Here at Dataiku, we’re starting 2024 with a bang. First with our three-peat data science, machine learning, and AI partner of the year awards announcement, and now with this news: IDC has named Dataiku a leader in its MarketScape for AI Governance Platforms 2023!
What Is AI Governance?
AI Governance means a lot of different things to a lot of different people. Generally speaking, an analytics and AI Governance framework enforces organizational priorities through standardized rules, processes, and requirements that shape how analytics and AI are designed, developed, and deployed.
AI Governance is linked to MLOps and Responsible AI, to be sure. AI Governance sits at the intersection of value-based (Responsible AI) and operational (MLOps) concepts. And of course the three depend deeply on the regulatory environment, especially in industries like banking, insurance, healthcare, and life sciences or pharmaceuticals.
It is thanks to this holistic view of AI Governance at Dataiku that we’re able to provide such breadth and depth of features to support AI Governance at a range of organizations, no matter what the requirements and use cases for analytics and AI.
Why Choose Dataiku for AI Governance?
IDC said it best in the report when they said:
Choose Dataiku if you need an AI governance platform that prioritizes democratization, trust, and scalability. Dataiku distinguishes itself through powerful integration capabilities, robust governance features, and proactive customer service. It is suitable for businesses of all sizes and has a user-friendly interface that enables users with varying levels of technical expertise to efficiently harness the potential of AI.
But choosing Dataiku goes beyond just AI Governance capabilities. With Dataiku, everyone can get involved in data and AI projects, from business people to analysts to data experts. All this on a single platform for design and production that delivers use cases in days, not months. No matter where they sit, users work in a safe and governed way that helps manage risk and create trust to drive high-quality outputs and value for your business.
What Dataiku Brings to the Table for AI Governance
Still not convinced? Here’s a deeper dive into how Dataiku drives safe AI at scale with oversight:
One Central Place
Dataiku Govern acts as the central control tower — one place to track data initiatives and ensure the right workflows and processes are in place to deliver Responsible AI. Bonus: it’s the same place where analysts, data experts, and business people are building and working with data, not an additional product — this makes the handover smooth, from designing and building AI systems to their governance.
As Generative AI initiatives take hold and your company scales its AI footprint, centralized program oversight is crucial for maintaining visibility and reducing risk.
Any-Model Governance
Dataiku offers a flexible and inclusive system that manages AI models regardless of their origin – whether developed within Dataiku or externally. IDC recognizes Dataiku's capability to integrate seamlessly with various platforms, allowing users to operationalize models created outside its system. The emphasis on auditability, fairness, and explainability positions Dataiku as an inclusive platform.
Compliance-Ready Templates
Organizations often struggle with the manual processing of regulatory policies, lacking the time and resources to thoroughly analyze each policy individually. This often results in compliance delays and increased complexity, making it challenging to keep up with rapidly evolving regulations.
Dataiku's ready-to-use solutions accelerate compliance readiness with both industry-specific and regional regulations such as the EU Al Act and GxP, helping you to keep an edge over regulations of any kind.
Adaptable AI Governance Workflows & Processes
Ensure the flexibility of governance workflows to accommodate various regulatory frameworks, making them more context-specific. Templates in Dataiku provide clear steps and gates to explore, build, test, deploy, and maintain AI projects. Assign stakeholders, capture notes, and attach relevant documentation to each stage of a workflow to ensure the process is documented and tracked, from design to delivery.
Sign-Offs & Approvals
Getting stakeholder approval for data projects can be challenging (but necessary) to manage and track. Dataiku makes it easy. Project owners can request and collect sign offs on models or project bundles prior to promoting them to production. This ensures audit readiness on deployment decisions — especially critical in regulated industries. Lack of appropriate reviews and sign-offs mean blocked deployment until proper approval is obtained.
Model and Bundle Registries
Dataiku’s model registry provides a centralized way to see all models (whether developed in Dataiku or externally) in one place, versioned, and with performance metrics and project summaries for leaders and project managers. The bundle registry delivers the same benefits for project bundles, so versions of analytics pipelines and project artifacts can be governed and managed according to a defined workflow.
Project Value & Risk Qualification
In Dataiku, stakeholders assess project value and risk using a customizable qualification framework. With limited resources to execute a growing number of AI project requests, a common value-risk matrix helps leaders compare initiatives, determine oversight requirements, and determine which projects should be prioritized for investment.