Digital Value Creation

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.TAKEAWAYSAI 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.CHAPTERS0:00 - Introduction to AI Agents03:05 - Defining AI Agents06:01 - The Complexity of Autonomous Agents08:50 - Cultural and Ethical Implications of AI Agents11:52 - Managing AI Agents at Scale15:02 - Current State of AI Agent Adoption18:03 - Trust and Expectations in AI Agents21:01 - 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.

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 #ROIChapter Breakdown & Titles:0:00 Introduction - Navigating the AI Hype Cycle1:00 The Challenge of Measuring AI's ROI2:00 Why the Tech Industry Embraces AI So Quickly5:43 The Risks of AI Hype7:02 How Companies Make Progress with AI8:23 The Rise of AI Agents10:33 What Makes AI Agents Different?11:13 Real-World Examples of AI Agents in Action12:43 Managing the Risks of AI Agents13:48 Creating Guardrails for AI Systems16:52 The Importance of Audit Trails in AI Systems17:30 Continuous Learning and Cultural Shift in AI18:46 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.

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 #KwaiKwaiReferences: BCG Study: https://www.bcg.com/publications/2024/from-potential-to-profit-with-genaiDeloitte Study: https://www2.deloitte.com/content/dam/Deloitte/us/Documents/consulting/us-state-of-gen-ai-report-q2.pdfMicrosoft / LinkedIn Study: https://www.microsoft.com/en-us/worklab/work-trend-index/ai-at-work-is-here-now-comes-the-hard-partWSJ: https://www.wsj.com/articles/tech-job-seekers-without-ai-skills-face-a-new-reality-lower-salaries-and-fewer-roles-db63f6e0Ethan 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.

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 AI1 - AI and GenAI is everywhere from LLMs to oil/gas to supply chains2 - countries and companies taking risks will outperform those that are cautious3 - Companies struggle to go beyond experimentation due to lack of prebuilt use cases and industry solutions by providers4 - 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 management6 - 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 mainstream3) Business Metaverse emerges4) 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 Up2) Hard vs Soft Benefits3) Speed vs Perfection4) Pilot vs Scale5) 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.

Why do some companies seem to completely digital transformations effortlessly while others struggle? I believe organizations can achieve the same flow state as people when faced with challenges. If the majority of the people working are in flow sate then their organizations are too. And that is what happens when new innovation projects including digital transformations just seem to click.

I'm clearly not in the studio this week. In fact, I  am in Las Vegas at HIMSS, the largest healthcare tech conference. We had around 20,000 executives here live and thousands more online. This was the largest post-pandemic business conference focused on digital transformation.  This was also one of the first times so many businesses came together to share how they dealt with the crisis, what they learned from it, and what technologies helped them succeed. More importantly, what they will do differently going forward. While the primary topic was healthcare, there were great insights that any industry can use. Here are a few that stood out for me.

If you ask someone how to create more value in business, you're likely to hear the obvious - drive revenue growth and cut costs. That is of course the physics of any business. But every executive knows that it is not that simple. To increase revenues, you likely have to spend more and if you cut costs, revenue tends to suffer. Either way, revenues, and costs are just indicators, they are not specific actions you can take. In the last few years, business strategists redefined what value creation means. It is all about the steps you take to improve customer experience and increase the customer's willingness to buy. Let's see how that may change your digital value creation strategy.

My latest post is on the massive post-pandemic digital expansion due to labor shortage and massive economic growth.While businesses focused on cost and lean operations last year - now it is all about growth, and major digital expansion.Companies are moving from tactical to the strategic use of automation, analytics, and customer experience like never before.

We are living in an unprecedented labor market. Over 10 million jobs were unfilled in May 2021 and millions of people quit their companies last month. While there are many reasons this is happening, one thing is clear. The expectations of your workforce have fundamentally changed in the last year. I believe digital technologies can help stop the exodus and attract new talent.Here is how

I went back on the road this week. I was having real meetings with real people in real offices in New York. Returning to normal business? Hopefully. The recurring topic of the discussion was this. How will hybrid work change how we work together and the technologies we use going forward?

Every few months I take a look at recent research studies and surveys on the state of digital transformation. Normally there are a dozen such surveys in 6 months. This time I found over 100 reports. This is a testament to the fact that digital transformation is now a top 5 strategy goal at most companies.  So let's take a look at what the data shows

In the last few months, I noticed a remarkable shift in businesses from cost to growth. In 2020 digital transformation mainly focused on cost efficiencies and labor arbitrage. This year it is all about growth, digital customer experience, and better employee experience. Economic expansion and labor shortage create great opportunities for companies with a digital-first mindset.

One thing that sets private equity apart is its relentless focus on value creation. That's why we have this channel. We want to bring  PE value discipline to any digital transformation program.A value creation plan, or VCP, is an enterprise-wide view of all initiatives that will improve the company. Above and beyond business as usual. These can be both digital and non-digital projects.There are some best practices that make this value creation plans particularly effective. There are 3 great things private equity firms do when they create value creation plans.1) Have very few but high impact initiatives2) Have the right executive own the results3) Treat value delivery as important as deadlines and budgets

When talking to digital-first companies I noticed 5 big differences in their way of thinking. 1) Digital is a business model2) Digitizing core functions3) Scaling digital capability4) Measuring business impact5) The C-Team's ownership of digital

How do you tell your value story in 5 minutes? A good 5-minute value pitch mostly talks about your audience's needs. Never about yours. The first return on investment you will ever demonstrate to a client is the ROI on those 5 minutes of their time. If you waste their time, they will assume you will waste their money.

"Go Fast and Break Things" has been the mantra of disruptors since Facebook coined the term a decade ago. Speed does differentiate industry disruptors from incumbents.But is going faster enough to win the digital transformation race? No. We need more than that.Digital success needs the combination of speed, customer collaboration and positive business impact. Digital leaders like you and I must excel in all these three areas to win. Here is why.

The disruption impacted everyone but not everyone responded equally well. The pandemic, like any crisis, created winners and losers that ultimately can be traced back to a few factors. Here is my summary of what drove the changes in remote value creation.

As we all noticed in the last year, digital projects became an urgent priority at most companies. What was amazing was the speed at which these projects got under way and completed. Urgency became the biggest priority. In normal times there would have been a dozen competing priorities but in crisis mode, it simply became speed and value. Is it possible that project priorities could be that simple even in normal times? Could it just be speed and value? I think so. Here is why.

Some businesses complain that it is difficult to realize the hard benefits of digital programs. In fact, hard benefits seem elusive in many transformation initiatives. Why is that happening? Let's dive into the dynamics of typical corporate finance decisions for the answer.

In business school, a professor told us this: Businesses exist for only 2 reasons: 1) is to make the world better and 2) to turn a profit and not necessarily in that order. His entire course was built around the tangible and intangible value businesses create. As we think about value creation, both tangible and intangible value drivers become critical. Here's how...

Research shows that lack of digital skills is the main reason why 70% of digital transformations fall short of their goals. Unfortunately, this has been the case for years now. Why is the digital skill gap so hard to fill?

It has become quite a cliche by now that years of digital transformations got done in weeks. It is true of course, but the question remains -why? How come that companies that resisted digital transformation for years finally got on board? Here is what I think.

All digital transformations ultimately need to improve customer experience. Digital project's ultimate value is when they increase revenues and business growth through better customer interactions, loyalty, and higher value exchange. Customers buy more from businesses they trust. We all understand trust in human interactions. But what does Trust mean in the Digital World? Let's take a look

There is a paradox in digital transformation. The Digital Leaders seem to accelerate their transformation efforts and focus on scaling faster and broader. At the same time, digital laggards who are behind, do not have the same urgency. They seem to think they have all the time in the world and tend to pilot and experiment instead of scaling. The latest industry research shows that the digital laggards may never catch up. Here is why.

A few months ago I had an episode about the 3 questions CEOs should ask. Why do anything, Why Now and Why You? Some clients and friends used that approach for months and here is what they learned from it

Is your digital team energized or deflated? If they were in a competition, do you think your team would win? Do they show up unstoppable and ready to conquer? Oh, yeah. We are here to talk about the softer side of value creation.Having seen a lot of transformation teams in my career, I can often predict how the team will perform based on how they show up every day and in every meeting.

I obviously love digital transformation and clearly believe that AI, automation and machine learning will help create amazing digital businesses. However way too often I see companies solve the wrong problem with the right tools and the right problem with the wrong tools.Here's what I mean...