Gear Up for Change: New AI Regulations

Organizations must proactively engage in comprehensive assessments to futureproof
AI initiatives and maintain a competitive edge in an increasingly regulated landscape. 
A thorough and multifaceted assessment process is required to accurately identify, track, and manage AI-related risks and comply effectively with impending regulation, like the EU AI Act.

When rapid growth
leads to exponential risks

We’ve identified and mapped over 1,600 AI risks sourced from AI regulations, industry standards, and scientific best practices. The rapid advancement of AI technologies, including the proliferation of Large Language Models (LLMs) and intelligent agents tools bring immense potential but also necessitate a heightened sense of responsibility.

Regulations and Compliance

staying ahead of regulatory compliance is not just about adherence; it’s about survival.

Legal risk
AI regulations carry the potential for significant fines, as well as damage to reputation and trust.

Market access
Affect a business’s ability to operate in certain markets, like the EU.

Business Risk

While AI promises significant business value, mismanagement or poor implementation can lead to substantial risks and financial losses.

AI Implementation
Implementation issues may incur risks such as costly implementation,
lack of adoption and insufficient oversight.

AI governance
Effective governance is crucial to mitigate risks and ensure responsible use. It includes establishing AI policies and integrating AI risks into corporate governance.​

Welcome assessAI

AssessAI provides organizations with the tools to navigate the evolving AI landscape. Our platform offers in-depth assessments and a robust framework for tracking and managing AI risks at both organizational and system-specific levels. Designed for a responsible approach, it ensures compliance and fosters a secure AI ecosystem.

What You’ll Get

SOME ANIMATIONS HERE

What We Cover

Standardization

Evaluating and ensuring consistency and uniformity across different AI systems and use cases.

Alignment with Business Needs

Ensuring AI models are up-to-date and aligned with changing business needs.

Operational Excellence 


Evaluating each stage of the AI lifecycle to guarantee operational procedures are robust and adhere to regulation.

AI Assets Integrity 


Assuring data quality and accuracy, as well as the accuracy of data sources and models.

Mitigations and Controls

Reviewing the design and implementation of current governance assurance and controls.

Legal and Ethical Issues 


Ensuring responsible and fair practices such as data privacy, bias mitigation, and transparent communication.

assess AI Brochure