Zeta Global (ZETA) The 38th Annual Roth Conference summary

Industry disruption and AI adoption

• AI is seen as a disruptive force, but robust software platforms with deep integration and proprietary data are positioned to benefit, while thin, workflow-only applications face existential threats.

• Adoption of AI is expected to be gradual, especially for complex, mission-critical systems like ERP, with incremental improvements layered over existing platforms rather than wholesale replacement.

• Companies that embrace AI and leverage proprietary data are achieving higher returns and stickier client relationships, with net retention rates and ROI metrics cited as evidence.

• The market is experiencing volatility and uncertainty, with CIOs and CFOs facing pressure to innovate while cutting costs, leading to cautious, structured AI adoption strategies.

• Industry leaders expect a multi-layered architecture with interchangeable AI components, anticipating a few dominant AI platforms but also commoditization and vertical specialization.

Business models, partnerships, and financial performance

• AI is driving new revenue streams, operational efficiencies, and partnerships, such as collaborations with OpenAI and ServiceNow to build agentic solutions and voice-enabled platforms.

• Financially, leading firms report strong growth, high EBITDA margins, and robust free cash flow, with some achieving Rule of 50+ performance and focusing on shareholder returns.

• AI is foundational to sales processes, enabling real-time decision-making and measurable ROI for clients, which strengthens competitive positioning and customer retention.

• Internal adoption of AI is improving productivity, reducing cycle times, and in some cases allowing for business growth without proportional increases in headcount.

• Companies are structuring innovation teams separately from IT to foster experimentation and rapid adoption, while emphasizing employee safety and a culture that encourages learning from failure.

Market trends, risks, and future outlook

• Open source continues to gain traction, especially in databases, but integration and security remain key concerns for large enterprises.

• Pricing models for AI services are still evolving, creating challenges for cost forecasting and adoption, but simplification is expected over time.

• The industry is in the early stages of AI adoption, with volatility in market valuations reflecting uncertainty about future revenue streams and winners.

• Complexity and mission criticality are seen as protective moats; companies with deep integration and proprietary data are less vulnerable to disruption.

• Long-term, AI is expected to enhance efficiency and profitability, but not to fully displace enterprise software or its major vendors within the current decade.