Artificial intelligence

AI strategy and advisory services

As AI’s power and reach accelerate from automation to creation, we provide up-to-date best practices and designs for developing guardrails, policies and governance, as well as AI operating (AIOps) models. AIOps models address issues of ethics, trust, transparency, explainability, fairness, non-bias, data/model/provenance, privacy, security, regulations, intellectual property and more. We also bring a set of design templates for AI Centers of Excellence.

We help you envision, plan for, and accelerate your responsible AI journey for the good of all stakeholders through our portfolio of advisory services, including:

AI strategy and roadmap

Our experienced multi-disciplinary consulting teams leverage CGI’s Responsible Use of AI methodology and consulting framework to help you crystallize your ambitions and guiding principles, potential risks and mitigations, and the required technical, operational and governance foundations.

Depending on where your organization is on your AI journey, we assess existing strategies, architectures and operations and develop recommendations. Such engagements typically follow 3 phases over a 6-12-week period:

• Discovery and assessment
• Ambition, strategy and blueprint
• Roadmap and plan

Our strategy development approach involves a mix of online surveys and questionnaires, interviews and, most importantly, in-person or virtual collaborative workshops. We leverage templates and tools to determine your vision, and then develop a tactical approach to implement best practices. We focus on targeted AI use cases to ensure a quick return on your investment by identifying opportunities for improved outcomes through AI solutions.

AI maturity assessment

While a maturity assessment is an integral part of our larger AI strategy development approach, it is also offered as a stand-alone service. The assessment provides a realistic baseline of where you are and serves as a holistic and inclusive beginning to build an AI-powered organization.

Using over 150 detailed capability statements, we assess an organization’s current state across three dimensions (direction, operating models, execution) and a cross-cutting range of “AI Golden Threads.” These threads include: organizational purpose, ambition, stakeholder alignment, data management and flow, data-to-insights, insights-to-decisions, decisions-to-automated-actions, generative content creation and intellectual property, guardrails and ethics, policies and governance, privacy and security, fairness, transparency and explainability, sustainability, regulation and compliance, shared value focus, technology and platforms, as well as agile mindset and practices.

Our digital business agility and strategic alignment platform manages the design, distribution, collection and analysis of the maturity assessment. The platform also provides access for clients to explore the findings in visual charts and interactive tools across capabilities, threads and dimensions.

AI design and build services

These services are designed with three objectives:

• Explore, discover and evaluate possible new AI use cases for your organization
• Validate promising use cases from a proof of value to minimum viable product (MVP)
• Rapidly scale successful MVPs to enterprise scale and production.

Our four design and build offerings may be bundled and sequenced together or delivered as a stand-alone service:

AI quick-look opportunity assessment

This is a 1-3-week rapid enterprise scan to identify opportunities, looking at both decisioning / automation as well as generative content creation. The collaborative engagement is centered around a day-long discovery workshop to look at your organization’s…

• Operating processes for decisioning, automation and content creation
• Data landscape
• AI and advanced analytics capabilities
• Technology stack analysis leveraging CGI’s technology-agnostic AI reference architecture
• AI and data governance, policies and guardrails, and operating model

The output is a priority-mapped inventory of AI opportunities (value vs. level of effort vs. risk).

AI discovery and design sprint

This 1-3-week sprint centers around a design workshop to explore 1-3 possible AI use cases. It is facilitated by a multi-disciplinary team of AI, business, process and industry domain experts, and decision and data scientists. Using CGI’s Value in Motion framework, we evaluate your AI value chain, including:

• AI awareness – “state of play”
• Stakeholder alignment and AI vision
• Value drivers
• Decision anatomy, criteria and velocity
• Critical insights
• Maturity assessment
• AI algorithms and models
• Trusted actions (augment, automate, autonomize)
• Training and execution data
• Ethics, transparency, fairness, privacy, regulations, security and provenance
• Proposal for proof of value and minimum viable product (MVP)

AI validation and value sprint

Once a promising new AI use case has been evaluated, this 4-6-week agile sprint develops a proof of value (POV) or minimum viable product (MVP) solution. The approach includes:

• AI design storyboarding
• AI use case definition • Defining the scope of the POV / MVP: Value, Action, Decision, Insight, Data
• Decision design and insight engineering • Assessing data availability and suitability
• Understanding and preparing data
• Exploring the datasets (looking for correlations and patterns)
• Rapid prototyping / pilot of an AI platform (CGI PulseAI hyper-automation and decision engine platform or partner platforms)
• Architectural, technology and platform considerations
• AI risk assessment: ethics, transparency, fairness, privacy, regulations, security, provenance
• Trusted automation / action design; human experience

AI agile scaling and production

After a successful POV or MVP, we use our proven agile development methods to help you rapidly build, within 8-16 weeks, and scale your AI solution. Using CGI and/or partner platforms, accelerators and multidisciplinary, skilled resources, your organization can quickly go from MVPs to enterprise-scale production. Key aspects include:

• Architecture
• Platform selection and set-up
• Partner ecosystem (including cloud, foundation models, large language models (LLMs), digital twins, etc.)
• DataOps + AIOps + CloudOps
• Governance setup: Ethics, transparency, fairness, privacy, regulations, security, provenance
• Data management
• Launch / roll-out planning
• Change management program / training
• Launch go-live support