After a decade of stop-and-go development, artificial intelligence has now begun to provide real, tangible value to the business world. An 80-page report titled "Artificial Intelligence: The next digital frontier?", which provides a comprehensive analysis of the value that artificial intelligence (AI) creates for businesses.
The report points out that "wide application of artificial intelligence technology will bring great returns to businesses." This means that the disruptive nature of AI will continue to become more apparent in the future. Governments, enterprises, and developers should all be clear on this point. Moreover, the report raises some interesting points (all of which we will discuss later in this article):
Currently, researchers and businesses are focusing on artificial intelligence systems such as robotics and automated transportation, virtual agents, and machine learning (including deep learning and the foundations of several recent advancements in AI technologies). Investments in AI are growing by the day, led by a host of familiar digital giants.
Lately, there has been a lot of talk about the potential and dangers of AI. However, AI is far from a new concept. It has experienced ups and downs throughout history, both expectations and disappointments. Will things be different this time? The answer as per the new analysis is "yes": artificial intelligence has finally begun to deliver real business benefits. The conditions for a breakthrough are already in place.
Computing capabilities have grown considerably, algorithms have become more refined, and more importantly, a large amount of data has been generated globally, and data, as we know, is the fuel for artificial intelligence. At present, most industry news comes from providers of artificial intelligence technology. Many new use cases are still in the experimental stage. The products on the market are limited, or there are fewer products that businesses can apply instantly and universally. As a result, analysts' have two distinct opinions: some are optimistic about the potential of artificial intelligence, and some are still very cautious about their economic benefits. This inconsistent concept leads to huge differences in the size of the market.
Driven by technology giants, investment in AI is increasing, but commercial applications are still falling behind.
Technology giants are investing billions of dollars in AI. They see the future direction of AI technology - robust computer hardware, increasingly complex algorithmic models, and vast amounts of data - all of which have already been realized in part. In fact, the internal investment of large companies occupies a major position in the field of artificial intelligence.
Though AI has developed rapidly in the recent years, the subsequent adoption is still in its infancy. This makes it challenging to assess the potential impact of artificial intelligence on companies and industries. What happened to the companies that have already invested in AI? There is early evidence of large-scale adoption of AI bringing lucrative returns.
It reviewed a large number of case studies in five industries to study how AI can transform some business activities and bring potential fundamental changes to other businesses. These cases demonstrate how AI is shaping different functions across the entire value chain and different industries. These cases also have a wide range of impact on stakeholders, such as multinational corporations, start-ups, governments, and community organizations.
The study includes five case studies to provide an understanding of the wide-scale application of AI in the commercial field. These case studies show how AI influences specific behaviors through multiple forms. The study covers retail, electricity, manufacturing, healthcare, and education industries. Types of companies include private, public, and social enterprises, including heavy asset operations from labor-intensive industries to B2B.
If it is to meet expectations, artificial intelligence needs to play an actual role in the field of economics to significantly reduce costs, increase profits, and increase asset utilization. The study includes a classification of the ways in which AI can create value in four areas:
The creation of value in these four fields depends on specific use cases. Many organizations have already discovered or deployed solutions around these use cases (we have listed these AI use cases at the end of this article). Similarly, these use cases have different relevance from industry to industry, meaning that there are numerous opportunities to use artificial intelligence in the planning and production layers.
Additionally, when machine learning can bring valuable benefits to all industries, some particular technologies may have unique commercial application in specific sectors. For example, robotics in sales and manufacturing, computer vision in the medical industry, and natural language processing in the education industry.
It is time for enterprises, developers, and governments to recognize the true potential of AI. Although artificial intelligence has the potential to reshape society as a whole fundamentally, we are still unsure how the technology will develop. For enterprises, governments and workers, this uncertainty means that we have to "wait and see." However, we still consider it necessary to take positive and clear actions to make the most of the emerging opportunities while tackling risks.
For many businesses, this means that they need to accelerate the digitization process and ensure that they deploy AI tools efficiently. Because AI integrates large amounts of high-quality data into automated workflows, the influence of that data is also growing. AI is not a shortcut to the foundation of digitization; rather it is a powerful extension of that digital foundation.
Developers play a crucial role in helping companies realize the potential of technology. The problem that developers need to consider is that AI products need to solve practical business problems. Instead of developing interesting solutions, they have to solve real-world problems on a large scale.
The governments and workers need to prepare for the transformational changes that AI can bring in the future. There is a need to rethink the public education system and employee training problems to ensure that the skills that employees have are complementary to machines, rather than competing with them. Furthermore, regions or countries wishing to establish a local AI ecosystem must join the global competition for AI talents and investment.
The unresolved legal and ethical issues for the society as a whole are likely the most significant obstacles to realizing the true benefits of AI.
Use cases/Sources of value
Technology and tools
Regarding career distribution, there are only a few occupations that automation will completely replace. Analysts claim that in 60% of the occupations, automation will be possible for only 30% of the work. From a geographical perspective, America and China are leading the world in AI, and Europe is, unfortunately, lagging behind.
The rise of artificial intelligence poses a wide range of issues to government and society. Our progress on solving these issues is critical to realizing the potential benefits and avoiding the risks of artificial intelligence.
Current AI applications are concentrated to industries that are already at the forefront of new technologies. Extending the application scope of AI to support new technological fields, especially for smaller companies, is essential to ensure the growth of productivity and economic development, and can ensure a healthy and competitive market. The application of AI across industries can also help in balancing the wage levels of different industries. AI can increase productivity and thereby increase wages. Instead of restricting AI to frontier companies and employees who are already at the top of the income pyramid, a wider scope of application will push the benefits of AI to more companies and their employees.
The AI-driven automation revolution will deeply affect the work and wages of people everywhere. An overwhelming majority of companies stated that they didn't believe that AI poses any threat to employment. However, it is clear that some skills in some occupations will fail to meet the requirements of the future. The government may have to rethink the model by which they provide social services. Of course, there will be several different approaches to solving these issues, including adjustments to the sharing of labor, negative income tax, and global basic income levels.
AI raises a series of ethical, legal and regulatory issues. For instance, there is a common real-world risk of prejudice seeping into training datasets. Due to racial, gender, and other prejudices, the real-world data that machine learning algorithms thrive on is also unavoidably full of discriminatory features. Eventually, this can affect AI systems as they are at risk of developing these biases in the training process.
These issues become even more intense as the prejudices become more internalized. At the same time, the public may be skeptical of these algorithms themselves. Since the ethical opinions of the programmers may be coded into the algorithm, which parts of the algorithm do people have a right to know about? Who is responsible for what the AI outputs? This has led to calls for algorithmic transparency and accountability.
Another issue is that of privacy. Who owns the data? What measures do we need to take to protect highly sensitive data (like medical data) without harming data availability? Organizations and institutions that are working to address these issues include Partnership on AI, OpenAI, Foundation for Responsible Robotics, and the Artificial Intelligence Ethics and Governance Foundation.
A large amount of data is crucial to training an artificial intelligence system. Opening up public-sector data can stimulate private-sector innovation, and setting up common data standards can also be quite helpful. In the United States, the Securities and Exchange Commission forced all listed companies to disclose their financial statements in XBRL (Extensible Business Reporting Language) format in 2009 to ensure that the public data is machine readable.
Artificial intelligence has great potential for the public sector. Its ability to enhance planning, goal setting, and personalization of services, makes it essential to increasing the quality and efficiency of government services. In the appendix to the report, the report explores the future of AI technology in two major public areas - medical and education.
The report details five specific use cases in the appendix section. There is a visual description of three of these use cases. We have summarized these AI use cases in the section below:
We have discussed how AI is solving real-world business problems and is gaining traction as a ubiquitous technology for businesses of all sizes and scale. The need of the hour is to recognize AI's unique value proposition, make it an integral part of business strategy, and realize its transformational benefits.
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