What is generative AI?

In simple terms, generative AI (GenAI) is a type of artificial intelligence that can create new content including text, pictures, and sounds by learning from existing data it has been exposed to. The sources of knowledge leveraged by GenAI can be restricted and confined through parameters and security to focus the GenAI solution on a specific task or function (e.g., contact center responses, contract generation, training modules, etc.).

GenAI uses advanced computer programs called large language models or foundation models to understand, synthesize and generate human-like natural language responses and information based on material it has been trained and fine-tuned against.

Some of the ‘services’ and capabilities of GenAI solutions include:

Generation
  • Synthetic data generation
  • Marketing communications
  • Employee support
  • Customer support
  • Market research
  • Credit risk modeling
  • Personalized financial planning
Reduction
  • Real-time risk assessment
  • Fraud detection & case summarization
  • M&A due diligence
  • Investor relations communications
  • Employee training and institutional knowledge management
  • Post-call summarization
Transmutation
  • Foreign language translations
  • IT development / coding
  • Sentiment-driven market analysis
  • Regulatory compliance by interpreting changes
  • Business intelligence reporting generating visualizations
  • All written communications
Knowledge access
  • Access to financial industry corpus of knowledge
  • Access to institutional knowledge
  • Retrieval augmented generation
  • Historical trends analysis
  • Regulatory knowledge / compliance
Emergent behaviors
  • Dynamic portfolio management
  • Regulatory planning support
  • Financial planning support
  • M&A strategy support
  • Operational efficiency planning support
  • Client relationship management
  • Strategic business planning support

 

Rail yard

Focused on solving business and mission challenges

Generative AI is reshaping industries and fundamentally changing how businesses and governments operate. According to the CGI Voice of Our Clients research, 80% of executives say their organizations are exploring generative AI.

Even with its rapid advances and hype, we don’t see GenAI as a standalone technology. We start with the business problems and often help clients realize its potential by combining GenAI with other technologies like digital twins, conversational AI, and traditional AI. We connect it with foundational technologies like responsible use of data and cloud to make sure the solution is scalable and brings demonstrable ROI to the business.

Importantly, we explore GenAI ourselves within CGI across various use cases—from generating bid responses to analyzing employee sentiments.

Solar Farm

Responsibly using generative AI to accelerate high-quality outcomes

Through a combination of scientific rigor, human-centric principles and deep industry expertise, we help organizations convert GenAI’s transformative potential into trusted and tangible outcomes. Our GenAI-powered intelligent solutions, like CGI PulseAI, help clients accelerate the implementation of use cases and trusted outcomes by abstracting the underlying technologies, embedding responsible use principles and integrating AIOps.

Our robust frameworks ensure responsible use principles are embedded across the AI delivery lifecycle—from strategy to operationalization, and that emerging regulatory requirements are considered. We focus on the quality of the AI outcomes by applying Explainable AI, or XAI techniques to enable users and stakeholders understand how the GenAI model works. ​

Looking ahead: The age of multi-agent AI ecosystems

AI cornerstone, green plant, CEO on a mobile device

CGI continues to invest in the next wave of AI advancements, exploring areas such as agentic AI and multi-agent AI ecosystems, generative and explainable AI-driven third-party advisors (digital triplets), synthetic data, and hyper-automation. As AI ecosystems become more decentralized and modular, we are leading the charge by ensuring these technologies are both scalable and transparent, providing clear human-AI interactions and outcomes.

Let’s shape the future of innovation together.

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