Emerging technologies, such as artificial intelligence, machine learning, data analytics, and biotechnology, greatly transform society and reshape the global economy. However, these technologies also come with a significant challenge regarding ethical and social implications. Global collaboration by governments, regulators, and industry leaders can help ensure that emerging technologies are developed and deployed responsibly.

Challenges of Regulating Emerging Technologies

Emerging technologies have led to complex situations that traditional governments might find difficult to manage. For instance, today’s advanced technologies also come with new forms of crime. This requires law enforcement and public safety organizations to keep up with new and innovative crimes. Today’s governments face challenges that affect the development of effective digital laws.

One of these challenges is the independence of technology from physical state territories. The interconnection of technology devices over the internet has no boundaries. This makes it impossible for any country to regulate all aspects of the technologies. Secondly, all states are not the same, and each enhances its technology-related laws according to its capabilities. While strong economies can afford robust IT infrastructure, other countries do not have the technical capacity.

Other factors that complicate technology regulation include the ability of major technology companies to bypass established regulations. Additionally, states are consumers of technology products and services developed by private corporations. Since they are not innovators, policymakers, and regulators, they do not understand the intricate technology systems that affect the regulatory decisions that must be made.

The above-mentioned are only a few of the challenges that make technology regulation complicated. Still, there is a growing need for digital governance and a digital constitution.

Why Global Collaboration is Crucial in Regulating Emerging Technologies

1. Address ethical and social issues – significant ethical and societal issues, like data privacy and security, are brought up by emerging technology. However, international cooperation can help ensure coordinated and efficient responses to these issues.
2. Growing competition for technological dominance – political, societal, and economic rivalries are driving technological dominance. Increased competition for elements of technology supremacy can only result in conflict, obstructing technology’s ethical use.
3. Technology diffusing globally – in most cases, new technologies are available for adoption anywhere in the world. Thus, international regulatory frameworks must be coordinated to prevent competing or incompatible laws.
4. Harmonizing standards – global cooperation can assist in harmonizing standards and laws for new technology, making it simpler for businesses to comply and lowering entry barriers for new players.
5. Promote inclusivity – emerging technologies have the potential to make existing social and economic inequalities even worse. Collaboration on a global scale can ensure that these technologies are usable by everyone and do not reinforce or introduce new forms of exclusion.
6. Enhance innovation – collaboration across borders can facilitate the exchange of knowledge, ideas, and best practices, leading to more innovation and faster technological advancement.
7. Avoid existential risks – technology can potentially introduce threats that endanger life globally. Such risks might include nanotechnology weapons and engineered pandemics. However, developing strategic global legal frameworks that identify potential risks can help avoid the proliferation of dangerous and harmful technologies.

Existing Efforts for Global Collaboration in Regulating Emerging Technologies

There are numerous initiatives for international cooperation in regulating emerging technologies. For example, the Global Partnership on Artificial Intelligence (GPAI) brings together governments and business executives from across the world. Its goal is to ensure artificial intelligence (AI) is developed and deployed responsibly in a human-centric manner. GPAI’s main focus is on responsible AI, data governance, the future of work, and innovation and commercialization.  

The Organization for Economic Cooperation and Development (OECD) is another international organization where governments work together to solve common challenges and develop global standards. A good example is their recommendation on responsible innovation in neurotechnology, adopted by the OECD Council in December 2019. Other organizations working toward promoting global collaboration and coordination on emerging technology issues include the World Economic Forum (WEF) and the United Nations.

Unfortunately, there is still a lot of work to be done. Continued global cooperation is crucial to ensure that emerging technologies are created and used to benefit society. Currently, there is no global agreement on technology regulation; instead, regulators take different and sometimes conflicting standpoints.

Conclusion

The pace and impact of emerging technologies are likely to keep increasing. Although these developments improve human experiences, the potential for these technologies to disrupt social, economic, and political systems worldwide means that it is essential for governments, private companies, and civil organizations to work together to ensure that they are developed responsibly.

Customer loyalty is critical to any successful business strategy in today’s digital age. With emerging technologies such as the internet of things (IoT), companies are now leveraging a new approach called the internet of behavior (IoB) to gain deeper insights into their customers’ behavior and preferences.

What is IoB?

The internet of behavior exists because of the internet of things. IoT is the interconnection of physical digital objects that gather and exchange information over the internet. On the other hand, IoB makes sense of the collected data from various sources, including wearable devices, digital household devices, human online activity and social media.

The acronym internet of behavior (IoB) was coined by Gartner, a tech research firm, as identified among the top 10 trends in their strategic technology report for 2021. However, the concept of using data to influence customer behavior was developed in 2012 by Göte Nyman, a psychology professor at the University of Helsinki, long before the internet of things took hold.

Gartner defines IoB as an extension of the internet of things, focusing on capturing, processing and analyzing the “digital dust” of people’s daily lives.

Simply put, IoB interconnects IoT, consumer psychology and data analytics. The data is analyzed in terms of behavioral psychology to capture patterns that marketing and sales teams can use to influence customer behavior.

How IoB can Influence Customer Loyalty

Aside from products and services, customer experience has become a significant factor in business success. By understanding customer behavior, businesses can leverage IoB data to influence customer loyalty in various ways.

Personalization

Personalization has the power to transform customer experience. This is reflected in a survey that revealed 76 percent of Americans are more likely to complete a purchase because of a personalized experience.

To take advantage of IoB, companies study insights extracted from collected data and use it to decipher customer behavior; that is, their practices, preferences, habits, needs, wants and more. The company can then leverage this data to offer personalized product recommendations, such as insurance premiums, saving plans, travel destinations, etc.

For example, an insurance company can have users install apps on their phones that collect data on distance traveled, car speed, etc., and optimize their car’s premium based on driving behavior.

Timely Improvement of Products and Customer Services

IoB also makes studying how customers interact with specific services or products easy. This saves companies from time-consuming surveys that are used to determine consumer preferences. The collected data is analyzed to identify pain points and issues of concern. The company can then address the issues before they become significant problems, such as by improving on products and services. This is an excellent way to build trust and confidence in a brand, leading to customer retention.

Behavioral Retargeting

Since companies can access customer preferences, recent activities, likes, dislikes, and location data, they can send real-time notifications to customers about discounts and new offers in stores nearby. They also can track loyal customers and offer them rewards. This kind of retargeting will make customers feel like a business values them and caters to their interests.

Develop a Tailored Marketing Strategy

Insights from IoB data can help tailor marketing strategies to individual customers. For instance, a retail store can offer products or services based on the mood, age or gender of a customer; thereby providing a satisfying experience that will lead to a stronger emotional connection with the brand.

Key Challenges that must be Addressed for the Success of IoB

Despite the opportunities IoB offers, companies must be aware of some key challenges to fully realize its benefits.

• Privacy Concerns – Although personalization will make consumer lives easier, there is a concern about privacy. Companies must implement strong cybersecurity policies and measures to ensure that customer information is used only for that which a customer has given consent.
• Convincing Users to Share Personal Data – People might not be comfortable sharing their personal data.
• Laws and Regulations – Strict regulations around collecting and using personal data, such as the General Data Protection Regulation (GDPR), require companies to comply in order to avoid fines and legal issues.
• Cybersecurity – As reliance on technology rises, so do cyberattacks. Cybercriminals may access sensitive data on consumer behavior, making consumers susceptible to online scamming and identity theft, among other threats.

Conclusion

Leveraging IoB can provide businesses with a competitive edge and drive revenue growth. Companies seeking continuous success should consider placing IoB at the center of business innovation to create personalized customer experiences. At the same time, they must also examine any challenges that might reduce the effectiveness of IoB.

Natural language processing (NLP) is a technology that allows computers to understand and process human language. Processing of natural language is necessary when you want an intelligent device to follow your instructions. NPL is an artificial intelligence (AI) component with many real-life applications.

As technology advances, business leaders have to figure out how to tap into the new trends to remain relevant, stay ahead of competition, and meet consumer expectations and needs.

How NLP Works in Brief

NLP involves making computers perform tasks with the natural language humans use. The input and output can be spoken or written text. NLP combines computational linguistics – rule-based modeling of human language – with statistical, machine learning, and deep learning models.

NLP aims to build machines that understand and react to text or voice data and then respond with text or speech in a similar manner as humans do. Examples of NLP in real life include voice-operated GPS systems, personal assistant apps, speech-to-text dictation software, and customer service chatbots.

As businesses seek better ways to improve efficiency, NLP is one technology promising huge rewards for enterprises dealing with vast quantities of unstructured text. In accounting, unstructured data include transaction descriptions, invoices, written communication, etc.

The use of NLP is growing significantly in enterprise solutions designed to help streamline business operations. Large companies such as Deloitte, Ernst & Young (EY), and PricewaterhouseCoopers (PwC) have implemented various NLP solutions. A good example is Deloitte, which incorporated NLP into its Audit Command Language to improve contract compliance.

How NLP Can Improve the Efficiency of Accounting Processes

Areas in which NLP helps improve efficiency include:

1. Forensic Investigations
   When CPAs want to perform forensic investigations, they have to deal with significant amounts of data from documents such as bank statements, transaction data tables, and data found in emails or deposition transcripts. Analyzing all the data as they try to look for specific patterns or gain insights is challenging. However, the application of NLP can be helpful in the investigative analysis process. NLP using algorithms can identify patterns automatically and reduce the time it would have taken to analyze the documents.
2. Accounting and Auditing
   Auditing is challenging due to the process of reviewing financial statements and ensuring they match regulations and legal standards. Auditors must have excellent analytical and decision-making skills to spot inaccuracies in financial statements. However, NLP helps to optimize the auditing process.
3. Financial Analysis and Automated Generation of Financial Reports
   NLP can automatically extract financial data from balance sheets, income statements, and cash flow statements. This can cut down on time and error-prone work. At the same time, it can obtain insights from massive financial data sets and financial reports. This enables accountants to make data-driven decisions and quickly identify trends and patterns in the data, hence, making it easy to provide guidance to clients on investments and household finances.
4. Automated Data Entry
   NLP can be used to extract data automatically from unstructured text documents, including bills and receipts. It also can be used to automate the entry of data from tax documents and input it into accounting systems. This can cut down on time and error-prone work.
5. Improve Centralized Data Management Solutions
   Incorporating NLP in accounting and procurement helps improve the ability of a centralized data management system to collect and integrate data from different sources. This enables standardization and collaboration. Additionally, the data provided has higher-quality insights. As a result, there is better financial planning and improved risk assessment and management.
6. Customer Interaction
   NLP can be used to enhance the effectiveness of customer interaction. This is done by automating the procedure for responding to client inquiries, such as concerning invoices, payments, and account balances.

Conclusion

Natural language processing is proving to be a powerful technology that can help improve the efficiency and effectiveness of accounting processes. As it continues to evolve, it will likely become an increasingly important tool for accountants and other financial professionals. Most importantly, these advanced technologies take care of manually reviewing unstructured data. This helps businesses scale and – at the same time – reduce costs.

Technology advancement has brought about great digital transformation. Unfortunately, this has come with a global tech talent shortage. IT executives highlight the shortage as a huge barrier to the adoption of emerging technologies, as reported by this Gartner study.

It is estimated that the demand for tech talent will keep increasing, and this could result in an estimated 85 million global talent shortage by the year 2030. Therefore, companies need to rethink their approach to hiring and retention.

Reasons Behind the Tech Talent Shortage

It is worth trying to first understand what is causing the tech talent shortage. A few of the reasons that have led to the shortage include:

• Advances in technology – technology is advancing at high speed, requiring workers with skills to match the new technology. Unfortunately, the tech education system can’t keep up with the speed, hence a shortage of people with the required skills.
• The great resignation – this became a buzzword with work from home that came with the Covid pandemic; unfortunately, even after the pandemic, people are still leaving jobs. A survey by TalentLMS and Workable found 72 percent of employees working in tech are considering quitting their jobs or exploring other opportunities.
• High demand for tech talent – There has been an increase in the demand for tech workers in recent years as more businesses and industries turn to technology for daily operations. New technology creates new roles, such as data professionals, data security specialists, and software engineers, among others that are highly competitive.
• Challenges in training and development – some companies might not have the resources and time to invest in employee development.

Business Challenges of IT Talent Shortage

Businesses are feeling the effect of the tech talent shortage, especially when it comes to digital transformation. Emerging technologies such as robotic process automation (RPA), artificial intelligence, blockchain, and augmented reality that promise to keep a business ahead of its competition require skilled workers.

Hiring new talent or reskilling employees also comes at a cost, and companies struggle to fill positions. On the other hand, failing to have skilled employees results in unrealized annual revenues.

As a result, businesses of all sizes find themselves failing to develop projects on time and hence fail to meet deadlines. In other cases, the existing employees end up overburdened with too much work, and this may lead to them quitting. Eventually, a business experiences slow innovation and slow growth.

How to Handle the Tech Talent Shortage

A few strategies to help address this issue include:

• Investing in employee development and training
  Providing ongoing training and development opportunities for current employees can help them acquire new skills and knowledge. This will not only make them more valuable to your organization, but also less likely to leave.

• Attract top talent through a strong employer brand
  Building a strong employer brand can help in attracting top talent to your organization. This can involve highlighting your company’s culture, values and mission, as well as offering competitive compensation and benefits packages. A good reputation will also help attract new talent.

• Partnering with educational institutions
  A company may also partner with local colleges and universities to gain access to a pool of talented students who are looking for internships or entry-level positions. Additionally, setting up mentorship or internship programs helps build a pipeline of talent for your organization.

• Increase recruitment efforts
  Sometimes it might be difficult to find the right talent, which makes it necessary to increase recruitment efforts. This could involve working with recruitment agencies, posting job openings on job boards and social media platforms, and attending job fairs and industry events.

• Consider hiring remote workers
  Even with all efforts in place, it may still be difficult to find the right talent in a business location. Today, technology has enabled people to work remotely. This offers access to a larger pool of candidates and also can help attract top talent from other parts of the country or even the world. It is also possible to work with freelancers or contractors to fill specific skills gaps on a project-by-project basis.

• Enhance the recruitment process
  An inefficient recruitment process will cost the company good talent. Therefore, any poor communication or delayed communication will affect talent acquisition. A company might need to streamline its recruitment process.

Final Thoughts

The global tech talent shortage is already negatively affecting businesses. Since the shortage is expected to rise, business leaders need to decide on the best way forward so they are not left behind in digital transformation. A good decision should fit business goals whether choosing to hire internal talent, remote workers, or outsource technology needs.