How to Integrate AI into Design to Elevate the Value of a Data Platform

The Challenges of Successful AI Integration

The transition from conventional solution design to Artificial Intelligence design has taken many designers off-guard. Their knowledge of AI design doesn't match their level of expertise in foundational design. The lack of depth of expertise in this area can prevent AI from being fully leveraged.

The complexity of ensuring a high level of quality in the data that drives decision-making while avoiding bias cannot be understated. Often complex capabilities compromise the user-friendliness of the platform interface which causes issues for rollout and uptake. That's just one of the balances designers have to navigate. There is a balance between adding sophisticated capabilities and managing costs. Then there is the ethical issue of protecting user privacy while maintaining accurate and detailed insights. How do these platforms utilize historical data without perpetuating biases?

The design process of an Artificial Intelligence-powered platform is unavoidably nuanced. Without proactive consideration of its complexities, those attempting to successfully integrate AI into their data platform may face issues navigating the intricacies of the design process when adding advanced capabilities, resulting in difficulties with smoothly integrating AI into an existing system, minimizing bias, garnering quality insights from data, ensuring consistent performance and building trust in a relatively unpredictable and non-transparent system, and complying with regulatory and ethical restrictions. Even building a model or pilot doesn't always help as this can present scalability issues. Such complexities mean budgets often don't stretch to the successful fulfillment of intended outcomes. On completion, there can be resistance to adopting the new AI-powered platform because users struggle to understand and therefore trust AI's role in the system.

That being said, by collaborating with the right expertise to carefully plan an Artificial Intelligence design, these issues can be mitigated and AI leverage to its full potential.

The Route to Successful AI Implementation

Our work at NTT DATA, supporting enterprises as they build cutting-edge solutions, highlighted the bridge between the potential of AI for businesses and the successful execution of AI solutions. We wanted to ensure that our clients could use AI to elevate their data platforms and propel their businesses forward in a cost-effective and future-focused manner. And so we launched our Intelligent Design Services, bridging the gap between AI's vast potential and the real-world design challenges businesses face.

Our team has built an in-depth understanding of how to utilize the full breadth of AI's capabilities resulting in a highly functional design that prioritizes data quality and data integrity. Our AI design is so advanced that it can used to solve complex problems that have previously been deemed unsuitable for AI implementation but that would be completely transformed by AI involvement. These complex problems include those that only humans have been able to handle such as visual and sound inspection, those that are dangerous for humans such as fighting fires, and those that aren't manually viable such as inspecting every screw on a production line. While extending the application of AI, we ensure ethical practices are standard in our designs, minimizing biases and protecting user privacy. As a global organization, we stay up to date with global AI regulations so that no client is caught out.

When taking on AI design projects, we have a refined framework that we follow. The framework enhances the process of creating systems, applications, or products where artificial intelligence technologies play a central role. It's comprehensive because it doesn't just cover the technical development of AI algorithms, but also the consideration of how these AI systems interact with users and fit into the broader context of their intended environment. Our process embraces how AI design is interdisciplinary, involving skills from computer science, data science, psychology, design, ethics, and domain-specific knowledge, depending on the application. The core pillars of this framework include:

• Algorithm Development:
  Designing and training machine learning models or AI algorithms tailored to specific tasks, such as image recognition, natural language processing, or predictive analytics.
• User Experience (UX):
  Ensuring that AI systems are intuitive, user-friendly, and effective in meeting the needs of their users. This includes designing interfaces that are easy to interact with and that provide clear, understandable outputs from AI processes.
• Ethical Considerations:
  Addressing ethical concerns such as fairness, privacy, transparency, and accountability in AI systems. This includes ensuring that AI does not perpetuate biases and respects user privacy.
• Integration:
  Seamlessly integrating AI into existing systems and workflows, ensuring that it complements and enhances rather than disrupts or complicates existing processes.
• Testing and Iteration:
  Continuously testing AI systems for accuracy, reliability, and usability, and iterating based on feedback and performance metrics.

The AI design framework we have developed has been informed by the multitude of successful client projects we have completed such as the Brazilian Electricity distribution company we worked with to develop an application to localize anomalies in billing processes. This was a real issue for them because as a utility company in Brazil, their taxes were calculated based on parameters determined by the government and reported by the company each month. So any mistake on their part could cause an error equivalent to millions of dollars. However, errors are difficult to identify manually in a company with records of millions of customers and processes.

A much more effective solution was to feed the parameters to AI so that it could automatically verify reports line by line and flag errors before reports are sent and taxes paid. The solution we built is able to calculate the correct amount of taxes to be paid within 30 minutes and easily find the root cause of errors in tax calculations. As a result, it was discovered that more than one million USD of taxes were overpaid in trillions of billing records. Due to their new AI-driven system, errors of such magnitude can be avoided in the future.

With such comprehensive Intelligent Design Services, our clients benefit from a seamless solution that serves their needs without compromise. We produce data platforms that have an intuitive user interface, in-built compliance to regulatory and ethical requirements, transparent decision-making based on high-quality data insights, and easy integration and scalability, all at a technological level that is so cutting-edge that it will create a competitive advantage for years to come.

Innovative businesses are staying ahead of the curve by integrating AI into their processes and systems. Keep up with this trend while avoiding common pitfalls and maximizing ROI by choosing NTT DATA as your value driver in AI utilization. As experts in solution design and AI usage, we will ensure you leverage AI with efficiency and minimal disruption. As your strategic partner, we can manage every step of the build from designing a user-friendly, transparent, and comprehensive platform to supporting implementation and uptake through training and trust building.