TELUS

It's likely that we're witnessing one of the most prolific periods for AI with major releases of impressive text and image generators such as ChatGPT, Bard and Dall-E. These generative AI models have been making headlines—sometimes writing the news articles themselves—but they are only one piece of the pie. Behind the scenes, many other AI technologies have been transforming industries and making companies more customer-focused, efficient and competitive.

Industries are looking to embrace new ways of working to benefit from these technologies especially due to aggressive competition along with an evolving regulatory landscape. The shift required to succeed in this environment is not only one that embraces new technology but also a profound change in the mindset of both leaders and employees. Enterprises that foster this cultural shift will be the ones to thrive, no matter where technology takes us.

Embracing Digital Transformation to Improve Customer Experience

Like any industrial revolution, an imminent transformation is ongoing, and although frightening to some, the benefits of responsibly operated AI systems are enormous. Not only is AI adoption accelerating businesses forward, but it is also helping to create smarter investments that will support customer experiences and reduce the strain on individual employees. For instance, by deploying conversational AI in our call centers at TELUS, we have provided agents with real-time and personalized data that enables them to support customers and provide faster response times to their inquiries, leading to improved experiences.

With application of confidential computing techniques, device management ceases to be a best-effort affair, because the designated portions of each device can now be assessed and fully trusted

Additionally, AI technologies offer industries the potential to leverage large amounts of data to optimize decision-making, increase efficiency and productivity, and reduce repetitive tasks so that employees can directly support customers with more complex challenges. For example, by joining massive network performance KPIs, we have adopted a proactive approach to network monitoring and issue resolution.

We have addressed network problems swiftly, sometimes even before they occur. This approach not only saves employees valuable time but also improves network reliability, leading to a better customer experience.

Collaboration as a Pillar for Success

A successful AI transformation needs proper alignment between business teams and data experts. Real tangible values cannot be generated without interdisciplinary collaborations. One effective approach is to organize stakeholders from multiple teams into pods or squads with common goals. The data experts must then adopt a strategic consulting approach to problem-solving, prioritizing the business outcomes of their work over their technology metrics.

In today’s competitive and fast-moving environment, having even a partial understanding can lead to significantly greater benefits than waiting for a complete understanding and missing a timely opportunity. By collaborating closely and gaining a deeper understanding of every stakeholder’s needs, data experts can deliver a continuous stream of actionable insights that the pod can learn from and use to refine further development.

Accepting a New Mindset

Although the benefits are high, the rapid pace of technological change has brought about significant challenges and risks for companies looking to embrace AI transformation. Implementing AI systems requires access to high-quality and relevant data, considerable computing power, and the ability to address factors outside of the technology, such as security and privacy compliance, end-user engagement, and trust in the insights generated. Furthermore, the willingness to change and transform work is critical for success, and the failure to consider these factors can result in projects that do not produce meaningful financial outcomes.

To reduce these risks, companies need to adopt an agile, explorative and adaptable mindset. TELUS has been using a multi-armed bandit approach to structure our prioritizations. Having a risk-weighted metric to compare opportunities helps us better select the right focus. Doing so, we are creating an effective "fail-fast and win-quick" culture where teams are encouraged to recognize when a project is unlikely to deliver the full expected outcome and when the time has come to move onto the next best opportunity. With an incentive to constantly explore alternatives, each squad can reduce the time spent on projects that may not produce a meaningful outcome and maximize the time spent on successful projects.

It is also important to track the right performance metrics and monetize at each stage of a project - not only once completed. Starting with insights in the form of consolidated data or statistics can be a great way to prove value early on before moving up to the more powerful tools that AI technologies provide.

Prioritizing Digital Safety

With the switch to AI, companies require a strong foundation in data management, collaboration across communities of data scientists and a relentless focus on prioritization of common goals. Equally important are processes required to efficiently ingest and then manage our data assets in a cloud environment while following high privacy and security standards to protect customers and employees.

All of these technologies do not come without risks. Without question, a safe, humanized AI experience comes through the intentional consideration of the impact of data on people and ensuring that there is a benefit every step of the way. By considering potential bias and using tools that allow users to explain how AI models concluded, we actively strive for fairness through the responsible use and enablement of data. For example, large language models (LLMs) are trained on billions of human-created data sets containing bias, stereotypes and mistakes. However, with the added layer of human oversight, we can potentially mitigate those issues to realize further benefits.

A Look Ahead

AI solutions are meant to boost productivity and allow us to be more efficient, but they all require oversight in terms of reliability, responsibly generated content and ensuring we continue innovating and creating new ideas, not regurgitating the same ones.

However, this adoption of AI is truly transforming how companies operate and create value for their customers while also allowing them to be more socially responsible. Embracing digital transformation, driving collaboration, prioritizing digital safety and accepting a new mindset is crucial as we move forward in ensuring that AI projects are successful. But we know that by embracing this change, we can tailor offerings and services to help meet specific needs and create a stronger and improved experience for our operations, and most importantly, our customers