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Projects keep failing, so what’s the
problem?
Projects
are about delivering an outcome that fixes a business need. Others suggest
projects are to take advantage of an opportunity. Those opportunities usually
are to fix a perceived problem. Those perceptions to fix that future problems still
needs a project to implement them and solve it. Those projects still need to be
justified.
Projects
fail for many reasons, building on shaky foundations will usually end in failure.
That foundation is a well-defined and explained problem. Problems need to be
clearly identified, stating how the proposed solution will fix it, and showing
a value proposition to the organisation, customer or both. A quantifiable and
demonstratable benefit, as most businesses are there to make money or provide
better services, why would you be doing it?
Projects
need to argue the logic for investing both time and money, more importantly
what the pay back will be. Business is about making money, providing a service,
or both. Funds are usually limited, rarely having a lack of opportunity to be
spent on the many challenges facing organisations.
What is the Business Case for this
project?
At
first, an organisation wants to understand the why of a project. Closely after
that is the how will it be achieved, and how much. But there needs to be a
compelling reason for carrying out the project. Often projects put the cart
before the horse. In other words, they have a new or updated product that will
future proof their organisation, addressing many of the perceived issues that
could be addressed by the many of the new features on offer all presenting
sound arguments. In a world of unlimited resources and funds that would not be
a problem, but that is not the case. Money and resources are a factor of every
business and they are not always limitless.
Projects
that fail are usually proposed with all the good intents, the arguments of the
new features all sound good. The biggest issue is that no one hears the same
benefits. This results in different stakeholders with different expectations.
As the projects progress it becomes a feature fest. More is better, right? But
time elapses, costs increase, expectations having been ill defined results in
no one being happy. Time and money start to run out, results are not achieved
and the project grinds to a halt. Does this sound familiar?
Questions are raised
Why
are these projects failing? What went wrong? We had all the governance in place
and it seemed to be working fine, then it all went south. I just don’t understand
what happened?
The
problem is there was no real problem being addressed, or that problem was
perceived and not correctly identified. Problems form the foundations of a business
case, needing to be clearly identified, quantified and expressed in a manner
that all parties can agree. Business cases need to clearly explain the intended
problem to be addressed. Identifying problems and explaining the consequences if
they were not addressed. Then describing the benefits that would result in
fixing them, more importantly how that would be proved.
When
defining the problems and proposed benefit, there needs to be an understanding of
the following:
·
Why invest? – Describe how this investment will benefit the
organisation
·
The Rational – What is the logic for this investment, how
will it be tested and proved that it has delivered the expected results
·
Who feels that this is a problem – gather views from all
appropriate stakeholders within the organisation through discussion with the
subject matter experts.
Defining the problem
Often
what is perceived as a problem is usually not the problem. To find the real
problem you will need to carry out “root cause analysis”. A good example of
this is a technique commonly referred to as the “5 Whys”. This is an iterative
interrogative technique used to explore the cause and affect relationships
underlying a problem.
What sort of questions should you be
asking?
A
famous quote of Einstein was:
“If
I had an hour to solve a problem and my life depended on the solution, I would
spend the first 55 minutes determining the proper question to ask…
for once I know the proper question, I could solve the problem in less than
five minutes.”
What
stakeholder say is a problem does not necessarily reflect the root cause that
created the problem. Every stakeholder potentially will have different issues
which they consider a problem. Your job is to dig, finding the root cause. You
need to identify both the cause and the consequence to any issue raised as
potential problems. A simple test is called the “so what?”, Similar to the “5
Whys”, which will be covered a little later.
Is
there any evidence that confirms the cause and effect of the identified
problem? What is the priority? Does it need to be addressed now or could it
wait? Is the issue specific to what you are looking at, or should that
perspective be broader?
Example of 5 Whys
“..
the finance director could not understand why his maintenance costs were
increasing on the factory floor. He had sent a directive to the department to
cut costs. He decided to venture down to the factory floor to speak with the
manager and better understand these increases. (His perceived problem)
..
as the finance director was walking through the factory he noticed a pool of
water on the floor. He called a maintenance staff member to inquire about the
water.
·
Why is there a pool of water here on the floor? The staff
member pointed out that one of the pipes above was faulty and leaking. (Maintenance
perceived problem) The director then asked for the manager,
·
Why was that pipe leaking? The manager pointed out the
replacement washer had not sealed properly. Again, the director then asked,
·
Why did the washer not seal properly? The manager suggested the
washer had possibly failed. The director then asked,
·
Why did it fail. The manager then suggested the washers were
cheap and that they had a tendency not to last too long. Again, the director
asked,
·
Why were we using cheap washers? I was following the budget directive
to cut my maintenance costs. We then sourced alternatives as our previous
washers were too expensive.
The
director had found the root cause. In this case there were several perceived
problems. The director had a problem with his costs of maintenance, the staff
member had a faulty pipe and the manager had issues with cheap washers. At
first replacing the pipe potentially could have fixed the problem. But as it
was not the root cause it would have resulted in an expensive fix and the pipe
potentially would have leaked again because of the washer. The root cause for
the pipe was the use of a cheaper alternative. It also highlighted the cost
increase to maintenance had indirectly been because of a cost cutting
directive.”
To
define a problem, you will need to consider the downstream effects of what you
and other stakeholders consider to be the problem and what it means to your
organisation. There are two parts to a problem what has caused it and what are
its consequence? Understanding these causes will help you chose how you
respond. The consequences of a problem will help in identifying relevant
benefits. Showing that investment can work to the objectives in this case,
those objectives will later provide an opportunity to identify alternatives.
Problems
that are not well-defined make it harder for decision makers, reducing the
chance of success. This can result in projects that results in less than fit
for purpose results. Either too little in the way of funds and resources, or
too many working on low-priorities. The worst case is lack of resources to
solve a major challenge.
Success
is through clearly understanding the problem and benefits from the beginning. This
will enable everyone to be on the same page, agreeing to the same expectations
and results. Aligning results to the organisations priorities and effectively
addressing the right problem. The idea of a well understood problem is that it
will potentially highlight an opportunity for better results.
Explaining the problem
This
is the elevator pitch, if you were trapped in the elevator with the key
stakeholder who was the approver of the funds needed. How do you relate the
issue in 90 seconds? That pitch needs to clearly identify the issue, providing
the evidence that supports your statement and the solution with definable
measure of success.
Problems
that are ill defined can result in benefits that do not align and undermine your
entire argument for the case. Businesses want to understand how much of a
problem it is? The goal being a call to action. It should have both cause and
consequence, answering both the ‘Why?’ And…’ Questions logically linked. A
great starting point is identifying the consequences of doing nothing?
Your
pitch will never be perfect, potentially changing as more information is
gathered. It will be tested against evidence and morph from its original state,
be prepared for change. The challenge is to go into this exercise without any preconceived
solutions. As further evidence is presented it will develop your understanding
and result in a better result, and a stronger foundation to build your case.
Mistakes in identifying problems
Many
people go into identifying problems sure of the solution, especially when it
comes to technology. In the technology space providers and IT specialist believe
their solutions will provide the answers to any problem. Its just a matter of
shoe-horning those problems into that solution.
Avoid
simply identifying the problem as a system failure, this has a tendency to drive
the results which usually does not align to the facts and the issue. Again, go
back to “so what?”. What is the evidence that will give you a confidence that a
problem exists? You must present that evidence to explain your rational.
Always
note where you found the evidence as you develop your pitch, it’s always harder
if you try to retrofit a problem with evidence. One of the best tests I would
use is called the “Mum Test”, find someone who is not related to the case to
read the pitch and benefits, ask them, “Does this make sense?”. For me, when I
was an interface designer I would as my mother if she could carry out a specific
task using that interface. With no instructions, I would see what she would do
to achieve the results. The idea is to remove the element of assumption, as we
don’t always know who the audience will be, we need to make sure it is clear
without having to be there to explain.
Benefits, what are they?
When
you understand the problem and its consequence most people will understand the
benefit of doing something about it. A benefit gives a measurable improvement,
showing the value gained. The consequence of a problem helps to identifying the
relevant benefit that lead to your objective.
They
should clearly align to the problem that links to the results your organisation
is looking to achieve. Explain the impact which credits to the solutions.
Justify the cost of both money and effort which are supported by demonstratable
returns.
Measuring those returns
The
best way to show a return is by having a measure based on current and future states.
Everyone will have a different measure of value, so there needs to be some more
good questions.
This
is the old “WIIFM”, (What’s in it for me). How are you going to show the value
you are declaring?
·
What will be the return to the organisation or its customers?
·
How will you measure and prove that benefit?
·
How will you show the connection of the benefit to the results?
These
are just a few points to consider when defining and showing benefits in a
project. These measures are to be defined with your stakeholders as they are
the people who will confirm the returns on investment (ROI). They need to be
identifiable, measurable and proven.
Prioritisation
As
you define your problems and benefits there is a need to priorities each of
them. It’s not an exercise in the level of investment is directed to fix the
problem but more enabling better decisions between available alternatives,
making sure you get the best bang for your buck. This will enable focus and to
direct both funds and effort in future, more importantly you can control scope.
These
priorities will enable better and more directed decisions when you may not get
all the funds you expect. A small problem which has Signiant results for an
organisation or its customers, compared to a large problem which has limited
impact will give a signal of investment. But it raises the question to the
larger problem, has it been clearly identified? And are the consequences fully understood.
All
of these are good questions and will need further examination. This is not an
exact science, but it is a major step in the right direction.
What tool can help with this process?
A
technique used to ensure robust discussion and thinking is carried out up-front
in a project is Investment Logic Mapping (ILM). It is a great tool to use
before a solution is identified and before any investment decision is made.
ILM
provides a way of identifying problems that need to be addressed. This will
identifying benefits hoped to be gained, more importantly how the project will confirm
the rational, showing the realisation of those benefits. The ILM tool is used
for complex investments but is recommended for any project and will enable the
ability to communicate that information on a single page.
Should you use ILM?
Many
organisations trigger this process based on the investment. It is something
that is not compulsory but is recommended especially for complex, high-risk or multiparty
proposals.
In
practice it should form the start of all projects, as the output forms the
foundation of your entire business case. The degree and level that you engage
is determined on the size, complexity and value of the project, but the format
and principles will always be useful to defining your problems and how the
benefits will address them.
As
the project progresses it will increase the project focus and clarity, helping
in defining an agreed scope and result, which will save debate and discussion
later in the project. It will become a powerful tool that will provide you
leverage in justifying your expenses of both funds and effort.
How does it work?
Using
a facilitator, key stakeholders in a couple of workshops will discover:
·
Your problems and consequences, then
·
The outcomes and benefits.
·
These workshops will build an alignment on the purpose of the
investment, it may not necessarily lead to an agreement, but it will be a
start.
What can you expect from an ILM
workshop?
You
should expect to have a single page flowchart that will be written in plain
English. It will define your problems to be addressed, potential benefits of
your investment, and how you will confirm those benefits. It will become the
underpinning logic around your project investment.
ILM
workshops will be a series of time-limited engagements up to two hours each. It
will bring together the accountable stakeholders for the benefits realisation.
It should be low-cost and low-effort that will produce new information. It will
bring together all available information to enable a better understanding,
leading to better results.
Problem
owners need to prepare by checking their evidence, identifying the right
stakeholders for the workshops and offering their opinion and expertise. The
right stakeholders are those who have identified and understood the business
problems, provide the evidence the problem is real, and is responsible for
delivering the benefits. Other stakeholders are those people responsible for
giving advise around the investment to the project. This will increase the
value of the workshops, avoiding the risk of having to start again. Most would
have already been engaged from the start.
The
problem owner needs to drive the effort, talking with the right stakeholders
and their willingness to contribute will lead the to the right pitch when
presenting your case.
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Artificial Intelligence (AI) stands at the forefront of technological innovation, promising transformative solutions to complex challenges across various domains. Recognising its potential to revolutionise industries and improve societal well-being, the National University of Singapore (NUS) has inaugurated the NUS AI Institute (NAII). Led by Professor Mohan Kankanhalli, NAII aims to accelerate AI research and its practical applications, fostering collaboration, innovation, and societal impact.
In an era marked by rapid technological advancements, AI has emerged as a powerful tool with the capacity to reshape diverse sectors, ranging from healthcare to finance, education, logistics, and beyond. The establishment of NAII underscores NUS’s commitment to harnessing AI for the greater good, addressing critical issues facing Singapore and the global community.
At the core of NAII’s mission is the advancement of fundamental AI research, aimed at pushing the boundaries of AI capabilities and exploring novel applications across various domains. Through foundational research initiatives, scientists at NAII will tackle complex AI problems, spanning hardware and software systems, AI theory, responsible AI, reasoning AI, and resource-efficient AI. By delving into these areas, the institute seeks to develop cutting-edge AI technologies that address real-world challenges and drive innovation.
Moreover, NAII will prioritise research into the ethical and societal implications of AI, aiming to develop robust governance frameworks that ensure responsible AI development and deployment. This includes examining issues related to transparency, accountability, and ethical decision-making in AI systems. By fostering dialogue and research on AI ethics and governance, NAII aims to guide the responsible use of AI technology and mitigate potential risks.
In addition to foundational research, NAII will spearhead applied research initiatives, focusing on developing AI-driven solutions for specific application domains. Collaborating with experts from diverse fields, including healthcare, logistics, manufacturing, finance, urban sustainability, and education, the institute will tackle pressing challenges and explore opportunities for AI-driven innovation. From optimising supply chains to improving healthcare outcomes and enhancing urban infrastructure, NAII’s applied research efforts aim to deliver tangible benefits to society.
Furthermore, NAII will serve as a hub for AI talent development, providing comprehensive education and training programs for students, professionals, and policymakers. By offering hands-on learning experiences and internships, the institute seeks to nurture the next generation of AI leaders and entrepreneurs, equipping them with the skills and knowledge needed to drive innovation in AI.
To support its research and educational endeavours, NUS has allocated significant resources to NAII, including external research grants and institutional funding. Moreover, the institute will collaborate closely with government agencies and industry partners to amplify its impact and drive innovation. Strategic partnerships with leading companies such as IBM and Google Cloud will enable NAII to leverage industry expertise and resources, accelerating the translation of research outcomes into real-world applications.
In alignment with Singapore’s Research, Innovation, and Enterprise (RIE) strategy, NAII aims to contribute to the nation’s AI ecosystem by fostering collaboration, innovation, and talent development. By positioning NUS as a global leader in AI research and application, the institute seeks to drive positive societal change and economic growth.
The establishment of NAII represents a significant milestone in NUS’s journey towards harnessing the power of AI for societal benefit. Through cutting-edge research, education, and collaboration, the institute aims to unlock the full potential of AI and pave the way for a more innovative, sustainable, and inclusive future. With its interdisciplinary approach and commitment to excellence, NAII is poised to make a lasting impact on Singapore and the global AI landscape.
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The Vietnam Posts and Telecommunications Group (VNPT) has reached a significant milestone with its artificial intelligence (AI) platform, VNPT eKYC, logging over 1 billion user authentication requests. This accomplishment solidifies VNPT’s position as a pioneer in electronic identification and verification solutions within Vietnam.
Since its inception, VNPT eKYC has been at the forefront of electronic Know Your Customer (eKYC) services for over five years, serving a diverse range of clients including banks, financial institutions, telecommunications companies, and e-commerce entities. With over 100 organisations utilising its services, VNPT eKYC has facilitated electronic identification for more than 40 million individuals across the country.
On average, the VNPT eKYC system processes an impressive 600,000 requests daily, with peak days witnessing over a million requests being handled seamlessly. This demonstrates the platform’s robustness and reliability in managing high volumes of authentication transactions efficiently.
The significance of VNPT eKYC extends beyond its technological capabilities, particularly in the context of evolving regulatory requirements. The State Bank of Vietnam’s decision mandating biometric authentication for transactions exceeding 10 million VND (approximately 416 USD) and other significant transactions from July 1, 2024, underscores the critical role of advanced authentication solutions like VNPT eKYC in ensuring compliance and security in financial transactions.
Moreover, the platform’s success highlights the increasing importance of domestically developed solutions in the banking and financial sector. Domestic solutions such as VNPT eKYC offer several advantages, including rapid implementation, cost-effectiveness, adherence to global technology standards, scalability, and high readiness to meet evolving regulatory requirements.
Central to the effectiveness of VNPT eKYC is its advanced AI models, which enable the verification of facial biometric data with an impressive accuracy rate of up to 99.99%. This high level of accuracy not only enhances the security of authentication processes but also contributes to building trust and confidence among users and regulatory authorities.
As Vietnam’s digital economy continues to grow and evolve, the role of advanced authentication and verification solutions like VNPT eKYC becomes increasingly indispensable. Beyond facilitating seamless and secure electronic transactions, these solutions contribute to enhancing the overall digital infrastructure and ecosystem of the country, paving the way for further innovation and economic growth.
Looking ahead, VNPT remains committed to advancing its AI platform and expanding its capabilities to meet the evolving needs of its clients and the regulatory landscape. With a strong focus on innovation, reliability, and security, VNPT eKYC is poised to play a pivotal role in shaping the future of electronic identification and verification in Vietnam’s dynamic digital economy.
VNPT’s achievement of logging over 1 billion authentication requests with its AI platform, VNPT eKYC, marks a significant milestone in Vietnam’s journey towards digital transformation.
Amid a swiftly changing global landscape, Vietnam emerges as a frontrunner in a digital revolution, strategically positioned to harness technology’s transformative power for economic progress and societal development.
It is embracing its digital transformation journey, highlighting collaborative efforts to drive the nation’s digital transformation. The nation’s digital technology industry aims to propel Vietnam towards high-income status by 2045 through technology mastery, innovation, and indigenous manufacturing capabilities.
Moreover, the nation is working to harmonise its regulations, streamline laws, and promote consistency in its legal framework to foster a more favourable and appealing cyber environment.
As the country continues to embrace technology-driven solutions to address emerging challenges, VNPT eKYC stands as a testament to the potential of domestic innovation in driving progress and excellence in the digital era.
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In a significant development, the Telecom Regulatory Authority of India (TRAI) released a comprehensive set of recommendations on the usage of embedded SIM (eSIM) for Machine-to-Machine (M2M) communications. This comes at a crucial juncture, as the proliferation of IoT devices and the imminent rollout of 5G services underscore the pressing need for clear regulatory frameworks to govern emerging technologies.
Prompted by a directive from the Department of Telecommunications (DoT), TRAI embarked on an extensive consultative process to solicit insights from stakeholders and industry experts. The formulation of these recommendations began with a consultation paper on ‘Embedded SIM for M2M Communications’ on 25 July 2022. TRAI then fostered extensive stakeholder engagement, including submissions and a virtual open house discussion on December 14, 2022, ensuring broad participation and inclusivity.
Against the backdrop of rapid technological advancement and evolving consumer needs, TRAI’s recommendations aim to address key challenges and opportunities in the realm of M2M communications. At the heart of these recommendations lies a dual commitment to fostering innovation and safeguarding consumer interests.
By delineating clear guidelines for the deployment and management of eSIM technology, TRAI seeks to lay the foundation for a robust and resilient M2M ecosystem that promotes transparency, security, and interoperability.
Central to TRAI’s recommendations is the imperative of ensuring robust security measures across the M2M value chain. Recognising the inherent vulnerabilities associated with IoT devices and the potential ramifications of security breaches, TRAI underscores the importance of implementing stringent Know Your Customer (KYC) protocols. By mandating proper verification procedures for device activation and subscription management, TRAI aims to mitigate fraud risks, safeguard network integrity, and enhance consumer trust in M2M communications.
TRAI’s recommendations encompass a comprehensive framework for profile switching of eSIMs and swapping of Subscription Manager-Secure Routing (SM-SR), thereby enhancing flexibility and choice for consumers. By enabling seamless transitions between different network providers and service plans, these provisions empower consumers to optimise their connectivity experience while promoting healthy competition within the telecom sector.
The rollout of 5G services in India has ushered in a new era of connectivity, unlocking unprecedented opportunities for innovation and economic growth. Against this backdrop, TRAI’s recommendations seek to capitalise on the transformative potential of M2M communications across diverse sectors such as agriculture, transportation, healthcare, and industrial automation.
Streamlining the regulatory landscape for M2M eSIMs will facilitate the seamless integration of IoT devices into existing networks, thereby catalysing the development of smart infrastructure and digital ecosystems.
Key stakeholders, including Unified Access Service License holders, Unified License holders, and M2M Service Providers, are envisioned to play pivotal roles in the implementation of these recommendations. By fostering collaboration and partnership between industry players, TRAI aims to ensure the effective deployment and management of eSIM technology, thereby enabling the realisation of India’s vision for digital self-reliance and technological sovereignty.
However, the journey towards realising the full potential of M2M communications is not without its challenges. TRAI acknowledges the complexities inherent in implementing these recommendations, particularly in the context of India’s diverse and dynamic telecom landscape. In this regard, TRAI has refrained from permitting the use of 901.XX IMSI series allocated by the International Telecommunication Union (ITU) for M2M services in India, citing the need for a phased approach towards adoption and implementation.
TRAI’s recommendations represent a significant milestone in India’s journey towards harnessing the transformative potential of M2M communications. By providing a clear regulatory framework for the deployment and management of eSIM technology, TRAI seeks to foster innovation, promote consumer welfare, and advance the nation’s digital agenda.
As stakeholders gear up to embrace these recommendations, India looks to emerge as a global leader in M2M communications, driving sustainable development, and inclusive growth in the digital era.
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As the rapid advancement of artificial intelligence (AI) technologies continues to reshape the world, the need for responsible governance and oversight has become increasingly evident. In a landmark decision, the United Nations General Assembly has taken a pivotal step forward in the regulation and promotion of artificial intelligence technologies with the adoption of a groundbreaking resolution.
Led by the United States and co-sponsored by over 120 Member States, this resolution underscores the imperative of developing and utilising AI systems that are not only technologically advanced but also safe, secure, and trustworthy. At its core, the resolution seeks to harness the transformative potential of AI while upholding fundamental human rights and advancing sustainable development goals on a global scale.
The adoption of this resolution represents a significant milestone in international efforts to navigate the complex landscape of AI governance. For the first time in its history, the General Assembly has formally recognised the need to regulate the burgeoning field of AI, acknowledging its profound impact on societies worldwide. The resolution serves as a testament to the growing recognition of AI’s potential to drive progress across various sectors, from healthcare and education to economic development and environmental sustainability.
Central to the resolution’s principles is the paramount importance of upholding human rights in the development and deployment of AI systems. It emphasises the need to respect, protect, and promote human rights throughout all stages of the AI lifecycle, including design, development, deployment, and usage. By affirming the principle that the same rights enjoyed offline must also be safeguarded online, the resolution underscores the necessity of accountability and ethical governance in the realm of AI.
Furthermore, the resolution highlights AI’s role in advancing sustainable development goals, recognising its potential to accelerate progress towards achieving the ambitious targets set forth by the United Nations. By harnessing the power of AI-driven innovation, Member States can unlock new opportunities for inclusive growth, enhance access to essential services, and address pressing global challenges such as poverty, inequality, and climate change.
A key aspect of the resolution is its call for collaboration and cooperation among Member States and stakeholders to bridge the technological divide and ensure equitable access to AI technologies. Recognising the varying levels of technological development between and within countries, the resolution urges support for developing nations to help them leverage AI for inclusive and sustainable development. By closing the digital divide and enhancing digital literacy, Member States can empower individuals and communities to fully participate in the digital economy and society.
Speaking before the adoption of the resolution, US Ambassador and Permanent Representative to the UN, Linda Thomas-Greenfield, underscored the importance of governing AI technology responsibly. She emphasised the opportunity and responsibility of the international community to shape the future of AI, ensuring that it aligns with principles of humanity, dignity, safety, and security. Thomas-Greenfield called for a collective commitment to using AI as a tool for advancing shared priorities and closing digital disparities, thereby fostering a more equitable and inclusive world.
The adoption of this historic resolution by the UN General Assembly marks a significant milestone in the global dialogue on AI governance. By promoting the development and use of safe, secure, and trustworthy AI systems, Member States are laying the groundwork for a future where AI serves as a force for positive change, driving sustainable development and advancing human well-being. As we embark on this transformative journey, it is imperative that we remain vigilant in safeguarding human rights, promoting ethical AI governance, and ensuring that the benefits of AI are shared by all.
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The rapid adoption of technological advancements and innovation in Singapore has spurred growth across various sectors, with the financial services industry (FSI) emerging as a frontrunner.
Recognising the importance of cutting-edge technology in a rapidly evolving digital landscape, the Monetary Authority of Singapore has partnered with banks and tech firms to develop an innovative Artificial Intelligence (AI) risk framework, exploring the multifaceted potential this technology offers the FSI.
In this dynamic landscape, the use of AI is paramount. Financial institutions are leveraging AI to distil crucial insights from vast datasets, enabling the development of highly financial products, services, and tools. Sectors like banking, trading, and insurance are modernising their operational frameworks with AI, utilising real-time insights to achieve superior outcomes, increased profits, and a competitive edge.
Further, the financial services industry is benefiting significantly from large language models (LLMs) – a specific type of AI algorithm. LLM applications utilise natural language processing (NLP) and machine learning (ML) methods to analyse extensive financial data, extract valuable insights, and facilitate well-informed decision-making. These applications are advantageous in diverse areas such as risk assessment, fraud detection, customer support, compliance, and investment strategies.
By automating recurring tasks and providing accurate and timely information, LLM applications improve operational efficiency, decrease the chances of human errors, and streamline decision-making processes. This technological advancement empowers financial institutions to stay competitive, adjust to dynamic market conditions, and offer personalised and efficient services to their clients.
Despite the significant competitive advantages offered by these advanced technologies, they also pose several challenges. One notable challenge is the integration of AI into the financial services sector, which raises complex issues concerning the security and privacy of data.
Given that the financial services industry deals with susceptible financial information, the use of AI, including LLMs, raises concerns about the safeguarding and confidentiality of this data. Navigating the delicate balance between harnessing the innovation and efficiency offered by AI and the crucial need to bolster defences against evolving threats remains a persistent challenge.
This necessitates continuous investment in security infrastructure, the implementation of rigorous data protection protocols, and strict adherence to regulatory standards, particularly in light of AI’s inherent challenge in the realm of data privacy within the dynamic landscape of the financial services industry.
Fostering sustainable IT is crucial in the FSI sector to mitigate environmental risks, enhance operational resilience, and align with growing expectations, ensuring long-term economic stability and regulatory compliance. AI is vital in helping organisations achieve sustainable IT through several means, including enhancing efficiency, reducing energy consumption, and optimising resource utilisation.
The OpenGov Breakfast Insight held on 22 March 2024 at Equarius Hotel Singapore explored the role of AI in addressing cybersecurity challenges in the financial services industry. The event highlighted the importance of AI in enhancing cybersecurity measures, particularly in detecting and responding to threats in real-time.
The conversation emphasised the vital role of public-private collaboration in crafting resilient cybersecurity strategies, highlighting the necessity of proactive measures and joint initiatives to protect financial institutions from emerging cyber threats amidst the AI-driven transformation. Participants and experts alike recognised the imperative of sharing information and working together to effectively counter cyber threats.
Opening Remarks
Mohit Sagar, CEO and Editor-In-Chief at OpenGov Asia, explained that platforms like OpenGov play a crucial role in enabling governmental bodies to evolve digitally, ensuring that governance is more efficient and accessible to the public.
“This digital shift is imperative as we stand on the cusp of a technological revolution, where the way we live, work, and interact is poised for dramatic changes,” he asserts.
The pandemic has underscored the significance of digital capabilities, thrusting the concept of remote work into the mainstream and accelerating technological advancements at an unprecedented pace.
The term ‘AI’ transitioned from a futuristic buzzword to a daily utility during this period. Towards the end of the crisis, AI technology had become democratised, making information derived from AI not only widely accessible but also remarkably accurate.
This surge in AI utility highlighted its potential in various sectors, notably in the banking and financial sectors, where intelligence and technology have become the primary drivers of differentiation. In an industry where trust is paramount, the integration of AI has opened new avenues for enhancing security, personalising customer experiences, and optimising operational efficiency.
“As we gaze into the future, the transformation powered by AI emerges as a definitive game-changer across all domains, including governance and public services. Yet, this transformation brings to the fore the critical challenges of data privacy and security,” Mohit cautions. “So how can societies become more innovative and efficient without open data sharing?”
The answer lies in navigating this journey with caution and care, underscored by the need for trusted partnerships that respect the delicate balance between leveraging data for advancement and safeguarding individual privacy.
Enhancing cyber resilience amid this AI-driven evolution is paramount. Data represents the lifeblood of our digital existence, akin to the biological imperative that one does not share blood with just anyone except in situations of utmost necessity.
“This analogy underscores the importance of meticulous data management and cybersecurity measures. In the digital age, as we march towards an increasingly AI-integrated future, the emphasis on cyber resilience cannot be overstated,” Mohit explains. “It involves protecting data against unauthorised access and ensuring that the digital ecosystem is robust enough to withstand and recover from any cyber threats or incidents.”
Amidst ongoing market fluctuations, the Financial Services Industry (FSI) finds itself in a transformative phase, compelling organisations to prioritise intelligence, efficiency, and security. With digital innovations reshaping the landscape, FSI entities are embracing advanced technologies like artificial intelligence to remain competitive and address evolving customer needs.
Large Language Models (LLMs), a specialised type of artificial intelligence (AI) algorithm, offer substantial benefits to the financial services industry (FSI). These benefits are crucial in enhancing operational efficiency, improving decision-making processes, and ensuring regulatory compliance:
- Extensive Financial Data Analysis:LLM applications leverage advanced natural language processing (NLP) and machine learning (ML) methods to analyse extensive financial data, providing valuable insights across various domains. These include risk assessment, fraud detection, customer support, compliance, and investment strategies.
- Operational Efficiency and Error Reduction:Automating recurring tasks and delivering timely information by LLM applications improve operational efficiency within the financial sector. By minimising the chances of human errors and streamlining decision-making processes, LLMs enhance overall operational effectiveness, positioning financial institutions to adapt to dynamic market conditions while staying competitive.
- Singapore’s Recognition of Tech Advancements:This collaborative effort reflects the nation’s recognition of the significance of cutting-edge technology, explicitly focusing on exploring the multifaceted potential that AI offers to the financial services industry (FSI).
Despite these benefits, integrating AI into the financial services sector presents challenges, particularly concerning the security and privacy of sensitive financial data. As the industry deals with highly confidential information, concerns arise about how AI technologies handle, safeguard, and ensure the confidentiality of economic data, necessitating a careful balance between innovation and data protection.
AI and ML are pivotal in bolstering cyber resilience within the Financial Services Industry. These advanced technologies can analyse vast amounts of data in real-time, enabling early detection of cyber threats and vulnerabilities, thus enhancing the industry’s ability to address security challenges proactively.
Mohit believes that fostering sustainable IT is imperative in the FSI sector to address environmental risks, enhance operational resilience, and align with rising expectations for corporate responsibility.
AI is crucial in helping FSI organisations achieve sustainable IT, he says. Prioritising sustainable IT practices contributes to long-term economic stability and ensures compliance with evolving environmental regulations, reflecting the industry’s commitment to environmental stewardship.
“Singapore’s commitment to technological innovation and the adoption of advanced technologies like AI have positioned the financial services industry for continued growth and competitiveness,” Mohit concluded. “However, addressing cybersecurity challenges and ensuring the responsible use of AI remain critical priorities for the industry as it navigates an increasingly digital landscape.”
Welcome Address
Singapore’s Financial Services Industry (FSI) has seen remarkable growth year after year, notes John Ng, Director & General Manager of Sales at Hewlett Packard Enterprise. With its substantial contribution to the economy and reputation as a global financial hub boasting diverse institutions, Singapore has cemented its position as one of the top five fintech hubs worldwide. The country is home to over 1,000 fintech firms and attracted a record US$1 billion worth of investments in 2019.
The Singapore government’s commitment to supporting technology adoption, innovation-driven growth, and cybersecurity capabilities has further enhanced the capabilities of existing firms and led to the creation of new industry sectors, such as digital banks and mobile payment providers. Over the past five years, the government has committed over US$250 million to these initiatives, contributing to Singapore’s status as a leading fintech hub.
Artificial Intelligence (AI) has played an increasingly integral role in the FSI sector in Singapore, mainly through the adoption of Large Language Models (LLMs) and Natural Language Processing (NLP). These technologies have been leveraged to enhance various aspects of the industry, including fraud detection, risk assessment, customer service, regulatory compliance, and predictive analytics.
LLMs and NLP analyse large volumes of data to detect fraudulent activities, assess credit risk, improve customer service through chatbots and virtual assistants, ensure regulatory compliance, and predict financial trends and market conditions. These technologies enable financial institutions to make more informed decisions, improve operational efficiency, and stay ahead of the competition.
Hewlett Packard Enterprise (HPE) can assist Singapore’s Financial Services Industry (FSI) sector. He underscores the significance of HPE GreenLake for Large Language Models (LLMs), a cloud service facilitating businesses of varying scales to train, refine, and implement machine learning models. Leveraging HPE’s Cray XD supercomputer, this service delivers an AI software suite, including the HPE Machine Learning Development Environment, to simplify the remote training and deployment of machine learning applications.
Deploying HPE’s supercomputers and AI software, organisations can efficiently train large language models for critical applications in various industries, including finance, healthcare, and legal services. This technology enables businesses to unlock new insights, improve decision-making processes, and drive innovation in their respective industries.
John observes that Singapore’s Financial Services Industry (FSI) sector flourishes due to its dedication to innovation and technology integration. He agrees that the government’s backing of fintech and cybersecurity endeavours has fostered an environment conducive to industry advancement and innovation.
“HPE firmly believes that by embracing AI technologies like LLMs and NLP, Singapore’s FSI sector is primed for continued growth and innovation, solidifying its status as a leading global financial hub,” he concluded. “I an confident that we will get a lot of insights from this meeting that can be implemented in your respective fields.”
Power Talk: How Can FSI Organisations Safeguard AI Capabilities for a Competitive Advantage in the Ever-Evolving Digital Landscape?
As the Executive Director of Data Science at OCBC Bank, Enguerran Dallet has seen the significant potential of artificial intelligence (AI) in the financial services industry (FSI), driving its transformative stages amid market fluctuations.
AI’s advanced capabilities empower FSI entities to modernise operations and secure a competitive edge in the evolving digital landscape.
However, challenges, particularly regarding data privacy and security, persist. Enguerran proposes several strategies and considerations to effectively harness AI and data within Singapore’s Financial Services Industry:
- Data Security: Implement strong data security measures and identity and access management (IAM) protocols to protect customer data.
- Data Quality and Infrastructure: Clean and structure data to mitigate risks and lay a foundation for AI applications.
- Expert Partnerships: Collaborate with third-party experts to bridge technical expertise gaps.
- Comprehensive Assessment: Assess current capabilities thoroughly to identify improvement areas.
- Ethical AI: Emphasise responsible AI practices, ethical considerations, and algorithmic transparency.
- Regulatory Compliance: Implement AI-powered RegTech solutions for compliance.
Implementing these strategies can help Singapore’s financial institutions leverage AI and data effectively, drive innovation, enhance decision-making, and achieve superior outcomes in the FSI sector.
“In today’s highly competitive financial services industry, personalisation is not just a strategy but a necessity for achieving customer satisfaction, loyalty, and overall business success,” believes Enguerran. “Personalisation allows institutions to go beyond generic offerings and tailor products, services, and interactions to meet individual customers’ unique needs and preferences, thereby building trust and loyalty.”
Enguerran acknowledges that AI plays a pivotal role in enabling this level of personalisation. In OCBC Bank, AI-powered algorithms can analyse our vast customer data, including their transaction history, browsing their behaviour, and even their demographic information, to gain valuable insights into their preferences and behaviour, elaborates Enguerran. This kind of analysis allows institutions to provide personalised recommendations, offers, and services that are more likely to resonate with customers, enhancing their overall experience.
One of the key areas where AI is transforming personalisation in the financial services industry is using chatbots and virtual assistants. These AI-powered tools can interact with customers in real-time, providing personalised support and assistance based on individual needs. This improves customer service and frees human agents to focus on more complex tasks, improving overall efficiency and productivity.
By leveraging AI, financial institutions can differentiate themselves, attract new customers, and retain existing ones. AI’s ability to analyse data, predict customer behaviour, and optimise operations leads to increased efficiency, reduced costs, and improved customer satisfaction.
“AI-driven personalisation is key in today’s financial services industry. It enables institutions to meet customer expectations, stay competitive, and drive business growth in a rapidly evolving digital landscape,” ends Enguerran.
David Sharratt, Global Head of Data Product Monetisation at Standard Chartered Bank, highlights the transformative impact of technological advancements on financial services. Over the past few decades, these advancements have reshaped how people interact with money and what they expect from financial institutions, leading to simplified processes, reduced error rates, improved communication, and altered consumer perceptions of money.
Financial organisations are poised to benefit significantly from these advancements, particularly through chatbots and automation. David emphasised that these innovations can reduce labour hours, enhance client connections, and boost profitability. The impact of these technologies varies across functions, but many institutions can adapt and gain from them.
One such transformative technology is blockchain, a digital ledger of transactions distributed across a network of computers and secured through cryptography, David explains. Initially designed for tracking digital currency, blockchain has the potential to revolutionise aspects of the financial services industry. For example, it can streamline processes involved in executing and clearing securities trades, reducing costs and errors associated with manual bookkeeping.
“Artificial Intelligence and Machine Learning have also led to significant improvements in financial services by helping banks automate processes and make informed decisions,” asserts David. “AI is used to identify fraud and illegal activity, while ML helps banks develop new products and services. Based on my experience, those technologies reduce costs and improve the customer experience.”
Cloud banking is another significant trend, enabling institutions to store and process financial data in remote locations. This cost-efficient approach allows access to robust technologies from anywhere in the world.
Embedded finance is a technology that improves the efficiency of financial services, potentially reducing costs for banks by automating processes. RPA automates tasks and processes, reducing manual work and improving organisational efficiency.
“However, these technologies also pose cybersecurity risks,” he warns. “Despite we know that technology is emerging anywhere, we have to be aware of its risk too.”
To safeguard data against threats and ensure data availability, businesses should implement robust security measures, conduct regular security audits, and provide data security in AI systems. Compliance with regulations, employee awareness, diverse dataset testing, error analysis, and backup and disaster recovery plans are essential for protecting sensitive data.
Amit Krishna, General Manager, Compute Southeast Asia at Hewlett Packard Enterprise (HPE), emphasised the company’s readiness to support the financial services industry (FSI) sector in overcoming its technological challenges. HPE offers a range of innovative solutions tailored to the specific needs of the FSI sector, with a focus on enhancing data security, automation, and operational efficiency.
One of HPE’s flagship solutions is GreenLake for Large Language Models (LLMs). This cutting-edge cloud service empowers businesses to train, fine-tune, and easily deploy machine learning models. This service, powered by HPE’s Cray XD supercomputer, provides a comprehensive AI software stack to streamline machine learning application training and deployment processes.
“Organisations can efficiently train large language models for critical applications across various industries, including finance,” believed Amit.
HPE also implements robust security measures to safeguard sensitive financial data. As AI and machine learning adoption continues to grow within the FSI sector, ensuring data security and compliance with regulations becomes increasingly vital.
“HPE’s security solutions, which include encryption, multi-factor authentication, and secure development practices, are tailored to help organisations mitigate cybersecurity risks associated with AI systems,” he reveals.
Moreover, HPE’s technologies enhance operational efficiency and customer service for financial institutions. For instance, HPE’s AI-powered solutions enable the development of chatbots and virtual assistants that improve customer interactions and reduce costs by minimising the need for human intervention in routine banking processes.
These technologies also enable financial institutions to gain deeper insights into customer behaviour and market trends, empowering them to make more informed decisions and maintain a competitive edge in the market.
“HPE’s innovative solutions and expertise can deliver significant benefits to the FSI sector, addressing key challenges and unlocking new opportunities for growth and efficiency,” Amit concluded. “By leveraging HPE’s technologies, financial institutions can enhance their competitiveness and deliver superior services to their customers in today’s rapidly evolving digital landscape.”
Closing Remarks
John Ng expressed gratitude for the participants’ enthusiasm during the session, considering it the beginning of their journey to explore various ideas and innovations poised to reshape the financial industry. He acknowledges the importance of collaboration among companies and stakeholders in fostering innovative and sustainable solutions.
A key topic of discussion centered around the incorporation of AI technology into Singapore’s Financial Services Industry (FSI), with John reaffirming HPE’s commitment to aiding the sector in overcoming its technological challenges. HPE stands prepared to offer customised solutions tailored to meet the distinctive needs of the FSI, particularly focusing on aspects like data security, automation, and operational efficiency.
HPE offers the GreenLake for Large Language Models (LLMs) solution, a cloud service that allows businesses to train, tune, and deploy machine learning models. Powered by HPE’s Cray XD supercomputer, this service provides an AI software stack that simplifies the training and deployment of machine learning applications. By leveraging HPE’s supercomputers and AI software, organisations can train large language models for critical applications in various industries, including finance.
Additionally, HPE provides expertise in implementing robust security measures to protect sensitive financial data. With the increasing use of AI and machine learning in the FSI sector, ensuring data security and regulation compliance is crucial. HPE’s security solutions, including encryption, multi-factor authentication, and secure development practices, can help organisations reduce cybersecurity risks associated with AI systems.
John encouraged experts, professionals, and all participants present to embrace the integration of AI into their operations to enhance efficiency, innovation, and customer experience. He also stressed the importance of adopting a sustainable approach to AI implementation, prioritising factors such as data security and regulatory compliance.
Given the elevated cyber risks in the field, companies must safeguard their data against threats and ensure data availability, especially when deploying cutting-edge technologies like AI, is John’s advice. But despite the risks involved, companies in the financial sector must be prepared to adapt to the rapid changes in the technology landscape, with AI emerging as a crucial tool for maintaining competitiveness in this digital era.
“By implementing AI technology wisely and responsibly, companies can optimise their operations, enhance data-driven decision-making, and deliver superior customer service,” John concludes.
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In the fast-evolving landscape of alternative investments, the convergence of technology, especially artificial intelligence (AI) and digitalisation is reshaping strategies, opportunities, and challenges. At the Alternative Investment Management Association Singapore Annual Forum, Ms. Gillian Tan, Assistant Managing Director at the Monetary Authority of Singapore (MAS), shed light on the pivotal role of technology, and how it is driving innovation and reshaping investment strategies in the realm of alternative assets.
Reflecting on the challenges faced in the preceding year, including geopolitical tensions and supply chain disruptions, Ms Tan noted the resilience of global financial markets. Despite these headwinds, the alternatives sector demonstrated robustness. She emphasised the pivotal role of technology and AI in navigating through such challenges and driving resilience in investment strategies.
Delving into the burgeoning role of AI within the alternatives sector, Ms. Tan highlighted its transformative impact on investment strategies and portfolio management. The adoption of AI-powered algorithms and predictive analytics has empowered asset managers to identify trends, mitigate risks, and optimise investment decisions with unprecedented precision. AI-driven insights are revolutionising traditional approaches to asset allocation, enabling managers to extract value from vast datasets and navigate complex market dynamics with agility.
Ms. Tan underscored the pivotal role of AI as one of the primary mega forces shaping the future of alternative investments. Beyond its application in investment strategies, AI is poised to revolutionise various facets of the industry, including risk management, compliance, and client servicing. From sentiment analysis to algorithmic trading, AI-driven solutions are driving operational efficiency and enhancing decision-making processes across the investment lifecycle.
Technology is playing a crucial role in accelerating the transition towards a sustainable future. By leveraging AI-powered data analytics, asset managers can identify and evaluate sustainable investment opportunities, ranging from renewable energy projects to green infrastructure initiatives. Tech-driven ESG (Environmental, Social, and Governance) screening tools enable investors to align their portfolios with sustainability objectives while optimising returns.
The convergence of AI and blockchain technology is catalysing the growth of the digital assets ecosystem. Predictive models enhance risk assessment and investment decision-making in digital asset markets, while blockchain facilitates transparent and secure transactions. MAS’s initiatives, such as Project Guardian and the Global Layer One initiative, are driving innovation in digital asset tokenisation and cross-border transactions, leveraging AI for enhanced operational efficiency.
Looking ahead, Ms Tan emphasised the transformative potential of generative AI (Gen AI) in reshaping asset management practices. Gen AI, with its ability to process vast datasets and generate content autonomously, promises to revolutionise portfolio optimisation, content generation, and client engagement. However, she cautioned against the inherent risks of AI, including data bias and algorithmic opacity, underscoring the importance of robust risk frameworks and ethical AI governance.
As the financial sector integrates Gen AI into its operations, careful consideration must be given to its ramifications on employment and skill requirements in Singapore. A collaborative effort between MAS and the Institute of Banking and Finance Singapore (IBF) will see the initiation of a joint study.
This research aims to pinpoint key uses of Gen AI, evaluate its integration and growth in financial services, and examine its impact on jobs and required skills. By doing so, it will inform strategies to enhance and adapt the financial workforce, enabling them to harness Gen AI’s transformative potential and transition effectively into new career paths.
As the alternative investment landscape continues to evolve, embracing AI and digital innovations will be paramount to unlocking value and driving sustainable growth. By harnessing the transformative potential of AI, asset managers can navigate complexities, capitalise on emerging opportunities, and deliver enhanced value to investors.
With technology as the cornerstone of innovation, the future of alternative investments promises to be characterised by agility, resilience, and unparalleled insights, propelling the industry towards new horizons of success.
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With the rapid advancement of digital technology and the proliferation of artificial intelligence (AI) in various facets of society, the legal landscape surrounding these innovations remains uncertain. The legal framework for AI systems is a complex issue that requires a comprehensive approach, combining binding and non-binding legal instruments that complement each other.
In light of this, Dr Olivia J Erdélyi, a Senior Lecturer at Te Whare Wānanga o Waitaha | University of Canterbury (UC) in the Faculty of Law, emphasises the role of mathematical modelling in identifying gaps in legislation and shaping policies to safeguard society.
“The legal framework for AI systems should cover various aspects, including categorising the risk level of each use case for AI, such as prohibited use, high risk, and minimal or low risk,” she explained. “High-risk AI systems are required to undergo continuous testing, monitoring, and auditing in areas like privacy, cybersecurity, intellectual property, antitrust, algorithmic bias, accuracy, and consumer product/health/safety.”
Dr Erdélyi highlights the challenges posed by legal uncertainty in the context of AI, noting that without specific provisions addressing AI-related issues, predicting court decisions becomes exceedingly difficult.
Drawing attention to the Cambridge Analytica scandal, where a political consulting firm utilised personal data from social media platforms to influence the 2016 United States presidential election, Dr Erdélyi’s research demonstrates how mathematical modelling can illuminate vulnerabilities in privacy and data protection regulations.
In her study, Dr Erdélyi illustrates how anonymised data, which initially conceals personal identities, can be manipulated through AI processing to uncover identifiable connections, thus breaching privacy regulations. This revelation underscores the inadequacy of current rules, which focus solely on personally identifiable information, failing to address the potential risks posed by anonymised data manipulation.
The interdisciplinary approach adopted by Dr Erdélyi’s team integrates mathematics, computer science, and law to formulate effective policy responses to AI-related challenges. By combining diverse expertise, they aim to bridge the gap between technological advancements and legal frameworks, ensuring robust regulatory measures.
UC’s Mathematics and Statistics Associate Professor, Gábor Erdélyi, collaborates with Dr Erdélyi, emphasising the importance of interdisciplinary collaboration in addressing AI complexities. Despite the benefits of such collaboration, he acknowledges the communication barriers that impede practical cooperation between scientific fields and policymakers. Overcoming these barriers necessitates mutual understanding and effective communication channels between stakeholders.
While awaiting comprehensive AI legislation, Dr Erdélyi advocates for leveraging existing laws as a foundation for addressing AI-related challenges. However, she underscores the imperative of designing new laws tailored to the unique demands of AI technologies to prevent potential loopholes and mitigate adverse consequences.
Despite the absence of a dedicated AI strategy in Aotearoa, New Zealand, Dr Erdélyi emphasises the importance of developing indigenous policies that align with international standards while catering to local needs. Striking a balance between international consensus and national sovereignty, she calls for the enactment of binding laws that safeguard individuals’ rights and provide avenues for legal recourse.
The integration of mathematical modelling and interdisciplinary collaboration emerges as crucial strategies in navigating the complex legal terrain surrounding AI. By identifying legislative gaps and formulating targeted policies, stakeholders can harness the potential of AI technologies while safeguarding societal values and individual rights.
The evolving legal landscape demands proactive measures to adapt regulatory frameworks to the challenges posed by digital innovation, ensuring equitable and transparent governance in the AI era.
As artificial intelligence (AI) increasingly influences society, regulatory frameworks will be essential in determining the trajectory of this impactful technology. Dr Erdélyi concluded that cooperation among governments, industry players, and the general public is vital for creating regulations that encourage the responsible development and application of AI, especially for New Zealand and beyond.