Building Bridges: How Team Topologies Can Transform Generative AI Integration
Applying a Team Topologies approach in contexts that are introducing generative AI involves structuring your teams and their interactions to maximize the benefits of generative AI while minimizing potential challenges. Here’s how you can implement this:
Understand Team Topologies Framework
Familiarize yourself with the four fundamental team types:
Enabling Teams: Help other teams to overcome obstacles.
Complicated Subsystem Teams: Focus on areas requiring specific expertise.
Stream-aligned Teams: Directly aligned with the flow of work and customer needs.
Platform Teams: Provide internal services and tools to reduce cognitive load on Stream-aligned teams.
Identify Your Generative AI Use Cases
Define Objectives: Clearly outline what you aim to achieve with generative AI (e.g., content generation, data analysis, customer service).
Assess Complexity: Determine the complexity of the tasks that generative AI will handle and align them with the appropriate team type.
Form Cross-Functional Teams
Diverse Skill Sets: Create teams that combine AI specialists, domain experts, and business stakeholders to foster collaboration.
Distributed Knowledge: Ensure knowledge sharing across teams to enhance understanding of AI capabilities and limitations.
Establish Clear Interfaces
Define Responsibilities: Clearly delineate roles and responsibilities among teams (e.g., who manages the AI model, who handles customer interactions).
Communication Protocols: Set up effective communication channels to facilitate collaboration and feedback loops.
Adopt an Iterative Approach
Experimentation: Encourage teams to experiment with generative AI tools, iterating on their processes based on feedback and outcomes.
Agile Methodologies: Implement Agile practices to allow teams to adapt quickly as they learn what works and what doesn’t.
Leverage Enabling Teams
Training and Support: Utilize enabling teams to provide training on generative AI tools and best practices to other teams.
Overcoming Obstacles: Enable teams to identify and address technical or organizational barriers to adopting generative AI.
Implement Feedback Mechanisms
Continuous Improvement: Create feedback loops where teams can share their experiences and learnings from using generative AI.
User Feedback: Regularly gather input from end-users to ensure the AI outputs meet their needs and expectations.
Focus on Ethical AI Practices
Governance: Establish governance frameworks to ensure responsible use of generative AI, addressing bias, privacy, and compliance issues.
Transparency: Promote transparency in how generative AI systems operate, encouraging trust among users.
Monitor and Measure Impact
KPIs and Metrics: Define key performance indicators to assess the effectiveness of generative AI in meeting business objectives.
Adjust Strategies: Use insights gained from monitoring to refine team structures and AI applications.
Foster a Culture of Innovation
Encourage Creativity: Promote an organizational culture that values experimentation and innovation, allowing teams to explore new generative AI possibilities.
Recognize Contributions: Acknowledge and reward teams that successfully implement generative AI solutions.
Determining the most appropriate team topology for including generative AI in a tech team
To determine the most appropriate team topology for including generative AI in a tech team, you can create an assessment matrix. This matrix will use specific criteria to evaluate each team topology—Enabling Teams, Complicated Subsystem Teams, Stream-aligned Teams, and Platform Teams—based on their suitability for generative AI integration.
Assessment Matrix for Team Topologies
Scoring Criteria
Assign scores from 1 to 5 for each criterion, where:
1 = Poor fit
5 = Excellent fit
How to Use the Matrix
Evaluate Each Team Topology: Score each topology based on the criteria.
Calculate Total Scores: Sum the scores for each topology.
Interpret Results: The topology with the highest score is generally the most suitable for integrating generative AI into your tech team.
Example Scoring
Team Topology Total Score
Enabling Team: 38
Complicated Subsystem Team: 30
Stream-aligned Team: 45
Platform Team: 35
Based on the example scoring, a Stream-aligned Team might be the most appropriate topology for including generative AI in a tech team due to its high adaptability, strong user interaction, and speed of delivery. However, the final decision should be based on the specific context and needs of your organization. Adjust the scoring based on your team's unique circumstances to ensure the best fit.
Why not an Enabling team instead of a Stream-aligned team?
Choosing between an Enabling Team and a Stream-aligned Team for integrating generative AI depends on the specific context and goals of your organization. Here’s a breakdown of why a Stream-aligned Team might be more suitable in many scenarios, along with when an Enabling Team could be beneficial:
Advantages of a Stream-aligned Team
Direct User Interaction:
Adaptability and Speed:
Integration with Business Goals:
Multi-Disciplinary Skills:
When an Enabling Team Might Be More Appropriate
Overcoming Barriers:
Technical Complexity:
Support Role:
Summary
Choose a Stream-aligned Team if your primary goal is to rapidly develop and deploy generative AI solutions that directly meet user needs and align with business objectives.
Consider an Enabling Team if your organization needs to build foundational knowledge, overcome initial barriers to adoption, or if there's significant complexity that existing teams aren’t equipped to handle.
Ultimately, the best approach may involve a combination of both types of teams, where an Enabling Team lays the groundwork and supports other teams, while Stream-aligned Teams drive the implementation and user-focused development of generative AI solutions.
About the author:
Roberta Lingnau de Oliveira, TTA
I am an accomplished leader in delivery management and service excellence, with over 19 years of experience driving transformative programs in dynamic business environments. As the Head of Delivery at CI&T, I am recognized for my strategic vision, innovative approach, and ability to deliver impactful results.
Connect with Roberta here.
