Responsible AI Solutions for a Trusted Future | HCLTech
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Overview

Our Approach
HCLTech’s approach to responsible AI is rooted in its foundations of trust and social responsibility. As a trusted partner to more than 10,000 clients we provide mission critical support across all major verticals, including solutions for high stakes areas like Financial Services, Healthcare, and Public Services. HCLTech has a longstanding commitment to improving our communities and planet. These foundations Responsible AI foundations lead to sustainable and scalable .

Our Values
HCLTech’s core values of Integrity, Inclusion, Value Creation, People Centricity and Social Responsibility serve as guiding principles for the actions we take and the capabilities we build. They provide a cornerstone for responsible adoption and deployment of AI, and enable us to deliver value for our company, clients, and the world. Learn more about our core values .

Overview

Our Capabilities

We have developed frameworks, methods, and tools that empower HCLTech and our clients to ensure actions and outcomes align with our core values. This foundation for implementing responsible AI enables us to prioritize fairness, transparency, accountability, security, and privacy.

Our expertise focuses on promoting responsible AI practices, reducing risks, and maximizing value for your organization. Key capabilities include:

  • Responsible AI consulting and risk assessment
  • RAIpilot for impact assessment documentation
  • Content safety moderation
  • TrustifAI framework and index
  • The ORA toolbox with over 30 responsible AI tools
  • Security measures and features in AI Force
challenges

Current Challenges

AI, and particularly Generative AI (GenAI), has ushered in an era of remarkable productivity and innovation across industries. However, this progress is often marred by dissatisfaction with return on investment (ROI) and frequent program failures. Our experience shows that success hinges not on identifying business problems or technology choices, but on the adoption of Responsible AI principles.

In our upcoming report with MIT Technology Review, 87% of respondents prioritize responsible AI, yet only 15% are prepared to implement it effectively. Additionally, 76% see it as a competitive advantage. This matters because properly executed AI builds trust, hence driving customer adoption of enterprise AI.

The five stages of responsible AI

Establish foundational policies

Every organization should start with a well-defined policy and set of guiding principles for responsible AI. These foundational policies should align with the organization’s ethical standards and operational needs.

Identify key stakeholders

Successful responsible AI implementation requires involvement across departments, including technology, IT, business, legal, and risk and compliance. These stakeholders should be represented in the responsible AI office and serve as champions of responsible AI within their organizations.

Develop a responsible AI architecture

Effective IT architectures encompass foundational principles and tools, and can leverage capabilities from trusted partnerships. This architecture serves as the backbone for implementing and scaling responsible AI across the organization.

Encourage user adoption and acceptable use

User training, acceptable use policies, and change management processes are crucial for ensuring adoption of responsible AI at scale. Proper training helps ensure that employees, users, and partners understand and adhere to AI usage guidelines.

Look to refinement and continuous improvement

AI systems require ongoing refinement based on user feedback, incidents, and evolving AI advancements. Establishing a feedback loop helps organizations respond to emerging challenges and improve their responsible AI practices.

Responsible AI at HCLTech

Established robust governance frameworks around AI/GenAI that enable responsible and ethical use of the technology.

Responsible AI frameworks and capabilities that provide key guardrails for fairness, transparency, accountability, security, and privacy.

Established an Office of Responsible AI and Governance that drives implementation and innovation of scaled responsible AI practices within HCLTech and capabilities in products and services.

Enabled subject matter experts with experience on NIST frameworks, Europe AI Act, ISO, Risk and Compliance, ethics, and bias mitigation that work together on responsible AI at scale.

Hallmarks of Responsible AI

So what characterizes good, responsibly developed AI solutions? From our proven track record, such deployments are characterized by three hallmarks of responsibly deployed AI.

User centricity

Building user trust through experience

Drawing on human-AI partnership

Interested to Learn More?

Reach out to us today.