Democratizing AI: Transforming Your Operating Model to Support AI Adoption

AI for Everyone

The big technology companies achieved early successes with AI. Some even built their specialized hardware, machine learning frameworks, and research and development centers. These companies entered new markets, providing artificial intelligence-led services and products, often out-competing the incumbents. They were rewarded with impressive growth.

artificial intelligence has become a strategic imperative. Early adopters are achieving massive returns, while others risk falling behind. Yet, with artificial intelligence knowledge and resources scarce, most companies cannot copy the FAANG approach. Even if their vast resources were more readily available, it’s hard to reboot an organization without disrupting the bottom line. Most executives need to work with the resources available — their existing people, processes, and technology.

Fortunately, any organization can implement and scale AI today. With the emergence of enterprise AI platforms that automate and accelerate the lifecycle of an artificial intelligence project, businesses can build, deploy, and manage AI applications to transform their products, services, and operations. As the pioneer of automated machine learning, DataRobot has the wider capabilities needed for an efficient end-to-end AI project, with a platform supported by data analysts who integrated their business intelligence and data visualization tools with artificial intelligence to quickly transform processes and decision-making.

Changing the Business Model


Microsoft has restructured significantly over the last decade. Today, there is no Windows division. Everything is increasingly centered around AI. Similarly, before 2015, Google used to make no mention of artificial intelligence in its earnings calls. Now it’s a core focus area. Netflix’s transformation is even more impressive. Having been founded in late 1997 as a DVD sales company, it quickly pivoted into a rental by mail. In 2000, it launched the streaming service many know today and became an artificial intelligence pioneer through its AI-powered, user-friendly interface and recommendations. The now-defunct Blockbuster reached its peak in 2004, employing 84,000 people, but it failed because it didn’t embrace the digital revolution. Its memory lives on in business school textbooks as a cautionary tale about failing to adapt to technological change.

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