IT 9: Entrepreneurship, Technology, and Society: AI Impact

This essay examines the development of Artificial Intelligence (AI) and its profound influence on entrepreneurship and society. It emphasizes the critical role of innovation and entrepreneurship in a knowledge-based economy, particularly in light of technological advancements. The essay discusses AI's ability to modernize business processes, products, and services, as well as its impact on various sectors like healthcare and manufacturing. It highlights the connection between AI and knowledge management, exploring how AI can extract information from big data. Furthermore, the essay addresses the social and technological transitions influencing AI's development, including the potential for job automation and the need for adaptation. It underscores the importance of AI adoption, competition, and other factors that drive its diffusion. The paper also explores the transformative effects of AI on the community, economy, and governance, emphasizing the need for oversight and adaptation to navigate the changes brought about by this technology.

Running Head: IT 0
Entrepreneurship, technology and society

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What explains the development of Artificial Intelligence and what is likely
to influence the development of Artificial Intelligence
In this present competitive era, innovation and entrepreneurship are perceived as the critical
components of knowledge based economy vital for businesses to sustain in the dynamic
business environment. The global business environment is transformed with advancement of
technology, e-business and e-commerce while challenging the conventional business models
demanding the implementation of innovation at both individual levels (start-ups) and at the
corporate level (Foss and Saebi, 2017). Furthermore, productivity, efficiency and
competitiveness now highly rely on the entrepreneurship and innovation for the organisation
of innovation and the production of knowledge. Recent technologies progress in the space of
Artificial Intelligence are transforming business and entrepreneurial landscape significantly.
These technologies and innovation have already infiltrated firmly into various areas of the
business, personal and professional and even routine life (Bounfour, 2016). In relation with
artificial intelligence, it has a great ability to modernise and develop business process,
products and services, innovative ideas and resolve complex tasks in producing new
outcomes for the huge growth of entrepreneurial operations and practices. However, there are
various social and technological transition likely to influence the development of artificial
intelligence and the value that technology brings to the world is worth the risk. Some industry
is at start of their AI passage and others are expert travellers. Both are influenced by this
transition and have a long mode to go and hence, the influence of AI is hard to ignore
whether on individual or business aspect.
According to Ghahramani (2015), artificial intelligence (AI) is comprehensive branch of
computer science related to developing smart machines proficient of executing tasks the
usually needed humanoid intelligence. In every industry, artificial intelligence is known to be
interdisciplinary science with manifold approaches, however, advancement in machine
learning is forming a standard shift in practically all area. Considering the future, AI will be
the mainstream recommendation engine in various sectors and business arena providing
facility to businesses and individual for accurate and effective predictions so as to take timely
actions and takes simulations to the next level. The development of AI lies its importance
where it powers monotonous learning and discovery via data and adds intelligence over
progressive learning algorithms. This technology also attains unbelievable precision while

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analysing more and deeper data and gets out the most out of it. If applied maturely, artificial
intelligence can benefit community and economy on a very positive mark while using data
and information gathered through algorithms and to identify significant threat and expression.
The usage of AI can also influence the practice of a number of rights and there are still main
revolutions that have to occur before one range at a particular level (Lee and Lee, 2015).
With increasing amount of data and complexities, each sector has a high demand for the
capabilities of artificial intelligence whether healthcare, retail, banking or manufacturing. For
example, AI applications in healthcare can offer tailored medicine and X-ray interpretations
and individual health care assistants can deed as life coaches, reminding an individual to take
the medicines, workout or consume healthier. In relation to characteristics of knowledge and
artificial intelligence, humans and organisations have started to preserve as much knowledge
as possible and the evolution of knowledge transformation and management has come a
considerable way where various researchers have claimed that knowledge management is a
tactical procedure where organisations form worth from intangible assets and here the
technology i.e. artificial intelligence has develop to be a buzzword while making its presence
ubiquitously from information technology to automobile industry, household utilisations and
many more. From the 1990s to the 2000s, AI has penetrated into several sectors and thus
multidisciplinary stream as various divisions such as robotics, virtual reality, expert systems,
natural language processing and many-more (Li and Du, 2017). On the other side, knowledge
management is an integrative field that is called to feature psychology and cognitive science
and therefore, help enterprise and people in creating, sharing, using, collaborating and re-
using knowledge as much as possible. Both knowledge management and artificial
intelligence circle near “knowledge” that can also be treated as a key component. On the
other hand, AI (artificial intelligence) offers all mechanism to systems that required to gather
knowledge and learn from different sources, processing data using of orderly rules and later
on, execute that collected knowledge in the best spaces.
This exceptional connection amid knowledge management and artificial intelligence has also
resulted in cognitive computing that uses various computerized models encouraging the way
in processing of things. From future perspectives, there will be massive online knowledge
bases that will have tons of data, information and knowledge over which businesses and
individuals will gain competitive advantage in the industry. However, there may be a
challenge relating to the presence of unstructured data bringing the scenarios and concepts
like of “Big Data” and there, AI and cognitive computing can be considered as a crucial tool

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for taking out information from big data (Sheth, 2016). Ultimately, AI integration will
develop itself as a significant part of the corporate practices and operations becoming highly
relevant for the decision makers and management. It also simplifies knowledge discovery
while connecting data from disparate sources. The decision support system of an organisation
will also get strong and it offers important knowledge management metrics in response to
direct outcome of the knowledge management efforts.
Artificial Intelligence and the production of knowledge act on the insights derived from the
bunch of data and with integration and improvements in storage systems, processing speeds
and analytic techniques, they are proficient of tremendous sophistication in decision making
and in-depth analysis. Bryson and Winfield (2017) said that AI is already altering the world
and bringing important questions for the community, economy and governance. The culture
also surrounded with increasing pace of change connected together with ICT and improved
capacities transformed the ease with which individuals and corporates from all over the globe
can gain knowledge and other benefits of modern inclusive society. In relation with AI
transitions and the gales of creative destruction, Artificial intelligence is just the technology
in the long line of innovation which contributes to creative destruction. This technology as
the potential to reshape skill demands, carer prospects and the distribution of employees
among different sectors. More specifically, artificial intelligence is designed to perform a
particular task which alters demands for specific workplace skills. Miailhe (2017) stated that
there is needed of potential reinvention and reform to make the AI revolution work for
everyone and enable viably and repeated professional transitions. The likely aids of the
artificial intelligence revolution are really value and as per many researchers, the predicted
surge of productivity increases has the latent to endure development and growth over the next
decades and rise of artificial intelligence could also completely improve the quality of life for
all, via revolution in the different sectors and domains. Taking an example, it was found that
Americans waste about 30% of their food and medicine as of highly inefficient supply chains
and Seeloz based in California is seeking to fix the issue through artificial intelligence
technology (seeloz.com, 2018). Leveraging AI and cloud platform, it's OOS (Operational
Optimization System) has already decreased product expirations by more than 50% and cut
overall supply spend by 5 to 20% via intelligent supply chain solutions (Campbell, 2018).
Ultimately, all this explains the development of AI where government and industries are
struggling on top of a continually rising set of risk vectors and massifs of data. This is the
place where AI can assist with an ability to process massive amount of data and the

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increasing acceleration of innovation add to AI ability to adapt to new situation and solve
issues that presently seem to be impossible. Artificial intelligence and machine learning are
just the beginning of a revolution that will transform everyday life and one interact with the
technology (Makridakis, 2017). The oversight required to be on the national and international
level so that all nations can be at pace to development and experience growth monitoring the
usage of artificial intelligence. With the prompt growth in development and technology,
businesses and corporates can expect a lot more exciting features and uses of AI applications
benefitting corporates with upsurge in productivity and new specializations along with the
fourth industrial revolution distinctly powering new global phenomenon with contributions
from all over the world.
In relation to artificial intelligence, there are various factors likely to influence its
development such as social shaping of technology, adoption and diffusion of innovations and
other environmental factors. The transformative impact of artificial intelligence on the
community will have far-reaching economic, social and political implications and AI
algorithms are powered by data and this requires collection of more number of data about
every single minute and therefore can be compromised to individual privacy (Ernst, Merola
and Samaan, 2018). Although it also frees up the humans' workforce to do work they are
better equipped for. According to Scherer (2017), algorithms of AI are not neutral and if
prejudiced data is fed into algorithms or factors that reflect current social biases are
prioritized certain factors – recognising statistical patterns from latent and observation. If
assumed that particular factors are right analysts of a result, an algorithm can exhibit a self-
enforcing bias.
In relation to businesses, the economic activity in a nation drive by different firms in different
sectors and if they are failing or slow to embrace AI, then its impacts are logically
constrained. The potential of AI can only be completely contented if its basic and functional
algorithms implemented by enterprises, synchronise in operations and largely diffused.
However, this consideration at a point is ignored and therefore, negatively influence in the
development of artificial intelligence. According to Osborne and Frey (2017), 47% of jobs
and employment confront a close term threat of automation from artificial intelligence.
Tigabu, Berkhout and Van (2015) also argued that it also cannot be said that new
technologies include set of commercial application and so they will be implemented and
diffused in a well-timed way. Hence, comprehending the aspects that impact the diffusion or
adoption of artificial intelligence in organisations is significant so as to enable effective

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forecasting and planning for management, policymakers and community. Recognising the
key drivers that take the development of applications of artificial intelligence can aid to
accelerate the many positive use cases in the pipelines like improved renewable energy
distribution at mark and Machine Learning disease finding systems in medical arena. AI
development in society can fail to develop as of its negative implication such as lowering
down of employment opportunities in the professional roles such as lawyer, accountant and
doctor and all such risks will arise out from individual or corporate activity from certain
technological development in the arena of AI. In the same way, there will be some
implications on the corporate world also such as shifting role of senior executive in a
company, instant judgement about consumer and potential consumer company is planning to
target and exploration of power of AI by competitors to attain competitive edge in the market.
Some of the explanatory variables for AI adoption and diffusion includes rivalry, enterprise
attributes, employee’s skill capabilities, digital maturity, probable yield on AI investments,
and artificial intelligence complements. The competition variable has the highest extent of
rivalry within marketplace causing impact on AI adoption as per the research undertake by
McKinsey Global Institute (mckinsey.com, 2018). Considering that new tech develops
extensively diffused, here come initial adopters characteristically appreciate unequal benefits
and this is the reason why slacker businesses are penalised with decrease share in the
marketplaces. Such competitive environmental aspect, hence, initiate adoption rates as
organisation push to state a viable advantage and gain stake in the market. Though decisions
of adoptions are created with imperfect data and it is challenging for an organisation to
recognise what its rivals are doing behind locked flaps. The next variable is the firm
characteristics that include the scale, level of income and sector of enterprises have been
visible to impact the level that a new tech implemented. For instance, bigger enterprises, by
income and numbers, usually embrace digital tech such as AI former at rapid rate as
compared to smaller firms (Semmler and Rose, 2017). In addition, businesses under ICT and
financial sector incline to adopt AI at a faster rate in comparison of construction or
agricultural industry.
Artificial intelligence also required definite skills and the obtainability of personnel
possessing these expertise and competencies can impact the level of diffusion or adoption and
it also varies from firms to firms and industries (Pannu, 2015). The execution of AI
applications and algorithm needs strong technical competencies and hence, if an organisation
have access to relevant skilled labour, there will be more likely that firms will adopt AI.

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Digital maturity is another significant variable where Gutierrez, Boukrami and Lumsden
(2015) stated that implementation of new digital tech typically relies on the implementation
of preceding digital tech and this connection also seems to clutch for artificial intelligence as
business that has taken on necessary cloud setup and web 2.0 channels are more likely to
adopt Artificial intelligence technologies. The adoption rates also influenced by enterprise
observation towards value that AI can build and thus likeliness of adopting this technology
will be greater where expected return on AI investment is positive. Ultimately, there are some
other elements too that are having impact on the business-level implementation of artificial
intelligence such as legal and political influence required to be considered when relating the
rates of adoption amid nation economies (i.e. comparison to US firms, there can be delay of
AI adoption in European companies as of strong data protection regulations there).
Artificial intelligence is ubiquitous today and the largest breakthroughs for AI study in
current time have been in the arena of machine learning and all of major tech companies
started offering various AI services, from the infrastructure to develop powered tools like
language processing, sentimentality identification on demand and language learning. To
understand the present renaissance of AI, it also needed to turn to the union of the three
developments including machine learning, big data and cloud super-computing. AI marks
towards a future since industrial revolution brings better planning, strategizing and making
decisions. The functions and algorithms of artificial intelligence will also increasingly be
offered as-a-service, delivering business a bite of competitive edge and ultimately, its benefits
can be gained to well agreed, support and administered in various areas while sustaining
growth and development. However, the ethical development and use of AI is necessary by
undertaking various principles and standards including data protection, transparency and
building the work of technology under nation-wide regulatory environment. In upcoming
years, this technology will highly be leveraged by both individuals and enterprises under
different places and exert sufficient control over different arenas and decision support system.
Hence, this explains the development of AI and the associated factors influencing its
development.

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