HOW TO SUCCESSFULLY SCALE
Companies that adopt an AI strategy, scale through the conscious use of technologies, eliminate background noise from data and define multidisciplinary work teams.
Companies that scale AI strategies plan pilot projects by defining medium-long times for the achievement of intermediate objectives. Generally, the time to pass from the pilot phase to the scale phase is around two years, spending less than proof of concept-oriented companies, but with relevant results.
Companies that scale strategies are equipped with systematic planning, leadership, and definitions of time and responsibility.
90% of the data in the world was created over the last 10 years, but after years of collecting, storing, analysing and reconfiguring information, most organisations cannot manage the huge volume of data and do not know how to clean, manage, maintain or use it.
Companies that scale AI strategies will be able to eliminate the “noise” surrounding the data. They recognise the importance of business-critical data, identifying financial, marketing, consumer, and master data as priority domains, and they are proficient at structuring and managing.
They use appropriate tools such as Cloud-based data sets, data engineering and data science work tables, research and data analysis for their applications
The ability to scale an AI strategy involves the integration of multidisciplinary teams, sponsored and aligned by management. These teams are usually led by data scientists, data modellers, machine learning engineers, AI engineers, data visualization engineers, process engineers, IT managers.