Sold by: Accenture
Deployed on AWS
The Responsible AI Suite brings together several accelerators to help deploy AI Systems with trust and manage compliance against a growing set of regulations.
The following features are offered:
1. Maturity Assessment and Benchmarking
2. AI System's Inventory: create an inventory of all AI systems that an enterprise/organization has in production either manually or automatically by scanning the cloud infrastructure.
3. Risk Screening: Use Risk Assessment Companion to assess risk against EU AI Act and provide a risk score
4. RAI Test Enablement: Apply a library of up to 280+ metrics to evaluate performance of AI systems over different RAI dimensions.
5. Continuous Monitoring: continuously monitor an AI system in real time, by providing dashboards displaying relevant metrics and alerts for missed compliance thresholds.
6. Red Teaming: our approach is designed to detect flaws and vulnerabilities in Generative AI models by designing test prompts and assessing outcomes.
Overview
AI is reshaping the risk landscape, and companies have a growing responsibility to address the ethical implications of AI decisions. There are several recent news headlines from reputable sources, illustrating the various ethical and practical challenges posed by AI.
Organizations must integrate responsible AI into their core capabilities to unlock value. This necessity is driven by regulatory pressure, the need for secure AI solutions, and customer demand for ethical and sustainable AI.
Key statistics indicate that 95% of businesses believe they will be impacted by the EU AI Act, only 30% have implemented a Responsible AI Governance Model, and 75% of consumers won't buy products or use services from unethical businesses. AI risks are systemic across various domains, and regulations dictate the mandates to assess, detect, and manage these risks for high-risk AI systems.
Accenture Responsible AI Suite: A Structured Approach to Operationalizing Responsible AI
Accenture's Responsible AI Suite offers a comprehensive, industrialized framework to help organizations embed Responsible AI (RAI) principles across the AI lifecycle. Designed to bridge the gap between high-level governance and practical implementation, the RAI Suite delivers a phased approach to ensure compliance, risk management, and long-term sustainability of AI systems.
Key Components of the RAI Suite:
1. Establish AI Governance & Principles: Lay the foundation with industry benchmarks, maturity assessments, and a tailored RAI strategy.
2. Conduct AI Risk Assessment: Build a detailed inventory of AI systems-automatically integrated with platforms like Amazon SageMaker and Bedrock-and classify them by risk.
3. Enable Systemic RAI Testing: Apply a reference architecture and over 280 quantitative metrics to assess AI model risks, fairness, robustness, transparency, and more.
4. Ongoing Monitoring & Compliance: Establish centralized monitoring to implement a continuous control plane for compliance and risk mitigation, enabling long-term accountability.
5. Red Teaming: The Responsible AI (RAI) Red Teaming approach is designed to detect flaws and vulnerabilities in Generative AI models. It aims to protect against brand and reputational damage, keep pace with emerging issues, and expose vulnerabilities not traditionally found by cybersecurity testing. The approach involves identifying AI Issues by creating Testing Prompts, Recording Responses and Assessing Results; Using this approach addresses the limitations of traditional manual RAI Red Teaming processes, which are time-consuming, manual, and narrow in scope. It offers advantages such as lower costs, real-time adaptation to emerging issues, advanced detection and understanding of language, a standardized approach to testing and reporting results, and reduced time to market while improving scalability.
The RAI Suite can be offered as a service hosted on Accenture cloud or deployed on client environment. As a service, outcomes delivered can include enterprise-wide RAI maturity assessment, RAI strategy and roadmap, revised RAI policies and controls, risk taxonomy, RAI operating model, RAI training plan, regulations readiness report, updated risk controls and thresholds, data and AI risk test results, mitigated AI risks, RAI monitoring office governance and operating model, AI, prompt and data risk assessment results, and mitigation approaches, to name a few.
Highlights
- Maturity and Risk Assessment: The Responsible AI Suite features tools for assessing the maturity of an enterprise with respect to AI and Responsible AI (RAI), as well as assessing the risk level at both the enterprise and use case levels.
- AI Inventory & Quantitative Testing: The Responsible AI Suite provides a robust capability for organizations to maintain a centralized inventory of AI systems. This inventory can be generated manually or automatically by scanning cloud infrastructure via our partner Securiti.ai. The RAI Suite includes a comprehensive library of over 280 metrics designed to assess AI system and model performance across key Responsible AI (RAI) dimensions.
- Red Teaming approach: detects flaws in Generative AI models. It identifies issues like bias, hallucination, propaganda, jailbreak, profanity, reasoning, politically sensitive content, and the need for disclaimers. The Prompt Perturbation Agent creates attack prompts, and the Target Model responds. Evaluator Agents assess and record responses. Results are reviewed and remediated, achieving faster outcomes than manual testing
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Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/12 months |
|---|---|---|
Tier 1 | Total one-time plus recurring service and license fees for RAI Suite | $1,253,135.00 |
Dimensions summary
This listing uses a single contract-based pricing dimension, Tier 1 (Units). You pay a combined amount that covers a one-time fee plus recurring service and license fees for the Responsible AI Suite. There are no separate tiers, instance sizes, or usage add-ons to choose between. The quantity of units you buy sets your total price. Because this is a contract model, the terms bundle setup and ongoing costs into one negotiated arrangement rather than billing them as separate line items.
Top-of-mind questions for buyers
A unit is the billing quantity you commit to for the Responsible AI Suite. The quantity you buy sets your total price, covering the one-time fee plus recurring service and license fees. The specific scope of each unit is set in your contract terms, so confirm the exact definition with the vendor.
The fee bundles setup work and ongoing services with the software license. Services can include establishing AI governance, running AI risk assessments, testing AI for fairness and accuracy, and ongoing monitoring and compliance. The scope depends on your contract, so confirm the included services with the vendor.
Both charges roll into the single Tier 1 (Units) contract price. The one-time fee covers initial setup and licensing. The recurring service and license fees cover ongoing work over the term. You pay them as one negotiated arrangement rather than as separate line items.
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