Koel, with over 27 years of experience in the tech industry. She has led major transformations and the adoption of new technologies at companies like Ericsson, Cisco, and Tata Communications. Her expertise spans wireless and wireline domains, covering multiple generations of fixed mobile technology.
In a recent conversation with Women Entrepreneurs Review Magazine, Koel shares insights into the evolving landscape of managed services in the telecommunications industry. She discusses emerging trends shaping the future, strategies for leveraging automation to drive innovation, and innovative approaches for accelerating AI-driven cloud adoption while ensuring robust data security and compliance.
Given the rapid advancements in cloud computing and AI, how do you see the current landscape of managed services evolving in the telecommunications industry? What emerging trends are shaping the future?
The technology landscape is changing at a very fast pace with rapid strides in cloud computing, cybersecurity and AI. Managed Services has more or less become the norm today with most of the enterprises and service providers believing in the power of the same. With the advancement of technology, there are lot of innovations that we are seeing in managed services space and there is still immense possibility. Most of the enterprises today have their applications and data across private and public cloud, and from a managed service provider, the key requirement is to maintain similar SLAs irrespective of where the application is hosted. This requires advancement in tools for measurement, reporting, fault management and assurance across private and public cloud infrastructure and close working with all the public cloud providers. We can see use of AI increasing to identify repeated failures and predictive maintenance planned from these inputs. Managed services are becoming more integrated with AI-driven analytics, allowing telecom providers to offer predictive maintenance, enhanced customer support, and optimised network performance. This shift is helping telecom companies reduce operational costs and improve service quality.
As automation becomes increasingly integral to creating digital ecosystems, what strategies should telecom companies adopt to ensure that automation not only enhances efficiency but also drives innovation across the industry?
We have seen the industry evolve from use of Network Management systems to use of automation for network assurance and evolving to use of AI. The primary driver for uptake of automation in companies is to improve efficiency, both in customer operations related processes as well as internal processes. However, to garner the complete value of automation in industry, there are few key strategies that companies need to adopt. First, it is necessary to involve all the teams in the company and to communicate that it is not the IT teams’ responsibility, but each individual needs to think on what part of the work that they are doing could be potentially automated and how will it help the bottom line and in some cases also the topline of the company. Once this approach is ingrained from the leadership into every employee of the company, innovation can be driven across the industry. This would involve significant investment in AI and ML both in terms of tools and systems and also extensive training. The other strategy could be collaborating with startups in AI space to support the AI initiatives.
The use of AI in Managed Services is transforming the way networks are monitored and maintained. How do you envision AI evolving in this space, particularly in predictive maintenance and customer experience enhancement, and what strategic shifts should organizations consider to leverage these advancements effectively?
Telecom companies have been in operation from many years across technology shifts in mobility from 2G to 5G and in wireline from Copper to Fiber with higher and higher bandwidth support. A significant part of the Opex of the companies still is involved in fault management and mitigation activities. There are databases with years of data available across the industry. With advent of AI, we finally have a mechanism by which we the AI models can be trained by ingesting the data and available and come up with clear understanding of repeated failure and optimized predictive maintenance schedules. There are multiple layered approaches to this. For generic faults which are common across networks, the AI engine could potentially be built by a third-party agency which is operator and vendor agnostic and the database would be very rich covering all the failure scenarios across all operators globally. This approach would require a strategic shift to develop an open ecosystem in which all operators are sharing generic fault information to be able to improve efficiency across the board. The other layer could be specific AI engine built by each operator, which could come up with localized issue resolution. In this approach all telecom companies need to invest in their own AI model.
AI-driven predictive maintenance can reduce network downtime by up to 30% and maintenance costs by 20%. The lowering of faults achieved through predictive maintenance also has a direct impact on improving customer satisfaction.
AI is already being leveraged for improving customer interfaces on digital channels, by being able to understand the complete history of the customer and able to predict possible issues and solve them proactively. AI-driven chatbots and virtual assistants can handle up to 80% of routine customer inquiries, providing instant support and personalized recommendations. However, there could be significant improvements in these areas by continuous investment. An open ecosystem based on collaboration across the industry could be significantly beneficial.
Cloud and AI are transforming managed services, but there are challenges in seamless integration. What innovative approaches could telecommunications providers take to accelerate AI-driven cloud adoption while ensuring robust data security and compliance?
As we move deeper into Cloud and AI, the boundaries between private Cloud and public Cloud are getting blurred as companies move their workloads across them, sometimes even dynamically based on load and other factors. Telecom Companies are getting into partnerships with Hyperscalers to achieve these scenarios. As we move into an AI era, information and data sharing between companies will be required for better training of the AI models so that we can generate better output for improving efficiencies. All these are leading to enhanced requirement of data security and compliance. Telecom companies will require to map all the processes end to end, recording the changes that need to be done under the new paradigm of Cloud and AI and devising specific data security practices for each process. Implementing robust data governance frameworks and compliance protocols will become essential to protect sensitive information and meet regulatory requirements.
Your point of view on gender diversity in technology and leadership roles? As a technology leader, throw some light on the Global Services business and STL’s future outlook.
There has been considerable focus on the increase of diversity across the board, though we still have a long way to go as an industry, across the globe, in this aspect. During my career journey so far, I have been fortunate to be able to get the opportunity to work across various geographies and cultures globally and I can vouch on the power of racial, cultural, geographical and gender diversity in a technology leadership role. Diverse teams bring a variety of perspectives, which can lead to more creative solutions and better decision-making.
Seeing women in leadership roles can inspire the next generation of female tech leaders. It’s about building a pipeline of talent and ensuring that women have the opportunities and support they need to advance their careers. At STL, we have over 8% of women in senior roles, with a gender ratio of 18% across the organisation. Apart from our plants, we have nearly 34% (and growing) gender ratio in our central functions, many of these women being in senior and leadership roles. As a part of building our young talent pipeline, we have hired a vibrant batch of Trainees this year, with 14% being women engineers/management trainees.
With its automation-led digital ecosystem creation capability, STL’s Global Services business has been making significant strides in India and the UK. It has been a major part of India’s digital growth story, blending the spirit of nation-building and digital infrastructure creation with automation. Global services strengths lie in Networking, Security, Data Center and Cloud and Fiber deployment services. Our focus area going forward is to intensify our focus on Cloud technologies and deeper into cybersecurity. Apart from this we have taken up mining and energy sectors for our foray into private sector and we are developing solutions around Industry 4.0 with our ecosystem partners.
Looking at the massive opportunity and the criticality of this business, we have recently announced to demerge and publicly list the Global Services Business of STL. The demerger will enable both businesses STL and the new Global Services entity to grow independently with more agility and focus, creating strong, distinct platforms for achieving their goals. This will also bring more value for investors and strategic partners having a specific interest in the Global Services Business.
