According to an AI forecast for 2018-2025, the global artificial intelligence presence will grow at a CAGR of just over 55% to reach a market size of over 169 billion in 2025. Additionally, PWC predicts artificial intelligence (AI) to contribute over $15 trillion to the global economy by 2030.
Whether it is increased cybersecurity, self-driving cars, or facilitating sustainable initiatives, AI has helped bring a positive change into the lives of individuals and businesses. Over the past few years, especially in 2018, there was a lot of buzz around artificial intelligence (AI). We don’t expect the hype to die anytime soon. When the AI hype does finally die down, it will be a time when the technology is an inherent part of our lives like electricity, internet etc. However, before that happens, you can expect a lot of breakthrough innovations and developments to occur in the AI sphere.
Today, it is almost impossible to escape the AI buzz that has slowly but surely become part of the popular culture all around the globe. We’re not just talking about Alexa or AI assistants. Instead, we’re referring to everything that is currently being transformed by AI from the political landscape to jobs creation to the shift in consumer behavior and more.
2018 was a year where artificial intelligence (AI) took the spotlight. We expect 2019 to continue this trend. In fact, we expect developments to take place in AI this year that will change our use of the technology forever. Following are the top 8 AI predictions for 2019 that are making the rounds today.
With the big tech companies like Google, Amazon, and Microsoft leading the way, 2018 was another year where we saw progression in the MLaaS field. In 2018, we saw an increase in the demand for prebuilt ML solutions and capabilities. The biggest demand for these solutions came from smaller businesses that lacked the necessary resources or talent in-house.
Packaged solutions that can be easily implemented by novices or non-technical people, MLaaS open tremendous possibilities for businesses and organizations that need AI services. Today, cloud-computing providers such as Amazon, Microsoft, and Google provide MLaaS on a usage or subscription basis. An example of this is the ML studio of Microsoft Azure that allows developers to create solid machine learning models using a drag-and-drop environment.
Similarly, developers can build sizeable, sophisticated algorithms for several applications by using the Machine Learning Engine of Google Cloud. With the launch of SageMaker, Amazon also entered the MLaaS market in 2017. Like Azure’s ML studio and Google Cloud’s machine learning engine, SageMaker also helps developers to develop, train and implement customized ML models. With the tremendous increase in its popularity in the past couple of years, MLaaS is expected to become widespread in 2019 and beyond. According to Transparency Market Research, the MLaaS market will grow at a CAGR of 40% to reach US$20 billion by 2025.
Most of the innovations and developments in AI and ML have come from big tech companies such as Google, Amazon, Facebook, Netflix, Apple etc. While the world focuses on the AI and ML developments and innovations of the big tech companies, many non-tech enterprises have quietly created their own AI strategies. This strategies focus on resolving real-world problems that have an impact on the business environment.
The purpose of the AI strategy is to focus on proven initiatives and conduct pilot projects before deploying an AI solution. For example, a retailer will look to test an AI-based customer engagement model before deploying it in the market for increased omnichannel presence and sales conversions.
To use their data to unlock new streams of revenue, more and more non-tech companies will implement solutions based on digitization and AI. Provided it is data and AI savvy, any company can reinvent itself by developing large transaction and customer activity databases that are enabled by AI.
An example of this would be a telecom company building models that correctly predict the timing of a customer’s smartphone purchase. Furthermore, the company can enable a transaction and generate revenue for itself by partnering with a manufacturer of smartphones to provide an incentive to customers that are highly customized. Also, as AI makes more inroads, more and more companies will start to consider AI as an investment that can potentially transform their people, culture, and processes. This will be a widespread trend in 2019 and beyond.
In 2018, we saw several global powers ‘build walls’ to protect their national interest in relation to defense and trade. This was most apparent in the relationship between China and the United States, the world leaders in artificial intelligence (AI).
Recently, the U.S Government imposed export restrictions and tariffs on the goods and services used to develop AI. This has propelled China to increase efforts to become self-reliant in research and development (R &D). An example of this is the announcement of Huawei, a Chinese information and communications technology (ICT) company, to develop AI processing chips. With these chips, China expects to lower its dependency on US manufacturers like Nvidia and Intel.
At the other end of the spectrum, Google is facing increased criticism within the United States for its willingness to enter into business agreements with tech companies based in China. Additionally, the company is facing intense scrutiny for withdrawing from its arrangement with the US government to develop AI solutions. The company is refusing to work any further with the U.S government because it has concerns that its tech could be used for military purposes.
So, how we expect AI to impact the global political landscape in 2019? It will play a bigger role in the relationship between the US and China and other global powers that are investing in the technology. In 2019, early AI adopters such as China and the United States will find it difficult to find a balance between their national interest and collaborating in R&D.
The tremendous growth in fields such as predictive analytics will be experienced by nations with ML capabilities and AI talent. This will create a wider technology gap. Also, there will be an increased emphasis on AI’s ethical use. Since the topic will be approached differently by different countries, it may lead to political conflict. However, the impact of this will be relatively small compared to other international issues. So, we don’t expect the issue of AI’s ethical use to be brought up too much in world conventions and forums.
There are several real-world examples that show how AI is transforming the world. However, it is still a challenge to explain the rationale behind the ML models enabling these AI solutions. AI is often said to be carrying the burden or problem of the ‘black box’. Humans are limited in their capacity to understand the logic behind the decision making that is supported by artificial intelligence (AI).
AI can realize its full potential only if it is trusted. This means that users must know what AI is doing with their data and how the decisions impacting our lives are made by it. However, this can be difficult to convey. Making AI systems trustworthy is not limited to reassuring the public. Openness which exposes data or algorithms bias will benefit research and business. One major reason companies shy away from implementing AI is the fear of having to face liabilities if the AI technology is adjudged to unethical or unfair at some point in the future.
In 2019, there will be an increased emphasis on initiatives that increase AI’s transparency. Recently, IBM unveiled a technology that helps make decisions more traceable. The technology provides greater insight into the decisions being made as well as into the process used for decision making. The technology does this by drawing connections between the data being used and looking for potential bias in the information.
Other open source tools enabling a more ‘transparent’ AI environment include PyTorch, TensorFlow, and Scikit Learn. These technologies and more will help people to understand the rationale behind AI models while enabling AI will expose bias in data sets. All this will lead to a more transparent AI in 2019 and beyond.
For long, people have feared that the introduction of AI-enabled machines into the mainstream will lead to widespread human unemployment and strife. However, Gartner has calmed these fears down to some degree by predicting that AI will create more jobs by the end of 2019 than it will take. According to the Gartner report, AI will cause 1.8 million jobs to be lost in manufacturing. However, the impact will be leveled out by the 2.3 billion that AI will create during the same period.
Contrary to popular belief, AI will not eliminate human labor in the future. Instead, it will require human assistance in making tasks less tedious and time-consuming. This will demand that human workers learn how to use and work alongside AI technology. However, the emergence of AI does paint a gloomy picture for workers in some industries. An example of this is the financial services industry where the human workforce is expected to decrease by 30% in the next few years. In this sector, we are likely to witness more and more banking functions being managed by AI-enabled machines in 2019 and beyond.
AI is slowly but surely becoming an inherent part of our lives. We turn to AI-driven predictions to ensure a smooth experience when searching Google, watching Netflix, or shopping at Amazon. However, a more apparent engagement with the AI technology is our use of virtual assistants like Google Assistant, Alexa, or Siri. These AI assistants help us to complete a myriad of tasks at home and on the road which is adding to their popularity each day.
In 2019, we expect more and more people to use AI assistants for personal and business purposes. Over the next few years, AI’s ability to anticipate human behavior and understand their habits will get better. As a result, we will witness more pervasive and useful AI assistants which will increase the use of these virtual assistants further.
There will be a shift in consumers understanding of AI in 2019 as the use of AI-based devices and services increases and as we move further away from the AI hype that has gripped the world for some time now.
Currently, our daily interactions with AI are in the form of our conversations with the AI assistants like Alexa and thus we are quick to associate the AI technology with them. However, as our interaction and usage of AI increases, we will no longer associate the technology with these virtual assistants. Instead, we will define AI as intelligence and productivity tools that help with everyday tasks and make our lives better. This will also shape the decisions of consumers regarding the purchase of AI-based products and services.
In 2019, there will be an increased emphasis on greater AI transparency. As such, we will see more focus on the design of the technologies and processes that enable this transparency. The discussions and efforts regarding this will be driven by the General Data Protection Regulation (GDPR) and similar initiates.
As businesses turn to AI to automate and simplify processes and increase efficiency, they will willingly or unwillingly share their data with third parties. Often, this data could contain sensitive information about customers. Thus, privacy-enabled AI will soon be a legal requirement and not just an ethical practice and good risk management strategy. This will increase the demand for AI applications that meet the requirements of privacy-enabled AI technologies in 2019.
A watershed year for AI, 2019 is going to be the year when the technology finally moves away from the hype surrounding it and starts to become widely adopted in different industries, products, services, and processes.
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