Anthony Behan on Driving Efficiency and Innovation in Traditional Industries
Anthony Behan is Global Managing Director, Communications, Media & Entertainment at Cloudera. In this role, they've shown an ability to constantly keep innovating and fueling growth within the business. Today, they share their insights with The Industry Leaders.
Could you tell us about your business and how technology has played a role in its evolution?
We’re data people. At Cloudera, we believe data can make what is impossible today possible tomorrow. We empower people to transform data anywhere into trusted enterprise AI so they can reduce costs and risks, increase productivity, and accelerate business performance. Our open data lakehouse enables secure data management and analytics, helping organisations manage and analyse data of all types on any cloud and on-premises, public or private. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. As a software company, technology is at the core of our business.
In what ways have you successfully integrated technology into traditional practices within your industry?
We help companies across industries build trusted Artificial Intelligence (AI) on trusted data. If we look into the telecommunications industry, many providers have invested heavily in AI to improve customer service. In the blink of an eye, it can do things that humans simply can’t, such as recognising the status of a customer’s service, whether there has been payment, dropped calls or bandwidth issues, and whether these issues have arisen. These insights immediately guide automated interactions, like chatbots, to have an empathetic and well-informed engagement with the customer. You might notice this as ‘the chatbot getting smarter’, but what’s happening behind the scenes is Cloudera-empowered AI driving better, smarter, faster outcomes.
Can you share a concrete example of a technological innovation that has significantly improved efficiency or productivity in your business?
AI is helping telecommunication providers to improve network resilience by making maintenance much smarter. For example, AI can analyse indicators of adverse weather events, correlating them with consumption patterns and other network data that may impact network performance or cause an outage. As a result, telcos can now predict where engineering assistance may be required ahead of time to make defences more robust.
It can also be used to predict patterns of human behaviour. For example, people may work from home more if the weather is poor, around national holidays, or events like teacher strikes put more strain on services in their home area. Likewise, if the weather is good and people are commuting into cities, this will put more strain on inner-city networks.
Finally, AI and ML tools can also forecast surges in traffic and autonomously analyse workloads to decrease network strain. We first saw these tools during the pandemic, with AI uncovering bottlenecks and enabling telcos to act, such as advising customers to change how they were connecting to networks. This helped to improve service quality during a very challenging time.
These are just three examples in the network – but how we interact with telcos, bill inquiries, upgrade requests or support queries are all dramatically transformed by AI.
Integrating technology is not always a smooth process. What challenges have you encountered, and how have you addressed them?
Trusted AI poses significant challenges. One notable example is the tendency of LLMs to produce ‘hallucinations’—i.e., outputs that read smoothly and seem plausible but are unfounded or nonsensical. Embedded biases, whether explicit or hidden, can also perpetuate harmful outcomes. Other challenges include the lack of transparency and explainability in AI systems and the need for continuous monitoring and inherent observability to maintain effectiveness. Addressing these and other difficulties is a precondition for trusted AI.
To do so, open-source AI is particularly primed to spearhead the AI revolution. Not just because it’s rapidly closing the feature-and-function gap with commercial/proprietary solutions but because it’s inherently transparent and adaptable. The benefits of open-source, proven in enterprise software, resonate even more in the context of AI. The ability to customise and scrutinise source code helps ensure trust and security, and the benefits of open source’s collaborative governance model help mitigate commercial AI’s “black box” problem. At Cloudera, we’ve been pioneering open-source for almost two decades. It’s in our DNA.
How do you see technology changing the landscape of your industry, and what role do you believe your business plays in this transformation?
With new AI use cases constantly emerging, the telco sector will increasingly leverage technology to improve products and services. However, the effectiveness of AI hinges on the quality of the data it learns from. Models trained on only a fraction of an organisation's data might overlook critical insights or generate "hallucinated" responses.
This means we’ll likely see more telcos utilising modern data architectures to underpin AI innovation. This will help them optimise networks, deliver more robust connectivity, and improve customer satisfaction. For consumers, that means more accessible interactions, fully digital engagement, fewer connection problems, and the kind of experience we expect from internet services.
How do you strike a balance between preserving valuable traditional practices and embracing technological innovation?
Many telcos have modernised and looked to the cloud to help them tackle rising data volumes and instant scalability. But certain types of information, such as customers' personally identifiable information (PII) or card information, will often require on-premises or in-country storage – to ensure organisations can maintain security and control over sensitive data and regulatory compliance.
We help customers address the complexity of running multiple concurrent workloads on different underlying infrastructures (like the public cloud and your data centre simultaneously) and make more informed decisions about their data architecture. We offer purpose-built data services allowing expansion across the data lifecycle, from the edge to AI, whether streaming massive data volumes (such as from the telecom network) or deploying and monitoring next-generation AI and ML models to help customers drive innovation.
What advice would you give to other businesses in traditional industries that are looking to leverage technology for growth and efficiency?
AI-powered automation is already driving significant margin growth by reducing costs. This isn’t the future. It’s here right now. But to truly drive transformation, telcos must ensure accurate, high-quality, trusted data drive AI models and determine how to manage and govern massive volumes at scale. And not just in ad hoc instances in pockets of the organisation, but as a part of the business's infrastructure.
In your opinion, what emerging technologies should businesses in your industry be paying attention to?
Telcos must deploy AI from the network edge to their core businesses. In addition to embedding AI to support back office such as billing and payment processing, network operations, etc., and front office, for example, customer service, sales and marketing, etc. functions, this might take the form of using AI to automate predictive maintenance for edge devices, like Radio Access Network (RAN) base stations and towers or Wide Area Network (WAN) endpoints. It could involve optimising the way the fleet is deployed or developing an ability to schedule the routes they take dynamically. It might entail leveraging AI to improve core network infrastructure's availability, performance, and security, e.g., supporting dynamic traffic prediction and load balancing across network technologies, adaptive network configuration, fault prediction and avoidance, and power consumption.