Artificial intelligence (AI) has become a driving force in reshaping industries, and the ICT sector is no exception. At TELUS Digital, AI is at the heart of innovative solutions, enhancing customer experiences, streamlining operations, and upholding the highest standards of data privacy.
During the 18th edition of the Telecom Review Leaders’ Summit, Gagan Tandon, Chief Data and AI Officer at TELUS Digital, expanded on the foundational strategies that are enabling successful AI implementation, the AI-driven initiatives transforming operations at TELUS Digital, and the vital role of data privacy in maintaining trust.
With artificial intelligence dominating the ICT landscape, what AI-driven initiatives is TELUS Digital currently pursuing?
I want to set the stage a bit here; what we have found is that most of the companies who achieve the greatest success with AI initiatives have taken some steps before they actually started to work on AI use cases.
Firstly, they made sure that they have an established operating model where they can funnel AI use cases and understand what value AI provides, what the ROI is, and what the total cost of ownership (TCO) of actually taking on an AI use case is.
The second dimension addresses the foundational architecture, which comes as a result of bringing on more AI initiatives and more AI case studies. The key question that should be asked is ‘What is the architecture that will make it the most impactful?’
And the third dimension addresses the governance structure whether it is data governance or AI governance. This needs to be established to ensure there is no bias, and data privacy compliance is met.
Lastly, we need to question which reusable frameworks and accelerators to deploy. Many companies want to get started with AI use cases right away, and sometimes it works a lot better if you already have a framework or accelerator you can use to deploy the use case quickly.
The AI initiatives that TELUS and TELUS Digital have embarked on encompass workforce management, where we can predict the number of hours the workforce will require in the next few months or so, and customer interactions, where we ensure the customer interactions are much simpler and optimized during interactions with agents or chatbots.
Another initiative is case management, where we’ve integrated AI and automation to enable RPA bots to send data on AI model use cases. These use cases are then categorized to inform their design.
We have also worked on some ‘next-best-action’ case studies, exploring the right recommendations for the agent to relay to the customer during interaction, reducing the agent analysis time as well as customer churn, and definitely increasing the customer satisfaction of the entire process.
How does TELUS Digital balance AI’s rapid growth with data privacy?
Data privacy is very central to our initiatives. We believe that we have a responsibility to our employees, our customers, our shareholders, and our partners, and we also know that this trust will not be given or granted; it will have to be earned. Thus, we have established an AI governance board within TELUS Digital and joined hands with TELUS, where we vet all the data in our AI initiatives.
One standout example of our commitment is the TELUS.com GenAI support tool, powered by Fuel iX, our enterprise-grade AI engine developed by TELUS Digital. This tool is the first in the world to achieve international Privacy by Design certification (ISO 31700-1), which is a testament to our leadership in embedding privacy into AI innovation.
Through our efforts, we aim to understand where data is collected from, where the data is stored, what data is stored, what the security guardrails regarding the stored data are, what data is shared, what cannot be shared, and which framework ensures the data never leaves the bounds of its respective domain. This also means that, if a customer says, ‘Delete my data; I don't want my data to be retained by you,’ we will make sure that we have enough processes in place to address the request.
We are not just setting up an AI governance board or data governance board for data privacy, we have also set up frameworks where an accelerator (that is pre-trained on PII and PHI) can scan texts and images and mask the data before it is actually used for AI training. This framework has been deployed to healthcare clients, telecom clients, and financial services.
In your opinion, how will AI transform global business operations in the next five years?
The key business functions, as anybody within the telecom industry would know, are network management, network capacity management, CRM, business process management, workforce planning, and HR and finance. Of these business functions, many companies are already embarking on journeys to solve the problem using AI.
For example, in network capacity management, AI can detect network traffic or network traffic congestion and divert the traffic to the right nodes, depending on where the problem may have occurred. In terms of network design, AI can select the right network configuration to achieve optimum output through a telecom network itself.
On the CRM side, AI is being used to understand the next best action, as I previously mentioned, and suggest the right recommendations to give to the customer. Generating leads through AI can also help in sales and marketing, where it helps to understand the consumer’s behavior. You can gather data from sensors and compile the different interactions the customer has had by demographic. This knowledge can then be used to target those customers.
Overall, I believe that AI is going to transform almost every business function, both in small and big ways, and it will be here to stay.
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