Strategic planning for AI: how to position your company for the future

1 Introduction: The AI revolution is here - Is your strategy ready for the future?

The transformative power of artificial intelligence (AI) is increasingly shaping the global economic landscape and is not stopping at Switzerland. The speed at which AI technologies are being adapted is unprecedented. Recent surveys show that a significant proportion of the Swiss population is already using AI applications such as ChatGPT or Gemini - 62.4% stated this in March 2025, a significant increase on the 49.7% of the previous year. This development underlines the fact that AI is no longer a distant vision of the future, but a present reality that requires a proactive approach. For companies, this means Those who fail to develop a clear AI strategy now risk losing touch and forfeiting decisive competitive advantages.  

The rapid spread of AI - faster than any other technology before it in Switzerland - indicates that the rules of the game are changing fundamentally in many industries. While the high individual use of AI tools suggests a general openness to the technology, this does not necessarily mean that companies already have a well thought-out, business-wide AI integration in place. It can be assumed that many organizations are still in an exploratory phase in which individual employees use tools, but lack an overarching, strategic anchoring. This gap between individual use and company-wide strategy harbors the risk of leaving the full potential of AI untapped and creating inefficient isolated solutions.  

Strategic AI planning is the systematic and forward-looking process of closely linking AI initiatives to a company's core objectives in order to promote sustainable growth and innovation. The aim is to view AI not as an isolated technology project, but as an integral part of the corporate strategy. The urgency of such planning is heightened by the speed of AI development. Companies that take a strategic approach at an early stage can not only realize efficiency gains, but also position themselves fundamentally better against the competition. The head start gained by strategic early adopters can potentially multiply, while procrastination can lead to a widening gap. This article serves as a guide for decision makers to understand the critical components of strategic AI planning and, based on current research findings for the Swiss market, to develop a future-proof AI roadmap.

2 The status quo: AI use and challenges in Swiss companies (findings from the Swiss AI Report 2025)

In order to enable sound strategic planning for artificial intelligence, a clear understanding of the current situation is essential. The "Swiss AI Report 2025", an empirical study by CorpIn, provides valuable data and analyses on AI adoption and the associated challenges in Swiss companies. These findings are particularly relevant for decision-makers, as they paint a specific picture of the Swiss AI landscape and thus support targeted strategy development.  

A key finding of the report is the need for many Swiss companies to catch up in terms of AI maturity. SMEs in particular are confronted with the urgent need to invest in areas such as data management, strategy development, technological infrastructure and the development of AI skills. This points to a heterogeneous picture of AI adoption: While some pioneers are already using advanced AI applications, many, especially small and medium-sized enterprises (SMEs), are still at an early stage or are struggling with fundamental hurdles.

The most common challenges identified in the report include

• Data silos: Isolated data pools within companies prevent the holistic use of data, making it difficult to effectively implement AI solutions based on comprehensive and high-quality data.   
• Lack of KPIs (key performance indicators): Many companies lack clear metrics to measure and evaluate the success and return on investment (ROI) of their AI initiatives. Without measurable goals, it becomes difficult to quantify the actual value of AI and adjust the strategy accordingly.   
• Strategic deficits: A lack of a coherent, company-wide AI strategy often leads to fragmented individual projects that do not contribute to the overarching business objectives.   
• Insufficient infrastructure and skills: A lack of technological prerequisites and a shortage of specialists with the necessary AI skills are slowing down the development and implementation of AI solutions.
  

The persistence of these challenges can often be attributed to a combination of a lack of awareness of the strategic potential of AI, limited resources, a lack of expertise or an unclear idea of the concrete benefits. Despite a high level of general awareness of AI applications - only two percent of the Swiss population state that they know nothing about AI applications - there is a discrepancy between knowledge and action. Companies are aware of the importance of AI, but struggle with its practical, strategic implementation. This "knowing-doing gap" must be bridged by moving from a general endorsement of AI to concrete, strategic steps.  

The "Swiss AI Report 2025" emphasizes that "Swiss SMEs in particular urgently need to improve their data, strategy, infrastructure and skills". This identifies SMEs as a segment with a particularly high need for action. Given their economic importance, the AI transformation of SMEs is crucial for the competitiveness of Switzerland as a whole. SMEs often face specific challenges such as limited financial and human resources. Strategic approaches must therefore be scalable and practical.  

The aforementioned "data silos" are a recurring and fundamental problem. Even if AI tools are available and a rudimentary strategy exists, the database is often the Achilles' heel. AI algorithms are dependent on high-quality and accessible data. Without a solid data strategy that ensures data governance and accessibility, AI initiatives run the risk of falling short of expectations or failing altogether. Strategic AI planning must therefore include a robust data strategy as a foundation. Companies that fail to address these challenges not only risk missed opportunities and inefficient investments, but also a lasting competitive disadvantage.  

3. what exactly is strategic AI planning - and why is it your key to success?

Strategic AI planning goes far beyond the mere introduction of new technologies. It is a continuous, adaptive process that deeply integrates artificial intelligence into the structure and culture of a company and makes it an integral part of the overarching business strategy. Instead of primarily asking: "What interesting AI tools can we use?", the central question of strategic AI planning is: "How can AI help us to achieve our core goals as a company more effectively and create sustainable value?" This is therefore not an isolated IT project, but a fundamental change that affects the entire company.

The core pillars of such strategic planning comprise several dimensions that are closely interlinked:

• Vision & alignment: The development of a clear AI vision that harmonizes with the overarching business goals and corporate vision. AI initiatives must make a comprehensible contribution to value creation.
• Opportunity identification: A systematic process for identifying, evaluating and prioritizing AI use cases that promise the highest potential return on investment (ROI) and strategic benefit.
• Resource allocation: Well thought-out planning of the necessary resources, including data availability and quality, technological infrastructure, qualified specialists and financial resources.
• Risk management: Proactively addressing potential risks associated with the use of AI - including ethical concerns, data security, operational risks and potential reputational damage.
• Governance & ethics: The establishment of clear framework conditions and guidelines for the responsible development, implementation and use of AI to ensure transparency, fairness and traceability.
• Change management & culture: Preparing the organization for the changes driven by AI. This includes promoting an AI-friendly culture, developing skills and actively involving employees.
• Measurement & iteration: The definition of meaningful key performance indicators (KPIs) to measure success and the establishment of a continuous evaluation and adjustment process for the AI strategy.

The advantages of such comprehensive strategic AI planning are manifold and decisive for the future viability of a company:

• Maximizing ROI: Ensuring that AI investments make a measurable and significant contribution to business success.
• Competitive advantages: Use of AI to promote innovation, increase efficiency, open up new markets and develop differentiating products or services.
• Risk minimization: Proactive management of the challenges and potential disadvantages associated with AI.
• Sustainable growth: Building up long-term AI expertise and capacities that make the company future-proof.
• Resource optimization: Avoiding bad investments and inefficient use of resources by focusing on strategically relevant and promising AI projects.
• Improved decision-making: Use AI-powered analytics and insights to inform strategic and operational decisions.

The dynamic nature of AI technology and the market environment means that strategic AI planning cannot be a one-off project, but must be understood as an agile, iterative process. A rigid strategy, once defined, would quickly lose its relevance. Instead, the aim is to create a framework for continuous learning and adaptation so that the AI strategy becomes a core competence of the company.

In addition, the human factor is an often underestimated but critical success factor. The best technology and the most sophisticated data strategies are of little use if employees do not have the necessary skills, are not open to change or the corporate culture does not support change. The need to improve "skills" and consider the "aspects of AI transformation in terms of people, governance, business model and integration into the company" underlines this importance. A successful AI strategy must therefore include change management, training and the promotion of an AI-ready culture as key elements.  

4 The foundations of a robust AI strategy: a tried and tested framework

To manage the complexity of strategic AI planning and pave a targeted path to successful implementation, a structured framework is essential. Such a framework helps companies to determine their current position, define clear goals and systematically tackle the necessary steps.

One approach that offers this structure is a multidimensional evaluation and strategy model. CorpIn's "Hexagon Model", for example, measures AI maturity - scientifically based across six dimensions - and provides benchmarks and recommendations for action. Even if the specific details of all six dimensions of this model cannot be fully explained here, the underlying concept of a holistic, multidimensional approach is of central importance. Such an approach ensures that all critical aspects of AI transformation are considered.

The strength of such a multidimensional framework lies in the realization that these dimensions cannot be viewed in isolation from one another. They are closely intertwined and influence each other. An excellent database ("data & analytics" dimension), for example, only unfolds its full potential when employees also have the necessary skills and the right attitude to use this data using AI ("people & culture" dimension).

A holistic view, as made possible by such a framework, helps companies to identify their specific strengths and weaknesses in the context of AI transformation. It uncovers critical interdependencies and thus leads to a more robust, resilient and ultimately more successful AI strategy. This is precisely where specialized analysis tools offer significant added value. For example, the CorpIn Hexagon platform "analyzes your AI readiness in a data-based, strategically sound and practical way" and helps companies to clearly determine their current position.  

The emphasis that a model such as the Hexagon Model is scientifically sound is an important differentiating factor. In an area that is often characterized by hype and elusive promises, decision-makers are looking for reliable and methodologically sound approaches. The reference to a scientific foundation signals rigor, objectivity and a validated methodology, which strengthens confidence in the strategic process.  

Another decisive advantage of a structured analysis approach is the possibility of benchmarking. The ability of a model to provide benchmarks is of great value to organizations. Many organizations struggle to assess their own AI maturity in isolation. Comparison with industry standards or competitors provides important context, reveals potential competitive disadvantages and can serve as a powerful catalyst for strategic investment and prioritization in the AI space. Knowing one's relative position motivates action and targeted development of the AI strategy.

5. your path to a customized AI roadmap: Set up for the future in 6 steps

Now that the basics and the necessity of strategic AI planning have been highlighted, the question of the concrete "how" arises. A structured, step-by-step approach is key to moving from vision to successful implementation. CorpIn itself outlines such a path with 6 steps to assess your organization's AI maturity level. These steps provide a field-tested orientation for developing a customized AI roadmap.  

The six central steps can be detailed as follows:

1. Step 1: Define vision & goals - What should AI do for your company? This first step lays the foundation. It is about going beyond vague declarations of intent and defining specific, measurable, achievable, relevant and time-bound (SMART) goals for the use of AI. A clear alignment with the overarching business strategy is crucial: how can AI contribute to achieving market leadership, increasing customer satisfaction, achieving operational excellence or tapping into new sources of revenue? The AI vision must be supported by top management and communicated throughout the company.
2. Step 2: Analyze AI maturity - where are you today? An honest and comprehensive inventory of current AI capabilities is essential. This includes an assessment of data maturity, the existing technological infrastructure, employee skills, established processes and the corporate culture with regard to AI. The previously discussed dimensions of a holistic framework (analogous to the hexagon model) can serve as a guide here. A SWOT analysis (strengths, weaknesses, opportunities, threats) specifically for the AI area can help to clearly define the starting position. A structured, data-driven analysis, such as that made possible by platforms like the CorpIn Hexagon platform, which analyzes your AI readiness in a "data-based, strategically sound and practical manner", provides critical and objective insights.   
3. Step 3: Identify & prioritize use cases - where is the greatest potential? Based on the defined goals and the maturity analysis, brainstorming and identification of potential AI use cases across all business areas takes place. These use cases must then be carefully evaluated according to criteria such as technical feasibility, expected ROI, strategic relevance, implementation costs and risk profile. The aim is to develop a balanced portfolio of AI initiatives that includes both quick wins and long-term strategic projects.
4. Step 4: Data, technology & talent - securing the necessary resources. This step addresses the specific requirements for implementing the prioritized use cases. A robust data strategy is key here in order to ensure data governance, quality, accessibility and security and to break down the "data silos" identified in the "Swiss AI Report 2025". At the same time, the technology stack must be defined, i.e. the selection of suitable AI tools, platforms and the underlying infrastructure (including build vs. buy decisions). Last but not least, talent development is crucial: a plan is needed for the acquisition, training and retention of specialists with AI skills in order to close the "skills gap" also mentioned in the report.   
5. Step 5: Implementation & change management - successfully anchoring AI in the company. The realization of AI initiatives requires detailed implementation plans with clear responsibilities, schedules and milestones. Agile methods and pilot projects are often useful in order to learn quickly and be able to react flexibly to new findings. A critical, often underestimated success factor is robust change management. The introduction of AI means change - for processes, for roles and for the way work is done. Active communication, employee involvement, training programs and the promotion of a positive, AI-friendly corporate culture are essential to create acceptance and overcome resistance. The aspects of "people, governance, business model and integration" are of central importance here.   
6. Step 6: Measuring success & continuous optimization - maximizing the ROI of your AI investments. Clear KPIs must be defined in order to evaluate the success of the AI strategy and ensure that the investments are delivering the desired benefits. These address the "missing KPIs" identified in the "Swiss AI Report 2025". A feedback mechanism needs to be established for continuous monitoring, the evaluation of results and the refinement of the AI strategy and roadmap based on this. AI strategy is not a static construct, but a learning system that adapts to new technological developments and business requirements.
   

These six steps are not always strictly linear. In particular, there will often be iterations between steps 3 (use cases), 4 (resources), 5 (implementation) and 6 (measurement). Assumptions may change and new insights may be gained that require the plans to be adapted. Rather, it is a cycle of planning, implementing, reviewing and adapting.

6 AI trends 2025: decision-makers need to have these developments on their radar

Artificial intelligence is a rapidly developing field. New technologies, models and applications are emerging at a high frequency and have the potential to transform existing business models and create new strategic imperatives. It is therefore essential for decision-makers to be aware of the most important AI trends and consider their implications for their own strategic planning. The article "AI trends 2025: These developments are shaping Switzerland" by CorpIn highlights some of these key developments.  

The defining AI trends for 2025 that companies should keep an eye on include

• Strategic AI adoption: This point describes less a single technological trend and more the overarching change in the approach to AI. It is about moving away from isolated experiments and pilot projects towards a profound, strategically anchored integration of AI into the core processes and value chains of companies. This is the goal that the strategic planning outlined in this article is working towards.
• Generative models (Generative AI): Advances in the field of generative AI, which go far beyond simple chatbots, are opening up new possibilities in content creation (text, image, video, code), product design, the generation of synthetic data for training purposes and many other areas. These models offer enormous opportunities for increasing efficiency and innovation, but also raise questions regarding quality control, copyright and ethical use.
• Autonomous agents: The development of AI agents capable of performing complex tasks with a higher degree of autonomy is progressing. Such agents could, for example, independently research information, prepare decisions or even automate certain business processes. This has far-reaching implications for the organization of work and the way in which decisions are made.
• Data-driven innovation: This trend is not new, but is being further accelerated by advanced AI methods. AI improves the ability of companies to gain valuable insights from large and complex amounts of data. These insights can form the basis for the development of new products and services, the optimization of existing offerings and the development of completely new business models. Overcoming "data silos", as discussed in the "Swiss AI Report 2025", is a basic prerequisite for this.
  

For strategic planning, these trends mean that companies must proactively address the following questions:

• What potential impact do these developments have on our current business model and our competitive position?
• What new business opportunities or efficiency potential does this offer us?
• What new skills, technologies or ethical frameworks do we need to integrate into our AI strategy to make the most of these trends?
  

One aspect that deserves particular attention in the context of generative AI is the change in information search itself. With the advent of Generative Engine Optimization (GEO), it is becoming increasingly important for companies to prepare content in such a way that it can be optimally captured and used by AI-based search engines and response systems. This requires high-quality, precise and authoritative content that provides direct answers to user questions. The way in which companies are found and perceived in an AI-influenced information landscape is therefore changing fundamentally.  

The aforementioned AI trends are not developing in isolation from one another. Rather, a convergence is to be expected in which generative models, autonomous agents and data-driven innovation approaches merge with each other and thus enable even more powerful and transformative AI applications. For example, autonomous agents could use generative AI to create personalized customer responses or creatively solve complex problems based on real-time data analysis. Strategic planning must anticipate these possible convergences and think beyond the isolated consideration of individual trends in order to take into account the resulting, often multiplicative effects.

With the increasing complexity and influence of AI models, particularly in the area of generative AI and autonomous systems, the challenge of explainability and trust will continue to grow in importance. "Black box" systems whose decision-making is not comprehensible to humans can lead to errors, bias or unintended consequences. Public and regulatory attention to AI systems is increasing, and concerns about misinformation or privacy are present. Proactive strategic AI planning must therefore firmly establish robust frameworks for AI ethics, governance and the development of trustworthy AI systems. This is not just a question of technical feasibility or compliance, but a fundamental business requirement for long-term success and social acceptance.  

7. CorpIn: Your partner for strategic AI excellence in Switzerland

The previous sections have highlighted the urgency and complexity of strategic AI planning. Companies that want to successfully master this journey not only need internal commitment, but often also external expertise and tried-and-tested tools. This is where CorpIn positions itself as a competent partner for Swiss companies on their path to AI excellence.

CorpIn's approach is characterized by a focus on data-driven, strategically sound and practical AI solutions. This is reflected in the analyses and recommendations that emerge, for example, from the "Swiss AI Report 2025". CorpIn has a deep understanding of the Swiss market and the specific challenges faced by SMEs in particular - a segment whose pent-up demand is clearly identified in the report. This local understanding, combined with international expertise, makes it possible to develop customized and effective AI strategies.  

Further evidence of CorpIn's commitment to supporting companies in their AI transformation are initiatives for knowledge transfer and exchange. The "CorpInSight - The AI podcast for decision-makers" serves as a platform for making future technologies understandable and sharing expert interviews on topics such as AI, digitalization and innovation. Such offerings help to promote "AI literacy" among decision-makers - an important prerequisite for well-founded strategic decisions.  

A central element in CorpIn's solution portfolio is the CorpIn Hexagon platform. This platform embodies the strategic and scientifically sound approach to AI planning described above. It is positioned as a Swiss solution for AI benchmarking & strategy that analyzes your AI readiness in a data-based, strategically sound & practical way. The platform measures the AI maturity level - scientifically based across six dimensions - and provides benchmarks and recommendations for action. The Hexagon platform therefore offers concrete added value for decision-makers:  

• Clarity: An objective assessment of your own AI maturity level.
• Identification of gaps: Uncovering specific weaknesses and potential for improvement in the various dimensions of AI capability.
• Recommendations for action: Concrete, practical suggestions for optimizing the AI strategy and closing identified gaps.
• Benchmarking: Classification of own performance in comparison to relevant peers or industry standards.
  

The CorpIn Hexagon platform is thus a comprehensive solution platform for companies that want to drive their AI transformation in a serious and structured way and are willing to invest in an advanced tool for strategy development and optimization.

CorpIn sees itself not just as a pure technology supplier or consultant, but as a strategic partner that supports Swiss companies in achieving AI excellence in the long term and future-proofing their business activities. The combination of market research (such as the Swiss AI Report), educational offerings (such as the podcast) and concrete analysis and strategy tools (such as the Hexagon platform) positions CorpIn as a holistic provider in the field of strategic AI planning.

8 Conclusion: Setting the course for your AI future with strategic planning

The comprehensive analysis has shown that proactive, well thought-out and strategic planning for artificial intelligence is no longer an option for companies in 2025 and beyond, but a fundamental necessity for sustainable success and competitiveness. The speed of AI development and adoption, as can also be observed in Switzerland, requires decision-makers to act decisively.  

The challenges on the road to AI maturity are real - from data silos and a lack of KPIs to strategic deficits and skills gaps, as the "Swiss AI Report 2025" shows. But these hurdles can be overcome. A structured approach that combines a clear vision with an honest maturity analysis, prioritizes promising use cases, secures the necessary resources, accompanies implementation with effective change management and continuously measures and optimizes success makes the complex task of AI transformation manageable and the benefits tangible.  

Taking current AI trends such as advanced generative models, autonomous agents and progressive data-driven innovation into account is just as crucial as adapting to new paradigms such as Generative Engine Optimization (GEO). It is about understanding AI not just as a tool, but as a strategic lever that enables new business models and optimizes existing ones.  

Developing a robust AI strategy is a journey, not a one-off project. It requires continuous learning, adaptability and a willingness to consider technological as well as human and cultural aspects. For decision-makers, this means taking a leading role in this transformation process and actively setting the course for an AI-supported future for their company.

Start assessing your AI maturity level and developing your strategic AI roadmap today. The first step is often the most crucial.

To support you on this important journey and provide you with customized insights and concrete recommendations for action, the experts at CorpIn are at your side. Contact the experts at CorpIn for a consultation to learn how we can support you on your journey to AI excellence and how the CorpIn Hexagon platform can provide you with valuable, data-driven foundations for your strategic decisions. Together, we can ensure that your company fully exploits the potential of artificial intelligence and is future-proofed.