High quality data is the foundation of successful artificial intelligence (AI) initiatives at leading organizations. It’s clear to me that teams succeed with AI when they aggressively look to leverage all accessible data, while remaining mindful of people and technology.
Based on Accenture research, organizations tend to increase their AIQ score (or measurement of effective AI adoption) when they combine in-house AI innovation with strong collaboration across multiple external partners. These "Collaborative Innovators" excel at all three ingredients that make up a solid AIQ score: technology, people and data.
When talking with clients about planning a strategy for AI, I focus on the importance of balancing the large amounts of data generated from multiple internal sources with the increasing opportunity to integrate external information sources.
Beyond the identification of new data sources, it’s vital to think about identifying specific data partners, legacy data integration, and the need to govern data use for responsible and ethical application. I always encourage people to think less about which specific algorithms they may use, and to focus more on high-value, potentially transformative data content and how it could be applied for maximum benefit.
As part of this approach to maximizing data benefit, it’s important to emphasize the need for collaborative data environments that encourage appropriate access, integration and trusted, secure data sharing.
Our methods for getting started with AI—including identification of opportunities to exploit third party data provided by big vendors—should stand at the center of any strategy. By establishing a strong foundation that enables AI to flourish within your agency, Accenture’s approach to AI will help you get off on the right foot.
For a deeper dive into how data in the cloud powers AI, watch my keynote presentation at the recent Oracle Federal Forum.