Digital Value Creation

In this episode of Digital Value Creation, brothers Tamas and Arpad Hevizi explore the psychological and career forces behind AI adoption, from the boardroom to the front line. They unpack why CEOs feel pressure to lead with AI, why employees see AI as a career catalyst, and how “workslop,” hype cycles, and vanishing entry-level jobs are reshaping the modern workplace. The conversation goes beyond technology, examining how AI challenges human ambition, expertise, and leadership itself. AI isn’t just changing what we do. It’s changing why we do it.  01:25 – The CEO Pressure Cooker  04:00 – The Rise of Workslop  07:45 – Backward Problem-Solving: The Hammer Looking for a Nail  12:20 – The Expert Paradox  16:10 – The Entry-Level Crisis  20:40 – The Psychology of Hype and Hesitation  25:30 – Redefining Leadership and the Human Role  27:45 – Closing Reflections

In this episode, Tamas and Arpad explore the concept of AI agents, defining their characteristics and discussing the implications of their autonomy in various contexts. They look into the complexities of integrating AI agents into existing workflows, the cultural shifts required for collaboration between humans and AI, and the current state of AI adoption in businesses. The conversation also touches on the trust issues surrounding AI agents and the expectations placed on them compared to human workers. The episode concludes with thoughts on the future of AI agents and their realistic potential to enhance productivity. TAKEAWAYS AI agents are defined by their autonomy and proactivity. The definition of AI agents varies widely across the industry. AI washing refers to mislabeling non-agentic systems as agents. Cultural implications arise when integrating AI agents into the workforce. Managing AI agents at scale presents unique challenges. Trust in AI agents is a growing concern among users. Expectations for AI performance are often higher than for humans. AI agents can potentially outperform humans in specific tasks. The current state of AI adoption is still in early stages. Future discussions will focus on specific use cases for AI agents. CHAPTERS 0:00 - Introduction to AI Agents 03:05 - Defining AI Agents 06:01 - The Complexity of Autonomous Agents 08:50 - Cultural and Ethical Implications of AI Agents 11:52 - Managing AI Agents at Scale 15:02 - Current State of AI Agent Adoption 18:03 - Trust and Expectations in AI Agents 21:01 - Closing Thoughts on AI Agents

Join us for another dynamic episode of Digital Value Creation, where  brothers from the worlds of AI hardware and AI software tackle the most pressing AI trends shaping our work and lives today. ✨ In this episode: Gemini 2.5 vs GPT-4: Two years post GPT-4's release, Google's Gemini 2.5 is out! Does it truly outperform OpenAI and Anthropic? And do we really need more AI in our personal lives? AI Integration in Daily Life: From groundbreaking real-time translation glasses to advanced text-to-video capabilities for creators—how is AI becoming more accessible and integrated into our daily routines? Hype vs. Real Value: Fresh insights from recent Chief Strategy Officer summits highlight the growing gap between AI hype and practical solutions. Are we guilty of creating technology in search of a problem? Autonomous Enterprises & Uncertainty: As businesses move towards autonomous AI agents layered atop quantum computing, can we handle the increasing uncertainty and lack of explainability? Welcome to the era of the 'unexplainable enterprise.' Hybrid AI & Determinism: Discover why hybrid AI solutions balancing deterministic and probabilistic methods are essential—especially in critical areas like loan processing and fraud detection. Generative AI Adoption Trends: Surprising insights from McKinsey’s latest AI survey reveal sales and marketing as leading sectors for Gen AI use. Which industries are truly benefiting? Career Transformation with AI: How AI tools are empowering both beginners and experts alike—accelerating careers, enhancing skills, and eliminating the need for traditional consulting. 🔥 Whether you're deep in AI development, strategizing its deployment, or just passionate about staying ahead in a rapidly evolving world, this episode is packed with insights you can't afford to miss. Hit subscribe for more future-proof strategies! 🌟

🎙️ Digital Value Creation Podcast: Future-Proof Your Career 🚀 Join us as we explore top AI trends for 2025 and their transformative impact on careers. From the rise of AI agents and robotics to the integration of AI as a core enterprise system, we unpack how you can adapt, thrive, and lead in the AI-native era. Key topics include:     •    AI as Your Collaborative Partner: How agents and physical AI are reshaping work.     •    Data and Analytics Evolution: Why understanding AI tools and data platforms is critical.     •    Enterprise AI Adoption: Moving from experimentation to operational excellence.     •    Edge AI and Industry Applications: Discover how AI is solving real-world problems.     •    Skills for the Future: AI literacy, design thinking, and leading cross-functional change. 🧠 Key Takeaway: The future is AI-native, and staying ahead means embracing change, leveraging technology, and developing digital leadership skills. 🎧 Tune in now to discover how to future-proof your career for 2025 and beyond. Don’t forget to like, share, and subscribe! Introduction: Future-Proofing Your Career (00:00 - 01:02)     •    Overview of the podcast theme and hosts' introduction. AI Becoming More Capable (01:03 - 04:07)     •    The evolution of AI agents as collaborative partners.     •    Leveraging personal strengths in the AI-native workplace. The Physical Evolution of AI (04:08 - 06:17)     •    Integration of AI in robotics and physical systems.     •    Preparing for robotic AI in industry workflows. AI as a Core Enterprise System (06:18 - 10:18)     •    The impact of AI on analytics and decision-making.     •    The shift from training to inference in AI systems. AI Operations and Enterprise Integration (10:19 - 14:51)     •    From experiments to enterprise-grade AI.     •    Managing inference costs, tools, and AI literacy. Transformational Impact of AI (14:52 - 19:05)     •    Industry-specific applications of AI across fields.     •    Edge AI and privacy-aware solutions in real-time environments. Real-Time Collaboration and Communication (19:06 - 21:37)     •    Real-time language translation for global collaboration.     •    Emotional intelligence in AI-driven communication. Design Thinking and User Experience (21:38 - 23:52)     •    The importance of user-centric design for AI adoption.     •    Integrating AI into workflows for maximum impact. Takeaways for 2025 (23:53 - 27:01)     •    Why AI literacy, leadership, and cross-functional collaboration matter.     •    Embracing AI as a universal and accessible skill. Closing Thoughts and Call to Action (27:02 - End)     •    Encouragement to stay curious, adaptable, and AI-native.     •    Call to share feedback and engage with the podcast community.

Are you excited about AI but unsure how to actually generate value from it? In this episode of Digital Value Creation, we explore the hype cycle of AI, discuss the emergence of AI agents, and delve into real-world examples of how businesses are using AI to drive tangible results. We also discuss the challenges of measuring AI's ROI and the importance of balancing experimentation with a focus on value creation. Tune in to gain valuable insights into navigating the evolving landscape of AI and learn how to unlock its true potential. #AI #DigitalValueCreation #Innovation #HypeCycle #AIAgents #ROI Chapter Breakdown & Titles: 0:00 Introduction - Navigating the AI Hype Cycle 1:00 The Challenge of Measuring AI's ROI 2:00 Why the Tech Industry Embraces AI So Quickly 5:43 The Risks of AI Hype 7:02 How Companies Make Progress with AI 8:23 The Rise of AI Agents 10:33 What Makes AI Agents Different? 11:13 Real-World Examples of AI Agents in Action 12:43 Managing the Risks of AI Agents 13:48 Creating Guardrails for AI Systems 16:52 The Importance of Audit Trails in AI Systems 17:30 Continuous Learning and Cultural Shift in AI 18:46 Key Takeaways for Implementing AI

In this episode, we reflect on our journey with AI over the past year, sharing how we use AI in both our personal and professional lives. Broadcasting from the Bay Area this time, we explore practical, day-to-day applications of AI tools, discussing how we've evolved from experimenting to leveraging AI for true productivity gains. We share personal insights, like using Perplexity for deeper research, creating custom GPTs to better communicate with diverse work teams, and even translating a family novel with AI from Hungarian into an English audiobook for future generations. The conversation covers AI use cases across different tools—Claude, Gemini, GPT, and more—and includes practical tips for integrating AI into workflows while staying compliant with corporate policies. Tune in to hear about: The impact of voice interfaces and custom GPT personas on daily productivity. Lessons learned from hosting an AI innovation tournament with over 200 teams. Best practices for balancing AI-driven convenience with data security and compliance. Examples of using AI for translations, personalized research, and ideation across multiple business functions. Join us as we dive into real-world AI strategies and share insights on staying productive and focused in a rapidly changing tech landscape. As always, we want to hear your own daily AI applications in the comments!

In this episode we dive into the growing phenomenon of AI fatigue, a sentiment increasingly felt by companies as they navigate the overwhelming number of AI technologies and startups in the market. We discuss the complexities of the AI gold rush, where massive investments and high expectations are met with varying degrees of success and skepticism. The conversation highlights the challenges buyers face in making informed decisions amidst the AI hype and the critical need for selecting the right use cases and vendors to drive real value. We also emphasize the importance of AI literacy and education within organizations to bridge the gap between potential and actual productivity gains. The episode further explores the economic implications of AI investments, particularly the significant role of AI hardware and chip makers, and the pressure on companies to justify the high costs associated with AI development. As we review strategies for surviving the AI hype cycle, we advocate for a use case-centric approach, urging companies to focus on real business problems rather than pursuing AI for the sake of it. We conclude by reflecting on the balance between innovation and process efficiency, encouraging you to be disciplined in their AI endeavors while remaining open to transformative ideas that could reshape their businesses.

🌟 Insights from IMAGINE 2024: Navigating the Realities of Gen-AI Implementations 🚀 In this episode, we share our learnings from a recent customer event in Austin, Texas, where we had the opportunity to connect with fellow executives and discuss the realities of Gen-AI implementations. 🤠 We explore three key takeaways from the event: To overcome the experimentation cycle, companies should pick a direction, identify an impactful area for their business, and experiment on the "how" rather than the "what." 🎯 We discuss the pros and cons of applying generative AI to core vs. non-core business areas, considering factors such as industry competition and potential disruption. 🧩 The conversation also touched on the potential game-changers in AI, with multimodal AI and agency being identified as critical for scaling up to enterprise-grade solutions. 🚀 Throughout the video, we emphasize the importance of continuous education in the rapidly evolving field of AI. As models and use cases keep advancing, it's crucial to maintain a modest and open-minded approach to learning. 📚 Join us in this engaging discussion as we navigate the exciting world of AI together! 💡 Don't forget to share your thoughts, reactions, and resources in the comments below. 📝 #IMAGINE2024 #AI #GenAI #BusinessStrategy #ContinuousLearning #AustinTX

In this episode, we discuss the latest trends and insights in the AI space based on our recent experiences at various tech events. We start by sharing a fascinating Taiwanese tradition of using Kuai Kuai chips to ensure smooth operation of electronics. The conversation then moves to the impact of AI on corporate strategy, the shift towards smaller, more efficient AI models, and the current state of generative AI adoption in companies. We emphasize the growing importance of AI skills for job seekers and discuss how AI can be leveraged to upskill and accelerate impact. We also explore the rise of lightweight AI models and their significance in making AI more accessible globally. The challenges of trusting AI systems, including interpretability and tolerance for mistakes, are discussed, along with suggestions for creating a trusted AI workflow. The video concludes with a unique Kuai Kuai song composed using AI tools, showcasing the creative possibilities enabled by artificial intelligence. Chapter Headings:  00:00 - Introduction: AI Trends and Kuai Kuai Chips  00:35 - Kuai Kuai Chips: A Taiwanese Tradition for Smooth Tech Operation  03:19 - World Economic Forum: AI's Impact on Corporate Strategy  05:30 - Microsoft Build: Focus Shifts to Smaller, More Efficient AI Models  07:30 - Generative AI Adoption: Experimentation vs. Scaling  11:18 - The Importance of AI Skills for Job Seekers  14:00 - Upskill and Accelerate Impact - You can not be satisfied with ‘average’ 16:55 - AI on the Edge - Democratize access, lower energy cost, reduce environmental impact   19:18 - Challenges in Trusting AI: How to select ‘fault tolerant’ use cases and improve guardrails  24:40 - Conclusion and Kuai Kuai Song #AI #MachineLearning #TechTrends #Innovation #Upskilling #KwaiKwai References:  BCG Study: https://www.bcg.com/publications/2024/from-potential-to-profit-with-genai Deloitte Study: https://www2.deloitte.com/content/dam/Deloitte/us/Documents/consulting/us-state-of-gen-ai-report-q2.pdf Microsoft / LinkedIn Study: https://www.microsoft.com/en-us/worklab/work-trend-index/ai-at-work-is-here-now-comes-the-hard-part WSJ: https://www.wsj.com/articles/tech-job-seekers-without-ai-skills-face-a-new-reality-lower-salaries-and-fewer-roles-db63f6e0 Ethan Mollick’s Blog: https://www.oneusefulthing.org

In our latest episode of Digital Value Creation, my brother and I continued our discussion on the personal AI journey from entertainment through education to efficiency and effectiveness. We started with a manifesto: don't roll your own large language model (LLM)! With over 500,000 open-source LLMs available, we believe most businesses don't have problems complex enough to require developing a brand new model from scratch. Instead, companies should invest their time and resources into fine-tuning existing models and optimizing prompts, search, and other parts of the AI pipeline.  We emphasized that the real edge for businesses is figuring out how to integrate AI outputs into their unique workflows and processes through the use of agents. Rather than just talking to us, AI needs to actively help accomplish tasks and solve real business problems in an economical way. This requires carefully considering the cost-benefit tradeoffs in terms of compute resources, context window sizes, precision, and more. Usability and seamless integration are key - adding friction defeats the purpose of AI automation. We discussed the fast-moving legal landscape around AI and how some companies are proactively addressing it, such as Adobe training on licensed images. The battle between AI companies and content owners is quickly evolving into a licensing model. Finally, I shared results from a poll showing nearly 30% of respondents are already using AI for business effectiveness, with coding as the top use case. While there are open questions around IP protection, AI is proving valuable for internal code refactoring, testing, and documentation. Exciting new innovations like AI software agents show the potential for AI to resolve real-world coding issues at increasing rates.  The AI journey is evolving rapidly, and we'll continue to discuss the latest developments. Please subscribe, like, and reach out with your own thoughts and experiences!

In this episode we explore the recent developments in Generative AI and the 4E Model of AI Mastery: Entertainment, Education, Efficiency, and Effectiveness. We discuss Microsoft's acquisition of Inflection's Pi chatbot, the monetization concerns surrounding AI systems, and the strategies employed by big tech companies like Microsoft, AWS, Google, and Adobe in the AI space.   We also ‘delve into’ AI's impact on academia and how it is changing the way we use language, as evidenced by Professor Nicolai J. Foss  analysis of word frequency changes in social media due to GPT. We highlight the growing popularity of smaller AI models and their performance improvements, such as Gemini Nano's integration in Samsung S24 for real-time language translation.   The episode also covers the potential of Gen AI in media, with tools like Sora and Pico, and their impact on advertising, training videos, and the media industry. We discuss the advancements in voice generation, including ‘Eleven Labs' work in text-to-voice and voice-to-voice generation, and its various applications.   Moving from the entertainment phase to education in AI mastery, we introduce Ethan Mollick's book "Co-Intelligence" and the importance of understanding AI tools as collaborators and partners. We also address the shift in academia from research to application and the need for educational institutions to evolve.   Finally, we explore AI's impact on the job market, the rapid changes in skill requirements, and the importance of staying ahead by moving towards efficiency and effectiveness in AI mastery.   Join us as we navigate the ever-evolving landscape of AI and learn how to harness its potential for digital value creation.

This episode focuses on the insights gained from the inaugural Wharton Gen AI for Business Transformation course. We discuss a study conducted by Boston Consulting Group, which found that consultants with access to GPT-4 outperformed those without AI by 40% in terms of quality and efficiency. The study also revealed that AI serves as a performance leveler, enabling even the worst performers to match the performance of top consultants without AI. This finding has implications for talent sourcing and global competition. The episode also touches on the stages of AI adoption, referred to as the "4Es": entertainment, education, efficiency, and effectiveness. We emphasize the importance of moving beyond personal efficiency gains and focusing on driving business outcomes. The biggest challenge in scaling AI adoption is explainability, as the inherent creativity and randomness of AI models can lead to trust issues. We suggest adopting a portfolio approach, engaging teams in experimentation and education, and identifying one or two projects where AI can disrupt or replace major elements of the end-to-end process. The conversation concludes with a preview of future topics, such as AI agents and the move from content to action.

In this episode, we dive into the remarkable experiences and groundbreaking announcements from LEAP 2024 held in Riyadh, Saudi Arabia. With an overwhelming turnout of over 215,000 attendees and a staggering $13.4 billion in investments, the event showcased Saudi Arabia's ambitious drive to become a global digital leader. Underpinning this transformation is the Vision 2030 initiative, aimed at diversifying the economy beyond oil through significant investments in technology sectors, including AI, which is expected to contribute 15% to the GDP. Highlights include the government's substantial support in attracting tech giants like AWS, Cisco, Dell, IBM, and ServiceNow, who announced major projects like regional cloud services, data centers, and local manufacturing. The event also spotlighted local innovation, with significant investments in Saudi startups and the development of advanced technologies like Aramco's METABRAIN LLM. LEAP 2024 not only reflects Saudi Arabia's technological ambitions but also poses questions about the impact of such government-led initiatives in reshaping the global tech landscape.

Dive into the how AI can accelerate your career!  In this episode, we explore the critical role of artificial intelligence in shaping careers and driving leadership in the digital era. Whether you're in tech, business, or any field in between, understanding and leveraging AI is no longer optional—it's essential for staying ahead.    Discover why now is the pivotal moment to embrace AI, with insights from the World Economic Forum and leading experts. Learn about the resources available to jumpstart your AI journey, from free online courses offered by tech giants to advanced learning paths at top universities. 💡   We'll discuss the steps to not just learn about AI but to apply it in impactful ways, transforming businesses, drive growth and innovation. This episode is a call to action for aspiring AI leaders and anyone looking to harness the power of AI to enhance their career, drive business value, and lead with confidence in the age of digital transformation. Don't just watch the future unfold—be a part of shaping it with AI. 

This episode discusses the impact of AI in business, focusing on its value creation, challenges, and the future of AI-driven enterprises. The hosts, who work for AI-focused companies, share insights on AI trends, business applications, careers, and leadership in AI-enabled workplaces. We explore topics such as code generation, the monetization of AI technologies, the role of large language models (LLMs), and the importance of AI in decision-making and automation. Additionally, we address the need for regulation, the potential of retrieval augmented generation (RAG), and the development of specialized LLMs for enterprise applications. The conversation also touches on the importance of reskilling and becoming a better AI leader.

These are my first impressions from Davos 2024 around AI 1 - AI and GenAI is everywhere from LLMs to oil/gas to supply chains 2 - countries and companies taking risks will outperform those that are cautious 3 - Companies struggle to go beyond experimentation due to lack of prebuilt use cases and industry solutions by providers 4 - Trust is main concern. Who do you trust to hold your data? LLM providers? Hyperscalers? 5 - GenAI gets beyond content generation to autonomous process creation and management 6 - Who will benefit from GenAI the most? Companies? Chip makers? Hyperscalers? Is there real value creation or just a rent to the hyperscalers?

I can't believe it's already been almost a year since game-changing AI like DALL-E and ChatGPT burst onto the tech scene. Even though many AI tools have been around much longer, GPT is what captured the magination of of all us. The energy and hype reminds me so much of the early blockchain and crypto days 10 years ago. The buzz, the startups, the dreams of getting rich quick. But looking back, blockchain didn't really change businesses as profoundly as we thought it would. So will generative AI follow the same path, or can we learn from history this time?

So here we go again. Inflation, recession and uncertainty. While these things happen every decade or so, noone likes a downturn. The last short downturn in 2020 actually accelerated digital transformation, investments and value creation. It can happen again if companies use the right digital playbooks.

I got into technology value creation exactly 19 years ago. I still remember how it happened. I read an article in the Harvard Business Review that made me question everything I was doing as a software executive. It was an article by Nick Carr, titled “IT doesn’t matter”. The article claimed that technology added no value. Or specifically, technology didn’t create any strategic advantage. Why? Because technology was everywhere, cheap and available to anyone who wanted it.  I disagreed with the article and wanted to do something about it. So I spent almost 20 years trying to prove the author wrong. In some ways he was right and in many ways he was wrong. No matter what, a single article changed everything I ended up doing for a living and made me obsessed about the value technology can create.  Here's what happened.

In the last few weeks, I was back on the planes meeting with clients and investors in London, New York, and San Francisco. We often talked about how the role of digital is changing for businesses and investors. How the early digital experimentations have all grown up,  real value is created now and many companies are becoming digitally reborn.  But not all.  Some struggled to take advantage of the digital revolution during the pandemic and may not be quite ready for the digital-first competition ahead. There were common themes I heard across geographies and industries.  For example: In past disruptions and uncertainty, leaders could just ”throw people” at those problems. Not anymore. With talent shortage, the great resignation, and great migration - digital tools became to go-to remedy for all problems in business. How is the digital remedy working out?