Dubai, UAE — By 2030, every dollar spent on AI-powered solutions is expected to generate US$4.60 in economic value, according to global analyst firm IDC. The study also predicts that AI will contribute an astounding US$19.9 trillion to the global economy by the same year.
The implications are transformative—but what does this mean for businesses navigating the complexities of the digital economy?
In an exclusive interview with TRENDS, Robert Coyne, Senior Vice President and Managing Director for Tealium, shares his insights into how AI is revolutionizing customer experiences, data management, and business strategies.
How does Tealium see AI transforming the digital economy over the next decade?
We envision a digital economy where AI fundamentally elevates how businesses connect with their customers. Over the next decade, we expect AI to drive hyper-personalization, replacing one-size-fits-all approaches with tailored, data-driven experiences that resonate on an individual level. By leveraging real-time data and predictive analytics, AI will empower businesses to anticipate customer needs and proactively deliver relevant solutions, enhancing both satisfaction and loyalty.
This evolution extends far beyond personalization. AI will redefine how businesses harness data, transforming complex insights into actionable strategies that keep pace with changing market dynamics. However, with great power comes great responsibility.
By prioritizing data privacy, compliance, and transparency, we aim to help businesses navigate this transformative landscape responsibly, unlocking sustainable growth while maintaining trust with their customers.
What are the biggest challenges Tealium anticipates in scaling AI-driven data solutions across industries, and how can companies prepare to address them?
Scaling AI solutions across industries presents significant challenges, particularly around data quality and privacy. It’s a simple truth: without clean, consistent, and compliant data, even the most sophisticated AI systems fall short.
With regulations like GDPR and CCPA setting high standards, businesses must prioritize governance and accountability at every level.
There’s also the technical complexity of building and maintaining robust AI models. Challenges like model drift, integration with legacy systems, and ensuring scalability require deep expertise and continuous innovation.
Tealium has invested heavily in addressing these issues head-on. From robust data governance frameworks to strategic partnerships with leading technology providers, we are building solutions that are scalable, secure, and future-ready.
What trends in AI and data management are you closely monitoring as potential game-changers for business investment strategies in the next five years?
AI and data management are evolving rapidly, and we see several trends poised to transform business strategies in the coming years.
Generative AI and large language models (LLMs) stand out for their potential to revolutionize content creation, customer service, and even product innovation. These technologies enable businesses to operate with greater efficiency and creativity than ever before.
Edge AI and IoT are also key trends, offering real-time insights and unlocking the full potential of sensor data to drive smarter decision-making. At the same time, ethical AI and responsible data use are gaining prominence as organizations recognize the importance of fairness, transparency, and privacy in building customer trust.
As AI adoption grows, how can companies educate and empower their customers to use AI responsibly while maximizing its potential?
AI is a powerful tool, but its success depends on responsible implementation.
At Tealium, we take an active role in educating and empowering our customers to maximize AI’s potential while mitigating risks. Through workshops, webinars, and in-depth resources, we provide the knowledge and guidance businesses need to navigate AI effectively.
Ethical AI is central to our approach. We work closely with customers to ensure their AI systems are fair, transparent, and inclusive, while also providing clear explanations of AI decision-making processes and implementing techniques to mitigate bias.
Furthermore, we emphasize robust data governance, ensuring compliance with privacy regulations like GDPR and CCPA.
What measures are in place to ensure transparency in Tealium’s machine learning models, particularly for clients seeking explainability in their data analytics?
We recognize that companies need more than just accurate information—they need to understand the “why” behind the results. This is why transparency is essential.
For this reason, we prioritize tools and frameworks that make our models interpretable and explainable. Features like SHAP* values and feature importance analyses provide clients with clear insights into the factors driving AI predictions. This level of transparency not only enhances trust but also empowers clients to make informed, confident decisions.
We also uphold rigorous data governance practices to ensure accuracy, privacy, and security. By tracking data lineage and implementing quality checks, we create a foundation of reliability. Coupled with our commitment to ethical AI practices, including fairness testing and bias mitigation, Tealium sets the standard for responsible, transparent machine learning.
