THE ELEMENTS OF THE SERVICE
Strategy & Framework — AI Strategy
INTRODUCTION
Artificial intelligence has begun to transform corporate operations at an unprecedented pace in recent years, the likes of which has not been seen since the first wave of digital transformation. However, most organizations today still lack the foundations necessary for AI to genuinely create business advantage rather than just be a series of experimental projects. Success requires more than just one or two well-functioning chatbots or automations — a cohesive strategic framework is needed to clarify how AI fits into the company's operations, in which areas it can create real value, and how to implement it in a controlled and predictable manner. Our Strategy & Framework service is precisely built for this: we establish the operational and technological foundation upon which future AI developments can reliably build. The process always begins with a thorough understanding of the company — we assess business goals, the current technological environment, workflows, as well as data management and security practices. Our objective is to clearly identify which developments will yield quick returns, which represent long-term investments, and which solutions are worth building on for the company's future. Following the assessment, we conduct a detailed AI audit, which breaks down the most significant automation and AI value creation points for each process. These typically include manual, time-consuming administrative tasks, customer service interactions, data analysis processes, and repetitive decision-making situations. Experience shows that even the most basic automations can result in significant time and cost savings, but strategic-level planning goes further: it illustrates how to elevate the entire company to a higher level of digital maturity. A modern AI strategy is incomplete without defining the tech stack. Most companies work with multiple standalone systems that often lack integration — as a result, data is scattered, hard to access, or present in insecure ways. Choosing the right technological foundation not only supports efficient development but also reduces long-term costs and significantly enhances operational security. In our analysis, we compare different AI platforms, cloud providers, and integration tools, then provide a well-founded recommendation from both business and technological perspectives on which is the best choice for your enterprise. One of the keys to successful AI implementation is preparing the management. Leaders must understand how AI systems work, what data they require, what limitations exist, and what risks may arise from implementation. Our management workshops aim to present the economic impact of AI, return models, the regulatory environment, and how to carry out an AI project as safely and efficiently as possible through clear, practical examples. By the end of the process, your business will have a detailed AI strategy that not only maps the current situation but also outlines the specific steps to steadily build an AI-driven operation in the coming weeks, months, and years. The organization will understand how to prioritize projects, what decision points arise during implementation, and what resources will be needed for the successful execution of developments. All of this ensures that AI does not appear as a cost center but instead brings measurable business results: faster processes, less manual work, improved customer experience, and greater competitive advantage. The Strategy & Framework service is the foundation of DetSystems' entire AI portfolio. When these strategic pillars are solidly in place, every subsequent development — whether it's about chatbots, automation, agent systems, or voice-based solutions — will be more predictable, faster, and of higher quality. That’s why we consider this the first and most important step in any AI project.
Strategy & Framework — AI Strategy
Details
1. AI STRATEGY
What does it include?
Complete corporate AI status assessment
Priority list for high-return projects
AI roadmap for 3–12 months
Risk analysis and governance recommendations
Suggestions for automatable and AI-driven processes
Detailed description
The aim of the AI strategy is to provide the company with a clear, feasible, and commercially justified pathway for the implementation of artificial intelligence. During the process, we do not only examine what technological opportunities AI offers, but also the business value it creates in the company's specific operations. This includes a deep understanding of current processes, mapping resources and constraints, as well as identifying the points where AI can deliver real, measurable results.
In strategy formation, we analyze each area individually to see clearly which problems can be solved with AI solutions, which tasks can be automated, and which require more complex intervention. The goal is for the company to receive not just a collection of ideas, but a detailed, time-scheduled plan supported by return calculations, making it clear which developments should be initiated and in what order.
The strategy is not a theoretical document; it is a compass built on the real operations of the company. Therefore, throughout the process, we continuously involve business areas, taking into account internal competencies, technological maturity, and growth objectives. The result is a multi-step roadmap that safely, predictably, and measurably integrates AI into the company's operations while reducing risks and maximizing business value.
2. AI AUDIT & CONSULTING
What does it include?
System and data status assessment
Analysis of processes and exploration of automation opportunities
Identification of AI application points
Recommendations ranked by return and business value
Detailed description
The aim of the AI audit is to gain a comprehensive view of the company's entire operation: what processes are underway, how effective they are, what manual burdens exist, how data flows, and where the highest losses occur over time or in resources. The audit covers not only the technical infrastructure but also the daily work performed by people, as most AI solutions do not replace systems but rather specific tasks and decision-making situations.
During the process, we identify the points where automation can bring quick returns, as well as those areas that require more complex AI solutions – for instance, agents, predictive models, or document processing. The goal is for the company to clearly see from the audit results what the quick wins are and which strategic projects require larger investments but offer significant long-term advantages.
The result of the audit is not just a status assessment but a concrete package of recommendations sorted by business priorities. Along with each suggestion, the expected return, resource requirements, technical conditions, and risk factors are detailed. Thus, company leadership can precisely determine which projects are worth initiating immediately and which ones require preparatory work or infrastructure development. Consulting is also an integral part of the decision-making support: we help understand which steps lead to the fastest and safest AI implementation.
3. TECH STACK SELECTION
What does it include?
Comparison of platforms (OpenAI, Anthropic, Google, Azure AI, etc.)
Examining integration and operational considerations
Analysis of security and data protection compliance
System proposals for specific technologies
Detailed description
Selecting the right technological foundation is crucial for the success of AI projects. A poorly built or inadequately integrated stack will increase costs in the long run, make operations inflexible, and may even carry security risks. Therefore, selecting the tech stack is not just a technological decision but also a strategic one: it determines how the company's AI capabilities will evolve over the coming years.
During the work, we analyze the company's current systems, data management practices, infrastructure, and how different AI solutions can fit into these. We compare various platforms, take into account security, operational, and integration considerations, as well as cost implications. The goal is to develop a technological foundation that not only meets current needs but also remains stable, scalable, and cost-effective in the long term.
The selected stack is delivered in a detailed proposal format, showcasing which technologies are best suited to the company’s operations. We not only recommend platforms but also concrete solutions on how to integrate them with existing systems, ensure data privacy, and how future developments can be scaled. The result is a technological environment on which both short-term and strategically significant AI developments can be securely built.
4. MANAGEMENT WORKSHOPS
What does it include?
AI implementation models and risks
Presentation of use cases with industry examples
Data and security requirements
Practical decision support for leaders
Detailed description
The aim of the management workshops is for the company's leaders to understand the opportunities and risks associated with the implementation of AI and how they can transform the organization's operations to ensure long-term sustainability. It is particularly important for leaders to see AI not only from a technological perspective but also as a business decision that influences strategy, resource allocation, and the overall structure of operations.
During the workshops, we demonstrate how a successful AI implementation process is structured, what mistakes should be avoided, and the role of leadership support in the success of projects. We review various industry examples in detail that show how AI can deliver tangible business results, how manual work can be reduced, how efficiency can be increased, and how data can be transformed into a strategic advantage.
The workshops are not theoretical presentations but practical decision-support sessions where leaders understand AI's functioning through real case studies. Their aim is for management not to view AI developments as outsiders, but to act as active leaders who can evaluate, prioritize, and oversee the project from a business perspective. By the end of the process, leaders gain a clear picture of how to build a sustainable AI strategy that creates real business advantages and supports the growth of the company.
CASE STUDIES
If you are interested in how artificial intelligence can be applied in practice, take a look at the case studies of our real clients! We will show you how we automated processes, reduced working hours, or increased revenue with well-targeted AI solutions. From these examples, you can draw concrete ideas and see the results we achieved for others. Click and discover our most exciting developments!
