INDUSTRY
Communications, Media and Information Services
Connect. Curate. Comprehend: Unlocking Value Beyond Boundaries
Highlights
- As companies in the information services industry adopt artificial intelligence (AI), they must balance innovation with trust and compliance.
- Responsible and explainable AI is crucial for building trust while ensuring ethical and legal standards are met.
- Frameworks such as the TCS Responsible AI SAFTI tenets© will help information services organizations develop AI systems that are secure, transparent, and aligned with regulatory needs.
AI imperative
The information services (IS) industry is experiencing a transformative phase as advancements in artificial intelligence (AI) continue to expand its capabilities.
AI is no longer just handling basic automation; it’s now helping with decision-making and even completing some tasks that previously required highly skilled human experts. For example, AI-driven chatbots and decision engines are reducing response times and improving accuracy in customer interactions, while autonomous systems are optimizing workflows in highly regulated environments.
Most businesses worldwide have integrated AI into their operations, and many are using it for multiple functions. The rise in AI adoption is changing industries in significant ways. In the information services sector, where regulations around data privacy and compliance are stringent and evolve at a fast pace, this rise in adoption rates means businesses need to adapt carefully.
Information services companies must balance innovating with AI and building trust.
As AI starts to make more decisions on its own, developing trust in these decisions among businesses and individuals becomes essential. This trust depends on two key factors: ensuring AI’s decisions and actions are responsible and easy to understand and aligned with the legal and ethical rules of the information services sector. Getting this right isn’t just about following the rules; it’s imperative for the industry to stay credible and fully benefit from the potential of AI.
By adopting frameworks and practices that prioritize responsible AI, explainable AI, and emerging applications such as agentic AI, organizations in the information services sector can address these complexities and create sustainable value while meeting regulatory and societal expectations.
Chatbots to agentic AI
Early AI applications largely consisted of rule-based chatbots, often used to provide limited customer support or answer FAQs.
For example, SmarterChild, a chatbot available on AOL Instant Messenger and Windows Live Messenger in the early 2000s, could engage in basic conversations and provide information such as weather updates or stock quotes. However, it struggled with more sophisticated tasks.
Over time, AI has become smarter. It can now better understand user questions and learn from real-world interactions. This progress has given rise to agentic AI—specialized AI agents that work like smartphone apps, each handling specific tasks.
Agentic AI brings some exciting improvements. One of its standout features is the ability to make decisions independently. These systems can take in and analyze data in real-time, learning from every interaction. For instance, imagine a generative AI (genAI) system that handles magazine subscriptions. It wouldn’t just suggest new titles; it could also negotiate prices, complete purchases, keep user preferences up to date, and more, all with minimal human input.
In the information services industry, with its large-scale data handling, client confidentiality, and strict compliance mandates, agentic AI has the potential to be transformative.
However, as these AI systems become more independent, it’s crucial to keep them responsible, transparent, and secure. This is especially important in regulated environments where trust and accountability are non-negotiable.
Responsible AI
Within a regulated ecosystem, trust is not optional; it is foundational.
Information services organizations must demonstrate that their AI-driven decisions are ethical, secure, and legally compliant. These needs can be addressed through a holistic framework called the TCS Responsible AI SAFTI tenets© based on five tenets: secure, accountable, fair, transparent, and identity protecting (SAFTI). This holistic mechanism is designed to embed responsibility and transparency into AI solutions.
Fig 1: Pillars of TCS Responsible AI SAFTI tenets©
TCS Responsible AI SAFTI tenets© for AI development and deployment
Fig 1: Pillars of TCS Responsible AI SAFTI tenets©
For AI systems to gain widespread acceptance and trust, they must also be explainable. In a regulated sector such as information services, explainable AI is key to making complex AI decisions easier to understand. It helps create transparency, accountability, and compliance, essential for building trust in AI systems.
Another aspect crucial to AI systems is responsible AI, which makes a real difference in people’s lives. For instance, financial services can help more people access credit, supporting goals such as financial inclusion. When organizations use AI responsibly, they can make fair and unbiased decisions, helping underserved communities access financial services and opportunities they might not have had before.
Explainable AI: Transparency in regulated industries
At the heart of trust is understanding how AI systems make their decisions. Deep neural networks, which power many advanced AI solutions, can behave like black boxes, which lack the ability to offer any insights into how they arrived at their conclusions. This lack of interpretability raises concerns for regulated industries, where clear justifications for automated decisions are often a legal requirement.
Explainable AI addresses these challenges by making AI-based decisions both intelligible and traceable.
It offers several benefits. From a regulatory standpoint, explainable AI offers a higher level of transparency by explaining the rationale driving the AI model’s decisions. For instance, in financial services, if a customer is flagged as high risk, companies should be able to understand why. This could be due to their credit history, a sudden job change, or other factors.
Innovation and compliance
It’s a common belief that AI and regulatory compliance are incompatible. However, in reality, they can coexist with a robust framework in place.
By integrating explainable AI into AI design and ensuring alignment with SAFTI principles, information services organizations can safely explore advanced capabilities such as genAI for content creation and agentic AI for autonomous actions.
Agentic AI grants systems the autonomy to make real-time decisions, but this level of independence requires additional safeguards.
As AI evolves, IS organizations must adopt solutions that balance innovative potential with responsible oversight. The TCS Responsible AI SAFTI tenets© framework can act as a guide for building trust in AI systems at every stage. By following its principles, information services companies can integrate advanced AI into their daily operations, speed up decision-making, and stay in line with regulatory requirements.
Organizations that excel in the information services industry will strike the right balance between creativity and compliance, ensuring trust remains at the heart of their AI strategy. By focusing on responsibility and explainability, they can unlock transformative value and set themselves up for long-term success in a world increasingly powered by AI.
