Cracking the ROI Code: Is Intelligence Meeting the Income Statement? | RAISE Summit 2026

Financial Recognition of AI:

• ServiceNow reported a direct $500 million improvement in P&L from AI-driven productivity gains last year, with expectations for similar impacts in the current year.
• Dynatrace notes that while P&L impact is frequently questioned by investors, the company emphasizes "meaningful value" and trust as prerequisites for ROI in production environments.
• FedEx and Vanta executives argue that AI ROI is often embedded in existing balance sheet metrics (yield, revenue, profitability) rather than requiring distinct line items, as AI is now foundational to operations.
• Dynatrace reports a 350% average return on investment for customers, primarily driven by autonomous agents in regulated industries like retail banking.

Metrics and Measurement Strategies:

• Panelists agree that traditional business metrics (P&L, balance sheet, NPS, yield) remain the primary arbiters of success, rejecting "token maxing" as an illogical metric for value.
• FedEx plans to have 100% of data consolidated for AI by end-of-2027 and aims to reskill its 500,000+ workforce, with an AI literacy program launching December 1, 2025.
• ServiceNow has set a target to rewrite 50% of workflows by 2028 with embedded AI and measures success against existing KPIs rather than creating new artificial scores.
• Vanta highlights that 70% of enterprises experience "shadow AI," with new customers uncovering an average of 140 unsanctioned AI tools, necessitating better governance to capture ROI.
• Dynatrace advocates for "business observability" metrics beyond technical uptime, such as customer journey outcomes (e.g., bag retrieval times at airports, chatbot advice accuracy).

Workforce, Talent, and Reskilling:

• Vanta and Dynatrace note a massive shift in hiring, with a 300% increase in functional engineering roles (e.g., go-to-market, legal, and marketing engineers) in the last three months.
• Dynatrace estimates that 4% to 7% of trained employees become "change makers" who drive the most significant agentic system innovations.
• ServiceNow reports a 25% efficiency increase in its go-to-market team through internal AI adoption.
• Executives emphasize that AI requires new job descriptions focusing on creativity, systems thinking, and subject matter expertise, moving away from traditional IT-centric roles.
• Dynatrace and FedEx acknowledge the retention risk of upskilled AI talent, urging Chief People Officers to develop clear career paths and leadership pipelines for these new roles.
• FedEx launched an AI literacy program to ensure organizational relevance over the next 5–15 years, treating retraining as a non-negotiable investment rather than a cost to be minimized.

Strategic Implementation and Trust:

• Dynatrace and ServiceNow stress that "trust" is the core enabler of scaling AI from development to production, citing the need for high accuracy, guardrails, and persistent data access.
• ServiceNow and Dynatrace utilize "AI Control Tower" concepts to monitor usage, costs, and lifecycle, allowing organizations to deprecate ineffective tools and manage spend.
• FedEx adopts a "fit-for-purpose" model selection strategy, using internal algorithms to choose between open-source, small, and frontier models without user intervention to ensure cost efficiency.
• Vanta differentiates between top-down, high-precision use cases (requiring strict harnesses and evals) and bottom-up innovation (using platforms like Dust for higher-risk tolerance in go-to-market teams).
• Dynatrace identifies three converging trends for future ROI: proactive memory layers, IP sovereignty over proprietary data, and advanced model harnessing for knowledge editing.

Future Outlook and Challenges:

• The panel predicts that "token maxing" will fade as companies focus on solution outcomes rather than technology inputs, with models eventually becoming interchangeable commodities.
• FedEx and Vanta suggest that true ROI may be difficult to isolate immediately due to the complexity of foundational work, such as data consolidation and process rewiring, which are leading indicators of future value.
• Dynatrace warns that "leading indicators" like adoption rates and anecdotal evidence may need to supplement financial metrics in the short term due to the rapid pace of model evolution.
• ServiceNow and Dynatrace anticipate that the ultimate metric of success will be "zero cases" or autonomous resolution of issues, eliminating the need for manual intervention in service desks.
• Executives agree that AI is a cultural shift requiring a complete rewrite of business processes, technology estates, and organizational culture, not merely a technological upgrade.