Effectiveness of Human-Centered Design in the introduction of Generative AI -Transforming business through users’ perspective- | Insights

With the advancements made in generative AI, its scope of application has expanded from mere streamlining of operations to provision of more professional support for business departments. The key to enhancing corporate values lies within how generative AI is leveraged to strengthen specialized work. To fully leverage its power and effect, it is essential to design the utilization of generative AI based on users’ perspective.
In this Insight, we will explain how generative AI has evolved from its use for streamlining of operations to provision of support for more specialized work, clarify challenges that businesses may face during its introduction, outline the feasibility, and share how a Human-Centered Design (HCD) approach can maximize the effect that generative AI may have on business.

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1. Generative AI and new business opportunities

The technology of generative AI is rapidly evolving. generative AI is no longer a new technology. It has become an essential business tool which could open up numerous new doors of business opportunities. In the eCommerce industry, for example, generative AI is being used for automatic generation of product descriptions, enhancing the efficiency of content creation. It has also enabled more personalized service by proposing products that better meet individual customers’ needs. In the finance industry, generative AI is being used in various ways to accelerate business operations, such as creating automated responses to customer inquiries or support credit risk assessment and analyzing customer data. In the manufacturing industry, generative AI is being used to automatically create technical documents and product manuals, alleviating the workload of engineers and improving their productivity.

At the dawn of generative AI, this new technology was introduced to businesses as a convenient tool that could be used by all in the organization, mainly used by IT departments to automate tasks such as the generation of meeting minutes and summarization of documents. At this point, generative AI was perceived and promoted as an valuable tool that would help streamline operations. For example, an automatic generation of minutes for a sales meeting enabled these information to be immediately shared among all departments, contributing to a more seamless internal communication. As illustrated in this example, generative AI was positioned as a vital tool by the IT department to support the streamlining of operations across the entire company.

With the help of technologies such as Retrieval-Augmented Generation (RAG), today’s generative AI can now be used to support more advanced and specialized work in business departments. At manufacturing departments, generative AI is used for real-time analysis of data during the product inspection process, helping to optimize quality control. In the healthcare industry, generative AI is increasingly supporting healthcare professionals perform their work. For example, it is used to provide doctors with supplemental information based on a patient’s medical history for them to make better diagnosis. As you can see, generative AI has transformed from a mere automation tool to a more strategic tool which supports decision-making processes.

For future introduction of generative AI to business, the key to gain competitive advantage would be close cooperation among the IT department and other business departments. While the IT department would be driven to centrally manage the use of generative AI across the company, business departments would be driven to seek specialized functionalities tailored to their specific needs. There is a significant gap among these departments in the expectations and challenges regarding the use of generative AI. For the most optimized application of generative AI in business, this gap needs to be filled and collaboration among IT and business departments is a must. Namely, the IT department should take lead in enforcing technical governance and managing platforms, while business departments should explore ways to leverage generative AI to meet the needs of its customers and markets.

Moving forward, to enhance the enhancement of added company values through the use of generative AI, using this new technology to support specialized work for business departments will be crucial in addition to general streamlining of operations. Thus, taking a more user-centric approach to design the utilization plan will play an important factor to make this happen.

2. Users’ perspective on the introduction of generative AI to business departments and the importance of HCD

At business departments, not only are they required to implement typical streamlining of operations, they are also required to resolve department-unique challenges and enhance added values in specialized work. With more and more application of generative AI in business scenes, an approach based on users’ perspective is essential to the introduction of generative AI to business departments. When introducing generative AI, it is important to first accurately understand the different challenges that each business department faces and design solutions to resolve such challenges.

Taking a HCD approach is quite effective for the resolution of specialized challenges. HCD is a method to design systems centered around users’ needs and usage conditions. The aim of this method is to optimize user experience. By taking this approach, the project team will not only be able to integrate target technologies in the solution, but will be able to design an user-friendly system with high compatibility with business operations, aiming at resolving department-specific challenges. To be more specific, this is how the HCD can be applied to a system development project (see Figure 1).

Observe and understand users
The first step of the HCD approach is to observe day-to-day operations and work environments, and dive deep to understand what kind of challenges and needs there are. In this step, the designers conduct users’ interviews and make field behavior observations to not only identify potential challenges, but also to draw out unmentioned inconveniences and expectations that users have.
Clarify challenges and form hypotheses for solutions
The next step is to clarify users’ challenges based on observations made and form hypotheses for possible solutions. When introducing generative AI, the next specific step to take would be examining what kind of functions and tools should be introduced based on the hypotheses formed. One question to ask may be, “Would information search or automation of summarization contribute to the improvement of operational efficiency?”
Design prototype and conduct user tests
The next step is to design a prototype based on the formed hypotheses and actually have users test the prototype. The prototypes made at this point may be on paper or just be simple simulations. The key is to verify the easiness of use and effectiveness of functions.
Make improvements based on feedback and iterate
The final step of this cycle is to improve the prototype based on users’ feedback and re-conduct user tests. Through iteration of this cycle, the project team will be able to refine the design for a generative AI tool which best fits users’ work conditions and addresses their challenges.

The aim of the HCD approach is to create designs that reflect users’ feedback as much as possible, which will ultimately lead to the development of an easy-to-use and practical tool. By incorporating HCD in the introduction process of generative AI, it will become possible to implement technology that satisfies the expectations and needs of actual users in the business department, maximizing the effect of introducing this new tool.

By having the business department take a HCD approach, it will become possible to clarify where generative AI needs to be introduced and what the most effective way would be from users’ perspective. For example, the focus of the sales department would be to improve quality of customer service with chatbots and predict customers’ needs based on data analysis, while the focus of the manufacturing department would be to optimize quality control and manufacturing processes. As it is obvious in the above examples, it is essential to address challenges from field workers’ standpoint, formulate and optimize solutions to meet their expectations when designing individual scenarios for　generative AI utilization at each department.

The introduction of generative AI to business departments should not just simply be a general adoption of new technology, but provision of a practical system or tool that is tailored to meet the needs of each department. Fully drawing out the potentials that each department expects while finding the most optimized way to integrate technology and business will surely lead to strengthen the company’s overall competitiveness.

3. How to formulate plans for the utilization of HCD-based generative AI

While we find that more and more companies show strong interest in the introduction of generative AI, we also see that not many projects which aim to introduce generative AI for streamlining of operations and enhancement of business values make significant progress. As mentioned above, the key is in determining how to utilize generative AI for specialized work in business departments. However, companies and departments that have little experience in using generative AI lack the knowledge and skill to use this new technology and find it difficult to formulate a practical plan. Thus, becoming reluctant to move on with the actual introduction.
As a solution to this challenge, we propose that our clients take the following HCD-based process when formulating a plan to introduce Generative AI.

1.

Experience generative AI
In the first phase, we have our clients experience using generative AI to understand its capabilities and feasibility. In-depth understanding of the technology allows our clients to better visualize how it can be applied to their business. For example, with a trial use of generative AI for general administrative tasks such as document creation and data summarization, the client will be able to understand what the generative AI can and cannot do. This knowledge helps them better illustrate the business scenarios that generative AI could be applied or better identify their needs and wants toward this new technology.

At ABeam Consulting, we offer the use of the “Generative AI Starter App” as part of the first phase to support our clients consider the most effective way to use generative AI in their business and identify which operations to apply to and goals they would like to achieve.

Use case creation support to improve business efﬁciency and value through Generative AI Starter App | Solutions | ABeam Consulting

2.

Determine utilization method
In the next phase, we support our clients to specifically examine how generative AI could be used in accordance with their business attributes and challenges they may face, based on the feedback they have given us regarding their first experience using generative AI. The aim of this phase is to clarify what kind of effects generative AI may bring about and points that need to be considered when actually implementing the new tool. These consideration points may be data quality, access control, or actual operation after implementation. Through this phase, our clients would be able to determine a practical plan which would effectively improve their operational efficiency.
3.

Create introduction plan
This last phase is to comprehensively review factors such as technical configurations, cost performance, and application to operational processes if the utilization method determined in the previous phase were to be realized, and create the most optimal introduction plan. The introduction plan will include a practical development schedule, budget, and security requirements for AI utilization. It will also include the formulation of a feasible roadmap which illustrates how the new generative AI tool will be deployed in the organization and how it will enhance business values.

By taking the above process, we will be able to help our clients alleviate anxieties and issues that their business departments may have toward the introduction of generative AI and determine utilization methods that fit well with actual operational processes. By formulating a plan to use generative AI which greatly takes into account of users’ perspective, our clients would be able to facilitate the introduction of generative AI with high affinity to their company attributes and ultimately streamline their operations as well as their business values.

4. Case examples of the introduction of HCD-based generative AI

The advancement of generative AI in the healthcare industry is progressing. In the healthcare industry, there are demands for enhancement of information management systems and streamlining of operational processes. However, in many cases, incorporating generative AI to conventional systems is not sufficient enough to fulfill these demands and meet the needs of doctors and other healthcare professionals. Thus, it is extremely critical to optimally design the utilization methods of generative AI to resolve challenges and meet needs that are specific to the healthcare industry.

We incorporated the concept of HCD, used a Generative AI Starter App to understand the challenges that healthcare professionals face in the field and determine the most optimal way to leverage Generative AI.
Namely, we had five doctors from neurology, cardiology, and general medicine use a Generative AI Starter App, and then designed and verified a prototype. As a result, we were able to clarify the challenges that these doctors faced in their everyday work, and were able to identify the following two scenarios for generative AI utilization.

Support to leverage knowledge
While various information (such as specialized books, documents, oral traditions, and personal notes) was available in the healthcare field, it was difficult to fully leverage these knowledge using the conventional information platforms. To address this challenge, we designed a system powered by generative AI which integrated, organized, and promptly delivered necessary information to doctors. For example, the AI in this system could integrate medical records and document databases to instantly provide references based on past medical cases and treatment approaches, which would lead to the improvement of quality of medical care.
Handling standard treatments and inquiries outside of specialty areas
When doctors need to find information relevant to medical care but not of their specialty, they need to inquire colleagues in other wards or peruse through voluminous documents. However, in reality, it is quite challenging to find time to do this while managing their everyday work. To alleviate this burden, we designed a function in which the generative AI conducts standard research and acts as a communication bridge between the doctor who wants to make the inquiry and the doctors from other wards. This function makes it possible for doctors to quickly gather necessary information and make better diagnoses.

The key point in this project was that the utilization methods of generative AI were not based on imagination. Rather, they was based on actual use of a simplified prototype which helped to better identify the real challenges that the doctors were facing. In other words, we were able to identify users' actual challenges from their generative AI experience and design a utilization method based on these identified issues.
As one can see from this case example, it is extremely critical to stand in users’ shoes when designing optimal utilization methods rather than simply introducing the technology when it comes to generative AI.

5. A future in harmony with generative AI

As emphasized above, the introduction of generative AI has become a significant factor in business growth and strengthening of competitiveness. It has an impact much greater than its contribution to the streamlining of operations. The use of generative AI in specialized work for business departments is expanding and growing, fueling the enhancement of productivity and operations across the company.

Today’s generative AI primarily generates text and data primarily according to the prompts made by the user. However, it is expected that generative AI will evolve to become a more autonomous entity acting as an agent on behalf of the user. Agentic AI will be able to learn operational processes without being prompted by users and be able to autonomously execute tasks. For example, an agentic sales AI may automatically optimize personalized services for customers while an agentic manufacturing AI may lead production planning and make adjustments on its own. Such applications are expected to provide more advanced support across various business functions.
It is highly expected that the dynamics of the AI and user will change, with AI acting as a business partner for the user.
Such technological advancements will empower generative AI to become capable of handling even more advanced tasks and open more new doors of possibilities. Note, however, that the more capable AI becomes of autonomously making decisions and participating in larger business processes, the more important it will be to design how humans and AI will cooperate with each other. For AI to become a reliable partner for the user, executing tasks appropriately, it is essential to incorporate users’ perspective at the point of its design.
And that is the point at which we stand today, proving that taking a HCD approach to design generative AI is ever more important. Need we not emphasize that using generative AI that satisfies users’ business needs is the key to be able to fully leverage this new technology. Feeding generative AI with feedback from actual users in the field will help design an AI solution with optimal functions and easiness of use. This will surely contribute to companies gaining a competitive advantage.

At ABeam Consulting, we recommend the HCD approach to draw out the full potentials of generative AI to support the company to grow and strengthen its competitiveness as well as create new business values for a more sustainable future.

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