5 Analysis 43
6.5 Summary of All Findings
Table 20 – Summary of unique themes grouped within contexts and into logical categories, part 2.
Organizational Context Environmental Context
Category: Investment Concerns
▪ Acquiring costly and problematic solution
▪ Price of an AI solution
▪ Risk of draining more resources than expected before seeing benefits
▪ Risky investment
Category: Legal and Policy Constraints
▪ Ethical consequences
▪ GDPR concerns
▪ Legislation, regulation and compliance constraints
▪ Regulator concerns Category: Owner and Management Views
▪ Management communication
▪ Not perceived as necessary right now
▪ Owner's interests
▪ Unrealistic expectations
Category: Risk Perception
▪ Losing human supervision
▪ Risk of becoming too vulnerable
▪ Risk of technology misuse
▪ Security concerns Category: Resources and Budgets
▪ Budget constraints
▪ Competing priorities
▪ Financial constraints
▪ Firefighting
▪ Human resources
▪ Resources constraints
Category: Strategic Benefits
▪ Unclear benefits of an AI initiative
▪ Lack of clear business case and strategy
▪ Proving short-term benefits
Category: Strategic Risks
▪ Losing human supervision
▪ Moving too fast
▪ Risk of becoming too vulnerable
▪ Security concerns
Category: Transformation Constraints
▪ Dependency on IT department
▪ Implementation capabilities
▪ Incompatibility of an AI solution with an organization's legacy IT systems or processes
▪ Lack of diversity to foster innovation
▪ Non-uniform structure or processes across organization
▪ Slow adoption process
The following four tables below display titles of the themes, descriptions of the themes, cases in which they were identified, and references to snippets of answers (evidence) which were labelled with these themes in the codebook (see Appendix C).
6.5.1 Themes of Multiple Contexts
Table 21 shows 13 themes that were classified within multiple contexts. Themes displayed Table 21 – Themes of multiple contexts.
Theme Context Description Case Codebook
Reference
AI or technology scepticism T/O/E
Having doubtful thoughts about the technology; fear of technology they do not understand; thinking that something could go wrong; concerns of being surveilled.
ABCD #27-39
AI talent access O/E Difficulties in the process of finding and hiring
AI experts. C #44-47
Incompatibility of an AI solution with an organization's legacy IT systems or processes
T/O
An organization’s legacy IT systems or processes are not compatible with or easily adaptable to a vendor’s AI solution or vice versa.
ABC #240-245
Lack of AI competence O/E Lacking skills to be able to manage an AI
adoption project. ABCD #4-26
Lack of AI understanding T/O/E
Employees or customers of an organization not understanding what AI is, not knowing what its purpose is and what the AI technology can do, or not understanding how it works.
ABC #262-271
Losing human supervision O/E
An organization or a regulator being concerned about replacing a human in an organization's process by a potential AI solution.
BC #286-289 Not perceived as necessary
right now O/E The impression that adopting an AI solution is
currently not necessary. BD #318-320
Price of an AI solution O/E
An expensive AI solution or the high cost of adopting a potential AI solution in an organization.
BCD #326-331
Risk of becoming too
vulnerable O/E
Concerns about becoming vulnerable due to reasons such as, e.g., not being able to contact a service provider’s support while using its cloud services to host an AI solution.
C #356
Security concerns O/E
The perception that a potential AI solution may be vulnerable, or may increase the
vulnerability of an organization's systems, to unauthorized external access.
AB #376, #377
Trust T/E Distrust in a potential AI solution. C #389
Unclear benefits of an AI
initiative T/O Unclear or no perceived benefits of the
technology. ABCD #66-80
Unclear use case T/O Unclear or no perceived opportunity to use AI
technology in the organization. BC #93-96
6.5.2 Themes of Technological Context
Table 22 shows 9 themes that were classified within the technological context, excluding 6 themes classified within multiple contexts of which one of them was technological context (see Table 21).
Table 22 – Themes of technological context.
Theme Description Case Codebook
Reference AI perceived as limited The perception that certain AI technology is limited for more
ambitious use. C #40-43
AI technology
perceived as immature
The perception that AI technology is still in its initial phase and
not ready for use. B #48
Complexity of technology adoption
Factors involved in a complicated process of adopting AI-based
technology. A #107
Data quality Missing, insufficient, incomplete or inaccurate data, or poor
structure of data. CD #125-129
Data systems and their capabilities
Parallelly running systems for the same purpose; outdated systems; systems difficult to operate or manage; insufficient options or functions of a system.
AB #130-135,
#137-141 Data systems are not
properly connected
Systems do not communicate with each other, i.e., do not
exchange information effectively or at all. AB #136, #142,
#143 Lack of data Missing data necessary to adopt a potential AI solution. D #272 Technology complexity Attributes of AI technology that make it difficult to adopt it for
certain use cases. C #387
Technology transparency
An AI solution not being transparent enough which makes it
difficult to explain its decisions. C #388
6.5.3 Themes of Organizational Context
Table 23 shows 30 themes classified within the organizational context, excluding 12 themes classified within multiple contexts of which one of them was organizational context (see Table 21).
Table 23 – Themes of organizational context.
Theme Description Case Codebook
Reference Acquiring costly and
problematic solution
Being discouraged by a past technology acquisition which was costly, and it did not prove to be a good decision for the organization.
B #1, #2
Budget constraints An estimate of revenues and expenses for a set period of
time preventing to acquire AI technology. A #49, #50
Theme Description Case Codebook Reference Demanding and long
onboarding process
Difficulties in connection with the process when new employees competent in AI or IT acquire the necessary knowledge, skills and behaviors to be able to contribute to the adoption of AI technology in an organization.
C #144-145
Dependency on IT department
An organization is dependent on knowledge, skills and IT resources of an outsourced IT services department, that was contracted by the owners.
A #165-176
Employee age High employee age in an organization. ABC #178-185
Employees to lead or
promote an AI initiative An organization lacks clear candidates to lead an AI initiative. AB #191-193 Fear of losing job Employee concerns about being replaced by AI technology. AD #203-206 Financial constraints Limited financial resources allocated to acquire AI-based
technology in an organization. ABD #208-212
Firefighting
Spending time and resources on problems that need to be dealt with quickly, instead of focusing on innovation and moving the business forward.
ABD #214-225 Human resources Lack of skilled and experienced employees. AB #234-236 Implementation capabilities
The perception that insufficient implementation capabilities of an organization might hinder adoption of a potential AI solution.
D #237-238
Insufficient employee training
Lack of training and educational solutions for employees in order to make them understand or be able to operate AI technology.
ACD #186-190 Lack of clear business case
and strategy
Unclear or no plan and estimation of time and costs to adopt
the technology. ABD #81-88
Lack of diversity to foster innovation
An organization lacking diversity and new ideas due to the homogeneity of its employees that possess similar competencies and experiences.
B #273, #274
Lack of IT competence or knowledge
Lacking IT expertise and experience with IT projects; low digital and computer skills necessary to operate or work with technology.
ABCD #247-261
Management communication
Lack of communication of the management with employees about the onboarding of a potential AI solution, how the technology will work in an organization and how it will align and fit into an organization.
AD #290-292
Moving too fast An organization is not ready for, is unwilling to, cannot
afford to, or cannot cope with change. A #294-298
No or little prior AI experience
An organization lacking experience with AI-based
technology. ABCD #299-308
Non-uniform structure or processes across
organization
Inconsistent structure, processes or workflow across an
organization. B #309, #310
Not following AI trends
Not being aware of, not being interested in or not spending time to get informed about AI technology and its potential use cases and best practice strategies.
ABD #311-317 Owner's interests Owner(s) not being interested to invest in an AI solution. A #324
Theme Description Case Codebook Reference Proving short-term benefits
An organization not being content with the estimated return on investment in AI technology within a relatively long timeframe.
BD #332-334
Resources constraints
Limited time, financial, human and IT resources, skills, tacit and explicit knowledge, IT infrastructure and equipment, and IT expertise of an organization.
ABD #345-355 Risk of draining more
resources than expected before seeing benefits
An organization’s concerns that adoption of a potential AI solution might consume more financial or human resources than estimated before achieving any return on investment.
AB #358-361
Risky investment Investing time, financial and other resources in new
technology perceived as risky. D #373-375
Slow adoption process The perception that adopting new technology an
organization is a slow and lengthy process. AB #379-381 Tasks or processes that are
challenging to streamline
Tasks or processes in an organization that are not standardized or consistent and therefore are difficult to streamline using AI-based technology.
ABD #382-386
Unrealistic expectations Expecting more than what a potential AI solution can be or
can do. A #391
6.5.4 Themes of Environmental Context
Table 24 shows 13 themes that were classified within the environmental context, excluding 10 themes classified within multiple contexts of which one of them was environmental context (see Table 21).
Table 24 – Themes of environmental context.
Theme Description Case Codebook
Reference Customer contract constraints
Limited flexibility or conditions of a customer contract preventing the adoption of technology that would affect the relationship with a customer.
A #110-114
Customers misunderstanding or not knowing what AI is
Customers discouraged due to used AI definitions;
customers do not understand or are afraid of AI-based technology.
AC #115, #116 Customers not being able to
utilize AI
Factors preventing customers to use and benefit from
AI technology. C #117
Customers not being ready to adapt to change
Customers are not mature enough or not prepared yet
to use AI-based technology. AD #118-124
Dependency on external help
An organization needs consulting services, software development services or human resources of a vendor to able to adopt AI-based technology.
ABCD #146-164
Ethical consequences
Moral concerns related to the use of AI-based technology such as due to potential biases of an AI solution.
C #194-196
Evaluating external vendors and consultants
Inability to choose a reliable and competent company or consultants to help with the adoption of AI technology.
A #197-202
GDPR concerns Data privacy concerns. An organization or a regulator
being concerned about how and where data is stored. CD #226-233 Industry specifics prevent long
term investments
Concerns due to reasons such as, e.g., that the
technology acquisitions of an organization operating in a fast-paced industry might become obsolete in a few years.
B #246
Legislation, regulation and compliance constraints
Rules, policies and law requirements hindering
adoption of a potential AI solution. AC #277-285
Regulator concerns
A regulator not understanding how AI works or being concerned about the use of AI technology due to ethical consequences, biases, security and other factors.
C #335-344
Risk of losing reputation and damaging customer
relationships
Concerns about adopting a potentially problematic AI solution and alienating customers, discouraging customers by using the term AI, or replacing personal services with an automated solution.
ACD #362-370
Risk of technology misuse
Concerns about the misuse of an AI solution by a third party, e.g., by knowingly influencing parameters that the algorithm takes into account.
C #371