In the last few years, the world of informatics has been focusing on a specific concept: the importance of data. We often hear suggestions that data is humans' most valuable asset, and with growing data and the quality of data retained, how artificial intelligence (AI) can work wonders in analytical systems is something to think about. Experts give us a road map of data, and companies follow these recommendations. But perhaps these institutions need to take a step back before they go too far and make sure they set up the initial requirements correctly. Why?
The year 2020 will be one of the hybrid cloud in the field of corporate software. According to IBM, the value of the hybrid cloud market is $1 trillion. The cloud is no longer a type of storage where only individual users send photos and documents they want to keep, reflecting their most precious memories. At this point in the software extension of Industry 4.0, software and AI companies now want corporations to protect their data, and they want companies to create their own AI architecture by offering open source technology.
In other words, for software companies to invest in the hybrid, they must hold data of corporations as well as individuals, use it correctly and thus add value to the data itself. In 2020, software companies will encourage organizations to embark on a hybrid cloud attack. Figures show that only 15% of data appears globally, while 85% remains idle and is not suitable for use in business. In the simplest terms, institutions cannot derive income from the data they have accumulated.
A lot of progress in a year
While many companies are halfway through the data-cloud-AI level in the global sense, how should the world and Turkey progress "in the second part?" How should they convert their data to value? We discussed this issue with IBM vice president for Artificial Intelligence and Global Sales, Alyse Daghelian, who delivered a speech titled "Journey to Artificial Intelligence" at the IBM Think Summit in Istanbul on Dec. 4.
Recalling that AI is a technology that has been on the agenda since the 1980s and that more AI applications have evolved with increasing computational power, Daghelian said that in recent decades, the accumulation of data in institutions has led to the interpretation of data.
"The real value created by consumers lies in how we make sense of this data. As this data becomes meaningful, new applications are constantly emerging where we can use these meanings. At this point, both new areas of use emerge, and AI provides better predictions for these uses," Daghelian said. "The best example is health care. As the areas of use develop, better patient care emerges. Or just take a look at customer services. Better customer service is now available. Look at production, there are new applications that can make millions of dollars. AI makes sense of this data and leads to new applications in new fields. If we look at the applications of AI in the field of production and business, we see that it remains as single-digit figures. But it is moving very fast. Even in 12 months, great progress is being made. A year later, as our customers build better data infrastructure, we will see more and more AI applications in large areas. And companies will begin to take advantage of these practices and rapidly increase their success."
Daghelian said that Anadolu Sigorta, working with IBM, is a very good example in this regard. "Anadolu Sigorta used to receive 1,200 accident reports per day. They took a lot of time to reveal the difference between documents and facts and identify real accidents. With Watson's visual recognition solution, they experienced a 70% increase in customer returns," Daghelian continued. "Another example from Turkey is a media-entertainment company with 7 million members. They used Watson to train their customer service staff. They started with 200 scripts, now they have reached 2,000. When a customer asks about a service, they can respond much faster. This technology not only made it easier for members to access simple questions in their own way, but customer service officials began to answer more difficult questions. Thus, customer satisfaction increased."
Information architecture accelerates
Daghelian pointed out that AI cannot be used to its full efficiency unless accurate information architecture is created. "You cannot use AI unless you create information architecture. To use AI applications, you must first establish the data infrastructure and the framework of the system," Daghelian noted. "For this reason, companies that want to make the most of AI in Turkey or another country should rebuild this infrastructure, and some of them have. Because the right structure provides tremendous speed during the maturation process."
Arzu Sözen, IBM Turkey's software, cloud and cognitive country leader, stated that due to Turkey's demographic advantages it could process masses of data, led by the finance and insurance sectors. She added that these sectors were able to analyze the data very well, but this was just the beginning. "Companies in Turkey are quite aware of the importance of data and are building their databases well. They are currently in the process of building their data strategies, that is, in the process of scaling their experience."
Prepare for success stories from Turkey
According to IBM Institute of Business Value's report covering 98 countries and 20 industries, 21% of C-level participants (top decision-makers) in Turkey have achieved their goals, focusing on the data and creating their own data culture and infrastructure. Managers say they want to invest in machine learning and AI in two to three years.
"In a few years, we will hear a lot of success stories from Turkey because throughout this journey they will see many opportunities based on data, spearheaded by the finance sector," Daghelian said, evaluating this report. "Finance seems to be one of the best opportunities for investors, followed by insurance and health care. We are experiencing a transformation in Turkey at this point. In the coming years, we will see an increase in the number of institutions that use AI to analyze data.