When it comes to technology adoption, enterprises often prioritize speed over cost, even if it means sacrificing some efficiency. This trend is evident in the widespread adoption of cloud computing, open source, and generative AI, despite potential drawbacks. The driving force behind this phenomenon is the need for rapid execution to capitalize on market opportunities.

In today's fast-paced business environment, companies cannot afford to move slowly. As an IT executive at a large financial services firm noted, "it's expensive to move slowly when market opportunities require fast execution." This sentiment is echoed by RedMonk's Steve O'Grady, who emphasizes the power of convenience in driving developer decisions. Open source technologies, such as Linux, MongoDB, Git, and MySQL, have gained popularity due to their ability to lower barriers to using great software, allowing developers to focus on getting things done quickly.

Cloud computing, in particular, has become a cornerstone of modern enterprise technology strategies. By providing easy and speedy access to code and hardware, cloud infrastructure enables developers to deploy applications rapidly. This aligns with the priorities of enterprise line-of-business owners, who are more focused on meeting evolving customer needs than counting pennies. While cost is still an important consideration, it takes a backseat to the need for speed.

This trend is also reflected in the adoption of generative AI, which has seen significant investment despite limited success in deployment. According to David Linthicum, "companies are good at spending money [on AI] but bad at building and deploying AI." However, developers are actively using AI tools, such as GitHub Copilot, to build and test code faster. The convenience and speed offered by these tools are driving their adoption, even if the cost-benefit analysis is not always clear-cut.

The emphasis on speed is not limited to developers. Data scientists, who are often constrained to tactical analyses or operational dashboards, have the potential to drive transformative change in businesses. By embracing technologies that enable rapid execution, enterprises can unlock the full potential of their data scientists and stay ahead of the competition.

In conclusion, the desire for speed is driving enterprise technology adoption, even if it means accepting some imperfections. As the business environment continues to evolve at a rapid pace, companies that prioritize speed and agility will be better positioned to capitalize on market opportunities and stay ahead of the competition.