Sports clubs are not only places for physical activity and sporting competition, but also important social and cultural institutions. They promote a sense of community, health and integration. Despite their positive influence, sports clubs face numerous challenges, especially in the modern, digitalised world.
The 5 most important challenges when implementing artificial intelligence in sports clubs
- Data integration and managementSports clubs generate a large amount of data from various sources such as member registrations, training schedules, match statistics and social media. This data needs to be centralised and managed in order to be used effectively for AI applications.
- Lack of expertiseMany sports clubs do not have the technical expertise to implement and utilise AI technologies. There is a need for training and further education for employees and managers.
- Cultural acceptanceIntegration of AI can meet with resistance, mainly from employees and members who have concerns about data protection, job loss or changes in the organisation's philosophy.
- Financial resourcesSports clubs often have limited financial resources, which makes it difficult to invest in expensive AI technologies and hire specialists.
- Ethics and data protectionThe use of AI raises ethical issues and privacy concerns that need to be addressed in order to gain the trust of members and the public.
Importance of a company-wide AI strategy
It is important that all departments of a sports club pursue a consistent AI strategy in order to utilise synergies, avoid duplication of work and ensure that all areas of the club benefit from the advantages of AI. A coherent strategy promotes efficiency, improves decision-making and strengthens the club's competitiveness.
Why the KIROI strategy is so highly valued by over 400 companies
The KIROI strategy offers a structured and comprehensive approach to implementing AI in sports clubs. It covers all relevant aspects, from knowledge transfer to skills development, and ensures that all stakeholders are involved. KIROI promotes the ethical and sustainable use of AI and helps clubs to achieve their goals efficiently and effectively.
KIROI masterplan for sports clubs
Step 1: Share knowledge
- Create understandingStart with information events and training for all employees and association members to raise awareness of the possibilities and benefits of AI.
- Identify target groupsIdentify the key stakeholders, including coaches, players, administrators and members, who will be directly impacted by the use of AI.
- Develop communication strategiesUse various communication channels such as newsletters, social media and association meetings to disseminate information.
- Share best practicesOrganise workshops and seminars with experts who have presented successful AI implementations in similar organisations.
- Obtain feedbackEncourage employees and members to voice their concerns and ideas about the use of AI.
- Appoint AI ambassadorsAppoint AI champions within the organisation to act as contacts and promoters of the AI strategy.
- Presenting success storiesShow concrete examples of how AI has helped other sports clubs to make the added value more tangible.
- Continuous further trainingOffer regular training and information sessions to keep knowledge up to date.
- Use internal platformsSet up an internal knowledge platform where materials and resources on AI are centrally available.
- Promote networkingEncourage exchange and collaboration between different departments and teams to learn from each other.
Step 2: Explore tools
- Needs analysisIdentify the specific needs and challenges of the organisation that can be addressed by AI.
- Market analysisInvestigate available AI tools and technologies that are relevant for sports clubs, such as data analysis software, chatbots or training optimisation tools.
- Initiate pilot projectsCarry out pilot projects to test the effectiveness and suitability of various tools in practice.
- Seek expert adviceConsult AI experts and providers to select the best solutions for your organisation.
- Cost-benefit analysisEvaluate the potential costs and expected benefits of the different tools.
- Plan integrationDevelop a plan for integrating the selected tools into the organisation's existing infrastructure.
- Check user-friendlinessMake sure that the selected tools are user-friendly and intuitive to ensure a high level of acceptance.
- Training and supportOffer training and support for users of the new tools.
- Define success criteriaDefine clear criteria to measure the success of the tool implementation.
- Continuous evaluationMonitor and evaluate the use and effectiveness of the tools on a regular basis and adjust the strategy if necessary.
Step 3: Big data and smart data
- Identify data sourcesIdentify all available data sources in the club, including member data, match and training data, financial data and social media.
- Data integrationDevelop a strategy to centralise and integrate this data in a common platform.
- Ensure data qualityImplement procedures to ensure data quality and accuracy.
- Use data analysis toolsUse advanced data analysis tools to gain valuable insights from the collected data.
- PersonalisationUse the data to create personalised offers and recommendations for members and players.
- Performance analysisAnalyse player and team performance data to optimise training plans and improve match strategy.
- Increase member engagementUse data to increase member engagement, e.g. through targeted communication campaigns.
- Financial managementOptimise the association's financial management through data-driven decision-making.
- Risk analysisUse data analysis to recognise and mitigate potential risks at an early stage.
- Transparency and reportingEnsure that relevant data and analyses are transparent and accessible to all stakeholders.
Step 4: Cultural aspects
- Promoting a culture of opennessCreate a culture of openness and change where innovation and new technologies are welcome.
- Addressing concernsActively address the concerns of employees and members and provide clear information and solutions.
- Role models and leadership rolesPromote managers who act as role models for the use of AI and drive cultural change.
- Change managementImplement systematic change management to support the acceptance and successful integration of AI.
- Teamwork and co-operationPromote cooperation and exchange between different departments and teams in order to utilise synergies.
- Communication strategyDevelop an effective communication strategy to continuously inform all stakeholders about the progress and benefits of AI implementation.
- Share success storiesShowcase success stories and best practices to highlight the positive impact of AI on the organisation.
- Values and visionsIntegrate the use of AI into the values and vision of the organisation.
- Continuous feedbackEncourage regular feedback from all stakeholders to support cultural alignment.
- Reward and recognitionImplement a system to reward and recognise employees who actively contribute to the successful use of AI.
Step 5: Ethics and compliance
- Guidelines and standardsDevelop clear guidelines and standards for the ethical use of AI.
- Data protectionEnsure that all data processing procedures comply with the applicable data protection regulations.
- TransparencyPromote transparency in all AI processes and decisions to gain the trust of members and the public.
- Ethical monitoringImplement a committee or commission to monitor the ethical aspects of AI use.
- Training coursesOffer regular training on ethics and data protection for all employees.
- Responsibility and liabilityClarify the responsibilities and liabilities in connection with the use of AI.
- Avoid conflicts of interestDevelop strategies to avoid conflicts of interest.
- SustainabilityEnsure that the use of AI is sustainable and socially responsible.
- Regular auditsPerform regular audits and reviews of AI systems and processes.
- ReportingCreate regular reports on the ethical and data protection aspects of AI use.
Step 6: Own department
- Needs analysisIdentify the specific needs and challenges of your department that can be addressed by AI.
- Set goalsDefine clear goals for the use of AI in your department.
- Pilot projectsStart pilot projects to test the effectiveness of AI solutions in your department.
- Data managementImplement systems for the efficient management and utilisation of relevant data.
- AutomationIdentify processes that can be automated using AI to increase efficiency.
- PersonalisationUse AI to develop personalised services and offers for members and stakeholders.
- Training and further educationOffer training and further education for your employees to increase their expertise in dealing with AI.
- Feedback mechanismsImplement feedback mechanisms to enable continuous improvement.
- Performance reviewMonitor and evaluate the results of AI implementation in your department on a regular basis.
- Integration and cooperationPromote the integration of your department's AI strategies with other departments.
Step 7: Ideas for other departments
- Marketing and communicationUse AI to analyse target groups and personalise marketing campaigns.
- FinancesImplement AI-supported systems for fraud detection and optimisation of financial decisions.
- Member supportUse chatbots and AI-supported systems to improve member service and process enquiries more efficiently.
- Training departmentDevelop AI-supported training plans and analysis tools to optimise athletes' performance.
- Event managementUse AI to plan and optimise events and increase visitor numbers.
- Human ResourcesImplement AI-supported systems for recruitment and personnel development.
- Facility ManagementUse AI to monitor and optimise the use of sports facilities.
- Security departmentUse AI to monitor and improve safety in the club.
- Research and developmentPromote the use of AI to develop new training methods and technologies.
- Fundraising and sponsoringUse AI to identify potential sponsors and optimise fundraising strategies.
Step 8: Skills development for employees
- Training programmesDevelop comprehensive training programmes to introduce and deepen AI skills.
- Further training programmesOffer regular training programmes to keep employees up to date.
- E-learning platformsUse e-learning platforms to enable flexible and location-independent learning.
- Workshops and seminarsOrganise workshops and seminars on specific AI topics.
- Practice-orientated learningPromote practice-orientated learning through participation in pilot projects and practical applications.
- CertificationsOffer certifications to officially confirm the competences acquired.
- Mentoring programmesImplement mentoring programmes in which experienced employees pass on their knowledge.
- Co-operation with educational institutionsCollaborate with universities and universities of applied sciences to integrate the latest research and best practices.
- Internal knowledge platformsSet up internal knowledge platforms where employees can access training materials and resources.
- Motivation and incentivesCreate incentives and rewards for employees who actively train and improve their AI skills.
Step 9: Skills development for managers
- Management trainingDevelop special training programmes for managers to introduce them to AI.
- Strategic planningProvide managers with the knowledge and tools to strategically plan and implement AI initiatives.
- Change managementTrain managers in change management to support cultural change.
- Ethics and responsibilityOffer training on the ethical and legal aspects of AI use.
- Decision makingPromote the use of data-based decision-making processes.
- Leadership by exampleEncourage managers to act as role models for the use of AI.
- Networking and exchangeEncourage dialogue and networking with other managers and experts.
- Innovation cultureSupport the development of a culture of innovation and continuous improvement.
- Mentoring and coachingOffer mentoring and coaching programmes to strengthen leadership skills.
- Evaluation and feedbackImplement systems for regular evaluation and feedback to continuously support leadership development.
The view from scientific research
Artificial intelligence (AI) is increasingly revolutionising many areas of our lives - and sport is not immune to this. More and more sports clubs are looking at the opportunities offered by AI technologies to optimise processes, improve the performance of athletes or create new experiences for fans. However, the introduction of AI also poses challenges for clubs, as scientists emphasise.
Wide range of possible applications for AI in sport
The potential of AI in sport is enormous. Algorithms and self-learning systems can help athletes to improve their performance by optimising training plans, analysing movement sequences and providing feedback in real time[1][3]. AI can also provide valuable services in talent scouting and player monitoring[9]. There are also applications off the pitch, such as in the administration and marketing of clubs. Chatbots can take over routine tasks in communication with members and fans[4][13]. AI-generated content for social media and newsletters has the potential to increase the reach of clubs[12][14].
The challenge of implementation
As tempting as the possibilities are, the introduction of AI systems is a challenge for many clubs. There is often a lack of technical expertise and financial resources[16]. There are also reservations among coaches and athletes who fear that AI will "dehumanise" sport[8].
According to experts, it is therefore important that organisations take a strategic approach to the topic of AI. "AI projects must be carefully planned and implemented step by step," says Carlo Dindorf from the TU Kaiserslautern[3]. It is important to involve all stakeholders at an early stage and to take fears seriously. Ethical and legal aspects should not be neglected either, emphasises the Nonprofit Academy in a seminar[15]. This is because the use of AI in organisations generates sensitive data, the protection of which must be guaranteed.
Despite the hurdles, scientists agree that there is no way around AI in sport. "Clubs that don't address the issue now will be at a disadvantage in the medium term," predicts Michael Fröhlich from Saarland University[20]. This is because AI is increasingly becoming a decisive competitive factor - not only in professional sport, but also in popular sport. This makes it all the more important for clubs to lay the foundations for the successful implementation of AI technologies now. In doing so, they can count on the support of academia and associations, which are increasingly developing guidelines and best practices for the use of AI in sport[17][19].
Sources and further reading:
[2] https://www.swr.de/sport/hintergrund/kuenstliche-intelligenz-im-sport-100.html
[3] https://ai.hdm-stuttgart.de/downloads/student-white-paper/Winter-2122/KI_im_Sport.pdf
[4] https://sportfive.de/beyond-the-match/insights/digital-support-for-fan-experience
[6] https://www.gecko.de/wissenshub/kuenstliche-intelligenz-im-sport-die-digitale-revolution/
[8] https://www.dw.com/de/k%C3%BCnstliche-intelligenz-im-sport-vom-code-zum-sieg/a-67235020
[11] https://link.springer.com/book/10.1007/978-3-662-67419-2
[13] https://www.zks-zuerich.ch/infodossier-podcast-folge-11
[14] https://www.lsb.nrw/medien/news/artikel/kuenstliche-intelligenz-kreative-maschinen-im-sport
[15] https://hls.global/de/alle-aktuellen-events/
[16] https://www.bisp.de/DE/Home/Shiny_Projects/KI_Expertise.html
[18] https://hls.global/de/produkt-kategorie/kuenstliche-intelligenz/
This KIROI masterplan offers a comprehensive approach to implementing AI in sports organisations. By applying the KIROI steps in a structured way, organisations can ensure that all levels of the organisation are prepared for the use of AI and can use these technologies effectively.
DE 
EN 
EL 
ES 
ZH 
IT 
FR 
PT 
PL 
SK 
TR 
JA 
SV 
DA 
ET 
FI 
KO