Data Strategy: The Missing Link in AI-Enabled Transformation Webinar
Thanks to an explosion of data, exponential increases in computing power and storage capacity, and better algorithms, artificial intelligence (AI) and machine learning (ML) capabilities are poised to revolutionize business processes. These intelligent capabilities will not only underpin increased automation and process optimization, but also improve business results with better and faster planning, decision-making, and risk forecasting.
However, many businesses are not yet seeing significant business impact from their AI/ML investments. A recent survey of 247 executives by HBR-AS finds that 61% do not yet have a data strategy specifically optimized for ML and data science.
In an HBR-AS audio webinar, Alex Clemente shared the results of this recent pulse survey about data strategy in the field of AI and ML.
He led a discussion on how organizations can use data and AI/ML to maximize efficiency. With Priyank Patel, VP of Product and Machine Learning at Cloudera, and Sushil Thomas, Corporate VP of Machine Learning at Cloudera, Clemente shared perspectives on HBR-AS’s survey results and discussed:
- The AI imperative and the state of enterprise AI
- Why an effective data strategy is essential to enable applications of AI/ML
- How your company can overcome challenges that surround data and AI
- The promise and pain of cloud solutions for AI/ML modeling
- Lessons from early adopters of data strategy and best practices for an AI-first future
The effective integration of AI/ML models will soon be an existential issue. Now is the time to work through the key data challenges, learn from early efforts, and develop the most effective data strategies and processes for the future.