Digital Value Creation

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.

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?

If you Google the difference between efficiency and effectiveness you will find over 1.4 billion hits. There are endless opinions from accountants, business strategists, linguistics, and even psychologists on the topic. Clearly, there is confusion out there and my short video won’t clear it up. Instead of deciding on the debate, let me share a story on how a customer of mine uses these terms to create value for their business.

The ultimate success in business is to be considered a value creator. Whether you and I are employees, executives, consultants or vendors we should think about the 5 ways we can add value to the business. - Growth - Simplicity - Speed - New Business Model - Thinking Big

For the last 20 years there has been one big debate around technology innovation. Should you be a first mover or a fast follower? First movers would take on higher risk experiments expecting higher returns, but also tolerating higher rates of failure. Fast followers, on the other hand, would wait for the kinks to be worked out or the market to be validated before investing. So which strategy is better?

I was thinking about the most relevant trends for 2022. Almost everything we know about digital has changed and morphed in the last two years. So I looked at what my peers were predicting about the future. I counted over 500 different trends and predictions and it was hard to find a common theme that resonated with me. In the end, I narrowed them down to 5 major trends that I knew my customers were often talking about. So here is my 2022 prediction list. 1) Hybrid Workforce (People + AI) 2) Decentralized Finance becomes mainstream 3) Business Metaverse emerges 4) Digital Offshoring (Digishoring) 5) Convergence of Employee and Customer Experience +1) First Fully Autonomous Businesses

Welcome to 2022. What a year we have had! While it represented a crisis on many fronts, it also created once in a generation across digital from automation to digital supply chains to new digital customer experiences to blockchain and crypto literally everywhere. I had so many learnings from this unusual year - I chronicled them in 30 episodes in my channel and in several articles in Forbes. Here are my highlights from a year that will go down as the most transformational in a generation.

The majority of the companies nowadays are in some stage of digital transformation. Some are very tactical, improving their website and app maybe or automating basic customer interactions. Others are fundamentally changing how the business operates. Business model innovation and digital transformation are two buzzwords and they are increasingly interlinked. How should you and I think about business model changes as we become more digital?

In the last couple of weeks, I had numerous conversations about what I call the hierarchy of value. A good friend of mine, I call him Jeff, a private equity investor coined this term to me a few years ago. He used this model to decide which improvement projects to invest in and which to pass on in his companies. He wanted simple rules to help his management teams that go beyond hard value and soft value. He even used it in his personal life to decide what to buy and what not to buy. I keep coming back to the simplicity of the model whenever we discuss the value of digital transformation. So what is this hierarchy of value and why does it matter for digital projects?

The massive global talent shortage is driving businesses to automate in even more areas of their operations. Surveys show that more than 60% of the companies already started their automation journey. There are always some tradeoffs, of course, when doing any enterprise-wide initiative. It would be cool if you could deploy new automated processes overnight. If you could just start your fully autonomous processes. But that is not possible. At least not quickly. So companies are making various tradeoffs on their way to their automated future. Here are the 5 biggest tradeoffs I have seen in intelligent automation projects. 1) Top-down vs Bottom Up 2) Hard vs Soft Benefits 3) Speed vs Perfection 4) Pilot vs Scale 5) Short Term vs Long Term

Those of you following this channel, you know this. I’m obsessed with finding out what makes some companies succeed with digital transformation while others struggle. Companies of the same size, same industry, same access to talent, but very different results. \ One key factor is how the digital project gets initiated. Does the transformation start with the CEO or a line manager? Does it really need to happen for the business to reach its goals? Or is it someone’s science project? In my experience, transformation projects seem to take 3 possible paths and the results can be predicted almost on day 1. Here’s why.