Many enterprises are now shifting from using regulated processes to work such as production and analytical testing, which in reality have little opportunity for radical changes, to a more free and open structure of algorithmic solutions. In practice, AI is able to replace well structured processes, greatly increasing efficiency and reducing costs and resource requirements. In turn, extending the scope of application, such as IoT and its related intelligent technologies, which can really provide an efficient business, will allow enterprises that fully support the changes and even seek local scaling to achieve significant success in the competition. On the whole, 2019 year will be a turning point for AI when technology is gradually coming out of the cycle of agios and will become widely used in all types of business, regardless of third-party investment.
Thrills and nuances
Experts believe that, given the latest trends, many non-technical companies that have created their "artificial intelligence strategy" will now focus on addressing real issues that have affected their business performance. After spending the past few years on digitization efforts, companies will move forward with more proven initiatives and pilot training to bring their data into order and identify areas where AI could bring its fruits. And only then - to launch the AI for global deployment step by step and "softly".
In this scenario, for example, a retailer will focus on building the very model of AI, which focuses, above all, on direct or indirect customer interaction - to maximize the presence of all channels and switch to more efficient sales. The advantage is that the relevant forecasting systems indicate, first of all, the influx or vice versa of the outflow of consumers, and therefore helps businesses get early warning signals that they need to change or improve their approaches to promoting a product or service at a certain stage.
Obviously, taking advantage of digitization and artificial intelligence, businesses will begin to use their data to generate new revenue streams. Creating large transaction and client databases and affiliate relationships with related industries can, in effect, allow any business that is well versed in data and artificial intelligence to actually redesign the structure and its former techniques from scratch.
Consequently, according to analysts, as companies expect the real impact of business on investment in technology and staff, we will see shifting the focus from the "AI strategy" to the pursuit of accelerated qualitative "managed AI" results. Technology as such will be less important - the very fact of its implementation will matter, because it is the key to understanding the underlying of any business and becomes its basic tool in achieving the set goals. On the other hand, as AI develops, businesses will begin to realize that artificial intelligence is in itself a key investment for transforming business processes and corporate culture, and not just a magic lever that can be used to instantly eliminate inefficiencies.
Change in consumer perception
As the AI goes beyond affordable luxury and becomes a prerequisite for the competitiveness and development of all forms of business, as well as the growing use of AI-based devices and services, requirements for it are also rising directly by consumers.
Initially, the daily interaction with AI did not go beyond the rather primitive communication with digital assistants - chat bots. However, increasing the number of such interactions has led to accelerated technology development to the level of opportunity to address strategic issues. It is beneficial not only to business but also to customers, and therefore the need for contact with innovations becomes urgent for many users. People no longer associate AI technology with robotics, voice consultants and stand-alone vehicles that never break. People associate them with productivity tools and predictions that help them accomplish their everyday tasks and improve their lives. And in the 2019 year, the so-called practical AI will be directed, first of all, to the efficiency and quality of service. This includes, among other things, the possibility of making online purchases with the most convenient selection of goods according to individual preferences; to receive the most effective treatment and medical care in accordance with the absolutely accurate diagnosis; to unleash the potential and talents of students with the help of innovative methods in education in accordance with the real requirements for future qualified professionals in the labor market.
AI will become a good platform for the realization of common business interests
As more and more companies use AI to improve their products and services and begin to rely on data-based solutions, it takes time to develop new processes and structures for working with such an ecosystem. For example, the marketing department, before deploying global customer outflow prevention, would like the system of checks and balances to ensure that there is no "revenue leakage" or damage to customers. It's not easy when it comes to working with human data. And, since AI is still sometimes turning from an assistant to a "black box", there are some difficulties in achieving the goals.
However, one always needs to take into account one important factor - time. For a new AI ecosystem, it is critical to adapt to new processes and structures. Today, business is well aware of this and is well-equipped to use it. Experts believe that digital AIS-based ecosystems will grow, gradually turning into profitable platforms for various business interests. Using data platforms and sophisticated artificial intelligence technologies, companies will be able to multiply their efforts and implement global and carefully designed work patterns that will enhance brands and sales.
All this entails a number of risks associated with manipulation of data, however, all have long been aware that the launch of any AI system from the beginning should be taken "clean" hands of highly skilled professionals.
Confidentiality of data
As enterprises implement AI in their systems, processes and day-to-day activities, they need to be trusted to fully realize its potential. AI consumers are always first of all to know how cautious they are in dealing with confidential data, why and how they make decisions when it comes to issues that affect the resolution of many issues. From a technological point of view, it is often difficult to organize. What makes an AI useful is its ability to establish relationships and make conclusions that are not obvious, or may even be illogical for us. On the one hand, research and business benefit from openness, which does not require an examination of the objectivity of all processed data and algorithms used, on the other hand, they lose because it increases the risk of violating the protection of information from dangerous influences.
In the 2019 year, according to experts, these problems will face "foreheads", as one part of the developers and consumers of technologies will insist on maximum transparency of data, and the other - on their concealment for maximum confidentiality. In this situation, the general data protection regulation (GDPR), which was put into effect in Europe in 2018 year, will become relevant for many countries. The GDPR protects against decisions taken by machines that, in particular, have a legal or ethical pressure on the human factor. And, at the same time, the desire of large companies to combine their efforts by creating common open databases using AI, will make them sacrifice established measures and endanger many systems, because information will be removed from the castle and will be able to get into the hands of the third to people
Ensuring the confidentiality of data and, in turn, customer confidentiality will not only be a good business practice and risk management strategy, but will most likely become a mandatory legal requirement soon. Advanced artificial intelligence technologies will provide a basis for all applications and systems while maintaining strict confidentiality with the use of cryptography in 2019 year.
One of the most popular options today is the new technology of secure computing called homomorphic encryption. This method of secure computing is a special way of encrypting data, so that third-party users can collect valuable information using machine learning techniques, while data continues to be encrypted while maintaining the confidentiality of users. Based on homomorphic encryption and other innovative methods of secure computing, new technology startups will grow, providing even more personalized content and recommendations for consumers.