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AI Adoption and Implementation Strategies: Examining The Challenges and Best Practices
in Adopting AI Technologies Within Businesses
Janet Ramos
janet.ramos@ue.edu.ph; University of the East, Manila, Philippines
Abstract
Global corporate operations have transformed due to AI integration. This revolution has
significant challenges and great practices, like every other. Our article examines corporate AI
adoption and implementation methods, highlighting the difficulty of this transformation. We work
on governance measures that ensure AI's ethical use and regulatory compliance. A smooth AI
augmented transition requires change management. Employees, consumers, and regulators are
crucial to this revolutionary path. Globally, we monitor AI adoption patterns across continents
and economies. In the US, a powerhouse of innovation and diversity, AI faces a mass of laws and
business uses. Canada and the UK prioritize ethical AI and data regulation. With government
support and lots of data, China can dominate AI ethically. Japan uses AI in senior care, a novel
technique given its aging population. We investigate beyond these global titans. We analyze the
Philippines, a fast-changing economy influenced by AI. This country uses AI in banking,
healthcare, and agriculture. AI chatbots increase banking customer service and innovative AI
apps boost waste management. Equitable AI access and digital inclusion are the Philippines'
specific issues. This report exposes the complex yet exciting environment of AI acceptance and
implementation through meticulous research and nuanced review. It intends to educate companies
and decision-makers about AI's issues and opportunities to foster ethical and effective AI growth
and global industry improvement.
Keywords:Artificial Intelligence, AI Adoption, Implementation Strategies, Challenges, Best
Practices, Governance, Change Management, Stakeholders, Global Economies, Philippines.
Introduction
Artificial intelligence (AI) technology integration is a turning point in business, presenting
many benefits and many formidable problems. These AI advances could improve decision
making, operational efficiency, and entire sectors. However, the path to AI adoption and seamless
deployment is complex. This essay navigates the complexities of integrating AI into workflows
and strategy in enterprises. It tries to uncover the complex problems that typically accompany this
revolutionary journey and illuminate its guiding principles and best practices. Understanding how
to harness AI's potential and overcome its challenges is crucial as it grows more widespread. This
exploration intends to provide organizations and decision-makers with the insights and
information needed to join this transformative journey, establishing an environment where AI
can drive innovation and growth.
Literature Review
World View
The ethical and legal frameworks that govern the appropriate use of transformational
technologies shape AI adoption worldwide. The US California Consumer Privacy Act (CCPA)
and EU General Data Protection Regulation (GDPR) form the basis for ethical and compliant AI
implementation (Singh et al., 2020; Taeihagh, 2021). The CCPA and GDPR are strong laws that
protect user data and ethical AI. California residents have the right to know what data is
collected, seek its deletion, and opt out of data sales under the 2018 CCPA. This law requires
California enterprises to follow strict data privacy and security rules (Singh et al., 2020). In
2018, the GDPR expanded its authority beyond the EU, affecting firms worldwide that handle
EU residents' data. GDPR requires firms to utilize personal data ethically and transparently. It
requires consent, data protection impact evaluations, and data breach reporting to promote ethical
AI (Taeihagh, 2021). These regulations demonstrate the global shift toward data privacy and
ethical AI deployment. They force organizations to review their data handling practices, promote
openness, and guarantee AI applications follow strict ethical norms.
China's AI adoption strategy is unique and extraordinary. Chinese government backing
and data availability are crucial to AI research and application (Alsheibani et al., 2018). This
encouraging atmosphere drives AI invention, but also makes it difficult to balance AI's fast
advancement with ethics. The "New Generation Artificial Intelligence Development Plan," which
defines China's goals to lead AI research and applications, shows its commitment to AI
development. Government initiatives boost innovation, but also raise worries about data privacy,
extensive monitoring, and AI abuse (Thowfeek et al., 2020). China's AI ecosystem presents a
significant ethical issue for corporations and regulators. Global AI progress and implementation
need a delicate balance between innovation and ethics. China and the US have different AI
adoption strategies, which affects enterprises.
AI deployment in the US prioritizes ethics and compliance. Companies under pressure
from government legislation like the California Consumer Privacy Act (CCPA) and the EU
General Data Protection Regulation (GDPR). These standards require transparent and responsible
AI development, favoring ethical AI despite hurdles and business compliance costs. The US
prioritizes data security, transparency, and AI responsibility (Singh et al., 2020; Taeihagh, 2021).
In contrast, China promotes AI via government-led initiatives and research funding. This has
boosted AI advancement across sectors, making China a formidable AI power. Innovation must
be tempered with ethics. China's AI ecosystem must handle data security, monitoring, and AI
abuse prevention (Alsheibani et al., 2018; Thowfeek, 2020). China's creative incentives and
ethical issues reflect companies' worldwide AI conundrum. They highlight the delicate balance
enterprises must find between AI innovation and ethical and regulatory compliance, using the
Philippines as a context. Laws and ethics increasingly impact AI adoption worldwide (Chen et
al., 2023; Dwivedi et al., 2021). China and the US use AI differently, but their methods show how
rules and innovation incentives interact. These contrasts highlight the global responsibility of AI
adoption, where ethics, compliance, and innovation affect its acceptability and effect, especially
in the Philippines.
Regional View
Canadian and British AI adoption is shaped by their dedication to ethical AI techniques
and strong data governance frameworks. These two countries want to create a worldwide
standard for ethical AI use (Papagiannidis et al., 2023). They prioritize ethical AI adoption in
their AI adoption strategy. Canada and the UK promote AI deployment openness, justice, and
accountability. This devotion is shown through ethical AI efforts and organizations. The Canadian
Directive on Automated Decision-Making shows their commitment to ethical AI deployment.
The UK's Centre for Data Ethics and Innovation emphasizes their commitment to ethical AI use
(Papagiannidis et al., 2023). Additionally, these two governments acknowledge the need of strong
data governance frameworks in their AI adoption efforts. These frameworks are carefully created
to protect data privacy, security, and ethical data management. PIPEDA underpins Canada's data
governance approach (Leone et al., 2021; Mikalef et al., 2019). The UK's Data Protection Act
strengthens its data governance environment. Canada and the UK's data governance efforts
include these laws to ensure ethical and responsible use of data-driven AI technology. In
conclusion, Canada and the UK are models of responsible AI adoption due to their ethical AI
policies and strong data governance frameworks. They take a proactive approach to using AI
technology ethically and protecting data by committing to openness, justice, and accountability
and implementing legal measures.
China's aggressive government-led AI adoption strategy shows its unshakeable
commitment to global supremacy (Alsheibani et al., 2018). China's AI policy emphasizes
government-led innovation. To progress AI technology, the Chinese government has provided
huge funds, continuous support, and several incentives. These endeavors span cutting-edge
technology to the growing healthcare area. This government support has fostered innovation and
quick technical progress in China, fostering AI development. China wants to dominate the world
in AI. AI drives worldwide technology innovation and economic prosperity, therefore this
objective goes beyond economic goals (Mogaji & Nguyen 2022; Newman et al., 2021). The
Chinese government understands AI's potential to change sectors, boost productivity, and boost
national competitiveness. This acknowledgment has driven China's ambition to become an AI
leader. Overall, China's AI adoption is driven by government-led innovation. Government
funding and consistent backing have accelerated AI growth across industries. This fierce pursuit
of AI leadership shows China's desire to use AI to boost economic development and technical
innovation and achieve global domination.
According to research by Tominc & Rožman (2023), Japan's demographic issues,
particularly its elderly population, shape its AI adoption strategy. Japanese AI adoption has
focused on healthcare and elderly care in response to this demographic transition, demonstrating
a sophisticated approach to AI incorporation into society (Jöhnk et al., 2021). Japan's AI adoption
plan recognizes AI's potential to solve an aging population's healthcare problems. Due of this, the
nation has prioritized AI-powered healthcare solutions. These solutions are used in diagnostics,
patient monitoring, and senior care. Japan wants to improve healthcare and meet the requirements
of its aging population by using AI in these important areas. Japan's strategy to AI adoption
emphasizes academia-industry-government cooperation in AI research and implementation.
Initiatives like "Society 5.0" promote collaboration. Society 5.0 aims to create a human-centric,
super-smart society via AI and digital innovation (Upadhyay et al., 2023). Japan encourages such
cooperation to use these industries' knowledge and resources to promote AI that is both
technically advanced and sensitive to demographic shifts' social demands. In response to its
aging population, Japan's AI adoption strategy focuses on healthcare and senior care. The
country's commitment to academia-industry-government cooperation shows its commitment to a
future where AI addresses vital social demands while driving innovation and scientific
advancement.
The US is leading AI adoption despite different restrictions that generally target certain
businesses (Singh et al., 2020). US AI adoption is heavily influenced by industry-specific
applications. Healthcare, finance, and technology have various AI integration difficulties and
agendas. Healthcare may use AI for diagnostics and medical care, while finance may use it for
fraud detection and risk management. This industry-driven approach to AI adoption shows how
flexible and adaptable businesses in diverse industries must be to leverage AI's disruptive
potential. The US's regulatory variety distinguishes it in AI adoption globally. In contrast to
nations with comprehensive federal AI regulatory frameworks, the US has a patchwork of state
and sectoral legislation. In healthcare and communications, the FDA and FCC regulate AI uses
(Wamba Taguimdje et al., 2020). This regulatory environment shows how fragmented AI
governance in the US is, with industry- and location-specific restrictions. Overall, the US' AI
adoption strategy relies heavily on industry-specific applications and has no federal regulatory
consistency. This variety shows the nation's dedication to innovation and tackling AI adoption's
distinct problems and possibilities across industries. These regional perspectives, including
Canada and the UK's focus on ethical AI, China's government-led initiatives, Japan's
healthcare-focused innovation, and the US' industry-specific considerations, demonstrate the
diverse strategies and priorities organizations and nations use to adopt AI.
Impact of AI in the Philippines
The Philippines' AI ecosystem is changing rapidly, offering several possibilities and
problems that reflect the nation's willingness to adopt new technology. In finance, especially
banking, AI-driven advancements are prominent. AI-driven chatbots have transformed customer
service (Indriasari et al., 2019). These AI-driven chatbots customize help and expedite common
enquiries, improving customer service. Customers may use these chatbots to obtain rapid
responses, solve common problems, or complete purchases. Thus, these AI-driven chatbots
improve Philippine financial industry consumer experiences and banking efficiency. This change
shows the Philippines' dedication to using AI to boost its economy. These advances have great
potential to improve customer service and operational efficiency, but the country also faces issues
connected to AI equity and the digital divide. This dichotomy emphasizes the need for a
comprehensive and inclusive AI adoption strategy in the Philippines to ensure that AI helps
everyone and addresses any inequities.
AI applications are used in waste management in the Philippines to improve waste
management. AI algorithms drive this effort to improve waste management efficiency and
sustainability (Andeobu et al., 2022). AI-powered trash sorting and disposal optimization systems
are one significant Philippine project. These systems use AI algorithms to segregate recyclables
from non-recyclables effectively. AI optimizes garbage disposal routes, reduces transportation
costs, and reduces waste management's environmental impact. AI in trash management is a major
step toward more sustainable and eco-friendly Philippine practices. AI-driven algorithms can help
the country address urbanization and population expansion while creating a cleaner, greener
future. As with any technical innovation, equal access and distributing AI advantages throughout
the community are important to optimize its beneficial effect.
Challenges in AI Adoption
AI technologies are facing problems in the Philippines as they spread across industries. As
the government works to maximize AI's advantages for everybody, the digital gap remains a
major obstacle. Digital divides typically include socioeconomic gaps in internet and technology
access. AI has transformational potential, but its broad acceptance and use might exclude some
groups, worsening inequities. Without initiatives to bridge this difference, underprivileged
populations may have restricted access to AI-driven services and opportunities, continuing
education, employment, and quality of life inequities (Yathiraju, 2022). The Philippines needs
comprehensive digital inclusion measures to address this problem. This means providing
technological infrastructure, digital literacy initiatives, and inexpensive internet access to
everybody, regardless of financial class or geography. The country can maximize AI's benefits
while encouraging diversity and avoiding vulnerable people from being marginalized. This
strategy supports worldwide efforts to make AI adoption more egalitarian and emphasizes
technology's role in social progress.
To guarantee the sustainable and fair integration of artificial intelligence into the
Philippines' economic and social fabric, there are hurdles to overcome throughout the dynamic AI
adoption path. One of the biggest difficulties is closing the digital gap. AI has great promise, but
socioeconomic disparities in internet and digital technology access are concerning. The digital
divide highlights digital access gaps, particularly along economic lines. AI may alter society, but
its broad use may exclude some groups. Exclusion may exacerbate inequities in education,
employment, and quality of life. Collaboration is needed to address the digital gap. The
Philippines must create comprehensive strategies to ensure that people from diverse
backgrounds, regardless of socioeconomic status or location, have equal access to technology
infrastructure, digital literacy programs, and affordable internet connectivity. Such efforts are
crucial for excluded populations to fully benefit from AI-driven services and opportunities. This
strategy supports worldwide efforts to make AI adoption more inclusive and emphasizes
technology's role in social advancement. Skills shortages are another major AI adoption issue in
the Philippines. Creating a workforce with the skills and capabilities to exploit AI's promise is
crucial to the nation's transformation. The Philippines needs extensive AI skill development and
education initiatives. For individual empowerment and global economic development and
competitiveness, the country must equip its inhabitants with AI-driven knowledge and skills. The
Philippines must address these difficulties within its AI adoption framework to guarantee that AI
helps everyone, regardless of socioeconomic background, and that the country is ready to
succeed in an AI-driven society.
Regulatory issues are important in the Philippines' evolving AI field and need careful
preparation. The Philippines, like many countries adopting AI technology, must navigate
complicated legislative frameworks to responsibly and securely use AI. These regulations center
on data protection and ethical AI usage. Creating strong data privacy frameworks is crucial. This
requires laws and rules to protect personal data and promote responsible, transparent, and secure
data handling. This framework must match with international best practices and regulations to
allow data to move freely across borders while protecting data privacy. Ethical factors also
influence responsible AI adoption in the Philippines. To avoid abuse, prejudice, and
discrimination, ethical AI usage rules are essential. AI ethics should include openness in
algorithms, justice in decision-making, responsibility for AI results, and the avoidance of damage
to persons and society. The Philippines must collaborate with government, regulatory, business,
and civil society parties to overcome these regulatory issues. Collaboration can create regulatory
frameworks that balance innovation and ethical AI deployment. The Philippines can integrate AI
technology ethically, securely, and responsibly into its economy and society by aggressively
addressing these legislative matters and adopting data privacy and ethical AI usage best practices.
These measures will establish the country as a responsible AI adopter and build confidence
among its residents, companies, and foreign partners, enabling a sustainable and inclusive
AI-powered future.
Stakeholder cooperation is key to the Philippines' AI adoption and environment. In this
dynamic environment, stakeholders' active engagement and collaboration drive AI innovation and
responsible AI integration into varied industries. Governments, regulatory agencies, the
commercial sector, academia, and civil society groups collaborate. Each stakeholder group
contributes distinct viewpoints, knowledge, and resources to AI progress in the Philippines.
Governments are crucial to AI adoption. Funding, incentives, and supporting policies may help
AI research and development. Regulatory bodies must create and enforce AI ethics frameworks.
AI innovation relies on businesses and technology firms. They fund AI research, development,
and application in banking, healthcare, agriculture, and customer service. The corporate sector
and government may collaborate to boost AI-driven economic development. Academic
institutions and research groups promote AI adoption via research, teaching, and workforce
development. These institutions produce AI specialists and innovators via knowledge
development and distribution. Civil society and advocacy groups are vital to guaranteeing ethical
and social AI adoption. They monitor the effects of AI technology on underrepresented
populations and push for openness, justice, and accountability in AI decision-making.
Partnerships and information exchange among these stakeholders are key to AI advancement in
the Philippines. A robust AI ecosystem that benefits society may be created via collaborative
research initiatives, public-private collaborations, and idea exchange forums. The Philippines can
maximize AI technology's potential, solve specific problems, and become a responsible and
creative AI actor by collaborating with these different stakeholders. This collaborative strategy
assures that AI adoption is technologically sophisticated, socially responsible, and inclusive,
boosting the nation's sustainable development and global competitiveness.
Inclusion is key to the Philippines' AI journey. A comprehensive and inclusive strategy is
needed to maximize AI's transformational potential and make its advantages available to
everyone. The method includes policy formulation, infrastructure improvement, skills
development, and marginalized community participation. First and foremost, inclusive policies
are needed. The government should aggressively develop an AI adoption regulatory framework
that promotes justice, equality, and accessibility. These policies should emphasize disadvantaged
groups and use AI to solve healthcare, education, and poverty issues. Infrastructure improvement
is also crucial to AI inclusion. Broadband and digital infrastructure investments are needed to
narrow the digital divide. Internet and digital device access should be inexpensive and
widespread, especially in rural and underdeveloped regions. AI solutions can reach every state
with this infrastructure. Skills development is essential for everyone to profit from the AI-driven
economy. The Philippines should fund comprehensive AI skill development and education
initiatives. This involves training and educating people of all ages and ability levels.
Empowering people with AI knowledge and skills equips them for AI-driven possibilities and
challenges. Inclusivity requires active participation in underprivileged populations. The
government, civil society, and corporate sector should collaborate to make AI adoption
community-driven and meet underprivileged groups' needs. Outreach, community involvement,
and AI application customization to benefit these populations are required. In conclusion, the
Philippines has achieved tremendous AI adoption progress, but fair access, skills development,
regulatory frameworks, and cooperation remain issues. The government must take a
comprehensive and inclusive strategy to solve these problems and fully fulfill AI's promise for all
residents. By doing so, the Philippines can stay up with global AI advances and develop an AI
ecosystem that benefits everyone, improving social well-being and growth.
Method (Review)
This paper uses a strong approach based on a thorough literature analysis to examine AI
adoption difficulties and best practices. We examined several scientific publications, reports, and
case studies to get a comprehensive grasp of this complicated area. This technique lets us pull
from a rich tapestry of studies to provide a nuanced view of AI adoption. We searched Google
Scholar and PubMed extensively to verify our review's inclusion and relevancy. These venues
were chosen because they provide significant coverage and access to AI adoption scholarship.
We used an interpretive and qualitative approach to this review to explore the key themes and
insights from the chosen literature. We want to provide a thorough and informative analysis of
AI adoption problems and best practices using this rigorous methodology.
Findings
Organizational governance enables ethical AI adoption. These frameworks provide
business AI deployment standards, rules, and concepts. Fair, ethical, and transparent AI are their
goals. Today's global data protection and privacy sector needs governance structures for
regulatory compliance. AI businesses must have strong control in the US and EU, where data
protection rules are unparalleled. The US California Consumer Privacy Act (CCPA) and EU
GDPR contain strict AI privacy and data usage restrictions. To prevent legal issues, these
organizations must carefully match their AI strategy with these constraints. The California
Consumer Privacy Act is recognized for protecting consumers' privacy. Data gathering must be
disclosed, opt-outs offered, and security implemented. Since CCPA violations entail substantial
penalties and legal responsibilities, governance frameworks are needed. The GDPR's
extraterritorial reach restricts firms that handle EU individuals' personal data. Data protection
impact assessments, explicit permission, and breach reporting are GDPR requirements.
Compliance infractions may cost the company €20 million, or 4% of worldwide sales.
Governance systems that include ethics, compliance, and responsible AI deployment may
circumvent data privacy constraints in the Philippines. They advise companies on AI ethics and
legislation in a global framework with stringent data protection rules.
Companies in the Philippines must adapt to AI via change management. These strategies
help restructure businesses and make AI technology adoption fun. Change management aids
workplace AI adoption. Change aversion hinders AI adoption. AI threatens job security and
routines, according to employees. Skepticism and hesitancy might become animosity.
Overcoming this hesitancy and winning acceptance requires effective change management. A
clear communication technique is necessary. Companies in the Philippines must show how AI
benefits personnel and strategic goals. Help and training are essential. Employees need AI skills
to use it. AI teaching may include literacy through advanced tool use. Leadership support counts.
AI adoption leaders inspire trust with their strong message. Traditional models include Kotter's
Eight-Step Change Model and Lewin's Change Management Model. Urgency, a steering group,
and cultural changes help firms transform. Change management is needed to overcome AI
adoption's complex change resistance. They discuss the company's AI integration strategy and
disruptive tech users. Good change management can make AI a growth, innovation, and
productivity enabler.
AI adoption stakeholders are workers. Instead of execution in the Philippines, AI adoption
programs flourish via active engagement and dedication. Making people co-creators of AI-driven
change may boost engagement. Engagement of internal stakeholders, especially workers,
involves skill development. AI must learn continually owing to fast expansion. Training and
development organizations empower the Philippines. Programs provide staff AI skills and
confidence. AI decision-making may boost employee engagement and skill development.
Employees co-author the AI narrative when they influence AI use in their domains, connecting
their goals with the company's AI goals. To foster collaboration and commitment, solicit input,
address challenges, and adjust AI strategies. Clients and regulators in the Philippines affect
non-business AI adoption. Expectations, concerns, and feedback inform AI deployment by
companies. Customers strongly discriminate against AI-driven products and services. Companies
need AI to understand and meet client demands. AI should improve user experience, streamline
procedures, and provide tailored suggestions to increase consumer value. Customer-focused AI
increases loyalty, trust, and advocacy. Transparent regulator coordination is needed. Ethics and
responsibility are coming to AI rules. Engaging with authorities, sharing AI practices and
protections, and following new legislation reduces legal issues and boosts trust. AI adoption
requires internal and external stakeholder engagement. Companies may negotiate AI adoption
with resilience and authenticity by respecting and engaging staff as active contributors and
balancing AI operations with consumer expectations and regulatory restrictions.
Governance, change management, and stakeholder involvement in Philippine’s hamper AI
deployment. Each element of this dynamic ecosystem impacts AI adoption differently. Ethics
based governance ensures AI deployment and regulatory compliance. AI integration is promoted
via corporate culture transformation. Stakeholder engagement helps AI systems satisfy consumer,
regulator, and other expectations. Enterprises traverse complicated, interconnected networks.
Balance is needed for AI adoption. Organizations need governance to employ AI responsibly.
These organizations set rules. Organizations should invest in change management to transform
culture. Integrate AI into processes and increase adoption and flexibility. Change management
requires leadership, training, and communication. AI aids workers by combining old and new.
Actively involving internal and external stakeholders is key. It manages AI projects to meet
internal and external clients seeking better experiences. Value these stakeholders' views to boost
your organization's success. AI adoption is continually evolving, thus there is no one answer.
Instead, success needs governance, change management, and stakeholder engagement. Dedicated,
honest, and collaborative organizations will prosper. Through these aspects, they harness AI's
revolutionary potential and responsibly advance this new technology. Those that navigate
complexity with agility and sincerity will drive AI adoption in business.
Discussion
This section discusses business AI adoption difficulties in Philippines. Governance
frameworks, change management, and stakeholder engagement drive our research. These three
pillars must work together to overcome AI integration challenges to promote AI adoption. AI
companies follow ethics and law. AI adoption is controlled. Balance ethics with innovation for
long-term AI integration. The US and EU GDPR and CCPA emphasize this crucial criterion.
These limits emphasize ethical AI use and data protection. Change management affects AI
adoption. Organizational acceptance, learning, and technical adaption result from good change
management. This mental change makes AI a facilitator and easy to integrate. Change
management strategies that emphasize communication, training, and leadership support may help
organizations incorporate AI. They may also improve AI efficiency and decision-making.
Regional differences in AI use mirror global trends. The UK and Canada encourage ethical AI
deployment via data governance and AI practices. Government initiatives in China fund AI
research and application. Japan localizes AI use in healthcare and elder care due to its aging
population. US AI policy is a mess, reflecting a sectoral approach to AI integration where
industry-specific applications drive adoption.
Our discussion concludes in the Philippines, where artificial intelligence is making
significant strides across industries. The Philippines illustrates how AI adoption influences every
industry, from banking, where chatbots enhance customer service, to waste management, where
AI applications optimize procedures. These developments have downsides. Concerns about
unequal AI advantages and the digital divide underscore the need for a comprehensive and
inclusive AI deployment strategy in the country. By investigating these numerous facets of AI
adoption, we hope to gain a deeper comprehension of this revolutionary world. In addition, it
provides a nuanced view of global and regional differences that affect AI adoption. With the
findings of this analysis, businesses can better navigate AI's challenges, embrace ethical
principles, and maximize its potential.
Conclusion
In the broad pattern of technological growth, AI integration is crucial. Our examination of
corporate AI adoption and implementation techniques shows complex barriers and effective
practices. This tale shows how governance, change management, and stakeholder involvement
affect the world. These parameters guide AI adoption. While exploring AI adoption globally,
ethical concerns, data governance, and government actions portray different stories of AI
integration in key economies. China's state-driven AI supremacy objectives contrast with Canada
and the UK's ethical AI policies and strict data regulation. Japan's demographic issues make AI
ideal for healthcare and senior care, while the US's patchwork of legislation shows sector-specific
AI journeys. In the Philippines, AI is growing with hope and creativity. AI advances finance and
waste management while facing equity and digital inclusiveness issues. Business transformation
requires orchestration and global and regional viewpoint harmonization with AI adoption and
execution. In this complicated and changing context, firms must prioritize agility, ethics, and
stakeholder involvement as AI shapes business. They can traverse the AI adoption maze and
design a trajectory toward an AI-powered future by doing so.
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