Artificial Intelligence: From Task Automation to Simulating Smart Decisions

Current Use of Artificial Intelligence: Automation and Efficiency

Currently: Most organizations rely primarily on Artificial Intelligence to accelerate administrative tasks. Large language models draft emails, summarize documents, and automate customer support.

Additionally: They can perform tasks such as data analysis, document drafting, and project management, significantly enhancing efficiency and productivity. These tools are undoubtedly useful, but they only touch a fraction of the true potential that AI in business holds.

The Real Opportunity: Artificial Intelligence as a Decision Simulator

The real opportunity: for companies integrating Artificial Intelligence lies not only in automation but also in simulation. The goal is not just to get tasks done faster, but to make smarter decisions before executing them.

Artificial Intelligence can: now model the complexities of the real world, test strategies, and predict the potential impact of decisions before they are made. This changes the nature of leadership: from focusing on performance speed to focusing on the wisdom of the decision.

Major decisions are often based: in both business and government, on historical data, limited scope surveys, or executive intuition. But in a rapidly changing world, this is no longer sufficient. Intuition-based decisions can be difficult to justify, often inaccurate, and limit the ability to see alternative options, especially in complex situations (Harvard Business Impact, 2025).

This was clearly demonstrated: during the COVID-19 pandemic, where critical decisions were made with incomplete data and a high degree of uncertainty. Business leaders face the same risks today when making high-stakes decisions using tools not designed for speed or handling complexity.

Synthetic Populations and Human Behavior Prediction

Simulation provides: a different, more exciting path. Artificial Intelligence can now act as a virtual strategic training room; a digital environment where pricing decisions, product changes, or policy proposals can be tested against realistic, data-rich models of how people respond.

This means: fewer surprises, better timing, and more confident execution. "Synthetic populations" – realistic and data-driven models of audiences – now help companies simulate how potential customers would react to a product, price, or message before launch.

For example: a company like Burger King can simulate the purchasing behavior of Hispanic customers, or Wendy's can understand the impact of a new marketing campaign on sales of a particular product among women (Digital Native, 2025). It's a faster, more accurate way to test decisions, and an increasing number of companies are using it to avoid costly mistakes and optimize strategy early.

Predicting human behavior: is one of the most critical and unsolved challenges in both politics and business. Often, intuition simply replaces evidence due to a lack of Agentic AI tools. But this situation is changing now.

But Data alone: is not enough. Often in business, politics, and public discourse, we speak without a true understanding of the lived experiences that shape how people think and act.

By grounding simulation models: in precise science and a realistic understanding of these diverse perspectives, we provide decision-makers with a clearer picture of how people will respond – not just in theory, but in the real world.

Predictive Artificial Intelligence and Complementing Human Judgment

Management consultants at: Gartner expect more than half of complex business decisions to involve Artificial Intelligence by 2027. But most companies are still in the first stage: using Artificial Intelligence tools to automate tasks, not to shape choices. This is a significant missed opportunity.

For example: predictive Artificial Intelligence tools can be used to simulate how different audiences will respond to advertising campaigns before launch, including testing new product features and developing creative ads (Delve AI).

Instead of relying on intuition: or hoping for a creative risk to succeed, brands can practice reactions in advance – testing everything from sentiment and tone to audience emotions and media placement.

It's not about: replacing human judgment, but complementing it – using Artificial Intelligence to provide insights that would only emerge after the event. Just as prediction revolutionized financial services, predictive simulation is on its way to becoming a natural part of the business decision-making process.