Predicting the Future: Using AI to Enhance Strategic Futuring Processes
By Rick Aman on"Prediction is very difficult, especially if it's about the future." — Niels Bohr
Forecasting the future has long been a challenge for individuals, institutions, and entire regions. Strategic futuring, the process of envisioning and planning for potential futures, has evolved from guesswork and speculation into a more structured and insightful approach, particularly with the integration of artificial intelligence (AI). In the futuring process, AI is increasingly used as pre-work to support committee discussions, providing data-driven insights and trend analyses that inform human deliberation. By analyzing available public data and identifying emerging patterns, AI sets the stage for more focused and informed conversations about the future. In this third article in my series on strategic futuring, I’ll explore how AI enhances the preparation phase of committee-based or leadership team futuring and share examples related to community colleges, Eastern Idaho, and in-demand jobs for technical graduates.
As I reflect on the role of AI in strategic futuring, I’ve come to appreciate how it enhances accuracy, reduces bias, and speeds up predictions compared to traditional methods. Instead of relying on instinct or anecdotal evidence, AI allows us to analyze data in ways that were once unimaginable. The central question I’ve been exploring is: How can AI be used not only to enhance predictions but also to help leadership draft outlooks that shape strategic decisions? AI plays a critical role in the early stages, aiding institutions in conducting draft environmental scans, guiding leadership discussions, and engaging with business and community stakeholders. This foundational work helps colleges move toward a "preferred future" as part of their strategic planning efforts.
The Advantage of AI in Predicting a Draft of Future Trends
One of the key advantages of AI is its ability to process large amounts of data and identify patterns. By leveraging machine learning algorithms, natural language processing (NLP), and predictive analytics, AI can generate forecasts based on historical trends, real-time data, and emerging signals from various sectors. This is done with publicly available regional data. This ability to find correlations and patterns hidden within complex datasets gives organizations an advantage when planning.
In my work with strategic futuring, I’ve used AI to provide high level insights that traditional forecasting methods might have missed. It’s not just about numbers or trends; it’s about connecting the dots in ways that weren’t previously possible. AI does this by processing and analyzing a variety of data sources, everything from economic reports and industry projections Department of Labor reports, and academic research. This capability makes it invaluable in predicting future developments in industries as varied as education, regional economic development, and workforce trends.
Conducting Environmental Scans with AI
Before diving into any strategic planning or futuring work, one of the most important steps is to conduct an environmental scan. This process involves systematically analyzing external and internal factors that could affect a region and organization’s future. It involves assessing trends, opportunities, and threats in areas such as politics, economics, society, technology, and the competitive landscape. Colleges often turn to consulting firms for thorough research, but I propose leveraging AI to identify trends and themes before embarking on the time-intensive process of a formal environmental scan. AI has the capability to quickly analyze vast amounts of data, uncovering patterns that may not be immediately apparent to human analysts. By automating the early stages of this process, AI can deliver valuable insights, laying a strong foundation for team discussions and informed decision-making.
Here are key components of a draft environmental scan:
Trend Identification: AI can sift through extensive datasets, including government reports, industry studies, economic forecasts, and even social media, to identify emerging trends relevant to your institution. Whether it’s demographic shifts, technological advancements, or policy changes, AI can highlight crucial factors that should shape your strategic conversations.
Competitive Analysis for Community Colleges: AI can benchmark your institution in real time by analyzing enrollment trends, program offerings, and workforce alignment at peer colleges. By scanning public reports, industry data, and regional job market trends, AI offers a clear view of how other institutions are adapting and evolving. This competitive analysis helps your college identify program gaps, position offerings effectively, and anticipate challenges prior to strategic planning.
SWOT Analysis: AI can support the identification of Strengths, Weaknesses, Opportunities, and Threats by comparing your college’s data such as graduation rates, enrollment figures, and community impact against broader industry benchmarks. This helps reveal areas of opportunity and highlights vulnerabilities that may need to be addressed.
Regional Focus: AI can delve into specific regional economic and workforce data crucial for community colleges. For instance, in Eastern Idaho, AI can analyze trends in sectors like energy, agriculture, and technology, providing insights into how these shifts might influence future workforce needs and inform program development at your college.
By the time the team gathers for strategic futuring sessions, AI-generated insights would allow the group to focus on higher-level decision-making rather than data gathering. This kind of AI-enhanced environmental scan ensures that everyone starts the conversation with the same, up-to-date, and comprehensive information.
Community Colleges and the Future of Education
Community colleges play a vital role in preparing students for the workforce, particularly in an era where technological advancements and economic shifts require continuous skill upgrades. However, predicting how the educational landscape will evolve over the next decade can be difficult. This is where AI can provide some clarity, or at least some ideas.
By using AI to analyze educational patterns, we can identify and predict key opportunities for growth in community colleges.
1. AI-Enhanced Learning: Community colleges are increasingly adopting AI-driven tools to boost student engagement, personalize learning pathways, and optimize course offerings. AI can forecast which programs will see rising demand by analyzing labor market trends and societal needs. For example, AI can scan regional and national employment data to pinpoint emerging industries that require specific technical skills, allowing colleges to adjust their curricula to meet future workforce demands.
2. Student Retention and Success: AI models can predict which students are at risk of dropping out by analyzing factors such as attendance, academic performance, and social involvement. Predictive analytics can guide timely interventions, enabling colleges to build personalized support systems that improve student retention and overall success rates.
3. Program Offerings and Future Demand: AI is already assisting colleges in determining which programs to expand or phase out based on job market projections. For example, AI can assess job postings and employment data to reveal growing fields like healthcare professions, renewable energy, and cybersecurity. This insight enables community colleges to adapt their course offerings, ensuring students are equipped with the skills required for tomorrow’s job market.
I will provide several sample AI “prompts” to help guide leadership in exploring futuring opportunities for community college initiatives. AI excels at generating ideas and lists, and its effectiveness increases with more focused and precise prompts.
These AI-generated insights are key for community colleges leadership to adapt and stay relevant as the workforce evolves. AI offers guidance in determining which sectors to invest in, which programs to cut, and how to realign missions around workforce needs.
Eastern Idaho: Predicting Regional Growth with AI
For the purposes of an example, Eastern Idaho has a unique economic landscape, shaped by industries such as agriculture, energy (particularly nuclear energy), and manufacturing. As the region evolves, predicting its economic future is crucial for ensuring sustainable growth and job creation.
AI Prompt Example: “List five potential future two-year technician jobs for eastern Idaho in the next five years”
Results:
Nuclear Energy Expansion: Continued growth in nuclear energy research and innovations, particularly at the Idaho National Laboratory (INL).
Renewable Energy Projects: Increased investment in solar, wind, and energy storage technologies in the region.
Agri-Tech Growth: Expansion of precision agriculture and automation in farming to enhance productivity and sustainability.
Manufacturing and Advanced Technologies: Growth in advanced manufacturing sectors, including robotics and automation-driven industries.
Tourism and Outdoor Recreation: Moderate growth in tourism, outdoor recreation, and eco-friendly industries due to the region's natural attractions.
AI Prompt Example: "Analyze the future economic growth and industry trends for Eastern Idaho, focusing on health care, energy and agriculture sectors"
Results:
Energy: Continued expansion in nuclear energy research at the Idaho National Laboratory (INL), along with growth in renewable energy sectors like wind, solar, and energy storage technologies.
Health: Increasing demand for healthcare services driven by an aging population, with telemedicine and healthcare technology playing significant roles in regional healthcare infrastructure.
Agriculture: Growth in precision agriculture, with innovations in automation, robotics, and sustainable farming techniques improving efficiency and crop yields.
Manufacturing: Advanced manufacturing and automation technologies will support local industries, particularly in energy and agricultural equipment production.
Workforce Development: Regional workforce training will increasingly focus on technical skills for energy, healthcare, and agri-tech sectors, aligning with the evolving demands of these growing industries.
These AI insights can help educational institutions prepare for the programs that will serve for a future where energy, health and agriculture are bolstered by technological advancements. By understanding where the growth is happening, stakeholders can better allocate resources, support higher ed, and plan for a prosperous future.
In-Demand Jobs for Two-Year Technical Graduates
Another key area where AI has proven invaluable is in predicting future job markets, especially for technical graduates. As the workforce continues to evolve, understanding which careers will be in high demand can help community colleges tailor their programs to better serve students and local economies.
Here’s how AI enhances our ability to forecast the job market for two-year technical graduates:
Job Market Analysis: AI can analyze job posting data, salary trends, and employment rates to predict which jobs will be most in demand over the next five to ten years. Fields like healthcare technology, advanced manufacturing, and green energy are currently showing signs of strong growth, but AI allows us to drill down further to discover specific job roles that are emerging.
Skill Matching: AI tools are becoming increasingly adept at matching students’ skills with future job markets. This goes beyond simply looking at current job titles. AI can analyze trends in required skills and qualifications, helping institutions design programs that teach the most relevant and in-demand competencies.
Critical Skills Identification: AI can identify not only key technical skills, but also soft skills that are becoming essential across all industries. Skills such as teamwork, critical thinking, adaptability, writing, and communication are increasingly valued alongside technical proficiency in fields like renewable energy, data analytics, and cybersecurity. AI can analyze job market trends to pinpoint which soft skills, in combination with technical expertise, will give graduates a competitive edge, allowing colleges to integrate these competencies into their programs and better prepare students for the existing workforce.
Automation and Future-proofing Careers: AI is also instrumental in predicting which jobs are most likely to be affected by automation. This enables technical programs to focus on roles that require a human touch or those that involve the maintenance and operation of automated systems fields that are less likely to be replaced by AI itself.
Conclusion: AI as a Strategic Futuring Tool
The examples I’ve shared represent only a glimpse of how AI is reshaping the process of strategic futuring. Whether it's forecasting the future of education, regional development, or workforce trends, AI provides unparalleled insights that enable more informed decision-making. It’s important to remember that while AI tools are valuable, they don’t replace leadership retreats, planning sessions, expert input, employer feedback, or economic forecasts. Instead, AI serves as a starting point, enhancing the efficiency and focus of the overall planning process.
In my work, AI has become an indispensable tool for exploring different scenarios and preparing for a preferred future. What excites me most about AI is not just its ability to analyze data or identify patterns, but its potential to challenge our assumptions and expand our thinking. When used effectively, AI can help us see possibilities that we might have otherwise missed.