AI Self Assessment - SilverQ Intelligence

AI Self-Assessment

Create an AI self-assessment for your development team.

Find out where your company stands and how Silver Q Intelligence can support you.

Assessment AI Development Strategy

Answer the following questions to assess the current state of your AI development strategy.

1. What is your primary motivation for using AI tools in your software development?

We expect productivity gains and more output for the further development of our products.

We want to bridge resource bottlenecks.

We want to use AI to document our architectures and processes better.

We want to use AI to help bring the grown structures of our development back to a sustainable architecture and future-proof them.

We want to use AI specifically in creative work to improve our products and implement industry trends faster than competitors.

2. How clearly is the strategic use of AI tools in your software development defined?

We do not yet have a concrete plan for this.

Individual developers are already using tools on their own initiative.

A responsible person or working group is identifying processes and tools.

We are already using AI tools in pilot projects.

We manage the use of AI tools across the organization. AI governance is integrated and part of a continuous improvement process.

3. How clearly do you understand the offerings and terms of commercial providers such as Microsoft, OpenAI, Anthropic, xAI, Google, Zhipu AI, or Moonshot AI?

We have not yet looked into commercial providers.

We are using commercial tools. They mainly come bundled with our development tools, for example Microsoft Copilot.

We have evaluated a small number of providers, understood their offerings and terms, and purchased business licenses.

We have comprehensively aligned offerings and terms with our AI compliance rules.

4. How systematically do you evaluate the use of AI to increase productivity in your development work?

We evaluate the productivity of our employees and processes, but not specifically with regard to AI.

Individual developers have tried AI and provide their subjective assessment.

We started where we assume AI can be used particularly efficiently, for example in UI, reports, or bug fixing.

We have systematically evaluated initial uses of AI tools.

We have an organization-wide system that lets us manage and monitor who solves which tasks with AI tools.

5. How far along is your organization and team in preparing for the use of AI-based coding assistants and agents in development?

We do not yet have a concrete plan for this.

We use components of our development platforms, for example Microsoft Copilot.

We use agents such as Claude Code or Codex in isolated cases.

We have established agents in the company.

We have reached a level of integration where agents independently solve tasks, for example processing bug tickets or implementing features.

6. How advanced are you in the technical handling of AI tools?

We do not use any tools, or only isolated gray-area use by individual developers.

AI tools have been procured, for example business accounts, and are operated with standard models from OpenAI, Anthropic, or other providers.

There is a technical evaluation of the tools, for example model size, context window, benchmarking, and cost-benefit.

The tools are used deliberately, and we rely on experience, benchmarking, and in-house AI experts.

We have integrated our own tools into our system landscape and use AI agents as part of our ecosystem.

7. How well prepared are you to handle business-critical data, such as source code, securely when using AI tools?

We do not use any tools.

The use of the tools takes place in a gray area.

We have an idea of where our source code ends up during use and what may be used for training purposes.

We have a clear understanding of whom we want to expose our source code to and under which conditions. We use AI tools deliberately with risk management in place.

We maintain comprehensive governance for handling business-critical data when using AI tools.

8. How do you assess the use of AI with regard to the protection of personal data?

We do not use any tools.

The use of the tools takes place in a gray area.

We have a general policy that ensures the protection of personal data and try to apply it when using AI tools.

We have implemented clear measures for the use of AI tools and the protection of personal data, for example anonymization, choosing the server location, or running our own models.

The protection of personal data is an integral part of our processes when working with AI.

9. How well do you understand how AI tools handle security-critical data such as passwords or customer data?

We do not use any tools.

The use of the tools takes place in a gray area.

We have a vague understanding of where data from chats with models or agents ends up, for example passwords or excerpts from customer databases.

We have a good understanding of the operational risks that arise when dealing with AI tools, for example unintended deletion of development results by agents.

We have taken measures that address operational security, for example rules such as: passwords must never be entered into a chat.

We maintain comprehensive governance for handling AI tools.

10. Sandboxing refers to restricted environments, for example for file access or networks, in which an AI agent may act independently. How familiar are you with sandboxing?

We do not use any AI agents.

We have no deeper knowledge of the restrictions an agent is subject to, or we have enabled the default behavior.

We have an idea of the environment in which an agent operates and how access can be restricted.

We know the critical resources, such as the company network, the entire computer in the context of the logged-in user, or production systems such as databases, and have established rules.

We have regulated and established sandboxing and AI-agent access to critical resources.

11. How well established are skills and knowledge such as prompt design and context management when working with AI tools in your company?

We do not use any tools.

The use of the tools takes place in a gray area.

We leave it up to the developers how they work with the tools.

We have an idea of what professional use of AI tools looks like.

We offer specific training for our employees to sustainably increase their productivity with AI tools.

12. How is working with AI tools embedded in your collaborative and, where applicable, agile way of working?

We do not use any tools.

The use of the tools takes place in a gray area.

The work still remains with a developer. They may use AI tools to increase personal productivity, for example for generating tests.

We have created a fixed place for AI tools in our development process, for example for summaries in daily meetings or for evaluation and prioritization.

The stages of our process are finely tuned. AI creates detailed issue specifications, independently handles implementations, or carries out tests.

We have already considered post-agile approaches and want to align our work processes more strongly with the use of AI tools.

13. How systematically do you plan the use of AI in testing, quality assurance, and error analysis?

We do not yet have a concrete plan for this.

We have gained initial experience with tools and agents and are identifying potential.

We have a good idea of where we use AI for which purposes.

We can already measure where AI is being used efficiently.

14. How well prepared is the use of AI for development documentation and knowledge management?

Over time, due to grown structures, we have partly lost insight into our internal software architecture and want to restore it with AI.

We have a good overview of our architecture, but would like to document it better and want to use AI to do so.

We want to use AI tools to make our documentation more efficient, for example for automatic architecture diagrams, summaries, and recommendations.

We want to use AI as a sparring partner to explore new approaches and new knowledge in product development.

15. Are there any additional notes or specific challenges?