There is great interest in artificial intelligence and its related technologies, as business leaders are eager to test them to enhance their visibility, analysis, and predictions. Generative AI, in particular, has become widely available to everyone and is considered democratized. However, the type of AI that operates behind the scenes in systems and has the potential to provide immediate and tangible benefits to businesses is not as easily accessible, making it harder for businesspeople to understand fully.
The above paragraph can be paraphrased as follows: Rachel Woods, a research data scientist formerly associated with Meta/Facebook, recently shared insights via a Twitter essay generator format. In her essay, she emphasizes that while AI’s potential in the business realm is promising, its usability is still a work in progress.
She stated that AI is still faced with a significant issue regarding its usability. Many individuals need help effectively utilizing ChatGPT, Language Models (LLMs), and Generative AI. Everyone is eagerly anticipating discovering a valuable application that would revolutionize the field. Consequently, numerous individuals are questioning the practicality of these tools. However, the fundamental problem lies in their usability rather than their lack of usefulness, as suggested by misleading articles.
Other industry experts also concur to a great extent. Andy Thurai, a principal analyst at Constellation Research, explains that ChatGPT and AI gained immense popularity due to their user-friendliness and the ability for business users to explore their possibilities easily. Thurai highlights that generative AI, specifically its capability to produce text, content, video, and audio, impressed non-technical users with the potential of AI.
According to Thurai, technology professionals restricting their usage to non-tech users due to bias, technology limitations, liability concerns, and others were amazed and impressed by the immense response and quick adoption. This not only boosted the creators’ confidence in the adaptability of the technology but also eliminated the need for further explanations.
According to Dr. Vishal Sikka, the founder and CEO of Vianai, there is still a limited number of individuals who genuinely understand AI. He estimates that this group consists of approximately 20,000 to 30,000 people worldwide. Although there may be around a million data scientists globally, Sikka emphasizes that many need a comprehensive understanding of AI. They cannot explain the reasons behind the system’s actions, its recommendations, potential issues, or the underlying techniques used.
There is a distinction between the ways AI is used in businesses and the ways it is used to generate content. These two types require different approaches and purposes. According to Thurai, more than simply creating content is needed. AI should address a business problem and adhere to responsibility, ethics, explanation, and audibility principles. Moreover, it should be able to defend its originality and its decisions. These factors are more significant than just matters of usability and can potentially impact any enterprise significantly.
Enterprise implementation will take time, although potential applications are becoming more prominent. According to Thurai, various departments such as legal, HR, ethics, and finance are currently investigating use cases that can offer significant advantages to their respective fields. Thurai also emphasizes the potential high cost of AI, especially if not approached correctly, as it could jeopardize the survival of these departments. Therefore, proceeding with caution and careful consideration is essential before fully embracing this trend.
ChatGPT has made AI much more accessible; however, according to Woods, a considerable amount of time is still required to fully realize its true potential. To discover innovative and practical applications, one must either put in the effort or wait for AI to become more widely adopted and user-friendly.
How can supporters of technology enhance the functionality of AI? Professionals in the industry suggest a few approaches to begin with:
Frank, technology managers, and professionals need to have open and honest discussions about the possibilities and challenges of AI. One crucial skill they need to develop is convincing their businesses to adopt suitable approaches to AI effectively. According to Thurai, many technology and innovation ideas fail because they cannot gain the support of business users, budget holders, and CXOs who need to recognize the value these ideas can bring to their companies. On the other hand, it is also true that techies often dismiss the needs of business users by claiming that they are impossible to execute or impractical due to budget, technology, resource, or cost limitations.
AI education is necessary for all companies, regardless of size, to improve their understanding and utilization of AI technologies. This will allow a broader range of talent to work on AI systems. According to Sikka, employees must be educated not only on the benefits and capabilities of AI but also on its limitations and weaknesses. An AI system should be built with compensatory measures to address these limitations. Thurai suggests conducting collaborative workshops where individuals from various roles and positions, including tech experts, innovators, strategists, business users, budget holders, and CXOs, can explore and witness real-life use cases. This collaborative approach sparks new ideas and helps participants recognize the potential value that AI can bring to their respective areas.
Develop a team with a strong pool of AI expertise: Artificial Intelligence, similar to various other technological fields, is a specialized skill. According to Woods, skills like Photoshop, Excel, and Facebook Ads Manager require a significant investment of approximately 100 hours or more to become proficient enough to seamlessly incorporate them into one’s everyday professional and personal life.
According to Sikka, AI must prioritize human needs. He believes many systems must be tailored to humans and advocates for combining human understanding with data and AI technology. Intelligent systems can be developed by focusing on human-centered AI to enhance business outcomes and processes. This approach allows for human feedback to improve AI’s performance and results.
You may be interested in: What is user experience? Definition and examples