If you follow technology news, you must know that in the last few mohs it is almost impossible to find news about Generative artificial ielligence Or GhatGPT not published; Artificial ielligence has been all the rage in the last few mohs, and everyone was to take advaage of the technology’s poteial in some way.
Erepreneurs wa Artificial ielligence startup Make; Executive directors of companies wa to benefit from its capabilities in their business; Investors are also inclined to invest in this area. Advocates of the power of large language models believe that generative artificial ielligence has a wide range of capabilities and that these models have already demonstrated their ability to enhance individual performance in practice.
Is generative artificial ielligence a miracle for business?
Before answering this question, let us ask another importa question. Can various businesses (small or large) that were not involved in the process of creating large language models, to increase their focus on benefiting from The power of generative AI invest?
Unfortunately, there is a difference between benefiting from large linguistic models in the field of personal efficiency and using them in order to increase commercial profit, such as taking help from these models to create Business software solutions, there is a long way and benefiting from the capabilities of this technology for commercial purposes is much more difficult than it seems; For example Create a chatbot With GPT-4 It takes several mohs to create only one chatbot It costs millions of dollars; Of course, this one example clearly shows the opportunities available to benefit from productive AI in the business field, and also shows the challenges facing this path.
Business expectations from artificial ielligence
Today, technology is an iegral part of business. When an organization starts using a new technology, it expects the technology to boost operational efficiency and drive better business results. Business expects the same from AI (regardless of its type). On the other hand, the success of a business does not depend only on technology. It is clear that regardless of the adve of AI and tools like GhatGPT, a well-managed business will always remain prosperous and a poorly managed business will always struggle.
The successful commercial use of artificial ielligence, just like the implemeation of any other commercial software solution, requires considering two basic principles; Firstly, the technology should work in such a way that it becomes the basis for creating a very good and expected business value, and secondly, the organization that has used this technology should also know how to properly manage it.
The evolution cycle of artificial ielligence and its frustration
Artificial ielligence, like any other technology, is evolving in the Gartner hype cycle. Gartner’s hype cycle relates to the evolution of a new technology, which includes 5 stages. These steps are as follows:
- Technology Trigger (at this stage, technology emerges and public atteion is drawn to it.)
- Peak of Inflated Expectations (At this stage, the ehusiasm for using new technology increases and the level of expectations becomes unrealistically high.)
- Trough of Disillusionme (at this stage, people’s disappoime with technology leads to a decrease in atteion and then neglect of it, the failure of the experience of using it, and finally the elimination of investme in it; of course, in some cases, investme coinues only if the technology able to satisfy people or organizations that have just started using it.)
- Slope of Enlightenme (in this stage, more examples of how the technology in question can be beneficial for businesses are preseed, and the preseation of these examples will clarify existing uncertaiies about the technology and increase public awareness. In this stage, the second generations and (Third, the technology is offered by its providers; also the number of organizations investing in its pilot implemeation is increasing, but conservative companies remain cautious.)
- Plateau of Productivity (at this stage, the widespread use of technology begins and the necessary criteria for its sustainability or non-sustainability become clearer. The process of expanding the use of technology in differe markets is completed, and if the new technology can go beyond a stereotyped market and position establish itself in more markets, it will coinue to grow in the future.)
Artificial ielligence has passed the technology trigger stage; Because it has been around for a long time and its capabilities have been made available to the general public through tools like GhatGPT. This technology has passed the peak stage of inflated expectations and will soon eer the slope stage of disappoime.
The slope of frustration will be created for several reasons such as the immaturity and inapplicability of the technology. These two common reasons can discourage erepreneurs, managers and investors during the artificial ielligence disillusionme stage. If an individual or an organization is not aware of these two factors, it will underestimate the challenges facing the use of AI in the field of business and miss the opportunities of timely and wise investme in the field of this technology.
Determining the level of differe activities by artificial ielligence
Currely, millions of people are ieracting with AI ielligence tools to perform various tasks; From information acquisition to coding. It seems that this technology determines the level of activities of differe areas of businesses; Anyone can use this technology and English will become a new programming language.
This also applies to some specific use cases of coe creation (copywriting marketing triangle). Generative AI also focuses on natural language understanding (NLU) and natural language generation (NLG).
Due to the nature of artificial ielligence, this technology has difficulty in performing some tasks and requires domain knowledge (expert knowledge about a specific field) to perform them.
Of course, on the other hand, experts with domain knowledge are also not fully proficie in the field of IT (information technology) and artificial ielligence or cannot understand how productive AI works; For example, they don’t know how GhatGPT can provide answers related to voice searches quickly, or they don’t know anything about the application of artificial ielligence programming to program a software.
The rapid progress and fierce competition in the fields of artificial ielligence make the ierpretation of basic linguistic models and these models increasingly become widely used products. The competitive advaage of business solutions created by large language models is highlighted elsewhere; Either in owning proprietary data of high value properties or in mastering a specific field of knowledge.
It is likely that business operators have acquired such special knowledge earlier than other people; However, they may still be using outdated systems, which preves them from starting to use productive artificial ielligence.
Beginners can also benefit from zero to hundred power of this technology; Of course, in order to acquire the necessary set of expertise, they must succeed in their business; But both large and established companies and start-ups will face the same basic challenges.
The main challenge in the path of providing artificial ielligence access to specialized knowledge in the field of business is to be able to use special knowledge and skills to teach this technology and monitor its activity without the need for technology to become specialized in a specific field. In the following, we state the necessary pois for the successful use of productive artificial ielligence.
Tips for successfully using artificial ielligence in business
Although generative AI has advanced technologies in both language understanding and language creation, it is not capable of doing everything. We should use the advaages of each technology and ignore its shortcomings. In the following, we will state some of the necessary technical pois that erepreneurs, company managers and investors who are determined to invest in the field of artificial ielligence should know.
- Get help from an expert to create AI solutions: Generative AI is still a long way from being perfect. If company managers wa to create their own solutions using this technology, they must first make sure that one of their forces has enough expertise to deeply understand how artificial ielligence works in differe fields and, if necessary, can strengthen the ability of such a system. (If there is no such person in the company, an expert must be hired). If you wish, to partner with other companies to create solutions based on artificial ielligence, you should also make sure that the company in question works with a skilled expert in this field so that you can achieve the best possible result.
- Gain expertise in software engineering: Creating a productive AI-based solution is just like creating any other software solution and involves a series of engineering activities. If you wa to create your own solutions, naturally you need to have the tale to engineer a complex software to create it. If you wa to collaborate with another company to create such software, make sure they provide you with a code-free platform that you can easily use to create, maiain, and update your solution.
- Acquiring domain knowledge: Creating solutions based on productive artificial ielligence in most cases requires acquiring domain knowledge and customizing technology using this knowledge. Make sure you have the ability to work with someone who has domain expertise and knowledge of how to use the technology built io the solution. It is importa to make sure of this whether you wa to create your own solution or you wa to get help from another company to do this. In addition, whether you wa to create your own solution or you wa to do it in cooperation with another company, you need to help domain experts who often do not have the necessary knowledge and skills in the field of IT, so that they can easily create solutions based on productive artificial ielligence. Create, customize and maiain without coding or IT support.
final word
Having an unbiased view of generative AI can help us coinue to shape the business landscape with this technology. It is better to review the importa pois together once again at the end.
- Generative AI-based solutions can solve a large number of language-related problems; But this technology is not able to do everything.
- Creating and implemeing a successful business solution based on generative AI is more difficult than it first appears.
- Generative AI does not benefit everyone equally. To benefit from the full benefits of this technology, you must hire or collaborate with an expert with domain knowledge as well as an expert in artificial ielligence and IT technology so that you can use the power of AI faster and safer.
Erepreneurs, corporate executives and investors are fully engaged in the rapidly evolving world of productive AI; For this reason, it is necessary to get acquaied with the challenges and opportunities of this path, and we also need to know who has invested more in the field of this technology and can make faster decisions and make more prude investmes to maximize the return on investme.
