Table 2 Guidelines Challenge Category...

Table 2

Guidelines

	Challenge	Category	Guidelines for AI platforms
SMEs	Low awareness about AI opportunities provided for the manufacturing sector	Social	Provide an effective dissemination of the services, the products and all the aftersales to attract new companies
	The misuse of data with the huge amount of information that AI algorithms need	Data	Secure SMEs’ trust by the provision of a very clear and easy-to-understand data management
	Difficulties within companies to support the implementation of AI with proper training which can be effective for the company workers	Managerial/Social	Understand the skills of each worker and propose a personalized training path is of primary importance to differentiate the offer from the other platforms and attract SMEs
	The mechanism to eliminate threats to data security and privacy and cyber-attacks derived from the sensible data that the AI algorithms are processing	Data	Emphasize data protection; constantly update conformance with new European laws in the field
	Lack of concrete use cases of companies that perform in the same sector with successful results	Managerial	Provide a section with videos and experiences of users that already joined the platform and implemented some solutions
	Difficulties in finding which technology is the best in accordance with the problem of the company	Social/Technological	Start the proposed solution from the analysis of the critical issues leading to the identification of the best AI technology to deploy, and not from the technology
	The lack of skill is often a barrier to approach AI adoption	Managerial/Social	Provide solutions easy to use and also support the SME in all the steps from selection and implementation till continuous improvement; offer-dedicated trainings tailored to the needs of the specific organization
	The necessity to understand the logic behind the AI algorithms	Managerial/Social	Offer a package of offerings that provide some explanations (tutorials, how to interpret results)
AI developers	Quite low market size of their existing solutions is quite low	Economic	Create an ecosystem with DIHs, companies, and potential customers that are interested in implementing new AI technologies
	Low integrability of the AI solution with the specific platform infrastructure	Technological	Provide minimum requirements that the solution needs to meet to be uploaded in the platform infrastructure
	Low integrability of the AI solution with the modules of other developers	Technological	Provide a common framework for the development of the AI solutions
	The low awareness of the needs of the manufacturing companies	Managerial	Understand the needs of companies and communicate to the developers the most recurrent needs on which they can focus; provide a section with videos and experiences of users in the manufacturing world
	Difficulties in hiring staff with the right skill	Social	Create services supporting AI developers in this context, including training about the platform itself
	The lack of skill/knowledge regarding AI and programming among the staff of potential customers	Social	Assign to each company a person (one from each organization involved in implementation) in charge of assisting and helping with the implementation of the solution
	The high cost of the development of a single AI solution related to the number of customers that use it	Economic	Allow to start from a general version of the solution, and personalize it at a later stage
	The intellectual property of the AI solutions	Political and Legal	Include clear IPR management rules and communicate them directly online
DIHs	The lack of skills/competences to deal with technologies such as AI	Managerial	Include services to enrich the pure platform features with the support in this context, including offer of trainings, mentoring, and tutoring along AI implementation (especially in early phases) to limit the risks of insufficient competences
	Relatively small network/ecosystem of partners (AI developers and SMEs)	Social	Involve more AI supporters than just DIHs, including the academia and consulting companies
	Not recognized reputational risk if the platform is reliable and trustworthy	Ethical	Provide documents that certify the commitment of the platform and the results obtained to be of high quality
	The difficulty in understanding what each AI solution does and understanding if the platform can be a solution to the company’s needs	Managerial	Provide a package of offerings that include some explanations as tutorials for each AI solution
	Reputational risks in using AI	Ethical	Provide materials and online training sessions in this matter, involve professional ethicists/philosophers of science and technology on this issue

	Challenge	Category	Guidelines for AI platforms
SMEs	Low awareness about AI opportunities provided for the manufacturing sector	Social	Provide an effective dissemination of the services, the products and all the aftersales to attract new companies
	The misuse of data with the huge amount of information that AI algorithms need	Data	Secure SMEs’ trust by the provision of a very clear and easy-to-understand data management
	Difficulties within companies to support the implementation of AI with proper training which can be effective for the company workers	Managerial/Social	Understand the skills of each worker and propose a personalized training path is of primary importance to differentiate the offer from the other platforms and attract SMEs
	The mechanism to eliminate threats to data security and privacy and cyber-attacks derived from the sensible data that the AI algorithms are processing	Data	Emphasize data protection; constantly update conformance with new European laws in the field
	Lack of concrete use cases of companies that perform in the same sector with successful results	Managerial	Provide a section with videos and experiences of users that already joined the platform and implemented some solutions
	Difficulties in finding which technology is the best in accordance with the problem of the company	Social/Technological	Start the proposed solution from the analysis of the critical issues leading to the identification of the best AI technology to deploy, and not from the technology
	The lack of skill is often a barrier to approach AI adoption	Managerial/Social	Provide solutions easy to use and also support the SME in all the steps from selection and implementation till continuous improvement; offer-dedicated trainings tailored to the needs of the specific organization
	The necessity to understand the logic behind the AI algorithms	Managerial/Social	Offer a package of offerings that provide some explanations (tutorials, how to interpret results)
AI developers	Quite low market size of their existing solutions is quite low	Economic	Create an ecosystem with DIHs, companies, and potential customers that are interested in implementing new AI technologies
	Low integrability of the AI solution with the specific platform infrastructure	Technological	Provide minimum requirements that the solution needs to meet to be uploaded in the platform infrastructure
	Low integrability of the AI solution with the modules of other developers	Technological	Provide a common framework for the development of the AI solutions
	The low awareness of the needs of the manufacturing companies	Managerial	Understand the needs of companies and communicate to the developers the most recurrent needs on which they can focus; provide a section with videos and experiences of users in the manufacturing world
	Difficulties in hiring staff with the right skill	Social	Create services supporting AI developers in this context, including training about the platform itself
	The lack of skill/knowledge regarding AI and programming among the staff of potential customers	Social	Assign to each company a person (one from each organization involved in implementation) in charge of assisting and helping with the implementation of the solution
	The high cost of the development of a single AI solution related to the number of customers that use it	Economic	Allow to start from a general version of the solution, and personalize it at a later stage
	The intellectual property of the AI solutions	Political and Legal	Include clear IPR management rules and communicate them directly online
DIHs	The lack of skills/competences to deal with technologies such as AI	Managerial	Include services to enrich the pure platform features with the support in this context, including offer of trainings, mentoring, and tutoring along AI implementation (especially in early phases) to limit the risks of insufficient competences
	Relatively small network/ecosystem of partners (AI developers and SMEs)	Social	Involve more AI supporters than just DIHs, including the academia and consulting companies
	Not recognized reputational risk if the platform is reliable and trustworthy	Ethical	Provide documents that certify the commitment of the platform and the results obtained to be of high quality
	The difficulty in understanding what each AI solution does and understanding if the platform can be a solution to the company’s needs	Managerial	Provide a package of offerings that include some explanations as tutorials for each AI solution
	Reputational risks in using AI	Ethical	Provide materials and online training sessions in this matter, involve professional ethicists/philosophers of science and technology on this issue

Source(s): Own elaboration

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