How AI Will Transform the Business Landscape

Companies can start now in utilizing and developing AI products

Today, people interact with artificial intelligence (AI) on a daily basis without even realizing it.

Think of something as simple as a chatbot on a random website or even Siri on your phone. All these little applications are powered by AI, which uses data to train algorithms that can mimic human-like intelligence.

The rising popularity of ChatGPT has made conversations around AI more prominent in recent months. The chatbot, which was created by OpenAI, was estimated to have reached 100 million monthly active users in January 2023, just two months after launch, becoming the fastest-growing user base ever launched.

The public likes to associate AI with science-fiction dystopias that see technology taking over our lives, Terminator style. However, AI is a tool with the potential to transform the business landscape exponentially, offering unprecedented opportunities for transformation and growth. Its ability to automate tasks, analyze vast amounts of data, and make intelligent decisions is essentially revolutionizing various aspects of businesses across industries.


A number of businesses see AI as a supporting tool instead of a replacement for human intelligence and ingenuity.

Its capability to handle large data sets, for example, sets it apart from traditional analysis methods and allows businesses to unlock the potential hidden within their data, leading to valuable insights and informed decision-making.

AI has a very strong pattern of recognition capabilities, which allows it to identify patterns, correlations, and trends that might go unnoticed by human analysts. Such insights enable businesses to understand customer behavior, market dynamics, and operational patterns, providing a solid foundation for devising effective strategies.

Moreover, AI enables predictive analytics, which goes beyond descriptive analysis and means AI models have the potential to forecast future trends and outcomes. Essentially, AI algorithms can forecast future trends, customer behavior, and market demands, thus empowering businesses to anticipate customer needs, optimize inventory and supply-chain management, and develop targeted marketing strategies.

In addition to analyzing large data sets, AI-powered automation systems can perform repetitive and mundane tasks with speed and accuracy, freeing up human employees to focus on more complex and strategic activities. This not only improves productivity but also reduces costs and minimizes errors, leading to enhanced operational efficiency and better resource allocation.

It is vital to mention that AI is also revolutionizing the customer experience, which many of us have experienced firsthand. Through natural-language processing and machine learning, AI-powered chatbots and virtual assistants can engage with customers in real time, providing personalized and efficient support. Such AI-driven interfaces can understand and respond to customer inquiries, assist in product recommendations, and resolve issues promptly, leading to improved customer satisfaction and loyalty.

AI also plays a significant role in enhancing cybersecurity. As businesses become more digitally connected, the threat of cyberattacks grows. AI algorithms can analyze vast amounts of data to detect patterns and anomalies that may indicate potential security breaches or malicious activities. By leveraging AI-powered cybersecurity solutions, businesses can proactively identify and respond to threats, protecting sensitive data and minimizing risks.


One of the challenges of implementing AI technologies has been the wide array of technologies from different parties. Companies need an ecosystem to integrate these technologies to get optimal benefits. Further complicating usage has been the need to adjust the AI technology based on data to be analyzed (video, sound, text, mathematics) and difficulty getting an integrated view. Finally, governments are implementing new regulations around AI ethics and trust that need to be adhered to. 

According to a recent survey, only 19% of companies interested in AI have been able to use AI solutions in production. This points to the complexity of turning AI into real business-use cases. However, 73% of companies that have completed proofs of concept have moved to actual use-case deployments. 

A solution to this is to implement a platform-based approach where companies look at a broad spectrum of AI solutions and use a plug-and-play approach to bring the right technology to the problem at hand. 

An example of an AI platform is Fujitsu Kozuchi, which comprises multiple Fujitsu and third-party AI technologies to address the issue of deployment. The advantages of this approach are the ability to get results immediately and with high precision, based on your data type and requirements, and resulting in rapid deployments of AI solutions. Additionally, a platform like this one enables you to componentize AI solutions with industry-based knowledge pre-built into the system.

Developing AI products is a multifaceted and agile process that requires careful planning, technical expertise, and collaboration, which means that the first step in developing AI products is defining clear objectives. Companies need to identify the specific problems or opportunities that AI can address and determine the value it will bring to customers and the business. This clarity of purpose will guide the entire development process and ensure that the AI product aligns with the company’s strategic goals.

Building an AI team is crucial for successful development, which means that companies should assemble a team of experts in AI, data science, and software development before commencing with development of AI products.

In addition, establishing a robust data infrastructure is another fundamental aspect of AI product development. Companies need to invest in collecting, storing, and organizing data effectively. Therefore, following best practices for data quality, privacy, and security is essential to ensure the reliability and integrity of the AI models and algorithms.

By leveraging machine-learning techniques, companies can build AI models that can analyze data, make predictions, or perform specific tasks. Training these models with relevant and high-quality data is crucial for their accuracy and performance. Companies should continuously refine and optimize the models based on user feedback and real-world testing, adopting an iterative development process.

Collaborations and partnerships can also help. Companies should seek collaborations with research institutions, universities, startups, or technology providers to stay at the forefront of AI advancements. These collaborations provide access to cutting-edge AI tools, platforms, and expertise, enabling companies to leverage the latest innovations in their product-development efforts.

Finally, companies should remember the ethical implications of AI development. This means that companies must ensure that their AI products adhere to legal, regulatory, and ethical standards. Addressing concerns related to bias, privacy, and transparency is crucial for building trust and maintaining ethical standards. Implementing robust governance frameworks and risk-mitigation mechanisms is essential.


Fujitsu Kozuchi will deliver access to a number of powerful AI and machine-learning technologies to users worldwide. 

The platform will allow customers from an array of industries to accelerate the testing and deployment of advanced AI technologies for the unique business challenges they face with a portfolio of tools and software components. 

The platform’s key features include:

  • AI Innovation Components: AI components having customer value proposition by combining strong Fujitsu IP and other companies’ IP
    • Worker Behavior Analysis: Visualizing workers’ process by analyzing camera images in a factory
    • Customer Behavior Analysis: A heat map analyzing the customer’s interaction with a product shelf and walking lines on the shop floor
    • Suspicious Behavior Detection: Analyzing suspicious behavior on camera images and alerting security
    • Product Defect Inspection: High-accuracy detection of low-quality products on factory lines by analyzing images
  • AI Core Engines: AI technology as an engine to deliver to users
    • Fujitsu AutoML: A solution for automated generation of machine-learning models
    • Fujitsu AI Ethics and Fairness: A solution for testing the fairness of AI models 
    • Fujitsu AI: For causal discovery 
    • Fujitsu Wide Learning: A solution to stimulate scientific discovery processes and streamlines access to open-source software and AI technologies from partner companies
    • Generative AI sandbox: Sandbox environment where customers can try ChatGPT securely

Overall, AI can be used by companies to help effectively transform operations and achieve success in today’s competitive business landscape. By embracing AI-powered automation, data analytics, enhanced customer experiences, predictive analytics, improved decision-making processes, and robust cybersecurity measures, companies can unlock new opportunities, improve operational performance, and deliver exceptional products and services. The successful utilization of AI requires a strategic approach, collaboration with AI experts, and a commitment to ongoing learning and adaptation. Embracing AI is no longer a luxury but a necessity for companies aiming to thrive in the digital age.

Yasuhide Matsumoto is Senior Director of AI Subject Matter on Technology Strategy Unit at Fujitsu.