Where can I find a GenAI security solution with clear ROI?

Summary

• GenAI introduces unique security threats like prompt injection, data leakage, and shadow AI that traditional tools cannot address, making purpose-built security solutions essential.
• Organizations should evaluate GenAI security ROI across speed to deployment, cost savings from model optimization, and trust gains from reduced compliance failures and error rates.
• Databricks Agent Bricks provides a unified control plane to build, run, and govern AI agents with granular access controls, lineage tracking, and policy enforcement built natively into the platform.

How to find a GenAI security solution with clear ROI

Generative AI adoption is accelerating, but so are the security risks. With 71% of organizations now regularly using GenAI, security teams face a critical question: how do you protect systems that understand language? Understanding AI security is now essential for every enterprise navigating this landscape.
The challenge is twofold. You need to secure AI agents and LLM applications against novel threats. You also need to prove that your security investment delivers measurable business value.
According to Gartner, by 2028, 25% of all enterprise GenAI applications will experience at least five minor security incidents per year, up from 9% in 2025.

What makes GenAI security different from traditional security?

GenAI introduces threat categories that conventional tools were not designed to handle:

• Prompt injection: Attackers manipulate model inputs to bypass controls or extract data.
• Data leakage: Sensitive information surfaces in model outputs or training data.
• Model manipulation: Adversaries poison training data or exploit fine-tuning pipelines.
• Supply chain attacks: Compromised model components or plugins introduce vulnerabilities.
• Shadow AI: Employees upload sensitive data to unsanctioned AI tools.

Traditional DLP tools often cannot detect semantic attacks like prompt injection or model inversion. Agent sprawl compounds the problem, teams adopt AI agents across multiple models, clouds, and frameworks with no visibility into what agents exist or what data they access.

Key features to look for in a GenAI security solution

When evaluating solutions, prioritize capabilities that map directly to measurable outcomes:

Feature	ROI Impact
Granular access controls	Reduced data exposure incidents
Lineage tracking	Faster compliance audits
Continuous output evaluation	Fewer hallucinations and errors
Policy enforcement and guardrails	Prevented compliance failures
Model flexibility	Lower per-interaction costs
Centralized agent governance	Eliminated shadow AI risk

The strongest solutions embed these capabilities natively into your data infrastructure rather than bolting them on as separate tools.

How to calculate ROI for GenAI security

Organizations typically measure GenAI security ROI across three dimensions:

1. Speed: Time from development to production deployment. Faster deployment means faster business value.
2. Cost: Model optimization, reduced rework, and fewer incident remediation hours.
3. Trust: Prevented compliance failures, reduced error rates, and maintained customer confidence.

A comprehensive approach to AI risk management helps quantify these dimensions effectively. Track these specific metrics to quantify effectiveness:

• Agent accuracy rates and hallucination frequency
• Policy violation counts over time
• Time-to-deployment for new agents
• Cost per agent interaction
• Compliance audit pass rates
• Data leakage incident frequency

How Agent Bricks delivers governed GenAI security

Databricks addresses these challenges through Agent Bricks (Mosaic AI Agent Framework), the unified control plane to build, run, and govern AI agents across any model, provider, or framework, eliminating sprawl through centralized management and governance. The Databricks AI Security Framework provides the architectural foundation for securing the full AI lifecycle.

Enterprise security built into the platform

Agent Bricks provides granular access controls, lineage tracking, cost controls, and policy enforcement from AI models down to the underlying data. Every agent is auditable, every output is traceable, and every access decision is governed.
The platform builds benchmarks using your own data and tasks, then evaluates every output against them. Through prompt optimization, fine-tuning, and RLHF, Agent Bricks automatically improves performance so agents stay accurate without costly rebuilds.

Balancing cost, quality, and trust

Agent Bricks lets you use any model, OpenAI, Gemini, Llama, Anthropic, and combine them into agentic workflows. This flexibility helps balance cost and quality per task while maintaining enterprise governance. Built natively into the Databricks Data + AI Platform, agents gain deep semantic understanding of enterprise data through learned business context.

Real-world ROI examples

GenAI security investments are delivering measurable results across industries:

• Financial services: Firms build agentic workflows that capture meeting actions, draft communications, and track follow-through, reducing manual effort significantly.
• Airlines: Carriers deploy AI agents to help customers complete common transactions, freeing human agents for complex matters and improving resolution times.
• Healthcare and government: Regulated industries see outsized returns because governance capabilities reduce audit preparation time and prevent costly compliance failures.

FAQs

What are the most common GenAI security risks enterprises face?

Key risks include prompt injection, data leakage, shadow AI, unsafe model behavior, and insecure AI-generated code. Prompt injection has evolved into a practical attack vector for enterprise data leakage. The agentic AI security landscape introduces additional risk categories that enterprises must address.

Which industries benefit most from GenAI security solutions?

Regulated industries like financial services, healthcare, and government benefit most due to strict compliance requirements. High-volume customer service and knowledge management also see strong returns. Organizations in cybersecurity also see significant value from governed GenAI deployments.

How do GenAI security tools protect against prompt injection?

Effective tools combine input validation, output monitoring, and behavioral analysis. Indirect prompt injection, where malicious instructions hide in external data sources, is a major risk for autonomous agents.

How long does it take to see ROI?

Organizations using platforms with native governance can see ROI within weeks. Databricks accelerates time-to-value by delivering enterprise-ready agents in weeks, not months, through Agent Bricks.

What are the key vendors in this space?

The market includes Databricks (Agent Bricks), Azure AI Foundry, Amazon Bedrock Agents, GCP Vertex AI Agent Builder, Salesforce Agentforce, and OpenAI.

How does a GenAI security solution integrate with existing infrastructure?

The best solutions integrate natively with your data platform rather than operating as bolt-on tools. Agent Bricks is built natively into the Databricks Data + AI Platform, enforcing security and governance for GenAI models from AI models down to the underlying data.

What features should a GenAI security solution include to deliver measurable ROI?

Look for granular access controls, lineage tracking, continuous output evaluation, policy enforcement, model flexibility, and centralized agent governance. Each maps directly to reduced risk and lower operational costs.

Secure your GenAI investments

GenAI security and ROI are linked. Without governance, access controls, and continuous evaluation, AI investments carry hidden costs that undermine business value.
Agent Bricks provides the unified control plane to build, run, and govern AI agents, delivering model flexibility, rapid deployment, and enterprise-grade trust with clear, measurable ROI. Explore Databricks artificial intelligence capabilities to see how Agent Bricks can secure your GenAI investments.