Enterprises adopting AI are 81% more likely to have advanced data management capability and 73% more likely to report mature cloud capabilities.
The majority of enterprises responding to MIT’s global survey have initiated AI projects, reporting that they are in the planning stages or have already piloted or implemented AI technologies.
When CEOs and senior management teams get involved in defining, piloting, and guiding new AI use cases, AI pilot yield rates jump and more move into production.
Implementing AI successfully requires CIOs to prioritize cloud/data centers, data management, software development, and cybersecurity over the many other projects that compete for their time and resources.
These and many other insights are from MIT Sloan Management Review’s recent study completed in collaboration with SAS, How AI Changes the Rules: New Imperatives for the Intelligent Organization. A copy of the survey can be downloaded here (PDF, 24 pp., no opt-in). It’s a quick, interesting read that provides examples from enterprises actively adopting AI today, sharing their lessons learned. The methodology is based on a global online survey completed during June and July 2019, interviewing 2,280 survey respondents from MIT Sloan Management Review readers. 80% of respondents hold C-suite, board, or management roles distributed across 110 countries. 37% of respondents are from North America, 22% from Asia, and 20% from Europe. MIT Sloan Management followed up with interviews with analytics experts, including practitioners, consultants, and academics. These individuals provided insight into how the drive to implement AI is changing organizational culture, technology strategy, and technology governance.
The following are the key insights from the report:
Enterprise’s enthusiasm for AI is growing, with 62% increasing their spending last year. The majority of enterprises have initiated AI projects and are progressing from planning AI adoption, piloting AI projects, and implementing AI in their operating environments. The MIT study team found those succeeding with AI are differentiated from their peers by how their leadership teams prioritize and commit to planning, pilot, and production-level results while balancing risk and being mindful of the ethical trade-offs AI presents.