Prerequisite: None
Business success rides on a new generation of applications that are powered by artificial intelligence (AI), machine learning (ML), and advanced analytics.
For years, TDWI research has focused on the use of AI, ML, and advanced analytics to solve business problems. In this session, TDWI senior research director James Kobielus will look at the principal scenarios in which data-driven intelligent applications are being used to boost business performance, efficiency, agility, and other outcomes. He will focus on the following key tactics:
- Developing a digital business transformation strategy that hinges on AI, ML, and advanced analytics
- Gaining a competitive advantage through proactive adoption of disruptive technologies such as generative AI and AI-augmented business analytics
- Building an end-to-end IT infrastructure that can be evolved rapidly to support new applications of AI, ML, and advanced analytics
- Embedding AI, ML, and advanced analytics models into all back-end and customer-facing processes
Encouraging in-house collaboration among data scientists, programmers, business process management specialists, and other specialties in developing and operationalizing AI, ML, and advanced analytics applicationsImplementing a comprehensive set of governance, transparency, and other technological and procedural guardrails to mitigate the downside risk from deployment and usage of AI, ML, and advanced analytics applications