5 Steps to Creating an Artificial Intelligence Strategy

Artificial intelligence (AI) is becoming pervasive, impacting every aspect of business operations. Depending on the industry and company, the development timeline can vary greatly, but changes are inevitably on the horizon. This view is supported by numerous international studies forecasting improvements in work efficiency by tens of percentages through AI.

In 2023, the development and utilization of AI took significant leaps forward. Indications suggest that this rapid progress will continue through 2024. It is crucial for businesses to contemplate what this means for them and to start this reflection as soon as possible. AI can enhance business operations in various ways, not limited to efficiency improvements. According to McKinsey's State of AI report, utilizing AI can enhance the quality of existing products and services and enable the development of entirely new ones. Businesses can discover new competitive advantages through AI. Conversely, it is also about surviving in an increasingly competitive market. If the substantial effects of enhanced efficiency can be partially translated into pricing and quality, an intensification of competition in various aspects is easily foreseeable. Those businesses that integrate these opportunities into their operations will be among the first to reap the benefits of AI.

Another consequence of rapid technological advancement is the swift obsolescence of technical solutions. With new solutions emerging daily, choosing technologies for long-term investment becomes challenging. Gartner predicts that those businesses that integrate these opportunities into their operations will be among the first to reap the benefits of AI. How can a business create an AI strategy in such a scenario? How can a company's goals and realities, the opportunities and threats posed by AI, and the challenges brought by rapid development be harmonized?

In this blog post, I present a five-step process to begin integrating AI into your company's strategic discussion and operational management processes.

AI Strategy Phases:

• Step 1: Strategy, Business Models, Visioning
• Step 2: Technical Systems
• Step 3: Resources, Skills, and Processes
• Step 4: Prioritization
• Step 5: Metrics and Monitoring

Let's begin at the core of your business – why your company exists and how it creates value for its customers.

Step 1: Clarify Your Company's Strategy and Business Model

Your AI strategy must align with your overall business strategy. Therefore, it's essential to review your company's strategic description and business model documentation. These may seem obvious, but they are invaluable in many ways when you continue to the next phases in AI strategy development.

Key Aspects:

a. A clear understanding of the business core: This gives you a clear picture of how your company creates value and its direction. Keep this perspective in mind throughout the AI strategy process to maintain a connection between ideas and business operations.

b. AI ideas related to current business: The most promising AI applications are likely found by examining current business and value creation models. Documentation aids in envisioning potential applications, such as enhancing production, communication, customer experience, employee experience, or even sales support.

c. A comprehensive view for situating AI ideas: Documentation provides a map where ideas generated during the AI strategy phases can be placed. When envisioning possibilities, it's highly likely that AI could be applied across all business functions. Placing these diverse ideas in a comprehensive view helps not only in documentation but also in understanding their interrelations and the bigger picture.

d. Support for evaluating AI ideas: The comprehensive view aids in assessing the collected AI ideas. When they are evaluated against the company's overall picture, it becomes clear how well these ideas anchor to the current strategy and business models.

e. Materials for future use: Due to rapid changes, there will likely be a need to revisit both the company's operational documentation and AI ideas. Clear documentation and a structured process from ideation to realistic evaluation can accelerate progress.

Initial Questions to Consider:

• What added value could AI bring to our core products and services?
• What are our biggest challenges currently, and could AI help in solving them?
• Could our customer service be improved with AI?
• Does our company produce content that could be enhanced by AI?
• Are there data masses in our company that could benefit from AI analysis?

At this point, the more ideas, the better. More important than the realism of these ideas is that they bring AI possibilities into your thought process and kickstart the envisioning of AI applications.

Step 2: Assess How Your Company's Technical Systems Support the Utilization of AI

The utilization of AI requires data. While generative AI based on pre-trained language models can be employed in tasks like marketing material creation, customizing AI for your specific business needs hinges significantly on your technical systems and data quality. Understand your company's technical ecosystem and various data sources to realistically evaluate the possibilities of AI in different applications.

Data security and ethical use of data are crucial considerations at this stage. This assessment also reveals how information flows within and outside your organization, potentially uncovering clear AI applications in data production and distribution. Addressing any identified gaps, such as system compatibility and data quality, may be necessary before implementing AI.

For example, in maintaining and modernizing legacy software systems, tools like Microsoft's Azure Migrate and AWS Application Migration Service can help translate and modernize code, enabling significant cost savings.

Step 3: Evaluate How Your Current Resources and Processes Support AI Utilization

For AI to be effectively employed in your organization, you need people who will take responsibility for concretely advancing matters. Finding the right individuals and managing internal communication for development projects are vital for building a culture that supports AI use and continuous development.

AI should be seen as an essential and permanent aspect of all activities within the organization, even if the initial steps are taken within the scope of a single pilot project. Additional resources, such as budget for software acquisitions and technical investments, are also necessary.

Step 4: Determine Where to Start with AI Utilization in Your Business

After systematically identifying AI opportunities through business, technical ecosystem, resources, and process mapping, systematically review your business models to identify potential AI applications. Compare these opportunities with how current technical systems and data support these development ideas.

Besides assessing the complexity of development ideas, evaluate their impact on business operations. The goal is to map out a roadmap for potential development projects and metrics, which will be refined when selected projects commence.

Examples of current industry-specific AI solutions include:

• Microsoft Cloud for Healthcare
• IBM's Financial Services-specific AI tools
• Google Cloud's Retail AI solutions

Step 5: Ensure Monitoring and Evaluation of AI Benefits and ROI

To ensure AI brings tangible benefits to your business, regularly measure and evaluate the results of development projects. As you assess potential development pilots, their objectives become more defined. From these objectives, derive metrics for regular tracking.

Continuous and regular monitoring and evaluation of the pilot are critically important for your business to adapt to changes in technological development, the operating environment, or within your company. Changes in any of these areas are quite likely.

Key Points for Monitoring:

• Be prepared to flexibly increase development efforts
• Accept project termination if necessary
• Redirect resources to more promising development projects
• Maintain clear objectives and metrics
• Ensure regular monitoring

Conclusion

These steps may seem like significant leaps, but each has likely been contemplated at some level within your company. Systematically going through these steps will form a more precise and realistic picture of what an AI strategy could mean for your business.

Initiating and undertaking this process within the organization also builds capabilities for repeating different phases, and in a rapidly changing world, there is undoubtedly a need for this. An AI strategy cannot be a multi-year plan set in stone; it must be a living, flexible plan that can be continuously modified based on accumulating new information.

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Did this article spark any thoughts in you? If you want to discuss these topics, contact me, and let's talk more about it.