Confluent (CFLT) Global Technology, Internet, Media & Telecommunications Conference 2025 summary

AI supercycle and technology evolution

• AI is seen as a much larger and more transformative cycle than previous tech shifts, opening new problem domains and driving a consistent upward trend in benchmarks and capabilities.

• The current AI cycle is still in its early stages, with significant value yet to be realized, especially in enterprise use cases.

• Coding and knowledge work are being rapidly transformed by AI, serving as leading indicators for broader adoption.

• The impact of AI is expected to be underestimated in the short term but will likely be profound over a longer horizon.

• Major new capabilities from AI will fundamentally change how companies operate across industries.

Software industry changes and business models

• AI is driving a surge in software creation, with more applications being generated and a shift toward consumption-based pricing models due to high compute costs.

• Traditional seat-based licensing is less relevant for AI workloads, which require new pricing strategies to reflect ongoing compute expenses.

• The importance of UI as a moat is diminishing as agentic AI and API-driven architectures become more prevalent.

• Companies that effectively harness automation and custom software will gain a competitive edge, making adaptability crucial.

• Open source and standardization are increasingly important, with platforms that integrate and manage real-time data across environments gaining traction.

Real-time data and infrastructure

• Real-time data is becoming essential as software automates more business operations, especially for AI-driven use cases like customer support.

• The ability to process and act on up-to-date information is a key driver for AI effectiveness and business value.

• Managed, cloud-native platforms that offer complete solutions for real-time data are highly differentiated and in demand.

• Integration across edge, on-premise, and multiple cloud environments is complex but critical for modern data infrastructure.