Inner Circle

Amid the backdrop of organizations facing economic headwinds and uncertainty, it’s no secret that 2023 has been a revolutionary time for AI. Advances in AI are driving enterprises to leverage generative AI capabilities to improve business performance and create stakeholder value. However, AI is only as good as the data that fuels it. Therefore, a flexible data architecture, such as a data fabric, is needed to make trusted data accessible to AI teams so that they can drive impactful AI outcomes like tuning foundation models with proprietary data to create more powerful, customized customer service interactions.

Speed and agility have become essential components for an enterprise to make smarter, quicker decisions and CIOs must empower the organization with the right capabilities and information to maximize benefits and decrease time to value. At the core of a data fabric architecture is the integration of governance, security, observability, and data management capabilities. Once established, organizations can align their data strategy with enterprise goals to create a competitive advantage through data and generative AI.

Join your peers to discuss how CIOs create a data foundation to embrace the age of AI value creation together with actionable takeaways at the end of the evening.

Building the Data Foundations for AI

• What goals do you have around using data insights to create a more efficient business? What challenges are you facing when it comes to those goals?
• How do you create new avenues for accessible data, while fostering data literacy for quicker and smarter business decisions?
• Is your data environment mature enough to move forward with automation and/or generative AI models? What do you need to do to get there?

Leveraging AI in a Competitive Environment

• What business processes are you currently automating and how do you identify the areas of the business that should be automated?
• How do your future automation plans affect cost/resource optimization and people productivity?
• Have you identified small use cases or pilots for incorporating generative AI within the enterprise? What benefits have you realized?
• What does the future look like for generative AI in your enterprise? Are there pressures from the C-suite to implement this before your data environment is mature enough?