Discover AI application cases in strategic planning, including scenario planning, strategic analysis, and validating internal controls against new regulations.
- Responsible use of AI. With the variety of AI models and the ease of using them, organizations need to consider implementing a proper AI governance framework to ensure transparent and responsible use of AI.
Where AI can Potentially Help
Previously, we discussed the steps of the strategic planning process.
At the current stage of development, AI will be most helpful across a wide spectrum of tasks related to the strategy analysis stage.
During the prototype stage, the results of using AI can be implemented with spreadsheet software. For the best results, AI should be combined with specialized strategy execution software like BSC Designer, which would provide the AI with the required contextual information, guide the format of the output, and directly implement the AI’s results into the scorecards.
Preparing the Context of Strategy
There are various factors that contribute to AI effectiveness, and providing detailed context for a prompt is one of the most important. For better results, include the following contextual information:
- Company’s name and industry
- Company’s mission, vision, and values
- Existing high-level strategy, such as a cascading into scorecards
- The stakeholders and their needs
- Results of strategic analysis (external factors, competitors, etc.)
- Detailed hierarchy of existing goals
- KPIs aligned with the goals and their descriptions
- Initiatives aligned with the goals and their descriptions
If you use BSC Designer as a strategy execution software, this contextual information is already available in the tool and can be passed to the AI in a transparent and privacy-conscious way.
Scenario Planning: Generating Plausible Scenarios
Back in 2022, when ChatGPT became mainstream, I tried it for some typical tasks in strategic planning. AI hallucination was still common even with specific prompts, but due to its inherent ability to generate plausible text, it was a perfect match for scenario planning.
If you want to explore on what the future might hold, and how your organization can become more resilient in the face of coming changes, consider using AI for this purpose.
An example of a prompt:
‘Analyze the latest industry trends that might potentially affect our organization. Suggest what impact they would have on operations, talent, customers, finance, etc.’
As we discussed in our scenario planning article, the resulting scenarios can be implemented in separate functional scorecards.
Analysis of External Factors
Ask AI to follow the perspectives of the PESTEL analysis and identify the external factors that could potentially affect your organization.
An example of a prompt:
- ‘Conduct an analysis of external factors (PESTEL). Evaluate the factors that impact our industry, and assign each factor to a perspective according to the PESTEL acronym (Political, Economic, Social, etc.).’
Stakeholder Analysis
Stakeholder analysis is the starting point of the strategic planning process.
An example of a prompt:
- ‘Do analysis of the stakeholders. Assign each stakeholder to one of the perspectives from this set: External stakeholders, Suppliers, Internal stakeholders, Stakeholders that affect / are affected, Stakeholders due to legal obligations. Suggest an example of 2-3 strategic ambitions (high-level goals) for each stakeholder. Suggest a value metric for each stakeholder. ‘
Competitive Analysis Using Porter’s Five Forces
With the following prompt, AI will prepare a competitive analysis based on Porter’s Five Forces.
- Do Five Forces analysis. Assign each goal to a specific perspective in accordance with the Five Forces framework (Force 1: Current Competitors; Force 2: Customer Power; Force 3: Supplier Power; Force 4: Future Competitors; Force 5: Threat of Substitutes).
Analysis of Regulatory Requirements
AI is particularly effective at analyzing vast amounts of data, such as new regulatory requirements, standards, and internal policies.
A use case could involve uploading the following information to the AI:
- Details about existing internal controls
- Information about regulatory requirements
Then, ask the AI to analyze whether the existing controls satisfy the regulatory requirements.
In one of our cases, a client passed an existing scorecard with around 300 controls to ChatGPT, asking it to find gaps and improvement points. The results were not perfect and required human review, but the estimated time savings were about 70%.
Analysis of Existing Strategy
Similar to regulatory analysis, AI can be used to review the existing strategy. In this case, the context needs to be defined by the existing strategy itself, as well as by stakeholder analysis, trend analysis, and competitive analysis.
You can upload relevant documents to the AI and ask it to:
- Analyze the existing strategy considering the results of strategic analysis
Quantifying Goals with Leading and Lagging KPIs
When discussing KPIs, we always stress the idea that business goals come first, and then we find ways to quantify them using KPIs. Once the goals are defined, ask AI for suggestions on how to measure them.
An example of a prompt could be:
This is a goal within the strategy scorecard that is focused on a certain aspect of strategy. Taking into account the context of the organization, suggest KPIs that we can use to quantify this goal. Among the KPIs, define those that quantify success factors (leading KPIs) and the expected results (lagging KPIs).
Readiness for Future AI
We are monitoring AI trends along with other trends in strategic planning, and in its current state of development, it won’t replace strategists and is far from perfect for any mission-critical task. However, this is likely to change with:
- A decrease in computational costs and
- An increase in the adoption of AI models trained on proprietary data.
With more contextual information available, AI will provide more precise and fact-supported recommendations.
While this may not be within the current planning horizon for most companies, we can prepare for future AI adoption by starting to collect strategy data that can be used to train proprietary AI models.
Feel free to share your experience using AI in strategic planning in the comments.
Alexis is the CEO of BSC Designer with over 20 years of experience in strategic planning. He has a formal education in applied mathematics and computer science. Alexis is the author of the “5 Step Strategy Deployment System”, the book “10 Step KPI System”, and “Your Guide to Balanced Scorecard”. He is a regular speaker at industry conferences and has written over 100 articles on strategy and performance measurement. His work is often cited in academic research and by industry professionals.