In this article, my colleague Claire and I discuss our recent experiments in using AI as an innovative way to craft scenarios for public sector challenges. We walk you through our experience, so you can try it for yourself, and bring some impressive and valuable fuel for conversation to your next strategy meeting. <\/p>\n\n\n\n Imagine going into your next strategy meeting equipped with scenarios prepared in a flash!<\/em> <\/p>\n\n\n\n This article is for experienced futurists. It is not a beginner\u2019s guide to strategic foresight or scenario planning. It delves into experimental and unproven techniques, aiming to help experts apply and elevate their skills. We bypass the basic principles<\/a>. We assume you have a strong understanding of what goes into this type of scenarios, and a clear idea of your desired outcomes. AI writes for you; it doesn\u2019t think for you. Without a solid grasp of the discipline, you risk getting bogged down in nonsense. <\/p>\n\n\n\n If you’re new to strategic foresight, we recommend bringing in experts. You can also consult resources like Futures and Foresight in the OPSI Toolkit Navigator<\/a>, the publications of the OECD<\/a> Strategic Foresight Unit, and this advice on getting the most from publicly available scenarios<\/a>. <\/p>\n\n\n\n Claire and I both recently found ourselves preparing for strategy-type meetings, in which we needed to discuss unknown and uncertain future changes. Claire\u2019s was about preparing a communications strategy in a shifting organisational context. Mine was about planning a research programme with a partner institution facing political change. <\/p>\n\n\n\n Each of us realised that we had an incomplete picture of the future, which made it hard to know if we were making the right decisions. This was the first step: we needed to define the<\/strong> purpose of the exercise<\/strong>. It was to highlight where we had imperfect information, and to support internal dialogue on how to make our work a success. <\/p>\n\n\n\n Next, we needed to determine which elements to explore. This second step was thus to map all the relevant players and factors<\/strong> in our strategic environment<\/a>. This included: <\/p>\n\n\n\n It was important to separate out these three things: the value of the exercise was to test how we would act in a world we didn’t expect or choose. <\/p>\n\n\n\n By this point we had already spent about half the time available for our scenario-building, but we had only laid the foundations. <\/p>\n\n\n\n The next step would be to gather all the elements in our mapping, explore how they could change (predictions, forecasts, and weak signals), and imagine how they could interact to create different and disruptive future contextual environments<\/strong>. This horizon scanning is crucial to strategic foresight, because it imagines how the future could diverge from the present in surprising and significant ways. The step after that would be to craft story-like descriptions of those future contextual environments<\/strong>. Stories are one of the key strengths of scenarios<\/a>: they help humans to make sense of complexity, retain important facts, and question decisions. <\/p>\n\n\n\n These last two steps would normally be a weeks-long process involving research, surveys, workshops, analysis, reports, and review. We had minutes, not weeks. So instead of slow-cooking these scenarios, we decided to microwave them. Enter AI. <\/p>\n\n\n\n Before we go further, let\u2019s consider the limitations. Generative AI tools process input text, read the context and content, and then serve up responses. They don\u2019t possess reason, wisdom, or objectives. They don\u2019t know how the world works. They don\u2019t conduct research or analysis. They reproduce text patterns learned during training. <\/p>\n\n\n\n The division of skills was clear then: we humans did the analytical, critical, and strategic thinking; and then tasked machines with transforming our messy mapping of the strategic environment into something mentally digestible. <\/p>\n\n\n\n Here are the precautions we took: <\/p>\n\n\n\n Below we list the prompts we used, along with the rationale and some tips to help you make it the AI work better. <\/p>\n\n\n\n The word \u2018user\u2019 refers to the organisation, team, or individual whose strategic dialogue will be guided by the scenarios. <\/p>\n\n\n\n It is important to give feedback to each response generated by the AI<\/strong>. If anything is missing or incorrect, say so before issuing the next prompt. <\/p>\n\n\n\n Study this background information:<\/strong> <\/p>\n\n\n\n Prompt 1 introduces the AI to the user\u2019s contextual environment. This information isn’t immediately acted upon, but the model may regurgitate a summary, which you can check for accuracy and give feedback on.<\/em> <\/p>\n\n\n\n Write a list of the most important objectives for [user]\u2019s strategy<\/strong> <\/p>\n\n\n\n In prompt 2 we are testing the AI\u2019s understanding of the core goals and aspirations that will guide and shape the user\u2019s future planning and actions. These objectives should be aligned with the user\u2019s specific needs and values. Give the model feedback.<\/em> <\/p>\n\n\n\n Write a list of the most important hypothetical future changes in the transactional environment that could plausibly disrupt or redirect the objectives in [user]\u2019s strategy<\/strong> <\/p>\n\n\n\n Prompt 3 explores potential future changes in the transactional environment. You can add a timeframe here if that\u2019s important to you. In your feedback, top up the list generated with predictions, forecasts, and weak signals from your own horizon scanning if you have them.<\/em> <\/p>\n\n\n\n Write a list of the most surprising and impactful hypothetical political, economic, technological, social, or environmental future changes in the contextual environment that could plausibly disrupt or redirect the objectives in [user]\u2019s strategy<\/strong> <\/p>\n\n\n\n Prompt 4 extends the exploration into the contextual environment. You can add a timeframe here if that\u2019s important to you. In your feedback, top up the list generated with predictions, forecasts, and weak signals from your own horizon scanning if you have them.<\/em> <\/p>\n\n\n\n Combine elements of the above answers into four contrasting, coherent story-scenarios of a fictional future context in which [user] could find itself. For each story-scenario, describe the situation in the transactional environment, in the contextual environment, and how it affects [user]\u2019s objectives. Give each story-scenario a catchy-name.<\/strong> <\/p>\n\n\n\n Prompt 5 engages the AI in weaving together elements from the preceding steps to craft scenarios. Check if you want all four; your feedback might call for one to be dropped. Check also for hallucinations and politically sensitive ideas, but remember: scenarios are intentionally fictional; unbelievable things happen all the time; and <\/em>the future doesn\u2019t care if it disrupts, embarrasses, or even destroys your organisation and its beliefs<\/em><\/a>.<\/em> <\/p>\n\n\n\n For each story-scenario write a list of two key questions raised that [user] should ask itself now when developing its strategy.<\/strong> <\/p>\n\n\n\n Prompt 6 gets you started on bridging the gap between future foresight and present actions.<\/em> <\/p>\n\n\n\n Now produce a table using the above information, with each story-scenario as a column. First row is a three-sentence summary of the main ideas of the story-scenario. Second row is the main transactional changes. Third row is main contextual (political, economic, technological, social, or environmental) changes. Fourth row is opportunities for [user]. Fifth row is threats for [user]. Sixth row is how [user]’s activities might have to change. Seventh row is row is strategic questions for today to help [user] prepare. <\/strong><\/p>\n\n\n\n Prompt 7 gets you started on presenting the information in a structured and concise way. This visual aid serves as a quick reference for you to use in a briefing document.<\/em> <\/p>\n\n\n\n Scenarios on their own have no value; it is the learning they promote and the decisions they inform<\/a> that count. The most important consideration for us was how we would use the scenarios<\/strong>. <\/p>\n\n\n\n One idea was to summarise them in a briefing note<\/strong> to provide context and insights ahead of a strategy meeting. Another was to use them in a presentation<\/strong> as conversation-starters in a workshop. Another was to create handouts or posters<\/strong> with the scenarios and key questions to structure and guide creative exchanges for innovation. <\/p>\n\n\n\n These are just the start: futurists could consider integrating AI-generated scenarios into numerous other approaches including persona-building, design fiction, Futures Literacy Labs<\/a>, or Experiential Futures<\/a>. <\/p>\n\n\n\n Even with AI, humans still played a vital role in our process of generating and using scenarios. There\u2019s no substitute for in-depth research, critical analysis, or strategic thinking. We also believe that human-generated scenarios have unique value, particularly in settings where the creation process itself is beneficial for the reflection and engagement it fosters. <\/p>\n\n\n\n For us, the most important takeaway here is that we were able to bring strategic foresight to situations where it would normally be too time-consuming and costly. <\/strong>We\u2019ve said before that a little strategic foresight goes a long way<\/a>. Thanks to new tools, we can now make foresight go even further, faster. <\/p>\n\n\n\n![\"\"](\"https:\/\/oecd-opsi.org\/wp-content\/uploads\/2023\/12\/MicrosoftTeams-image-24-1024x686.jpg\")
<\/figure>\n\n\n\nAI writes for you; it doesn’t think for you<\/h3>\n\n\n\n
Why we needed scenarios fast <\/h2>\n\n\n\n
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Why we decided to try AI <\/h2>\n\n\n\n
We had minutes, not weeks <\/h3>\n\n\n\n
The warning label <\/h2>\n\n\n\n
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This is fast-food foresight, so don\u2019t expect gourmet quality <\/h3>\n\n\n\n
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How we made them: a prompt-by-prompt guide to creating strategic foresight scenarios using AI <\/h2>\n\n\n\n
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How we used them <\/h2>\n\n\n\n
Even with AI, humans still played a vital role <\/h3>\n\n\n\n
Help us learn more! <\/h2>\n\n\n\n