GenAI’s role in business development

Generative Artificial Intelligence (GenAI) has been rapidly transforming the way businesses operate, with new use cases emerging across various domains, from strategic planning to operational execution. One particularly exciting and impactful area of AI application is business development.

While GenAI-based chatbot tools like ChatGPT are easy to use and valuable for generating ideas and assessing their viability, they often fall short when it comes to addressing the more complex challenges that businesses face. Practically every organization, at some point, struggles making informed decisions on crucial business development issues with limited information. So, what tools are available to support these decisions?

This is where interactive GenAI simulations can play a key role. These simulations allow businesses to model complex scenarios, evaluate potential outcomes, and develop essential business development skills in a controlled environment. They provide leaders with the opportunity to engage in decision-making processes and test their strategies or hypotheses in realistic scenarios, all while avoiding the risks associated with real-world consequences.

To better illustrate this, let’s take a look at a concrete case example.

The farming industry as a case study

While often perceived as traditional, farming is actually one of the most complex and risk-intensive business sectors. Farmers must balance fluctuating costs, unpredictable weather, regulatory requirements, long investment cycles, and increasing pressure to modernize operations.

These conditions make farming an ideal testbed for AI-supported decision-making in the context of business development. From financial forecasting to equipment investments and compliance reporting, AI simulations can serve as a powerful partner in helping farm owners analyze trade-offs, manage uncertainty, and build resilience in their operations.

The Atria event: AI simulation in action in the farming industry

A recent example of this in practice took place at the Atria Liha-Akatemia event, an annual highlight for professionals in the meat industry. The event brings together hundreds of farm owners and key stakeholders from the agricultural sector, offering timely and thought-provoking presentations. One of the key sessions featured Professor Jaakko Kujala, who spoke on the topic, “What Defines Success in Farm Management.”

During his presentation, attendees were introduced to a new generative AI-based application developed using LessonLab’s Taito platform. This innovative tool was designed to support the development of management capabilities within farm operations, combining real-life decision-making scenarios with AI-powered interactions.

The simulation included four key components:

1. Goal setting: The tool helps farm owners set both short-term and long-term objectives tailored to their specific circumstances. AI guides users to reflect on their goals, summarizing these into clear, actionable objectives.
2. Cost evaluation: Focusing on farm cost management, the simulation uses a representative farm case to guide users through cost assessments. AI encourages users to refine their own cost structures by considering different variables and outcomes.
3. Investment decisions: This component addresses critical investment choices, particularly in relation to tractor purchases, one of the largest expenses for farms. Users first define their desired tractor specifications, and then AI challenges them to evaluate the investment from multiple perspectives, considering features like automation levels and tire specifications, which are key in making well-informed purchasing decisions.
4. Regulatory reporting: AI assists farm owners with the complex task of completing mandatory reporting. By simplifying this process, the tool serves as a reliable, always-available partner, streamlining a traditionally cumbersome task.

The simulation sparked engaging discussions among participants and demonstrated how generative AI simulations can not only enhance operational insights but also facilitate strategic dialogue and decision-making among stakeholders.

Broader implications: AI in business decision-making

What’s striking about this example is how applicable it is beyond agriculture. The core challenge, navigating complex decisions in dynamic environments, is universal across sectors. Whether in manufacturing, logistics, finance, or services, organizations are facing similar pressures to make smarter, faster decisions.

GenAI simulations can offer a scalable, adaptable approach to developing these capabilities. They allow businesses to replicate critical decision points, test strategies and hypotheses, and build skills. All without the cost or risk of real-world consequences.

Conclusion: The future of AI in business development

The case of Atria and LessonLab’s simulation shows that GenAI is already helping business leaders sharpen their thinking and drive better outcomes, even in industries not typically associated with high-tech solutions.

As GenAI technologies continue to evolve, we expect these tools to become even more intuitive, interactive, and integrated into everyday business development. Organizations that invest now in AI-driven simulations are setting themselves up for long-term resilience and success in an increasingly complex world.

At LessonLab, we believe that AI-powered simulations are not just tools for the future—they are practical solutions for fostering critical thinking and strategic insight today.

Authors

Jaakko Kujala, Ph.D., Professor, University of Oulu

Jere Lehtinen, Ph.D., COO, LessonLab Oy