The future of AI will involve a high level of automation for low-value tasks that currently take up much of our time. Artificial intelligence will help realize ideas such as human-robot collaboration and autonomous cars, and it will help computers not only understand human speech and gestures, but also our emotions.

The true power and rapid momentum of artificial intelligence (AI) in recent years have best been demonstrated in use cases such as IBM’s Watson and Google’s AlphaGo. In both of them, AI managed to beat the human contenders in Jeopardy and Go. The capability of AI to beat humans at social games may seem fruitless and insignificant, but it demonstrates the exceptional sophistication of AI, and its ability to imitate and outperform humans in solving highly complex tasks.

Artificial intelligence can be defined as intelligent computer systems with the ability to think and learn (in a way that resembles humans). An AI technology stack consists of various tools, techniques, and algorithms. AI applications range from neural networks to genetic algorithms, from pattern and speech recognition to machine and deep learning.

Current and past achievements point to a very exciting future for artificial intelligence technology. Read on to find out more about risks, challenges, applications, global economic impacts, AI industries, top jobs involving artificial intelligence, and how the technology will change the future of many fields.

History of artificial intelligence

Real-world applications of AI such as autonomous cars, personal assistants (smart speakers), intelligent robots, and cognitive automation are all possible thanks to AI’s ability to correctly interpret environmental data and learn from it to perform specific tasks such as pattern recognition or anomaly detection.

For over 50 years developments in AI were slow, and it remained mainly an academic discipline. Recently, due to the high availability of data (Big Data) and improvements in computation power, AI has gained momentum and revolutionized many business areas and industries.

The slow progress of AI was caused by the initial focus of research efforts on replicating human intelligence. So-called expert systems operated with collections of rules that attempted to formalize and reconstruct the human way of thinking. Despite many advantages, such systems perform poorly in applications with high impact such as image recognition.

Modern AI systems, on the other hand, are based on neural networks and deep learning. They are versatile and achieve superior performance in many tasks. AI has successfully become an indispensable part of our lives and caused a significant global economic leap forward.

The global economic impact of artificial intelligence

A robotic arm holding the Earth next to an AI icon

In 2015 only one in ten companies used AI technology. In 2019 that number quickly rose to one in three. At that time it was obvious that AI was a game-changer technology with huge potential to impact on the global economy in an unprecedented way. A recent study published by McKinsey Global Institute predicts that two out of three companies will use at least one type of AI technology by 2030.

The economic contribution of AI by 2030 is expected to hit $15.7 trillion. The sheer scale of this figure is best understood by realizing that it will result in a cumulative global GDP that is 16% higher than today.

Geographically speaking, the largest economic influence will be observed in China with around a 26% boost in GDP followed by North America with 14.5%. These two make up about 70% of the global economic impact.

Among different industries, the automotive industry will be one of the most driven by artificial intelligence. The autonomous vehicles market, which is completely driven by AI, is expected to be worth a staggering $3.2 trillion by 2030.

The future of AI will be driven by applications utilizing computer vision, natural language processing, virtual assistants, robotic process automation, and advanced machine learning. As you are reading this, at least one of these fields has already changed the way you live, work, travel, or shop.

Benefits of artificial intelligence

Most of the benefits of AI are related to increased efficiency of work performed by people, providing augmented decision making, better design of products and services. Let’s find out how it’s all achieved in an actual business setup.

Business efficiency

AI employs data analytics to better utilize resources across an organization. It can facilitate great cost savings and better time utilization by automating complex operational processes for people and minimizing machine downtime.

Data-driven decision-making

Artificial intelligence makes use of data to augment human intelligence. Based on this data, AI is capable of producing advanced analytics, predicting patterns that ultimately improve our decision-making capabilities and drive creative solutions. The future of artificial intelligence depends on the quality and density of the data we feed into our systems.

Intelligent products and services

Using data, AI-empowered software is capable of finding gaps and opportunities in markets more quickly and effectively. This capability will allow companies to make products and services that better fit the market. Furthermore, embedding AI into those products will ultimately make them more intelligent.

Increased employee productivity

By simplifying the decision-making process and automating many time-consuming tasks, AI increases employee productivity. With the additional support of such software, humans can focus on more demanding and relevant tasks that eventually generate more value and increase profits.

Better customer service

Advanced machine learning as a category of AI produces a continuous stream of insights about customers that allow for better personalization of products and services. On the other hand, AI-powered chatbots are capable of servicing customers 24 hours a day in real-time, increasing overall customer satisfaction.

Risks of incorporating artificial intelligence

People examining AI incorporating potential

Alongside many benefits, integrating AI technology into workflows does bring some risks and comes with certain challenges. These risks relate to trust, the ethics of AI-driven decisions, data privacy, and the transparency of AI-delivered outcomes.

Trust

Ultimately, AI does not and cannot have human moral values and that fact feeds our distrust in these systems. For example, despite the high level of accuracy in AI-generated medical diagnosis, we still have doctors in the loop to verify the results, making sure they are trustworthy. Having them present the results to patients is also the common practice as humans can provide empathy and walk the person through the best options for treatment.

Ethics

AI presents huge ethical concerns in three areas. Due to the need to collect large amounts of data, there are many concerns about the possibility of privacy obstructions and surveillance. AI-driven results are often influenced by biased data, which may lead to discrimination.

Artificial intelligence lacks human judgment capabilities and its conclusions and results are based only on the logical relationship between inputs and outputs found in the training data. Lack of judgment may lead to decisions that can impede the integrity of human life, and once this happens, who do we deem responsible?

Data privacy and security

Data privacy and security are the largest limiting factors to the full adoption of AI in applications such as government, healthcare, and consumer devices. In an era where cyber-attacks cost businesses billions in litigation and remediation, AI-related privacy concerns must be the first to check off the to-do list when building your smart digital solution.

Algorithm transparency

As AI technology is adopted in fields where humans were traditionally making decisions, the explainability of AI algorithms and transparency of their operation is becoming increasingly important. Nowadays, many AI methods act as a “black box” and there is no clarity into how they produce their results. Although those results are very accurate, we will need to invest much more effort into increasing their explainability.

Despite the risks associated with AI today, in the future, continuing technological developments in the field will lead to their minimization, and eventually their complete mitigation. Many of these challenges can be already avoided by partnering with an experienced team of machine learning and development experts who can suggest the best roadmap and tools for whatever AI project you have in mind. Ultimately, the promising benefits offered by artificial intelligence in the future will far outweigh the challenges and risks of today.

Industries that make use of AI

AI influences many industries and is predicted to gain even more exposure In the future by establishing its presence in consumer electronics, manufacturing, healthcare, transportation, agriculture, and other business verticals.

Consumer electronics

In consumer electronics, AI technology is opening up a new era of user experience. Automating our everyday routine tasks, it will allow us to focus on doing creative work. Ultimately, consumer products will be based on the blending of human and artificial intelligence.

Early signs of what’s possible are demonstrated through efforts such as Neuralink, an AI device that is embedded in the human brain and ensures that AI and the human brain learn and develop together. While today it is marketed as a medical device for treating mental disorders, devices like this will become the future of artificial intelligence and consumer electronics.

Manufacturing

According to a recent study by Microsoft, companies that use AI in manufacturing perform by nearly 12% better than competitors. The AI adoption curve in manufacturing is trending steeply upwards. According to McKinsey, half of the manufacturing companies that invest in AI will double their cash flow over the next 5-7 years.

Artificial intelligence future applications in manufacturing are not only lucrative but also technologically very exciting. The next age in manufacturing is human-robot collaboration. With embedded AI, robots will become intelligent and capable of working with humans side by side to augment human capabilities.

Regarding AI robotics and the future of jobs, humans and robots will be engaged in collaboration rather than competition. Next to human-robot collaboration, AI-driven smart manufacturing will become an industry standard, while predictive maintenance will make sure that the wheels of the industry keep turning smoothly.

Healthcare

Healthcare has always been an industry at the forefront of AI innovation. AI in healthcare promises to improve doctors’ productivity and quality of care, enhance patient engagement, accelerate and reduce the costs of discovering new medicine, and personalize medical treatments.

The future applications of artificial intelligence in healthcare will dominate two areas: providing a better patient journey, and delivering care in new ways. AI techniques such as language processing and machine learning will be employed across the entire patient journey extending to their activities and lifestyle outside of the healthcare institutions. AI-powered wearable devices and implantable biosensors will help develop a better understanding of the causes of poor health conditions.

Transportation

The most important role of AI in the future of transportation will be in providing new and intelligent algorithms for better autonomous vehicles. Next to the developments in self-driving cars, AI will improve traffic management systems. As well as improvements in the software of transportation systems, AI will play a crucial role in replacing inefficient static hardware systems with new and improved systems capable of sensing and capturing data from the environment. Governments around the world will shift towards the utilization of AI-augmented advanced hardware that will allow for better traffic prediction, vehicle identification and toll collection.

Agriculture

By 2050 the global population will have increased by 2 billion. This will in turn increase food demand by 50% of today’s production. The essential role of AI in the future of agriculture is to help us overcome the challenge of increasing food production while preserving the health of our planet. Future uses of AI in agriculture will include smart crop yield prediction, sensor-aided intelligent fertilization and pest removal, predictive insights and price forecasts that will enhance the food supply chain, advanced crop disease diagnosis, and agriculture robots.

Cybersecurity and IT

Even though AI applications in cybersecurity are relatively new they are quickly being adopted. Machine learning offers new ways to detect sophisticated cyberattacks and breaches. New generations of malware and cyberattacks are ever more advanced and very difficult to identify using traditional cybersecurity procedures.

As cyberattacks develop over time, AI can provide tools for more vigorous approaches to security. Machine learning can use data from previous attacks to respond to new ones. So, it’s evident that in the future AI will be an integral part of all cybersecurity systems.

Education

AI empowers educators with advanced tools and technologies to meet the growing needs of students and the rising demand for personalized education. AI is already a great part of the modern digital educational system. New systems will continue to be included in the teaching and learning process, helping instructors perform mundane tasks and adjusting lesson plans to aid struggling students. Students can be presented with helpful hints and suggestions for improvement, and personal assistants guiding them in solving intricate problems, identifying their knowledge gaps, and letting teachers.

Energy

The future of energy is the smart grid powered by neural networks and machine learning. With the help of IoT sensors and cloud computing technologies, smart applications will be able to manage supply-demand interplay in future energy distribution systems.

As more and more data is continuously collected, AI will help transform it into actionable insights and suggest timely decisions on how best to allocate available energy resources. Advances in machine learning algorithms will allow the energy systems of the future to spot patterns and anomalies in large data sets, and balance out the supply and demand of the energy economy.

Top future AI applications

A person do the jigsaw puzzle on the robotic arm background

Apart from the industry-wide impact of AI, some critical applications will become essential in the future. The most foreseeable future uses of AI will be in applications such as human resources, synchronized translation, road safety, surgery, emotion analysis, and cognitive automation.

Revolutionized human resources and recruiting

With the help of AI, companies can increase their efficiency by automating repetitive tasks. In human resource companies and departments, these intelligent apps can not just pick the right candidate to interview, but also make sure that current employees are properly motivated and kept busy with challenging assignments.

Finding the right candidate for the position can be a laborious task. HR departments nowadays use AI to help them screen candidates from CVs and job hunting websites, and narrow down their search to several candidates that are most likely suited for the position.

As it involves the collection of large amounts of data and learning from it, AI systems are bound to become more and more efficient at this task in the near future. Relieved from routine everyday burdens, HR managers will be able to spend more time interviewing the most suitable candidates.

In addition to this, with constant developments in natural language processing and machine learning, AI will allow HR chatbots to get better at understanding employees’ well-being and will be able to give better answers to their questions just like a human HR manager would.

Removed language barriers

With over 6500 spoken languages in the world, language can be a real barrier to global trade and also has the potential to profoundly shape our economy. Artificial intelligence empowered language translation is one of the most successful applications of machine learning.

The reason behind this success is the structure of the language. Language is based on a structured set of rules. Variations of these rules make it difficult for humans to interpret but easy for AI. Machine learning leverages repetition, pattern recognition, and large databases to translate better and faster than humans.

In the future, AI will continue to remove language barriers and connect even more communities with the global marketplace. With developments such as Neural Machine Translation (NMT), AI will continue to get better at language translation.

Improved road safety

Road safety has been an area of constant improvement in both the automotive industry – relating to systems inside the vehicle – and public and private transportation and road infrastructure organizations.

In the future, automated traffic solutions will become reality. Currently, advanced driver assistance systems and autonomous driving are the most noteworthy solutions. The maturity of these systems is still low. It is expected that these solutions will mature with further developments in image processing and advances in object recognition.

Together with advances in sensor fusion, we will be able to obtain a holistic understanding of the behavior of traffic participants, and AI will help vehicles calculate the best possible action in a given situation.

Emotion AI

Emotion AI is an emerging application of AI that gives machines the ability to understand human emotions. Emotion AI is capable of understanding not only the cognitive but also the emotional channels of human communication. Compared to traditional artificial intelligence solutions, it can offer higher value in many commercial applications.

Though still in its infancy, emotion AI will soon be able to detect and interpret human emotions from sources such as text, via natural language processing and sentiment analysis, audio, via speech recognition, and video, utilizing facial movement analysis, gait analysis, and physiological signals.

Cognitive robotic process automation

Artificial intelligence and automation technologies are transforming companies and industries and contribute to the economy through the increase of human productivity. AI systems like IBM’s Watson can learn from data and improve themselves over time. These systems are becoming very good even at knowledge-based tasks that were previously considered to be exclusively in human domains.

This trend will continue in the future as more and more cognitive tasks are automated using AI. The sophistication of these technologies is growing rapidly, and they will increasingly act as semi-autonomous decision-makers in an ever-widening variety of complex business and everyday situations.

Top AI jobs and the future of work

People predicting the future of work based on statistics

Many application areas and methods fall under the wide umbrella of AI. Such variability is opening up many opportunities for those looking to hone their professional skills in this department. Demand for artificial intelligence talent is on the rise and this will persist in the future. The top jobs will be in the areas of AI software design, implementation, testing, and application development. Let’s take a look at some of these jobs and their qualifications.

Data scientist

Data scientists gather, clean, process, and organize data for enterprises. Data scientists usually have a background in fields such as computer science, statistics, or mathematics. Their primary tasks include data analysis, processing, and modeling to create actionable insights.

Data scientists and business developers work closely together to analyze and understand business goals and how they can be achieved using data. They actively use AI techniques and methods to accomplish their tasks. This profession will be indispensable for any 21st-century enterprise.

Machine learning engineer

Machine learning engineers make use of their software engineering and data science skills to blend big data tools with various programming frameworks. Machine learning engineers often work side-by-side with data scientists to create pipelines that blend data from various sources and feed it into machine learning models.

While data scientists determine which machine learning approach to use, machine learning engineers make sure these models are properly implemented and can scale with the application infrastructure. The machine learning engineering profession is relatively new and is expected to be one of the most important AI professions of the future.

Computer vision engineer

Computer vision is an interdisciplinary field that deals with the development of methods and techniques that allow computers to obtain a high-level understanding of information from digital images and/or videos. Computer vision engineers work on the automation of computer software to imitate the human visual system.

These engineers mostly deal with automated extraction, processing, and understanding of useful information from images and videos. Computer vision engineering is highly demanded in many industries such as automotive, healthcare, and manufacturing. Professionals in the field will become critical members of the AI teams of the future.

AI-assisted healthcare practitioner

In the future doctors will rely on AI to do their jobs, in the same way that they rely on radiographic equipment or laboratory analysis today. Almost every aspect of a healthcare practitioner’s routine can be augmented with smart applications.

Artificial intelligence will be there to support practitioners’ skills and not to replace them. Nevertheless, using AI tools will require doctors to have a certain knowledge of the engineering behind them.

AI research scientist

AI research scientists primarily create new problem-solving methods and techniques through both theoretical design and experimentation. They are involved in planning, designing, and conducting experiments to investigate and analyze scientific phenomena in any of the application fields of artificial intelligence.

In the future, AI research scientists will be responsible for advancing the technology, creating better and more efficient models for machine perception, data mining, machine learning, and natural language understanding.

Deep learning engineer

Deep learning engineers are computer scientists specializing in the development of models that mimic the operation of neural networks inside human brains. Deep learning technology is at its infancy and the great promises of this technology are yet to be fulfilled. Deep learning engineers will carry this field forward in the future while making progress in areas such as self-driving vehicles, facial recognition software, and robotization.

Conclusion

In the past several decades, AI technologies have revolutionized many industries such as consumer electronics, manufacturing, healthcare, transportation, agriculture, IT, education, and energy. At the same time, it is creating new opportunities in human resources and recruiting, road safety, and the understanding of human emotions.

While AI is significantly increasing the efficiency of people and processes, it also creates demand for qualified personnel to handle operations. Data scientists, machine learning engineers, and deep learning engineers will be some of the most in-demand professions of the future.

AI solutions help businesses generate more profit and better serve their customers by creating new ways of extracting and analyzing preferences, behavior, and other complex unstructured data. Building AI-powered applications and their integration into business environments is a challenging process that involves performing a variety of tasks demanding technical expertise. Partnering with an experienced AI development company takes most burdens off your shoulders and lets you focus on the concepts of your project.

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