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As the artificial intelligence (AI) genie jumps out of the bottle and into big tech, no industry — from the cloud to telco to smartphones — is left untouched.
With the potential to deliver innovative generative AI solutions to billions of users worldwide, how telecommunications companies intend to deploy AI is an increasingly important question.
Techopedia sat with Jitin Bhandari, CTO and Vice President of the Cloud and Network Services (CNS) at Nokia, to discuss the company’s AI-powered networks and the technology behind the company’s solutions for customers, service providers, organizations, and governments.
We also discuss telco-specific guardrails, how AI can improve cellular networks, and how AI and engineering complement each other.
About Jitin Bhandari
Jitin Bhandari is the CTO and Vice President of Nokia’s Cloud and Network Services (CNS) business group.
The CNS portfolio includes software solutions across core networks, orchestration, assurance, analytics and insights, security, private wireless (CSP and enterprise), and enabling 4G, 5G, and Internet of Things services for mobile, fixed, and cable networks.
Jitin leads software technology strategy and disruptive innovation for the mid & long-term horizon, accelerating the transformation of networks, operations, and analytics to cloud-native, 5G, and beyond.
Jitin is known as a communications visionary with end-to-end expertise in networks, operations, and services with a unique ability of big-picture strategic focus and a proven ability to deep dive and execute. Jitin has 20+ years of experience in the software/IT/telecom industry and is based out of Austin, TX.
Key Takeaways
- A new wave of AI and GenAI is poised to transform network operations, automating tasks, personalizing services, and improving network security and efficiency.
- Nokia highlights the critical role of network understanding in developing effective AI solutions for telecommunications challenges.
- While AI is powerful, Nokia stresses the importance of human-centric design.
- AI should augment human capabilities, not replace them, and responsible AI practices are crucial to ensure ethical and unbiased solutions.
- Open-source tools, building strategic partnerships, and collaborating with leading AI companies and research institutions are all part of the answer.
- Show Full Guide
‘The Future of Networks Will Be Conversational’
Q: Nokia has a long history of innovation. Can you outline Nokia’s vision for the future of Artificial Intelligence and how it will shape the technological landscape?
A: Nokia, with Bell Labs’ heritage, has a rich lineage in driving technology advancement and innovation, and AI is an integral part of today’s strategy and our future vision. We strongly believe that future networks will be conversational in nature.
We see a future where AI (both traditional and GenAI) seamlessly integrates with network autonomous operations, helping customers simplify their networks; monetize faster by expanding industrial and enterprise opportunities; and lower costs with automation in the programmable digital ecosystem.
Q: Is Nokia working on new privacy and security technologies specific to AI environments? If so, what type of specific tech do you use or think is best and why? How is that tech different from what other providers offer?
A: AI safety is a critical focus for us, with specific initiatives in hallucination management, explainability of models and privacy in smart data annotation, and telco-specific guardrails.
Like most organizations, we’re committed to responsible AI practices, incorporating LLM [large language model] benchmarks and domain-specific knowledge. However, our approach differentiates itself by focusing on network-level security, providing a robust foundation for secure AI implementation across the entire network.
Q: What is your biggest concern when it comes to GenAI?
A: The biggest concern with GenAI, in my opinion, is potential bias.
Understanding causality in inference is a big challenge for GenAI. AI models are trained on data sets, and if those sets are biased, the resulting AI can perpetuate those biases.
One of our priorities is to use diverse and inclusive data sets to mitigate bias in our AI models. Likewise, response robustness is crucial, as low-quality responses can undermine the effectiveness of applications.
Infusing relevant knowledge, prompt engineering, and implementing safety measures are essential for responsible and accurate responses.
The Future of the Human-Machine Relationship
Q: As AI continues to evolve, how does Nokia envision the future of human-AI collaboration? If you have any technology or concrete case examples you want to share, those would be welcomed.
A: GenAI will drive increased productivity in network planning, deployment, troubleshooting, care and services, and security.
By enhancing knowledge discovery and simplifying the implementation of intent-based autonomous operations, GenAI will have a broad transformational impact on CSP operations.
Nonetheless, GenAI should be viewed as a powerful co-pilot in making networks conversational to humans, not a replacement. It should deliver insights, automate tasks, and free humans to focus on strategic decision-making.
Take our GenAI-enabled MX Workmate, for example, which was announced earlier this year at the Mobile World Congress (MWC).
This is a set of tools designed to improve communication between industrial workers and complex machinery, using AI to understand real-time data from machines and translate that data into clear, human language.
This helps workers to better understand how machines are functioning, troubleshoot problems, and improve overall productivity and safety.
Nokia Focuses on AI Research and Solutions for Analytics, Trust, Environment and Business
Q: Within the vast field of AI, what specific areas is Nokia focusing its research and development on? Are there particular industry verticals where you see Nokia’s AI making the biggest impact?
A: There are several areas where we are focusing our research and where we see our AI making the biggest impact on communications service providers (CSPs) and enterprises.
Using Nokia’s AI solutions, our customers can analyze vast amounts of data and proactively identify and resolve network issues before they impact end users. This leads to significant improvements in network performance, reliability, and overall user experience.
Our industry’s future goes beyond connectivity. We unlock network intelligence through innovative commercial models and AI-driven, contextual recommendations to drive new ways of delivering quality services.
For example, our customers can offer data products and intelligence via application programming interfaces (APIs), allowing them to create new AI use cases and monetize new revenue opportunities.
Environmental responsibility is a top priority of ours and the industry as a whole.
Our AI solution reduces CSPs’ energy consumption and carbon footprint by up to 30%, optimizing network resources, identifying areas for improvement, and contributing to a more sustainable future.
In a world where devices surpass the human population and security breaches are increasingly sophisticated — using AI — CSPs must be proactive and responsive to cybersecurity threats.
From our side, our AI-powered security solutions fortify network defenses and help our customers with an 80% improvement in incident analysis responsiveness.
AI integration goes beyond network performance to minimize costs and improve service delivery. As an example, AI can automate tasks, leading to an 85% reduction in field dispatches for on-site personnel, or imagine a 90% reduction in alarms through AI-powered correlation, root cause analysis, and automation.
Open-Source or Proprietary Tech? Strategic Alliances or In-House Development?
Q: Does Nokia see a future in strategic AI partnership, the development of proprietary technology, or are you leaning towards open tech that would easily integrate and support developers with open-source AI?
A: Our approach is a blend of open-source adoption, strategic partnerships, and in-house development, allowing us to deliver the most effective AI solutions.
We believe that open-source AI tools and frameworks are crucial for accelerating innovation and fostering a vibrant AI ecosystem; however, we also recognize the need for proprietary technology in specific areas to address complex network challenges.
What Nokia Brings to the AI Table for its Customers
Q: How can Nokia’s customers benefit from GenAI?
A: GenAI unlocks a wealth of opportunities for our customers, such as enabling a network to automatically adjust bandwidth based on real-time usage patterns as well as personalizing network services.
Other benefits we see are:
Automated Network Optimization: GenAI can dynamically adjust network configurations in real-time, ensuring optimal performance and resource utilization. This translates to a more efficient network, with less congestion and faster data speeds for users.
Predictive Maintenance: Network issues can be costly and disruptive. GenAI can analyze network data to predict potential equipment failures before they occur, proactively minimizing downtime and ensuring network reliability.
Personalized Network Services: GenAI can personalize network services based on the growing complexity of customer demands. This unlocks a huge opportunity for industries such as gaming. For example, a GenAI-enabled network will prioritize bandwidth for gamers during peak hours or optimize video streaming quality based on device capabilities. This level of personalization will become a baseline criterion in the 5G Era and beyond.
Self-Healing Networks: Network disruptions are inevitable, but GenAI can significantly reduce their impact. By analyzing network data and identifying the source of an issue, GenAI can initiate self-healing processes, automatically rerouting traffic and restoring functionality with minimal downtime. Self-healing networks not only improve network resilience but also reduce the need for manual intervention by network operators.
Improved Network Security: GenAI can analyze network traffic patterns to detect anomalies that might indicate a cyberattack. This allows for early intervention and mitigation of potential security threats, safeguarding sensitive data and user privacy.
Reduced Operational Costs: By automating network tasks, improving resource allocation, and minimizing downtime, GenAI can significantly reduce operational costs for network operators. This allows them to reinvest resources into network expansion and innovation.
As GenAI technology continues to evolve, we can expect more applications that will further enhance network performance, security, and the user experience.
Strategic Business Planning: Working Today for the Future
Q: Looking ahead, what breakthrough or innovation in AI do you foresee on the horizon, and how is Nokia preparing to be at the forefront of this advancement?
A: Multi-modality support, higher reasoning abilities, and the combination of GenAI and causal AI are expected breakthroughs that will enable creative applications, improved decision-making, and automation.
Likewise, GenAI can accelerate network transformation for CSPs that want to capitalize on massive amounts of untapped data. With our assistance, customers can reevaluate their current automation level and scope based on new AI capabilities.
By delivering large language models that are fine-tuned specifically for telcos, we help our customers understand which AI solutions (GenAI and otherwise) will advance their business objectives, particularly towards autonomous networks that sense, think, and act.
Nokia’s Cornerstones of Innovation: Network, Openness, and Human Focus
Q: What will make Nokia´s technology play a vital role in the future of AI?
A: Three key factors will solidify Nokia’s position at the forefront of AI, and each one builds upon the other: network expertise, openness, and a human-centric approach
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Network Expertise and Domain Knowledge
This is our bedrock. For decades, Nokia has been a leader in telecommunications infrastructure.
We understand that with the increasing cloudification of networks, the data, and the unique challenges our customers face, especially as the digital ecosystem in which we play continues to expand and involve new partners, new ways of working, and new ways of delivering services.
This deep understanding is crucial for developing AI solutions that are tailored specifically to network challenges.
Imagine trying to optimize traffic flow in a city without knowing the layout of the streets — that’s the disadvantage many AI companies face when they lack a strong foundation in network engineering.
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Focus on Openness and Collaboration
We embrace open-source AI tools and frameworks, which allow us to leverage the collective intelligence of the global AI community and build strategic partnerships with leading AI companies and research institutions, gaining access to cutting-edge research and expertise.
