Leadership in AI and big data today goes beyond simply leveraging technology. As these areas advance rapidly, enterprise leaders need to transform them from technology tools into powerful engines of growth, guided by ethical considerations. To stay ahead of market and technology trends, they require a strategic approach to incorporating AI and big data innovations and using them to drive business success.
Heping Liu, Senior Machine Learning Principal at Workday, is among The Most Impactful Leaders in AI & Big Data in 2024. Before entering the industry, he has published 20 academic papers in the areas of forecasting, optimization, and artificial intelligence algorithms and their applications, and worked as a reviewer for 20 top academic journals involving machine learning, deep learning, computing, modeling, forecasting, and optimization, and as an editorial board member of the International Journal of Business Analytics.
The Journey from Academia to Industry Leader
Dr. Liu’s journey began with academia, where his enthusiasm and passion for artificial intelligence grew. During his master’s thesis, he explored the application of neural networks to predict industry financial indices and applied the Markowitz model for portfolio optimization. This research laid the foundation for his understanding of computational intelligence. His subsequent Ph.D. studies and practice provided him with the theoretical knowledge and practical applications of artificial intelligence, including deep learning and machine learning models.
After completing the Ph.D., Dr. Heping Liu worked in several high-tech companies, gaining valuable experience that enabled him to found Unigroup AI Technologies Inc. in 2018. Leading a startup gave him the opportunity to develop AI products, secure funding, and manage teams, sharpening his leadership skills. One of the pivotal moments in his career was moving from entrepreneurship to a large corporation like Workday.
While working in industry, Dr. Liu’s passion expanded into big data during the early 2010s when it became mainstream. He realized that AI needed large datasets to fully harness its capabilities, and combining AI with big data became the primary focus of his work. Over the years, his interest in theoretical models transformed into a commitment to building practical AI solutions that could reshape industries. His entrepreneurial experience and academic expertise allowed him to view AI as a transformative force that could revolutionize industries and improve business outcomes. This belief continues to guide him in his work at Workday, where he leverages AI and big data to create adaptive enterprise solutions.
Empowering Businesses through Innovative Solutions
Workday is a leading provider of enterprise cloud applications for finance and human resources. The company’s mission is to deliver innovative cloud-based solutions that empower businesses to thrive in the digital age. Its applications for human resources, financial management, planning, spend management, and analytics are built with artificial intelligence and machine learning at the core to help organizations embrace the future of work.
At Workday, Dr. Heping Liu proposed, initiated, and led many important projects, some of which were showcased at the Annual Workday Product & Technology Conferences, known as the Annual Spelunking Conference. Below are a few of these initiatives:
- Workday Resource Forecasting/Optimization Platform
- Forecasting-as-a-Service
- Building a Conversational Front End for the Entire Workday System by Leveraging Large Language Models
- Transforming OMS to Be an AI-Agent Friendly Data Environment and Secure RAG Vector Storage
- Forecasting and Optimizing Infrastructure Resources through Workday’s Released New (AI) Features
This exemplifies Dr. Liu’s visionary leadership and his capacity to overcome technical and strategic hurdles.
Addressing the Challenges of Scaling AI Technologies
Scaling AI and machine learning solutions faces several key challenges, particularly when consuming and managing vast amounts of data while maintaining high performance, accuracy, and security. One of the most significant hurdles is building AI systems that can operate efficiently in large-scale environments where data volumes are constantly growing and processing speed is critical. As data increases in complexity and quantity, AI systems must be capable of handling this growth without compromising performance.
Navigating real-time data can be daunting. Today, businesses increasingly rely on real-time analytics for immediate decision-making, which means AI systems must ingest, process, and respond to continuous data streams quickly and accurately. Incorporating real-time data requires highly optimized and scalable architectures that can support low-latency data processing. To tackle this, distributed systems are
essential, allowing AI models to process real-time data in parallel, which enhances both speed and reliability while maintaining accuracy.
Ensuring data security and privacy is critical. As AI systems scale and handle larger, more sensitive datasets, the risks of data breach and unauthorized access increase, making it essential to implement stringent data privacy measures and comply with regulatory standards. Protecting sensitive information while maintaining performance requires the use of robust encryption, secured data pipelines, and advanced privacy-preserving techniques.
AI’s Role in Shaping Data-Driven Business Strategies
One of the most significant contributions AI and big data make to businesses today is their ability to transform decision-making processes through data-driven insights, predictive analytics, and automation. These technologies allow businesses to analyze vast amounts of data quickly and accurately, providing insights that would be impossible through manual analysis.
To support this, Dr Heping Liu has given some examples. In human resources, AI can predict future staffing needs, identify skill gaps, and recommend personalized training programs. In finance, AI-powered forecasting models can help businesses anticipate market trends and manage spending and risk more effectively. These applications of AI and big data are already reshaping industries and will continue to have a profound impact in the future.
Key Trends in AI and Big Data for Businesses
Several growing trends in AI and big data are poised to shape the future of businesses. Generative AI will continue to be a major trend, enabling businesses to create new products, designs, and solutions with increased efficiency. As this technology matures, it will open opportunities for innovation across industries ranging from entertainment to manufacturing. Alongside generative AI, multimodal AI is on the rise, where AI systems process and integrate different types of data, such as text, images, and video. This capability allows for more comprehensive insights and greater accuracy in business processes. By harnessing these advancements, businesses can make better decisions, optimize and automate operations, and gain a competitive edge in an ever-evolving market.
Artificial General Intelligence (AGI), which refers to AI systems capable of performing a wide range of reasoning and innovative tasks across different domains, might also become a norm. Although AGI is in its very early stages, it holds immense potential for transforming industries by enabling more autonomous and intelligent decision-making and innovation in an organization.
Dr. Heping Liu says that AI ethics will play an increasingly important role in industries that rely on big data. As AI systems become more autonomous and powerful, ensuring ethical use will be essential to maintaining public trust. He believes that industries like finance, healthcare, and human resources will be especially impacted by AI ethics, given the sensitive nature of the data they handle.
The regulatory bodies might introduce stricter guidelines for AI use in the future. Companies will need to comply with these regulations while also proactively building ethical considerations into their AI systems. This will ensure that AI solutions are aligned with societal values.
The Rise of AI Agents in Modern Enterprises
Over the next ten years, AI and big data are set to revolutionize industries in ways that are exciting and transformative, yet hard to fully grasp. According to Dr. Heping Liu, one of the most exciting developments is the recent increasing use of AI agents in enterprise applications. These agents will be able to automate a wide range of tasks, significantly improving efficiency and productivity across industries, such as customer service and support, finance, healthcare, retail and e-commerce, and logistics.
The emergence of humanoid robotics will introduce more human-like interactions in sectors such as customer service, caregiving, and hospitality. Autonomous driving technology, led by driverless cars, will completely transform transportation and logistics. In industries such as delivery services, ride-sharing, and long-haul trucking, driverless vehicles will reduce costs, increase efficiency, and improve safety.
The evolution of Artificial General Intelligence (AGI) will be another pivotal moment. AGI, which aims to mimic human cognitive functions across various tasks and domains, will redefine industries by allowing machines to perform tasks that traditionally require human intelligence. Industries like research, legal, and even creative fields such as marketing and design could see machines that not only assist but also innovate independently.
Artificial Super Intelligence (ASI) may become a revolutionary force in the future, exceeding human intelligence in every aspect. Although the timeline for ASI remains uncertain, its influence could transform not only various industries, but humanity itself. ASI systems might tackle some of the most intricate challenges in areas such as climate science, healthcare, and economics, with an unprecedented scale and depth. Especially, the application of ASI to life sciences has the potential to address some of the most pressing challenges in medicine, from curing complex diseases to creating more efficient healthcare systems worldwide.
The Culture of Innovation Within the Team
Throughout his career, Dr. Heping Liu has made sure to provide a culture of innovation within his team. He achieved this by creating an environment where team members are encouraged to take risks, explore new ideas, and think creatively. He provides autonomy to his team, allowing them the freedom to explore innovative solutions to complex problems while offering guidance and support when needed.
Dr. Heping Liu highly emphasizes the importance of being self-driven for team members. He supports open communication and collaboration and likes creating a work culture where team members feel comfortable sharing their ideas and feedback. Recognizing and celebrating achievements inspires the team to push limits and pursue innovative solutions.
Advice for Professionals in AI & Big Data Industry
Dr. Heping Liu emphasizes the importance of continuous learning for professionals looking to build a successful career in AI and big data. The industry of AI is constantly growing and staying up to date with the latest advancements is essential for remaining competitive. He also advises professionals to stay curious and open to exploring new ideas. AI is a field driven by innovation, and those who think outside the box will have the greatest opportunities for success.
