In this TechNode Global Q&A, we interview Daniel Posavac, Managing Director of CUE Group Southeast Asia, on how big data and AI can improve decision-making processes. Posavac discusses how AI technology can help discover outliers and missing values in big data and gives examples of how video AI technology can be customized to address different pain points for businesses or organizations beyond security and surveillance.

He also shares how CUE is working to ensure the ethical use of AI and stay ahead of the curve in the rapidly evolving AI industry, as well as the company’s notable partnerships and collaborations. Finally, Posavac discusses the potential impact of AI on the job market and shares some case studies and trends that show the potential of AI across industries.

Originally from Australia, Daniel Posavac has 20 years of marketing and digital marketing experience and co-founded Bonsey Jaden in 2014. The firm has offices in Southeast Asia, Australia, and the US, and recently partnered with CUE Group in 2020. Daniel currently holds dual roles as both Chief Executive Officer of Bonsey Jaden and Managing Director of CUE Southeast Asia.

Read on for the TechNode Global Q&A.

Can you give us an example of how AI technology has been able to discover outliers and missing values in big data to help influence organizational decision-making?

One example of how AI technology has been used to discover outliers and missing values in big data to help influence organizational decision-making is in the field of video analytics.

Many organizations, such as airports, malls, and manufacturing plants, use video surveillance systems to monitor their premises and ensure safety and security. However, analyzing the large volumes of data generated by these systems manually can be time-consuming and error-prone. Video AI technology can automate the process of analyzing surveillance footage, making it easier to identify anomalies and make informed decisions based on the data.

For example, video AI technology can be used to identify and track people or objects in real-time, detect unusual behaviors or movements, and alert security personnel when potential threats are detected. The technology can also be used to analyze historical video data to identify patterns of behavior that could indicate potential security threats, such as intrusions or thefts.

Video AI technology can also help discover missing values in video data by imputing them. For example, if a video recording has missing frames due to network issues, the technology can predict the missing frames based on the available frames, improving the overall quality of the video data.

As video datasets continue to grow, what are some ways your company is working to improve the efficiency and accuracy of AI-powered video analysis?

As video datasets continue to grow, AI can be used to help with a wide range of business applications. Here are a few examples of how AI can be used in this context:

Object detection and tracking: AI can be used to automatically detect and track objects in video footage, such as people, vehicles, and packages. This can be useful for identifying behavior patterns, optimization opportunities as well as security applications across Retail, Healthcare, Manufacturing, and live events.

Activity recognition: AI can be used to recognize specific activities in video footage, such as walking, running, lifting, picking up, or climbing. This can be particularly useful in Retail environments to better understand customer behavior as well as shopping and buying patterns.

Video summarization: AI can be used to analyze large amounts of video footage and generate summaries that highlight key events or activities. This can be useful for quickly reviewing large amounts of footage and identifying any areas of opportunity for businesses.

Can you provide some examples of how your Video AI technology can be customized to address different pain points for businesses or organizations beyond security and surveillance?

There are many key applications of video AI that can be customized to address specific business challenges. Today I will focus on a few examples which we are currently delivering for our clients and partners:

Marketing and advertising: Video AI can be used to analyze customer behavior and preferences, and to personalize marketing and advertising efforts accordingly. For example, an AI system might be used to analyze how customers interact with video ads and to optimize the content and delivery of future ads based on this analysis.

Customer service: Video AI can be used to improve customer service by analyzing customer interactions and providing real-time recommendations to customer service representatives. For example, an AI system might be used to analyze customer tone and body language and to suggest appropriate responses or actions for the representative to take.

Training and development: Video AI can be used to create personalized training and development programs by analyzing employee performance and providing personalized feedback and recommendations. For example, an AI system might be used to analyze employee interactions with customers and provide recommendations for improvement.

Supply chain management: Video AI can be used to improve supply chain efficiency by analyzing the movement of goods and materials through the supply chain, and identifying bottlenecks or inefficiencies that can be addressed.

Quality control: Video AI can be used to improve quality control by analyzing product defects and identifying trends or patterns that can be addressed.

How do you ensure the ethical use of AI in applications, particularly when it comes to handling sensitive data or potentially biased algorithms?

Ensuring the ethical use of AI in applications is a critical issue that requires careful consideration to address the potential risks and challenges associated with handling sensitive data or potentially biased algorithms. Here are some best practices that can help ensure the ethical use of AI:

Develop clear ethical guidelines: Organizations should develop clear ethical guidelines for the development and use of AI systems. These guidelines should outline the values and principles that guide the organization’s approach to ethical AI and ensure that these values are reflected in the design and implementation of AI systems.

Foster a culture of ethical AI: Organizations should foster a culture of ethical AI by promoting ethical practices and behaviors throughout the organization. This includes providing training and education on ethical AI and ensuring that all employees understand the importance of ethical AI and their responsibilities in ensuring it.

Ensure transparency: Organizations should ensure that their AI systems are transparent and explainable. This includes providing clear explanations of how the AI system works, how it makes decisions, and how it handles sensitive data. Transparent AI systems can help build trust with users and stakeholders and reduce the risk of bias and unfairness.

Ensure data privacy and security: Organizations should ensure that sensitive data is handled securely and with the utmost care. This includes implementing strong data security measures, complying with relevant data protection laws and regulations, and obtaining user consent for the use of their data.

As the AI industry continues to rapidly evolve, how do you see your company staying ahead of the curve and continuing to innovate in this space?

As a Technology company with a strong focus on AI technologies, Cue is dedicated to staying ahead of the curve and continuing to innovate in this space. Here are some ways that we are working to achieve this:

Investing in research: We invest heavily in research to develop new AI technologies and advance the state-of-the-art. Our team of researchers is focused on developing breakthrough AI models and algorithms that can be used to solve some of the world’s most pressing problems.

Collaborating with industry and academia: We collaborate with industry and academia to stay up-to-date on the latest AI research and developments. These collaborations help us stay informed on emerging trends and technologies and provide us with valuable insights into how AI can be applied in different industries and domains.

Fostering a culture of innovation: We foster a culture of innovation by encouraging experimentation and risk-taking. We encourage our team members to explore new ideas and approaches, and we provide them with the resources and support they need to pursue their research interests.

Can you discuss any notable partnerships or collaborations your company has formed with other organizations or businesses to apply AI technology in new and innovative ways?

Our recent collaboration with SYCARDA, a renowned Malaysian data analytics and business intelligence platform, resulted in the development of a customized retail solution that addresses the pilferage and sweethearting issues of a local grocery chain in Malaysia. By leveraging advanced data analytics and business intelligence techniques, this bespoke solution helps the grocery chain to better monitor and analyze its operations and identify any suspicious activities that may cause losses to the business.

As the retail landscape continues to evolve, we believe that data-driven solutions like ours will become increasingly critical for traditional brick-and-mortar retailers to stay competitive and succeed in the market. Our collaboration with SYCARDA is just one example of how we are leveraging AI technology and data analytics to help businesses overcome their operational challenges and achieve their strategic goals.

What kind of impact do you see AI having on the job market in the near future, and how is your company working to address any potential challenges or concerns in this area?

AI is already having a significant impact on the job market, and this impact is likely to continue and accelerate in the near future. While AI has the potential to create new jobs and improve productivity, it can also disrupt traditional job roles and require workers to adapt to new skills and technologies.

At CUE, we are committed to developing AI in a way that maximizes its benefits and minimizes its risks, including those related to the job market. Here are some ways that we are working to address potential challenges or concerns in this area:

Investing in AI education and training: We are investing in AI education and training programs to help workers develop the skills they need to thrive in an AI-driven economy. This includes supporting initiatives that provide workers with access to AI training and education programs.

Collaborating with industry and policymakers: We are collaborating with industry and policymakers to help shape the development of AI in a way that maximizes its benefits and minimizes its risks. This includes engaging with stakeholders to identify potential challenges and develop solutions that benefit workers and society as a whole.

Developing responsible AI systems: We are developing AI systems that are designed to operate ethically and responsibly, taking into account their potential impact on the job market and society as a whole. This includes designing AI systems that are transparent, explainable, and free from bias and discrimination.

Overall, we believe that AI has the potential to create significant benefits for society, including improving productivity, advancing scientific research, and enhancing human capabilities. At the same time, we recognize the potential challenges and risks associated with AI and are committed to working with stakeholders to address these challenges and ensure that the benefits of AI are realized by all.

Please share notable case studies or trends that show the potential of AI across industries.

We’ve had the privilege of partnering with some remarkable organizations that have recognized our AI capabilities and wanted to leverage them to their advantage. One of these partnerships was with UnderArmour, where we collaborated to create the world’s first smart retail digital store that utilizes cutting-edge technologies, such as customer traffic tracking and analysis system, virtual fitting room technology, and in-store e-commerce system, to enhance the customer experience and gather valuable data.

Another partnership was with LBX Pharmacy, where we implemented a traffic digitization system and customized kanban board system to help them make informed decisions and improve their operations to better serve their customers. We also worked with Hyundai to implement data-driven solutions and strategies to collect and analyze customer data at scale, allowing them to better understand their customers’ needs and improve their operations to meet those needs.

These partnerships have allowed us to showcase the power of AI technology and data-driven solutions to transform traditional retail operations, and we look forward to continuing to collaborate with forward-thinking organizations in the future.

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