#242: Tell me about the future of AI… Here Be Dragons?

This week on the Data Futurology podcast, we welcome Orla Glynn, Executive – AI, Reporting, Insights and Automation Configuration at Telstra. Glynn leads one of the biggest groups of data specialists to drive innovative AI and analytics across the company.

With more than 600 people working in her team, Glynn has to juggle competing priorities while aligning that team to drive greater innovation across the organisation. At the same time, she needs to work to gain executive buy-in while also articulating the risks and strategies for mitigating those risks.

During the podcast, Glynn also describes some of the impacts AI has on organisations and job roles. It’s undeniable that there are some big changes and disruptions coming in. Successfully engaging with data and AI will come down to how effective communication and the change management programmes are.

Glynn also talks about the concept of “productive discomfort”, and what that means. Essentially with emerging areas of technology, the same assurances aren’t there. The question then becomes how can the leadership team be positive with the steps it takes through the uncertainty.

For more deep insights into AI leadership in large and innovative enterprises, tune into the full podcast!

Enjoy the show!

Thank you to our sponsor, Talent Insights Group!

Join us for our next events: Advancing AI and Data Engineering Sydney (5-7 September) and OpsWorld: Deploying Data & ML Products (Melbourne, 24-25 October): https://www.datafuturology.com/events 

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

“At the moment we’re focusing on making certain the board and C-suite are very much engaged in transformation and that they're aware and educated around both the value and opportunities that we have, but then also the risks that we need to trade off and how we would look to do that.”

Orla Glynn, Executive – AI, Reporting, Insights and Automation Configuration at Telstra

WHAT WE DISCUSSED

2:18: Felipe introduces Orla Glynn and the topic for this podcast discussion. The first discussion point is on Glynn’s “non-linear” path into AI.

5:21: After studying humanities, and then working in law and finance, how did Glynn take her first steps into data roles?

7:24: Glynn summarises what she’s working on in her current role.

11:13: How data leaders can drive change across organisations of the size and scale of Telstra.

13:14: The value of making the data journey a team effort.

13:54: How are Telstra’s data teams measuring the value of their work?

15:25: Given the ongoing development in AI, what are some of the areas that are most impacted by technological progress, and what are the changes that are needed to address this?

19:11: How can you resolve the tension between building for the future and what is required in terms of short-term priorities?

20:33: What does “productive discomfort” mean and how does that work as a dynamic within organisations?

21:36: The first audience question comes in: How can a leader of a team of 600 people keep maintaining AI, innovation and progress?

23:17: What are the challenges of managing staff remotely and does this change the dynamics of management?

24:48: What is the most effective way of measuring the uplift of skills?           

26:05: What is the difference in presenting AI capabilities compared with data analytics capabilities?

29:30: What reading material would Glynn recommend for people that want to learn more about adaptive leadership and productive discomfort?

32:15: How is the world going to change as a consequence of AI and disruption?

EPISODE HIGHLIGHTS

• “The common thread throughout my career has very much been my drive to constantly be learning and as well as that good sense of curiosity and problem-solving.”

• “In my finance roles, I was looking at the investment banking platforms or the next migration that was happening and I sat as the translator between the tech and the business and finance. And then through many different restructures, I ended up in an operations division which then added on the role of Chief Data Officer. Because I had a strategy background, I ended up helping around what that function would look like. From there I took a leap.”

• “I chose roles where I was going to be exposed to those learning opportunities as opposed to getting promoted simply because I wanted to have a title.”

• “The team themselves have lots of PhDs and Masters and love doing certifications and we offer them and we're building content with them that's the right content for them. But then more broadly across the organisation we're looking at the very early stages of this but we're trying to figure out how to make it in a way that's sort of more gamified and more connected to people’s day-to-day jobs as well.”

• “At the moment we’re focusing on making certain the board and C-suite are very much engaged in transformation and that they're aware and educated around both the value and opportunities that we have, but then also the risks that we need to trade off and how we would look to do that.”

• “We look at what the high-value missions are, and we've categorised all of our work into three layers and of the high-value missions we've fully quantified that. As a result, we have quite a sizable value pool to go after.”

• “When you start to think about the divergent workforce, and if you think about what we have today, where we've got policies and procedures and codes of conduct around our human workforce, well, what does that look like when you've got an AI-driven workforce that's making decisions? And therefore, how might we monitor that differently? And then if we're to monitor that with AI, how do we build that ecosystem today?”

• “Engaging with the C-suite and the board on the tension between data and security, short-term and long-term goals means productive discomfort. A lot of it is the education and getting them to understand the risks but also balancing it with the opportunities. Because we can tend to go too far with risk and then at the end of the day, we're here to improve the customer experience and grow our business.”

• “You can't just jump in to solve some of these problems that we don't know yet. There's no solution, there's no roadmap that we all are working towards and it's actually about being comfortable with that discomfort.”

• “Good engagement comes back to my love of learning. I do something few executives do. But I don't take any meetings on Fridays intentionally. Instead, I spend my Fridays reading and just as much as possible having time to think and just that ability to absorb as much as possible.”

• “If you want to be innovative, you have to actually let your brain wander.”

• “The business strategy drives the value and data and AI enables that. We're trying not to say you've got to have an AI strategy and a data strategy. We've got a corporate strategy and it's enabled by data and AI.”

---

At Data Futurology, we are always working to bring you use cases, new approaches and everything related to the most relevant topics in data science to help you get the most value out of these technologies! Check out our upcoming events for more amazing content. And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. It really helps new data scientists find us.