Today, users and organizations are experimenting with and deploying solutions that, just a decade ago, would have been prohibitively time-consuming, complex, and expensive. One of the most transformative developments driving this shift is the rapid rise of AI and generative AI (GenAI). Noteworthy shift is occurring in the realm of automation. The gap between the tools and concepts used by large enterprises and those available to small and medium-sized businesses (SMBs) is narrowing. Interestingly, even large enterprises often begin their AI initiatives with small pilot projects - approaches that closely resemble those taken by SMBs.
Of course, there is no rose without a thorn. To the old adage about automation - “garbage in, garbage out,” which highlights the importance of data quality and relevance - we must now add concerns about the “black box” nature of many AI systems. For most users, AI remains opaque, making expertise more critical than ever for successful deployment.