The match offered a front-row seat to how impressively robots can move and react almost like humans. Robot combat just got a lot more interesting in Hangzhou, China. Four Unitree G1 robots, each steered by a human operator, went head-to-head in a tournament called Unitree Iron Fist King: Awakening! The event took place right next to Unitree's massive new factory and drew a lively mix of tech fans and people just curious to see what all the buzz was about. This wasn't only about showing off robotic strength; it gave everyone a front-row seat to how impressively robots can now move and react almost like humans.

Data lies at the core of all business strategies. It has been generated at an unparalleled rate since the outbreak of the epidemic that has led the entire world to go digital. Organizations have experienced an exponential increase in footfall on their web properties and become data-rich. Now, the majority of organizations want to tap into this data asset to improve their business further and gain a competitive edge. Once the business objective is decided, the executives bake it into their strategic goals which is what the business wants to position itself in the next three to five years.

More companies in every industry are adopting artificial intelligence to transform business processes. But the success of their AI initiatives depends on more than just data and technology -- it's also about having the right people on board. An effective enterprise AI team is a diverse group that encompasses far more than a handful of data scientists and engineers. Successful AI teams also include a range of people who understand the business and the problems it's trying to solve, says Bradley Shimmin, chief analyst for AI platforms, analytics, and data management at consulting firm Omdia. "The technologies and the tooling that we have available is skewing more and more toward enabling and empowering domain professionals, the business users, or the analytics professionals to take direct ownership of AI within companies," he says.

Over the past decade, many organizations have come to recognize that their future success will depend on data and AI (artificial intelligence) capabilities. Expectations are high and companies are heavily investing in the area. However, our experience advising organizations in diverse industries suggests that many have also become disillusioned in their journey to create companywide, data-driven business transformation. This article discusses some of the common pitfalls in the implementation of data and AI strategies and gives recommendations for business leaders on how to successfully include data and AI in their business processes. These recommendations address the core enablers for data and AI capabilities, from setting the ambition level to hiring the right talent and defining the AI organization and operating model. Many companies are currently investing in data and artificial intelligence (AI). Since the terminology varies, the activities may be called AI, advanced analytics, data science, or machine learning, but the goals are the same: to increase revenues and efficiency in current business and to develop new data-enabled offerings. In addition, many companies see an increasing responsibility to contribute their AI expertise toward humanitarian and social matters. It is well understood that to stay competitive in the digital economy, the company's internal processes and products need to be smart--and smartness comes from data and AI. Over the past 4 years, our company DAIN Studios has been involved in more than 40 Data and AI initiatives in different companies and industries in Finland, Germany, Austria, Switzerland, and the Netherlands. Our clients are typically large, publicly listed companies.

What is an AI strategist? It's an interesting question, particularly in the context of how artificial intelligence (AI) is reshaping the business world and revolutionizing how companies sell products and services. Here's some of what we've heard "on the street" from tech experts and industry professionals close to AI design. In some ways, an AI strategist is a lot like other roles that follow a particular process from beginning to end, from cradle to grave, or more accurately -- from prototype to reality. But that comparison is only skin deep.