Some challenges related to management, compliance, and safety need to be resolved to implement AI in the corporate environment. These challenges involve navigating a complex set of obstacles that consider professional, ethical, social, and regulatory factors.
IBM, with the introduction of its Watsonx answer set earlier this year, focused on addressing specific business requirements. The subsequent launch of Watsonx Granite Foundation Models further solidified the company’s AI security track record. The emphasis on meeting business needs continues with the upcoming release of Watsonx on the first of December, which will make Governance widely available to aid businesses in managing and overseeing various AI models effectively.
Watsonx by IBM provides organizations with a comprehensive set of tools for risk control, transparency enhancement, and preparation for future AI-related regulations. Through governance, businesses can implement AI governance processes, monitor models, and take necessary corrective actions to increase visibility and ensure compliance.
Recently, IBM introduced a new suite of tools under the name Watsonx Management, which performs essential functions for controlling and managing Artificial models:
- Watsonx Risk Management: Organizations can mitigate risks associated with AI models, particularly those powered by foundational or large language models (LLMs), with the help of governance. These models can pose risks due to the quality of training data, including information gathered from unreliable internet sources.
- Enhanced Transparency: Addressing the need for greater transparency in AI model decision-making processes, Watsonx offers tools and procedures to enhance accountability and improve the understanding of AI models and their outcomes.
- Compliance Readiness: Businesses need to ensure that their AI models comply with evolving AI regulations. Watsonx Leadership can assist companies in preparing for and anticipating future regulations, translating them into actionable policies for adherence efforts.
- Governance and Monitoring: Through governance, businesses can effectively manage and monitor their AI models, offering tools for automated AI management processes, design monitoring, and preventive measures to maintain control over AI operations.
- Improved Visibility: Governance provides increased visibility into AI processes, allowing organizations to monitor and evaluate the performance and behavior of their AI models for informed decision-making and issue resolution.
IBM Consulting is expanding its corporate expertise to help clients implement responsible AI practices, including automated model governance and broader corporate governance, addressing areas such as AI ethics, corporate culture, training, regulatory compliance, risk management, and cybersecurity threats.
As part of the IBM Watsonx AI and Data program, Management, along with other offerings like AI assistants and data storage solutions, aims to support businesses in scaling and accelerating their AI initiatives. IBM also offers intellectual property protection for its Watsonx models developed in-house.
In summary, businesses adopting advanced AI technologies face significant challenges in leadership, compliance, and safety. Safeguarding data privacy, addressing ethical concerns and biases, ensuring compliance with evolving regulations, enhancing transparency and accountability, and maintaining control over AI initiatives are critical aspects that IBM’s Watsonx suite, along with other leading AI service providers, aims to address. IBM’s comprehensive approach and technical capabilities position it uniquely to assist businesses in navigating the complexities of responsible AI adoption successfully.
