In the March edition of the “12th at 12” series, published on the MCSC website, we take a closer look at how artificial intelligence is moving from the stage of experimentation to real applications in business and healthcare. Monika Dobrzeniecka (IMiD) speaks with Tomasz Chyrchel – AI expert, CEO of Generator Pomysłów and the initiator of the AIDEAS program – about how the program is evolving, what kinds of solutions its participants are creating, and which AI trends may have the strongest impact on the healthcare sector in the coming years.
Tomasz Chyrchel has spent more than a decade working with new technologies in product and service development processes. He specializes in designing innovations using the Design Thinking methodology, supporting organizations in business development (customer experience) as well as in improving processes and the work environment (employee experience). He is the initiator and director of the AIDEAS program.
Monika Dobrzeniecka: How has the concept of the AIDEAS program evolved from the perspective of experts – from the first cohort to the current one?
Tomasz Chyrchel: From the very beginning, the AIDEAS program has been based on cohort learning, combining individual self‑learning with intensive teamwork on real case studies. This means the program cannot simply be “clicked through” – it requires active engagement and work on specific business problems.
However, the experience of subsequent editions has shown that this format is time‑intensive. That’s why the concept of the program is currently evolving toward greater flexibility and personalization. Alongside intensive development paths, shorter learning formats are being planned – “knowledge pills” that will allow participants to acquire specific skills in a shorter time while maintaining a high level of academic quality.
What sets AIDEAS apart from other development programs in the field of AI and digital skills?
AIDEAS stands out first and foremost through its cohort‑based model of working on real projects. Participants begin by acquiring knowledge individually, and then – working in small teams – they develop AI solutions that address real business challenges.
Case studies are provided by partners from various industries, including Grupa Polsat Plus, Polpharma, and Maspex. Another important element of the program is peer‑to‑peer feedback: participants evaluate each other’s ideas and solutions, which helps them learn faster and broaden their perspective.
What types of solutions have been developed within previous cohorts, and what potential do they hold for the development of medicine and healthcare innovation?
Participants of the program have demonstrated that creating useful AI tools does not require being a programmer. Among the project teams, the following solutions were developed:
- knowledge aggregators – AI agents that collect information from scientific publications, drug registries, or industry reports,
- substance analysts – tools that classify data on new active substances,
- innovation navigators – systems supporting the analysis of development directions for generic drugs.
These solutions can support, among other things, the analysis of clinical studies, monitoring of the therapy market, or the circulation of medical documentation. Thanks to automation, teams can make quicker use of scientific knowledge and make strategic decisions more efficiently.
Additionally, AI systems were created to generate documents compliant with regulations. They produce documents – such as powers of attorney or resolutions – based on approved templates and check their compliance with legal requirements. In the healthcare sector, this primarily means streamlining documentation processes and significantly reducing the workload of administrative and legal teams.
What skills do participants most often say they have gained thanks to the program?
The most frequently mentioned benefit is a structured understanding of artificial intelligence – its capabilities, limitations, and real‑world applications.
Another important area is the practical ability to build AI agents and automate processes. Participants learn how to design their roles, connect them into teams, and create functioning solutions.
A significant change is also a more conscious approach to prompting and communicating with language models, which makes using AI tools more effective.
Many participants also highlight an increase in confidence when working with technology – AI stops being a topic reserved for programmers and becomes a tool for everyday work. The program often inspires further professional development in the field of new technologies.
What does the process of integrating participants into teams look like, and what methods are used to support collaboration?
Participant integration is a multi‑stage process. Teams are formed based on individual interests, project areas, and the level of participants’ engagement.
Where teams do not form organically, participants are grouped around shared topics and project challenges. A key element of integration is working on a specific project – mfrom defining the problem to presenting the final solution.
The diversity of professional experience fosters an exchange of perspectives and strengthens communication skills. As a result, teams not only deliver their project but also learn how to collaborate effectively across different fields.
How does the AIDEAS program address AI ethics and regulation?
Ethics and regulation are an integral part of the program. Participants complete a module covering topics such as the AI Act, GDPR, and copyright law, learning how to use AI tools in compliance with current regulations.
The program also emphasizes AI governance and compliance – that is, managing risk, data security, and the responsible implementation of technology within an organization.
Additionally, participants take part in expert sessions where they can confront real organizational challenges with the knowledge of specialists in law and technology.
In the context of HealthTech trends – which directions of AI development are considered the most promising by experts?
Experts point to three main directions of AI development in medicine:
AI‑driven Drug Discovery – artificial intelligence can significantly shorten the process of developing new therapies, for example by generating new molecular structures and predicting their toxicity.
Digital Twins – creating virtual models of a patient’s body makes it possible to simulate the effects of therapies before they are applied, supporting the development of precision medicine.
Hospital at Home and remote patient monitoring – algorithms analyzing data from wearable devices can predict health deterioration even several hours in advance, enabling rapid intervention.
How can the AIDEAS program support the development of these trends in the future?
The development of technologies such as digital twins or AI‑driven drug discovery requires specialists who are able to work practically and effectively with artificial intelligence.
The AIDEAS program acts as a bridge between advanced technology and everyday business practice. Participants learn to build their own AI agents, work in a no‑code model, and solve real problems provided by industry partners.
Thanks to this, experts from the medical, legal, and administrative sectors also gain the competencies needed to initiate and implement innovation within their organizations.
What is the one key piece of advice AIDEAS experts would give to people in the medical sector who want to start implementing AI but lack technical experience?
The most important advice is: start acting and testing tools now.
The best way to understand AI is through practice – experimenting, learning from mistakes, and gradually introducing small improvements into everyday work.
In healthcare, innovation rarely begins with large systems. Most often, the first step is a simple solution that automates a single repetitive process. These small initiatives are the best starting point for building skills and gaining experience.