolutionising application development by empowering technical and non-technical users to quickly and efficiently build powerful applications. These platforms provide intuitive visual interfaces and pre-built templates that enable users to create complex workflows, automate processes, and deploy applications without writing extensive lines of code. By simplifying development, low-code and no-code tools open up software creation to a wider range of contributors, from professional developers looking to accelerate delivery times to business users aiming to solve specific problems independently. This democratisation of development reduces the demand for IT resources and fosters a culture of innovation and agility within organisations.The impact of low-code and no-code technology extends beyond just speed and accessibility; it’s transforming how businesses adapt to change and scale their digital solutions. These platforms allow companies to quickly respond to evolving customer needs, regulatory requirements, and competitive pressures without the lengthy timelines associated with traditional development cycles. In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Michael West, Analyst at Lionfish Tech Advisors about LCNC platforms and their benefits. Key Takeaways:Low-code and no-code platforms enable business solutions without coding.These platforms broaden the developer base to include non-technical users.Choosing the right platform involves considering functionality, standards, and vendor viability.Low-code platforms can handle enterprise-level applications effectively.AI integration is transforming how applications are developed.Democratisation of development addresses the shortage of professional developers.The market for low-code and no-code platforms is rapidly evolving.Future trends will focus on AI capabilities and user experience.Chapters: 00:00 Introduction to Low-Code and No-Code Platforms02:59 The Evolution of Development Roles05:49 Key Considerations for Adopting LCNC Tools09:04 Democratizing Development and Innovation11:59 Future Trends in Low-Code and No-Code Markets

The intersection of cryptography and GPU programming has changed the face of secure data processing, making methods for encryption and decryption much faster and more efficient than ever imagined. Cryptography is the science of encrypting data with intricate algorithms initially designed to operate on very intensive computational powers. GPU programming provides the ability to utilise parallel processing of graphics processing units in cryptographic processes so they perform with unmatched speed. While continuously evolving, GPUs are furnishing the computational muscle to execute ever-higher-level cryptographic algorithms without performance penalties. Developers now fully avail of the power of GPU parallelism to perform several thousand encryption tasks simultaneously, which is difficult for traditional CPUs to keep up with. This efficiency is critical in this growing data and rising cyber threat era, where organisations need rapid encryption and robust security. In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Agnes Leroy, Senior Software Engineer at Zama, about the significance of encryption in high-stakes industries, the role of women in tech and the importance of mentorship in overcoming barriers in the industry.Key Takeaways: GPUs have evolved from graphics rendering to critical roles in data security.Fully homomorphic encryption allows computations on encrypted data.Quantum-resistant methods are crucial for future-proofing encryption.High-stakes industries require robust encryption to protect sensitive data.Diverse environments in tech foster innovation and collaboration.The future of encryption technology is exciting and unpredictable.Chapters: 00:00 - Introduction to Cryptography and GPU Programming01:08 - The Evolution of GPUs in Data Security03:33 - Challenges in Traditional vs Modern Encryption05:50 - Quantum Resistance in Encryption Techniques07:40 - The Future of GPUs in Data Privacy08:38 - Importance of Encryption in High-Stakes Industries10:00 - Potential Applications of Fully Homomorphic Encryption11:42 - Women in Tech: Overcoming Barriers15:33 - Conclusion and Resources

LLMs and AI have increasingly become major contributors to transforming content creation today. Understanding and using prompt skills appropriately can help organisations optimise AI to generate high-quality content efficiently. While AI offers multiple benefits, it's important to acknowledge the potential risks associated with its implementation. Organisations are advised to carefully consider factors such as data privacy, bias, and the ethical implications of AI-generated content. In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Prof. Yash Shreshta, Assistant Professor at the University of Laussane, about prompt engineering and its benefits. Key TakeawaysPrompts are commands given to AI to perform tasks.Prompt engineering allows users to communicate effectively with AI.Iterative processes improve the quality of AI outputs.Understanding LLM limitations is crucial for effective use.Collaboration can enhance the creative process with AI.The role of prompt engineering is rapidly evolving with AI advancements.Data privacy is a significant risk when using LLMs.Over-reliance on AI can lead to skill degradation.Organisations should integrate human creativity with AI.Regular training on prompt engineering is essential for maximising LLM benefits.Chapters00:00 Introduction to Prompt Engineering and AI01:30 Understanding Prompt Engineering04:15 The Importance of Prompt Engineering Skills06:37 Best Practices for Effective Prompts08:31 The Evolving Role of Prompt Engineering11:20 Risks and Challenges of AI in Organizations13:15 The Future of Creativity with AI

The fraud division has witnessed a dramatic transformation in the age of artificial intelligence (AI). As technology advances, so do the methods employed by fraudsters. Modern criminals use sophisticated techniques, such as deep learning and natural language processing, to deceive individuals and organisations alike. Such techniques allow them to mimic human behaviour, manipulate data, and exploit vulnerabilities in security systems.That’s why organisations are embracing AI's strengths to combat these evolving threats. AI-driven solutions can provide real-time detection of fraudulent activities, analyse vast amounts of data to identify patterns and anomalies, and automate response processes. In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Xavier Sheikrojan, Senior Risk Intelligence Manager at Signifyd, about AI fraud. Key Takeaways:Fraudsters have evolved from individuals to organised criminal enterprises.AI enables fraudsters to scale their attacks rapidly and strategically.Phishing attacks have become more sophisticated with AI-generated content.Synthetic identities can be created easily, complicating fraud prevention.Opportunistic fraud is impulsive, while proactive fraud is well-planned.Businesses often fail to act post-breach due to resource constraints.Inaction after a breach can lead to repeated attacks by fraudsters.AI must be used to combat AI-driven fraud effectively.Balancing fraud detection with customer experience is crucial for businesses. Chapters: 00:00 Introduction to AI and Fraud01:32 The Evolution of Cybercrime05:43 AI's Role in Modern Fraud Techniques09:55 Opportunistic vs. Proactive Fraud12:44 Business Inaction and Its Consequences15:59 Combating AI-Driven Fraud with AI

As AI technologies become more integrated into business operations, they bring opportunities and challenges. AI’s ability to process vast amounts of data can enhance decision-making but also raise concerns about data privacy, security, and regulatory compliance. Ensuring that AI-driven systems adhere to data protection laws, such as GDPR and CCPA, is critical to avoid breaches and penalties. Balancing innovation with strict compliance and robust data security measures is essential as organisations explore AI’s potential while protecting sensitive information.In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Erin Nicholson, Global Head of Data Protection and AI Compliance at Thoughtworks, about the importance of compliance frameworks, best practices for transparency and accountability, and the need for collaboration among various teams to build trust in AI systems.Key Takeaways:AI systems are powerful but require ethical and compliant design.Lack of standardisation in AI regulations poses significant challenges.AI models often need help with explainability and transparency.Compliance frameworks are essential for implementing AI in critical sectors.Documentation and audits are crucial for maintaining AI accountability.Baselining pre-AI processes helps build public trust in AI systems.Organisations should map regulations to the most stringent standards.Cross-functional collaboration is vital for effective AI compliance.Chapters: 00:00 - Introduction to AI, Data Protection, and Compliance02:08 - Challenges in AI Implementation and Compliance05:56 - The Role of Compliance Frameworks in Critical Sectors10:31 - Best Practices for Transparency and Accountability in AI14:48 - Navigating Regional Regulations for AI Compliance17:43 - Collaboration for Trustworthiness in AI Systems

As organisations increasingly migrate to cloud environments, they face a critical challenge: ensuring the security and privacy of their data. Cloud technologies offer many benefits, including scalability, cost savings, and flexibility. However, they also introduce new risks, such as potential data breaches, unauthorised access, and compliance issues. With sensitive data stored and processed off-premises, maintaining control and visibility over that data becomes more complex. As cyber threats continue to evolve, robust data protection strategies are essential to safeguarding information in the cloud.In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Sergei Serdyuk, VP of Product Management at NAKIVO, about the factors driving cloud adoption, the importance of having a robust disaster recovery plan, best practices for data protection, and the challenges of ensuring compliance with regulations.Key Takeaways: Cloud adoption is accelerated by low barriers to entry.Scalability in cloud environments is easier than on-premises.Data in the cloud is vulnerable and needs protection.The shared responsibility model places data protection on the user.A comprehensive disaster recovery plan is crucial for businesses.Regular testing of disaster recovery plans is essential.Data protection strategies must include regular reviews and updates.Compliance with data protection regulations is complex and varies by region.Balancing security and operational efficiency is a key challenge.Chapters: 00:00 - Introduction to Cloud Technologies and Data Protection01:26 - Factors Accelerating Cloud Adoption03:48 - The Importance of Data Protection in the Cloud06:39 - Developing a Comprehensive Disaster Recovery Plan10:05 - Best Practices for Data Protection13:31 - Ensuring Compliance in Cloud Environments15:56 - The Role of Continuous Monitoring in Data Protection18:19 - Balancing Security and Operational Efficiency

Managed Service Providers (MSPs) are evolving beyond traditional IT support, becoming strategic partners in driving business growth. By embracing AI technologies, MSPs are improving operational efficiency, streamlining service delivery, and offering smarter solutions to meet modern challenges.As businesses navigate digital transformation, MSPs are crucial in optimising IT infrastructure, enhancing security, and providing tailored solutions that fuel innovation. With AI-powered tools, MSPs meet today's demands and help businesses stay competitive. In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Jason Kemsley, Co-founder and CRO of Uptime, about the proactive strategies that MSPs can adopt using AI, the challenges they face in implementation, and the ethical considerations surrounding AI solutions.Key Takeaways:MSPs are transitioning from traditional IT support to strategic partners.AI is enhancing operational efficiency but not replacing human roles.Proactive support is often neglected due to resource constraints.AI can help MSPs predict and prevent IT issues.Challenges in adopting AI include unrealistic expectations and lack of accountability.There is potential for MSPs to develop their own AI tools.Chapters:00:00 - Introduction to Managed Service Providers (MSPs)02:03 - The Evolving Role of MSPs in Business Growth04:00 - AI's Impact on Service Delivery Models07:22 - Proactive Support Strategies with AI10:16 - Challenges in Adopting AI for MSPs12:40 - Ethics and Accountability in AI Solutions

Trusted AI ensures that people, data, and AI systems work together transparently to create real value. This requires a focus on performance, innovation, and cost-effectiveness, all while maintaining transparency. However, challenges such as misaligned business strategies and data readiness can undermine trust in AI systems. To build trusted AI, it’s crucial to first trust the data. A robust data platform is essential for creating reliable and sustainable AI systems. Tools like Teradata’s ClearScape Analytics help address concerns about AI, including issues like generative AI hallucinations, by providing a solid foundation of trusted data and an open, connected architecture.In this episode, Doug Laney, Analytics Strategy Innovation Fellow with West Monroe Partners, speaks to Vedat Akgun, VP of Data Science & AI and Steve Anderson, Senior Director of Data Science & AI at Teradata, about trusted AI. Key Takeaways:Value creation, performance, innovation, and cost-effectiveness are crucial for achieving trusted AI.Trusting data is essential before building AI capabilities to avoid biases, inaccuracies, and ethical violations.A robust data platform is a foundation for creating trusted and sustainable AI systems.Generative AI raises concerns about hallucinations and fictitious data, highlighting the need for transparency and accountability.Teradata offers features and capabilities, such as ClearScape Analytics and an open and connected architecture, to address trust issues in AI.Chapters:00:00 - Introduction and Defining Trusted AI01:33 - Value Creation and the Importance of Driving Business Value03:27 - Transparency as a Principle of Trusted AI09:00 - Trusting Data Before Building AI Capabilities14:51 - The Role of a Robust Data Platform in Trusted AI21:09 - Concerns about Trust in Generative AI23:03 - Addressing Trust Issues with Teradata's Features and Capabilities25:01 - Conclusion

Balancing transparency in AI systems with the need to protect sensitive data is crucial. Transparency helps build trust, ensures fairness, and meets regulatory requirements. However, it also poses challenges, such as the risk of exposing sensitive information, increasing security vulnerabilities, and navigating privacy concerns.In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Juan Jose Lopez Murphy, Head of Data Science and Artificial Intelligence at Globant, to discuss the ethical implications of AI and the necessity of building trust with users. Key Takeaways:Companies often prioritise speed over transparency, leading to ethical concerns.The balance between transparency and protecting competitive data is complex.AI misuse by malicious actors is a growing concern.Organisations must educate users on digital literacy to combat misinformation.Confidently wrong information is often more trusted than qualified uncertainty.Chapters00:00 - Introduction to AI Transparency03:03 - Balancing Transparency and Data Protection05:57 - Navigating AI Misuse and Security09:05 - Building Trust Through Transparency12:03 - Strategies for Effective AI Governance

As organisations adopt AI, data literacy has become more critical than ever. Understanding data—how it's collected, analysed, and used—is the foundation for leveraging AI effectively. Without strong data literacy, businesses risk making misguided decisions, misinterpreting AI outputs, and missing out on AI’s transformative benefits. By fostering a data-driven culture, teams can confidently navigate AI tools, interpret results, and drive smarter, more informed strategies.Ready to boost your data literacy and embrace the future of AI?Key Takeaways: Companies are optimistic about ROI from AI investments.Data literacy is crucial for effective AI implementation.Technical debt poses challenges for AI infrastructure.Data quality and governance are essential for AI success.Trust in AI systems is a growing concern.Organizations must start with clear business priorities.The Data Festival will provide practical insights for AI adoption.DATA festival is where theory meets practice to create real, actionable knowledge. This event brings together #DATApeople eager to drive the realistic applications of AI in their fields.Leaving the hype behind, we look at the actual progress made in applying (Gen)AI to real-world problems and delve into the foundations to understand what it takes to make AI work for you. We’ll discuss when, where and how AI is best applied, and explore how we can use data & AI to shape ourfuture.Sign up now to secure your spot

Data labelling is a critical step in developing AI models, providing the foundation for accurate predictions and smart decision-making. Labelled data helps machine learning algorithms understand input data by assigning meaningful tags to raw data—such as images, text, or audio—ensuring that AI models can recognise patterns and make informed decisions. AI models struggle to learn and perform tasks effectively without high-quality labelled data. Proper data labelling enhances model accuracy, reduces errors, and accelerates the time it takes to train AI systems. Whether you're working with natural language processing, image recognition, or predictive analytics, the success of your AI project hinges on the quality of your labelled data.In this episode, Henry Chen, Co-founder and COO of Sapien, speaks to Paulina Rios Maya about the importance of data labelling in training AI models. Key Takeaways:Data labelling converts raw data into structured data that machine learning models can recognise.Reducing bias and ensuring data quality are critical challenges in data labelling.Expert human feedback plays a crucial role in improving the accuracy of AI training data and refining AI models.Chapters: 00:00 - Introduction and Background01:07 - Data Labeling: Converting Raw Data into Useful Data03:02 - Challenges in Data Labeling: Bias and Data Quality07:46 - The Role of Expert Human Feedback09:41 - Ethical Considerations and Compliance11:09 - The Evolving Nature of AI Models and Continuous Improvement14:50 - Strategies for Updating and Improving Training Data17:12 - Conclusion

Traditional KYC processes are inadequate against modern fraud tactics. While KYC helps with initial identity checks, it doesn't cover evolving threats like AI-generated deepfakes or ongoing account takeovers. Curious about how to protect your business from the latest threats like fake IDs, account takeovers, and AI-generated deep fakes? Tune in to our latest episode, where we dive into the essentials of full-cycle verification and real-time transaction monitoring. Find out how AI and machine learning can revolutionise your fraud detection efforts and why staying updated with regulatory changes is crucial for maintaining top-notch security. In this episode of Tech Transformed, Alvaro Garcia, Transaction Monitoring Technical Manager at Sumsub, speaks to Paulina Rios Maya, Head of Industry, about the manifestations of identity fraud during the user journey stages and the need for comprehensive fraud prevention measures.Key Takeaways:Identity fraud manifests at different user journey stages, including onboarding and transaction monitoring.Businesses must implement full-cycle verification and transaction monitoring solutions to detect and prevent fraud in real time.AI and machine learning are crucial in analyzing suspicious user behaviour and spotting complex fraud patterns.SumSub offers platform solutions that include KYC, business verification, transaction monitoring, and payment fraud protection.Chapters: 00:00 - Introduction and Overview00:35 - Identity Fraud in the User Journey02:01 - Types of Fraud and Fraud Prevention04:20 - Real-Time Monitoring and Enhancing Systems05:46 - Common Types of Fraud Faced by Financial Institutions08:40 - The Challenge of AI-Generated Deepfakes10:04 - Beyond KYC: Additional Measures for Fraud Prevention12:29 - Prevention Measures and Synthetic Identity Fraud15:21 - Effective Fraud Prevention Solutions17:45 - Assessing the Effectiveness of Fraud Prevention Strategies19:08 - Staying Up to Date with Regulatory Requirements21:31 - Conclusion

AI is revolutionising contact centres by automating routine tasks, reducing response times, and enhancing customer experience. AI is built to handle simple inquiries efficiently and at scale. It helps contact centres close the gap between customer expectations and conventional customer service by enabling engagement through digital channels. AI-driven analytics improve decision-making by capturing and analysing data from customer interactions. Organisations can overcome challenges by starting small and gradually building trust in AI's capabilities. In this episode, Paulina Rios Maya, Head of Industry Relations at EM360 speaks to Jon Arnold, Principal at J Arnold & Associates about the use of AI in contact centres. Key Takeaways:AI is a transformative technology that rethinks customer engagement and addresses customer problems in contact centres.AI enables engagement through digital channels and helps contact centres close the gap between customer expectations and conventional customer service.AI-driven analytics improve decision-making by capturing and analysing data from customer interactions.Organisations can overcome challenges by starting small and gradually building trust in AI's capabilities.AI helps protect privacy and mitigate fraud in contact centres.Chapters:00:00 - Introduction and Overview01:06 - The Transformational Power of AI in Contact Centers03:00 - Automating Routine Tasks and Enhancing Customer Experience06:24 - Engaging Customers through Digital Channels11:09 - Improving Decision-Making with AI-Driven Analytics15:28 - Overcoming Challenges and Building Trust in AI17:23 - Protecting Privacy and Mitigating Fraud in Contact Centers

Join us in this exciting episode of Tech Transformed, where we talk to Kelly Vero, a pioneering game developer, digital leader, and visionary in the metaverse. With a career spanning 30 years and a resume that includes contributions to legendary franchises like Tomb Raider and Halo 3, Kelly brings a wealth of knowledge and experience to the table.  Kelly’s unique journey in the tech world is nothing short of extraordinary. From joining the military to learn about ballistics for Halo 3 to founding the award-winning startup NAK3D, she has always pushed the boundaries of what’s possible. Kelly Vero speaks to Paulina Rios Maya about the hurdles of being a woman in the tech industry, the principles of gamification, and the overhyped trends in AI and NFTs. They discuss what’s genuinely beneficial versus what’s just noise.Key Takeaways: The gaming industry offers opportunities for problem-solving and creativity.Role models can come from everyday people who inspire and support others.Gamification is about creating an engaging user experience that encourages return and contribution.The tech industry has seen beneficial changes in globalized platforms and a focus on quantum solutions.Chapters: 00:00 - Introduction and Background02:28 - The Gaming Industry and Problem Solving07:36 - Challenges and Role Models in the Tech Industry11:54 - The Principles and Ethical Considerations of Gamification18:30 - Beneficial Changes and Overhype in the Tech Industry20:25 - Creating Digital Objects and the NFT Standard23:45 - Introducing NAK3D: Bringing Non-Designers into Design

Strategic choices with significant implications mark Latin America's approach to AI. Many countries in the region have adopted AI technologies and frameworks developed by leading tech nations, focusing on imitation rather than innovation. This strategy enables rapid deployment and utilisation of advanced AI solutions, bridging the technological gap and fostering economic growth. However, reliance on external innovations raises questions about the region's long-term competitiveness and ability to contribute original advancements to the global AI landscape.In this podcast, Alejandro Leal, Analyst at KuppingerCole, speaks to Paulina Rios Maya, Head of Industry Relations, about how socio-economic factors, including limited research funding, infrastructural challenges, and the need for quick technological catch-up drive this pattern of imitation. While this approach has led to swift AI adoption, it underscores a dependence on foreign technologies and expertise.Key Takeaways: Trust, ethics, and legal considerations are essential challenges in integrating AI into the security infrastructure.Public-private partnerships and regional cooperation are crucial for advancing AI technology in the region.Interoperability and alignment with international and regional standards are key areas of focus to ensure the ethical use of AI in Latin America.Chapters:00:00 - Introduction: AI in Latin America00:58 - Key Initiatives in the Security Sector in Mexico05:12 - Mexico's Evolution in National Security07:33 - Challenges in Integrating AI into Security Infrastructure12:40 - Comparison with Other Latin American Countries19:26 - The Role of Public-Private Partnerships22:51 - Focus on Interoperability and Alignment with Standards23:46 - Conclusion: Ethical Use of AI in Latin America

AI fraud is not just a concern, it's a pressing issue. As artificial intelligence technologies advance, fraudsters are developing increasingly sophisticated methods to exploit these systems. Typical forms of AI fraud include deepfakes, which use AI to create convincing fake images, audio, or videos for disinformation, blackmail, or identity theft, and advanced phishing schemes that leverage AI to craft highly personalized and deceptive messages. Addressing and understanding AI fraud is not just crucial, it's urgent for individuals, businesses, and governments to protect against these evolving threats. Join Alejandro Leal and Pavel Goldman-Kalaydin, Head of AI and Machine Learning at Sumsub, as they delve into the growing issue of AI fraud.Themes:AI fraudDeepfakesGlobal trendsRegulationChapters:00:00 - Introduction and Background01:13 - Understanding AI Fraud02:11 - Examples of AI-Driven Fraud08:02 - Global Trends in AI-Driven Fraud13:55 - Preventing AI-Driven Fraud18:11 - The Future Evolution of AI Fraud22:38 - Conclusion and Final Thoughts

While generative AI and large language models often receive inflated acclaim, their true value is found in harnessing intelligence and data-driven insights. Despite the hype, AI has its shortcomings, such as large language models sometimes being solutions looking for problems and challenges in understanding its impact on advertising and making savvy investment decisions.In this podcast, Dana Gardner, President & Principal Analyst of Interarbor Solutions, and Paulina Rios Maya, Head of Industry Relations at EM360Tech, discuss why AI should be seen as a transformational technology rather than just another automation tool. Key TakeawaysAI should be viewed as a transformational technology that can refactor our actions rather than just an automation tool.Large language models may be a solution in search of a problem, and their high costs and sustainability impacts should be considered.Making informed decisions about AI investments requires considering the potential benefits and costs.Chapters00:00 - The Current State of AI Development02:17 - Viewing AI as a Transformational Technology03:45 - The Limitations of Large Language Models05:40 - The Impact of AI on Advertising06:37 - Navigating the Complexities of AI Investments

Infosecurity Europe is a cornerstone event in the cybersecurity industry. It brings together a diverse array of cybersecurity services and professionals for three days of unparalleled learning, exploration, and networking. At its essence, the event is committed to delivering indispensable value to its attendees through meticulously crafted themes and discussions.This year's focus revolves around resilience, artificial intelligence, legislation and compliance, leadership and culture, and emerging threats. With a comprehensive program featuring keynote speakers, strategic talks, insightful case studies, state-of-the-art technology showcases, dynamic startup exhibitions, and immersive security workshops, Infosecurity Europe offers a comprehensive immersion into the dynamic landscape of cybersecurity.Pioneering new approaches, the event introduces QR-based tools for seamless content collection and unveils a digital meetings platform to foster enhanced connectivity and collaboration. By participating in Infosecurity Europe, cybersecurity professionals equip themselves with the tools, knowledge, and connections vital for continuous growth, networking, and industry advancements.In this episode of the EM360 Podcast, Paulina Rios Maya, Head of Industry Relations at EM360Tech, speaks to Victoria Aitken, Conference Manager and Nicole Mills, Senior Exhibition Director, to discuss: Cybersecurity Trends Security events Infosecurity Europe Register here to attend Infosecurity Europe | 4–6 June 2024Chapters00:00 - Introduction and Overview of Infosecurity Europe01:33 - Key Themes and Topics at Infosecurity Europe14:04 - New Approaches and Tools16:21 - Women in Cyber and Analyst Sessions

Ever wonder how search engines understand the difference between "apple," the fruit, and the tech company? It's all thanks to knowledge graphs! These robust and scalable databases map real-world entities and link them together based on their relationships. Imagine a giant web of information where everything is connected and easy to find. Knowledge graphs are revolutionizing how computers understand and process information, making it richer and more relevant to our needs. Ontotext is a leading provider of knowledge graph technology, offering a powerful platform to build, manage, and utilise knowledge graphs for your specific needs. Whether you're looking to enhance search capabilities, improve data analysis, or unlock new insights, Ontotext can help you leverage the power of connected information.In this episode of the EM360 Podcast, George Firican, Founder of LightsOnData, speaks to Sumit Pal, Strategic Technology Director at Ontotext, to discuss: Knowledge Graphs Use Cases Ontotext GraphDBIntegration of AI Industry best practices 

Gone are the days of merely safeguarding school computers! Censornet, a rising star in the tech industry, has undergone a remarkable transformation. From its roots as an internet security provider for educators, it has emerged as a trailblazing force in digital risk management. Today, Censornet offers a comprehensive suite of tools designed to confront the dynamic challenges of the digital landscape, ensuring a safer and more secure online environment for all. This evolution stems from recognising that traditional threats are no longer the sole concern. With the proliferation of Shadow IT, unauthorised applications and devices, and the rise of insider threats, organisations face a complex array of risks. In this episode of the EM360 Podcast, Jonathan Care, Advisor at Lionfish Tech Advisors, speaks to Gareth Lockwood, VP of Product at Censornet, to discuss:Inspiration behind Censornet Censornet’s Capabilities Censornet’s Clients Shadow-IT Prevention of future vulnerabilities with AI and Censornet

The traditional data warehousing landscape is changing. The concept of private data cloud offers a compelling alternative to both cloud PaaS and traditional data warehousing. Imagine a secure, dedicated environment for your data, existing entirely within your organisation's control.Yellowbrick, a leader in private data cloud solutions, empowers businesses to leverage their data on their terms. Their Bring Your Own Cloud (BYOC) approach offers unmatched flexibility and control. You can deploy Yellowbrick anywhere your data needs to be—public cloud, private cloud, or even the network edge. This ensures compliance with regulations and keeps your data exactly where you want it and can bring down costs. In this episode of the EM360 Podcast, Wayne Eckerson, President of Eckerson Group, speaks to Mark Cusack, Chief Technology Officer of Yellowbrick, to discuss:The need for hybrid multi-cloud data platforms How Yellowbrick differentiatesThe future of private data cloudWhy Yellowbrick? 

Amid the ever-evolving landscape of cyber threats, organisations are constantly challenged to ensure security. Conventional security methods are failing to keep up with the escalating volume and sophistication of attacks. By implementing Managed Detection and Response (MDR) with automation, Security Operations Centers (SOCs) can optimise workflows, augment analyst capabilities, and significantly enhance the organisation's overall cybersecurity defences. Palo Alto Networks offers comprehensive MDR services, leveraging its threat intelligence and cutting-edge technology expertise. Unit 42, its esteemed threat intelligence team, is crucial in providing valuable insights into emerging threats and trends, empowering organisations to stay ahead of malicious actors. In this episode of the EM360 Podcast, Richard Stiennon, Chief Research Analyst at IT-Harvest, speaks to Ophir Karako, Software Engineer (Unit 42) at Palo Alto Networks, to discuss: Palo Alto’s MDR Services Operational Automation Data EnrichmentThreat Response Job security for SOC Analysts Interested in learning more about XSOAR and Palo Alto Networks? You can find some additional resources below:Enloe Medical Center Strengthens Its Security Posture and Improves Efficiency With Unit 42 MDRUnit 42 Managed Detection and Response Service DatasheetA Practical Guide to Deploying SecOps AutomationChapters00:00 - Introduction and Background00:57 - MDR Services at Palo Alto Networks03:20 - Automation in Operations04:16  - Automating Data Enrichment05:13  - Intellectual Property Playbooks and Scripts05:41 - Customized Reports for Customers06:10 - Automated Threat Response07:08 - Insights and Lessons Learned from Automation07:37 - Benefits of Automation for SOC Analysts08:06 - Collaboration with Product Experts09:04 - Treating Automation as a CI/CD Process10:01 - The Future of Automation in Cybersecurity12:51  - Automation and Job Security for SOC Analysts14:20 - Cortex XSOAR: Security Orchestration, Automation, and Response Platform15:46 - Unit 42 MDR Service16:16 - Conclusion

The data analysis landscape is on the precipice of a paradigm shift. Generative AI (GenAI) promises revolutionary insights, but traditional systems struggle to feed its insatiable appetite for well-structured data. Imagine GenAI as a high-powered engine – it needs meticulously organised fuel to reach its full potential.In this episode of the EM360 Podcast, Analyst Christina Stathopoulos guides Deborah Leff (CRO at SQream) and Jason Hardy (CTO, AI at Hitachi Vantara) as they dissect:The Bottlenecks of Traditional SystemsUnlocking GPU PotentialFueling Insights with Structured DataFaster Time to InsightsThis episode goes beyond theory, exploring real-world examples (like a company querying a staggering 64 quadrillion rows) It showcases the potential for SQream and Hitachi Vantara to empower organisations to make data-driven decisions with unprecedented speed and accuracy.

The SolarWinds breach exposed vulnerabilities within DevSecOps practices, sending shockwaves through the tech world. The U.S. Securities and Exchange Commission (SEC) indictment against SolarWinds further emphasised the gravity of the situation, alleging the company misled investors by failing to disclose these vulnerabilities and the subsequent breach adequately. This lack of transparency raises crucial questions about accountability and risk management in the mobile app development landscape, pushing organisations to re-evaluate their DevSecOps practices and prioritise robust security measures throughout the entire development lifecycle.In this episode of the EM360 Podcast, Head of Podcast Production Paulina Rios Maya speaks to Richard Stiennon, Chief Research Analyst at IT-Harvest, and Tom Tovar, CEO and Co-Creator of Appdome, to discuss: The SolarWinds indictment The U.S. SEC 4-day ruleThe impact on DevSecOps practicesBYOD and VPN security The evolving role of cybersecurityBuilding cyber resilience 

The fight against cybercrime is a never-ending battle. Firewalls and antivirus software, our traditional defences, are like trusty shields—good against basic attacks but not enough. Advanced attackers can slip through the cracks, exploiting new weaknesses or mimicking harmless traffic. Thus, businesses are exposed and face potential data breaches, financial ruin, and damaged reputations.That's where Advanced Threat Intelligence (ATI) comes in – a game-changer in the cybersecurity arsenal. Unlike our old shields, ATI offers real-time intel on the latest threats, how attackers operate, and their ever-evolving tactics. Recognising the limitations of traditional security solutions, Radware goes beyond basic shields. Imagine a high-powered watchtower constantly scanning the digital horizon, identifying threats before they strike. In this episode of the EM360 Podcast, Analyst Jonathan Care speaks to Arik Atar, Senior Threat Intelligence Researcher at Radware, to discuss: The Current Threat LandscapeModern Attacker TacticsRomance Scams & Pig ButcheringThe Radware Advantage 

Cloud-native is the new gold rush for businesses seeking speed, efficiency, and innovation. But are you getting the most out of your investment? Legacy troubleshooting and observability tools can be hidden anchors, dragging down your developers' productivity.The result? You're not reaping the full benefits of cloud-native, and your competitors are leaving you in the dust. Chronosphere, a leader in modern observability, can empower your developers and unlock the true potential of cloud-native. Buckle up and get ready to discover how observability can become your secret weapon for unleashing developer agility and innovation.In this episode of the EM360 Podcast, VP of Research at Eckerson Group, Kevin Petrie speaks to Ian Smith, Field CTO at Chronosphere, to discuss: Observability Cloud-native software developersDeveloper inefficiencyThe Chronosphere solutionData pipeline best practices 

SaaS applications are the backbone of digital enterprises around the world. But with so many SaaS businesses out there, simply having a feature-rich product is no longer enough to keep your users happy and grow your business.In an increasingly crowded SaaS market, a smooth, intuitive user experience is what sets SaaS products apart. Businesses not only need to craft an exceptional user experience (UX) but also a User Interface (UI) design that makes your UX as seamless as possible. But what does an effective UX and UI design even look like today? And how are emerging technologies like AI and machine learning transforming what users expect from a SaaS UX and UI design?In this episode of the EM360 podcast, Matt Harris speaks to Jatin Leuva, CEO and UX Strategist at Tcules, to discuss:The current state of UX/UI designThe challenges companies face in implementing solid UX/UI design The emerging trends and technologies impacting the UX/UI space.

The cloud revolutionised how businesses operate, but managing dynamic, complex environments presents new and unique challenges.While digital transformation has brought significant benefits, the reality is that organisations now require innovative solutions to effectively navigate intricate, hybrid, multi-cloud environments.Evolven Software, driven by a mission to simplify complexity and mitigate risk, empowers large organisations to overcome the challenges of governing extensive hybrid ecosystems. By harnessing the power of AI/ML, Evolven enables a more secure, streamlined, and efficient cloud journey with fewer outages or compliance gaps.In this episode of the EM360 Podcast, industry veteran Tom Croll, advisor at Lionfish Tech Advisors, speaks to Sasha Gilenson, Founder and CEO of Evolven Software, to discuss: The current state of enterprise cloud architectures and the challenges in managing hybrid multi-cloud environments.Why managing risk in hybrid multi-cloud environments demands a new paradigm.The unique challenges large organizations face in maintaining visibility, control, and governance across their landscapes.How Evolven's AI/ML-driven solution empowers enterprises to overcome this complexity, enhance security, and optimize performance.

Intelligent document processing (IDP) is a technology-driven approach that automates document processing and extraction of valuable information.While handling structured data is considerably straightforward, processing and analyzing unstructured data is laborious. IDP equips users with the ability to process a multitude of document types, including PDFs, spreadsheets, and Word documents, among others. IDP platforms offer a powerful solution that streamlines data extraction from these documents by eliminating the need for any manual intervention. The extracted data, when integrated, enables you to make reliable decisions and improve business efficiency.In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Jay Mishra, COO at Astera, to discuss:Traditional document processing and the problems it causesAI-powered solutionsThe future of document processing and data extractionFind out more about Astera’s unified, no-code data management platform here.

From the rise of generative AI to the EU AI Act, it’s been a particularly explosive year in the AI and ML space.With most industry surveys pointing to bringing in some form of AI as the biggest priority for companies looking to level up their tech stack in 2024 - what challenges and trends need to be addressed before creating and honing that MLOps strategy?In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Yaron Haviv, Founder and CTO at Iguazio (recently acquired by McKinsey) as they discuss:The current AI landscapeImplementing AI and ML - in the right wayHow scalable is MLOps?

Austin Kronz is the Director of Data Strategy at Atlan, a modern data workspace enabling better collaboration between diverse users like businesses, analysts and engineers - creating higher efficiency and agility in data projects. The current world of data and AI is fast-moving - particularly when it comes to empowering companies and data leaders to ensure they’re set up correctly. But what are some of the key trends that are really shaping what we’re seeing today? And how can you ensure that your data is ready for AI? In this episode of the EM360 Podcast, Matt Harris speaks to Austin as they discuss:Data mesh and improving the way teams workEnsuring your data is ready for AIWords of wisdom for data leaders

Companies are evolving their approaches to managing content collaboration lifecycles, integrating security measures, and ensuring compliance with industry standards.The importance of enterprise file storage especially highlights a shift toward adopting standards from public cloud ecosystems and modernising on-premises applications.In this episode of the EM360 Podcast, Analyst Zeus Kerravala speaks to Jason Dover, CPO at FileCloud, as they discuss:The world of enterprise file storageContent collaboration and security Caring less about underlying infrastructure and more on surfacing content that meets end-user requests

Prof. Steven van Belleghem is an international speaker, EM360 partnered analyst and one of the world’s leading experts in customer experience.He helps the likes of Disney, Booking.com and Microsoft to develop their CX strategies by incorporating the latest technologies. He is also a highly sought-after presenter and commentator, recently sharing a stage with Barack Obama.In today’s episode of the EM360 Podcast, Head of Content Matt Harris speaks to Steven as they discuss:The customer experience landscapeWhat the biggest companies in the world are looking at right nowBuilding a customer-oriented company culture

Automated Security Validation. Involving tools, scripts and platforms to emulate true-to-life attacks, Automated Security Validation is a key part of assessing the readiness of the security infrastructure and guiding prioritized remediation. But how does this implementation of automation really work to empower human expertise? How does all of this relate to compliance? And what words of wisdom can be given for those looking to level up their security strategy in 2024?In this episode of the EM360 Podcast, Analyst Jonathan Care speaks to Thomas Pore, Director of Product Marketing at Pentera, as they discuss:The pen-testing landscape How important testing and validating areEmpowering human expertise and remaining compliant

Generative AI is changing the world of customer service. From deflection and reducing agent headcount using virtual agents/chatbots, or using automation to reduce handle time and after-call work, a lot of the conversation about generative AI in the customer service space has been centred around cost reduction. But what are some of the more exciting, emerging use cases for AI in the space? And what key challenges can be solved?In this episode of the EM360 Podcast, Analyst Zeus Kerravala speaks to Ping Wu, CEO at Cresta, to discuss:Improving experiences for the end customerHow AI can transform your businessAdvice for large enterprises attempting to build these solutions in house

It seems like VPN products are consistently the initial access vectors for ransomware groups and targetted attacks. This was demonstrated in the recent Ivanti Connect Secure zero-day vulnerabilities, as well as Cisco when they admitted last year that Akira Ransomware was specifically targeting their VPNs.But what is the real problem with VPNs - and are they vulnerable by design? How do they fit into wider security architectures and strategies? In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Benny Lakunishok, Co-Founder and CEO of Zero Networks, to discuss:The problem with VPNs‘Insecure by default’?ZTNA and remote access solutions

Kevin Lee is the Chief Digital Officer, Consumer at BT Group. Responsible for the overall vision and strategy for all digital products and services across BT’s consumer brands, Kevin works across the UK’s biggest brands including BT, EE and Plusnet. In this role, Kevin oversees a team of product, digital strategy, design, research, and engineering creators to drive innovation and deliver great products to extend BT’s market leadership and surprise and delight millions of customers.   Kevin has a long track record of digital leadership, including roles at eBay, PayPal, Visa, Samsung, Whirlpool and GE Healthcare, in the UK, US, Italy, Korea and beyond. He’s passionate about tackling challenging business and customer problems, working with brilliant growth mindset teams, and driving impact for the customers whose lives are touched by the products and services he and his teams deliver. In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Kevin about:The future of apps - and what separates the good and the badMastering customer experience Lessons learned from 15+ years of digital leadership

Data movement. The art and science behind moving data through the power of technology. An essential part of how modern businesses operate, the movement of data can encompass the replication, synchronisation and effective storage of company data. But what data movement challenges and obstacles are hurting the way that companies utilise their data? How will the data movement space look over the next 5 years? And what key pieces of advice can be given to those looking to level up their data movement?In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Harry Carr, Chairman and CEO at Vcinity, to discuss:How data movement impacts the business worldData movement challenges and obstaclesFuture trends in the movement space

Rainfall. Temperature. Humidity. Natural disasters. Human methods of reading and predicting weather can be tracked all the way back to native tribes and ancient civilisations - and it’s still prevalent in the modern world today. Whether (no pun intended) it’s an agricultural organisation looking to leverage precipitation data for planting schedules, energy companies looking at temperature trends to predict energy consumption patterns or transportation outfits looking to avoid delays, mastering weather data can really help modern companies to protect themselves against the unknown. In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Christian Schluchter, CTO at Meteomatics, to discuss: Key use cases of weather dataMastering data access and predictive analyticsThe importance of being data driven

Rapid breach response. The art of quickly reacting to a security breach or incident. Key for minimising the impact of attacks and ensuring your team is as effective as possible, rapid breach response is an important part of any security strategy. With the rise and innovation we see in the automation space right now, how could automation be implemented into a security strategy to level up the efficacy of rapid breach response?In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Devin Johnstone, Security Operations Specialist at Palo Alto Networks, to discuss: Demystifying rapid breach responseImplementing and leveraging automation in RBRAdvice for SOC teams and shifting mindset

Maximize business value with data products — they incorporate essential data and related capabilities to meet key business objectives. Data products contain datasets, related metadata and a wide range of functionality to understand if data is fit for use. But unlike relying on a raw dataset or data pipeline to generate value, data products deliver a comprehensive, packaged solution that enables data users to achieve their data-driven goals with easier accessibility.In this EM360 Podcast episode, Head of Content Matt Harris sits down with Nathan Turajski, Senior Director of Product Marketing at Informatica. They explore how to:Drive better business outcomes with data productsUnderstand the benefits of user-friendly and efficient consumptionImprove AI, analytics and customer experience initiatives

The audit process is broken. CISOs and CTOs have faced a multitude of challenges under this outdated audit landscape, and the efficacy of companies are being stunted by a system that desperately needs updating. But how can technology be leveraged to streamline or even transform that auditing process? And what does the future of infosecurity compliance look like?In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Leith Khanafseh, Managing Director of Assurance and Compliance Products at Thoropass as they discuss:The old audit landscapeChallenges for CISOs and CTOsMultiframeworks and the future of compliance

Violeta Martin is Vice President, Commercial Sales EMEA at DocuSign.She has over 15 years’ experience growing and leading high performing teams in a variety of fast growing startups and enterprise companies, including Oracle and SAP, thanks to a background in software engineering. Docusign, the revolutionary CX-first tech company that allows companies to manage electronic agreements on different devices, recently partnered with WhatsApp to facilitate quick and secure contract signing through the world's most popular messaging platform. In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Violeta as they discuss:Why businesses need to consider a mobile-first strategy to retain customers The value of multi-channel delivery for creating the best customer experienceThe evolution of the agreement process alongside consumer behaviour trends

In the world of complex supply chains, it’s not enough to secure our own data but also ensuring that third party vendors we work with have robust security.When it comes to proactively stopping threats and mitigating issues, supply chain monitoring and ensuring a secure software supply chain is crucial to keep organizations’ data safe.  In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Rahul Sasi, Co-Founder and CEO at CloudSEK, to discuss: Current state of cloud computing securityCommon vulnerabilities in the software supply chainRemote work, cloud reliance and mitigating risk

In 2024, the conventional approach of responding to threats is dead. As cyberspace becomes more complex, interconnected, and sophisticated, companies are beginning to recognise the shift from a reactive stance to a proactive one. This shift isn’t just a technological upgrade - it’s a fundamental change in mindset that can cause ripples throughout the business. In this episode of the EM360 Podcast, Analyst Jonathan Care speaks to Uri Dorot, Senior Product Marketing Manager at Radware as they discuss:AI-powered attacksResponsive protection vs proactive protectionHow proactivity works in practice