Project results
MERIT Project: Aligning Academic Programs with Industry Needs in AI, Cybersecurity, and IoT
The rapid pace of technological advancements in fields like Artificial Intelligence (AI), Cybersecurity (CS), and the Internet of Things (IoT) has created a growing demand for skilled professionals who can navigate the complexities of these domains. However, a persistent challenge has been the misalignment between academic curricula and the ever-evolving requirements of the industry. This blog post highlights the efforts of the MERIT project, a European initiative aimed at addressing this gap by equipping the next generation of experts with the knowledge and skills needed to thrive in these critical areas.
As part of its Work Package 3 (WP3), the MERIT project has developed a rigorous methodology to identify and prioritize the most relevant topics, skills, and technologies for its consortium universities to update and deliver their master’s programs. The methodology involves a comprehensive analysis of research literature, industry reports, and forecasts, as well as gathering valuable insights from small and medium-sized enterprises (SMEs) across various regions.
In its second year, the MERIT project has applied this methodology to validate and build upon the results from the first year. The key outcomes include:
- An updated understanding of the expertise areas within the MERIT consortium;
- A revised set of envisaged skills for students enrolled in the consortium’s master’s programs, derived from the program syllabi;
- An updated list of data sources and keywords used to investigate current and forecasted topics and skills in AI, CS, and IoT;
- A new set of topics and skills identified from research, statistics, reports, and forecasts, crucial for training experts in these domains;
- A collection of technologies derived from questionnaires administered to SMEs in the consortium’s partner regions, enabling the integration of industry needs into the study programs;
- A carefully defined mapping from topics to technologies, facilitating the application of the skills acquired during the study program;
- A prioritized list of topics that can be used to update and complement the MERIT courses and related activities.
The goals of this work are threefold:
- Guide the upgrade of the MERIT master’s programs to support current and future industry needs by producing highly specialized graduates in the most relevant AI, CS, and IoT topics;
- Impact society by aligning with the MERIT communication and dissemination strategy, involving regional SMEs to help fill potential skill gaps, and organizing future dissemination events;
- Increase the expertise of consortium members from both research and industry perspectives.
Key results from answers to questionnaires submitted by small and medium-sized enterprises (SMEs) across various regions
30 SMEs were inquired via questionnaires in MERIT partners’ regions to find current industry needs, that are essential to make the study programs operational. Questionnaires were composed by a set of 50 topics, technologies and application scenarios adopted currently or up to the next two years by SMEs.
The topics and technologies, as well as the application scenarios highlighted in the questionnaire replies seem to deviate from those obtained from the analysis in the literature: this demonstrates a gap between research and industry, which on one hand can highlight delays in the adoption of cutting-edge technologies; and on the other, the need to obtain a larger survey sample.
Following is the key results from answers to questionnaires submitted by SMEs across MERIT partners’ regions.
Artificial Intelligence questionnaire
The AI questionnaire received 13 responses from organizations in fintech, accounting, telecommunications, robotics, education, cybersecurity, marketing, and IT services. The results are:
- 6 out of 13 use AI for algorithm design, product marketing, business management, and technology design/programming;
- 7 out of 13 currently use data processing/management and knowledge representation/reasoning skills;
- 8 out of 13 adopt machine learning technologies and AI tools for reasoning, problem-solving and ideation;
- 9 out of 13 employ AI with cloud technologies
However, few organizations reported using AI in the future for smart manufacturing, AI adoption indexing, retail, agriculture, autonomous driving, or spatial data processing – signaling opportunities in those areas.
Cybersecurity questionnaire
The cybersecurity questionnaire was answered by 10 organizations operating in cybersecurity or related domains like fintech, robotics, AI, IoT, and IT services. The key results are:
- 4 out of 10 organizations are currently using machine learning with context-awareness, human-computer interaction, monitoring large-scale systems, ransomware prevention techniques, and SOC as-a-Service;
- 5 out of 10 leverage decision intelligence techniques to prevent operation systems vulnerabilities;
- 6 out of 10 adopt SaaS business models and phishing prevention techniques;
- 7 out of 10 use predictive analytics and user behavioral tracking.
Internet of Things questionnaire
This questionnaire had 8 respondents from software, marketing, robotics and IT service providers. The results are:
- Majority of organizations use IoT applications in environment (5/8), home (6/8), transportation (6/8), and industry (7/8);
- 4 out of 8 plan to deploy more home, transportation, and city applications within a year;
- Currently used technologies include digital twins (4/8), intelligent sensors (5/8), and cellular IoT (7/8);
- Within a year, 4 organizations plan to adopt blockchain for IoT, data ecosystems/spaces, and IoT platforms. 5 will use edge analytics and TinyML.
The interest of organizations from the IoT questionnaire focuses on digital twins and intelligent sensors; and ranges across different sectors, such as environment, home, industry, and transportation.
Overall, the questionnaires provided valuable insights into current industry adoption and future interests across cybersecurity, AI and IoT technologies – helping identify relevant skills for academic programs.
Key findings and final recommendations
Bridging the Research-Industry Gap: The analysis revealed a notable gap between the topics and technologies explored in academic research and those currently adopted or planned for adoption by the industry within the next two years. This highlights the need for closer collaboration between academia and industry to ensure timely knowledge transfer and the integration of cutting-edge innovations into practical applications.
Emphasis on Soft Skills: In addition to technical skills, the project underscored the importance of soft skills for future graduates, including leadership, communication, problem-solving, critical thinking, and ethical behavior. These skills are essential for effective collaboration, decision-making, and navigating the complex ethical and societal implications of emerging technologies.
Synergies Across Domains: The analysis revealed significant synergies across AI, CS, and IoT, highlighting the need for multidisciplinary expertise. Professionals with knowledge spanning these domains will be well-positioned for highly specialized roles, such as leveraging AI in threat intelligence or securing AI algorithms.
The MERIT project’s WP3 findings provide a roadmap for academic institutions to align their curricula with industry demands, equipping students with the skills and knowledge necessary to drive innovation and tackle real-world challenges. By fostering collaboration between academia and industry, projects like MERIT contribute to a more skilled and adaptable workforce, capable of navigating the ever-changing technological landscape.