IBM Watsonx: An AI Value Creator for Accelerating Your Firm’s AI Governance
Generative artificial intelligence, or GenAI, is now a global phenomenon. Leaders and decision-makers of enterprises creating this transformative technology strive to understand ways to govern, deploy, and ethically manage workflows and roles across the AI lifecycle. Enter IBM Watsonx, the next-gen AI and data platform to build meaningful and explainable AI. Tech leaders across industries can confidently unlock the magic of Gen AI using IBM Watsonx to overcome vague definitions of AI-related risks and inadequate modes of AI governance procedures!
2023 has been an exciting year for GenAI tools that have been routinely used in at least in one business function by a third of organizations. And nearly 40% of organizations are slated to increase their AI investments to adopt the latest GenAI advancements. Additionally, a survey by IDC suggests that the global AI market will likely surpass $500 billion by 2027. Despite the widespread adoption of traditional and GenAI, we are still in the early stages of understanding and managing AI-related risks. However, business leaders warn against blind assumptions that the promise of AI outweighs the associated risks.
In the US, AI has garnered lawmakers’ attention, while corporate America seeks to unlock its merits while also curbing potential risks. The White House recently announced the executive order on the safe, secure, and trustworthy development and use of AI. It also includes the receipt of AI commitments from eight tech giants. Additionally, several federal legislators and state-wide exploratory committees have expressed interest in addressing and protecting against AI risks. Businesses need AI governance or a set of tasks for directing, managing, and monitoring AI workflow and activities in an organization. AI governance tools and governance frameworks are a great starting point for reducing unintended biases and taking more informed steps toward responsible AI.
IBM Watsonx is an enterprise-ready AI and data platform which includes three components and a set of AI assistants to build, tune, and deploy AI models and scale AI initiatives with secure data within the business. The platform aims to help businesses customize AI solutions and leverage the components for specific business use cases.
In this first part of the two-blogs series, let’s examine the components within the IBM Watsonx platform and unravel the technical foundations of Watsonx.governance as an AI value-creator to accelerate AI governance.
Components within IBM Watsonx
Watsonx.ai: It is the studio for building AI tools and AI applications in a fraction of the time and with a fraction of the data. Watsonx.ai’s foundational models and traditional machine learning (ML) capabilities help users train, validate, tune, and deploy GenAI with minimal data, full SDK and API libraries, and cutting-edge prompt tuning capabilities. The studio’s opensource framework and code-based, automated tools and visual data science capabilities make it a secure and trusted studio architecture for AI builders to accelerate AI model lifecycle.
Watsonx.data: Watsonx.data is an open, hybrid, and governed data store with an open lakehouse architecture for enterprises to scale AI workload for all data wherever it resides. It eases connecting and accessing data across the hybrid cloud with in-built data governance, security controls, and automation features. The platform reportedly helps with a 50% reduced cost of data warehouse workloads across multiple query engines and storage and analytics environments by matching the right workload with the right engine. It enables data engineers, data scientists, and business analysts to collaborate in a single environment with a single copy of data.
Watsonx.governance: IBM’s powerful, Watsonx.governance is a brand-new toolkit for AI governance. The platform helps users design AI workflow and models on the principles of responsibility, transparency, and trust. It helps trace datasets, associated metadata, models, and pipelines from their source to monitor AI decisions. It helps consistently track AI models for fairness, transparency, and compliance. Customizable dashboards within the platform improve the accessibility and visibility of AI from data scientists to C-level leaders to govern and enable responsible, explainable, and high-quality AI models.
Watsonx Assistant: IBM Watsonx’s pre-built AI assistants are easy to deploy across business processes and applications. The common implementation use cases include customer service automation, code generation, and HR workflow automation. The conversational AI platform scales operations are built to elevate the experiences of customers, employees, or prospects with intelligent, contextually accurate responses by AI-powered agents and chatbots. Watsonx Assistant also enables seamless self-service support across channels and touchpoints across a business. The platform is reported to guarantee a 370% return on investment in three years of implementation.
Watsonx.governance: Governing Your Firm’s AI Workflow
Almost 72% of decision-makers across 7k+ companies around the globe believe that AI adoption is tied to building massive business advantages, finds a recent IBM study. Therefore, achieving responsible and explainable AI is imperative. Organizations in the healthcare, government, banking, and financial services industries face high regulatory pressures and industry-specific compliance regulations. The implications of non-compliance of regulations for AI governance include hefty legal fines, reputational damage, audits, and litigations. With AI becoming a core aspect of enterprise strategies, leaders of businesses in regulated business and industry landscapes face challenges in implementing AI such as difficulty to trace and justify specific AI workflow and decisions, lack of explainable processes and risk analytics, and awareness of changing AI regulations.
IBM Watsonx platform’s Watsonx.governance provides an opportunity to infuse relevant governance measures into AI initiatives and AI workflow. In the rest of this blog, we will deepen our understanding of the foundational aspects of IBM Watsonx platform’s Watsonx.governance to enable AI governance for building an explainable AI workflow:
- Ethics by Design: IBM is not only known for its trust and transparency principles, but it has also created ‘Ethics by Design’ playbook that is applied across the AI workflow within thousands of systems and processes. The integrated governance framework, Ethics by Design methodology, and AI Ethics’ board manage IBM’s use of AI as well as the technology lifecycle and development pipeline for AI. The enterprise-wide ethics and values around the use of AI are also embedded in Watsonx.governance to help users hold the highest standards for ethical AI deployment.
- Trusted Data Foundation: Watsonx.governance is built on IBM Cloud Pak for Data to streamline data management, enable AI innovation, and foster a data-driven culture. The integration of Watsonx platform with Cloud Pak for Data v4.7 helps organizations address AI implementation gaps like data accessibility and data volume and complexity. Its enterprise-grade infrastructure for data integration, data governance, and data observability accelerates AI journeys and initiatives.
- End-to-end AI Explainability: Watsonx.governance is a comprehensive AI governance platform that organizations can leverage across the entire AI workflow from AI design, building, deployments, monitoring, and centralizing facts for ‘AI explainability’. Without incurring any additional expense associated with upgrading from existing data science platforms, organizations can delegate relevant stakeholders to monitor models during production, live, and audit stages for fairness, quality, and drift. Users can also trace and document data, models, and pipeline origin including techniques, testing metrics, and hyperparameters to improve transparency and identify possible risks.
- Complete Risk Management: With Watsonx.governance, users can automate facts and workflows as per recent compliance standards. The platform helps identify, manage, monitor, and report risks and compliance at a scale. The open architecture supports governance of AI models that are built and deployed in third-party tools. Additionally, the dynamic dashboards and collaboration features enable clear, customizable, and comprehensive access to results.
- Robust Compliance: Watsonx.governance is built for meeting regulatory compliance by leveraging software automation to augment organizations’ capability to prevent risks and address regulatory as well as ethical considerations. These can be achieved without tweaking changes to the pre-existing data science platforms. The platform helps users leverage dynamic compliance and audit dashboards to aid a cohesive view and informed insights tailored as per compliance needs.
Final Thoughts: Time to Govern Your AI Workflow with IBM Watsonx
Any technological breakthrough between its initial adoption and maturity stage leaves stakeholders grappling for answers. As the GenAI use cases grow beyond the hype, decision-makers and IT leaders need an anchor for charting realistic governance protocols for the ethical creation and use of AI. Vague corporate governance policies that are disconnected from technology platforms for screening AI workflow, model, and methodology lead to many false positives, increasing risks for legal scrutiny. Platforms like IBM Watsonx are a perfect match to organizations’ overarching goal of building accountability in their AI workflows to intentionally meet their GRC objectives.
Stay tuned to read part two of the IBM Watsonx: An AI Value Creator for Accelerating Your Firm’s AI Governance.
At iTech, our certified consultants understand the urgency for AI governance and the varying values of AI ethics as a part of their GRC goals across industries. To thoroughly leverage the AI-powered, AI governance platform within the IBM Watsonx, our consultants can articulate how senior leaders and C-suite executives of your enterprise plant a culture of ethical and explainable AI.
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