The human challenge to AI adoption at banks
Transcription:
Transcripts are generated using a combination of speech recognition software and human transcribers, and may contain errors. Please check the corresponding audio for the authoritative record.
Chana Schoenberger (00:09):
What about the risks? What are the biggest risks you see right now for AI in the sector?
Vikram Sivakumar (00:14):
Where should we begin? Banks are very good at managing risks by nature. I mean, that’s why I bank with a bank. The conversation started at the trust level. So maintaining my brand and my trust with customers is kind of paramount to it. And I think it’s a conversation that is… When you talk about AI, it’s not about how do I operate at speed and safely, it’s about how do I operate safely and at speed in that order. And so trust is a big part of the risk that we talked through. The other side of it is the competitive lens of it, which is the inaction is also a risk of some form. And so how do we balance that? Look, I think banks do that better than most people in the world, and that’s one that they’ve managed for many, many years and just a new muscle to learn and completely expect them to do that.
Kirti Choudhary (01:05):
I’d say overall agree with Bikram. Risk management is sort of first nature to banks. I do think there’s a bit of a questioning around the posture of it, of how do you not be too conservative? At the same time, how do you anticipate different items and how do you not treat AI and models that it needs to sit above how a human would behave or an employee would behave in that same setting? I’d say in terms of specific areas where there is a lot more thought given is potentially cyber threats, fraud, increasingly third and fourth party risks, and finally just operational risks based on what these models might do when they become customer facing or bot facing.
Chana Schoenberger (01:50):
Yeah. There’s this whole question of what happens when my agent talks to the bank’s agent and there is a human somewhere, but the humans are not so involved.
Kirti Choudhary (02:02):
And I think there’s a big liability question there as well, but part of this is we can either first try and solve every question in every edge case, or we can run some experiments, see how things shake out, learn from it and make some progress.
Chana Schoenberger (02:19):
Tell me about how the human side is involved here. Obviously banks are people.
Vikram Sivakumar (02:23):
100%. I think it’s the crux of the challenge. We can get the tools out and then we’ve got to get the change done over a period of time. It is one that we are coming to grapple with. It is one that we are starting to recognize as the change management issue, but one where the playbook is not necessarily fully available for everyone to play out with. When I go in, we do a lot of work around the change management aspect and we start with a survey and there’s always three concerns that come up from the folks and the three concerns are in different orders, but always the same three. I’m afraid of losing my job. I don’t trust AI and I don’t have time to learn. And solving that therefore is both a conversation about how do you create that structured approach and environment for a team to learn and behave in a new way, but also showing them that they have a job at the end of that transformation.
(03:15):
It isn’t about taking their job away. There’s also a part of the leadership conversation we need to have, which is how do you model the change and not mandate it when you’re in a town hall and if you’re asked what is your favorite use case, you can actually talk about it in authenticity and in detail. So it’s a change both for the ground, but also both middle management and top management about taking the org along on that journey. More and more, I think the last part of it is that boards are also starting to ask organizations about what is that pathway for the rest with the post AI era? How are we responsibly taking care of our talent? What does that mean from both an upskilling, re-skilling pathway rather than a, hey, we got here and we don’t need people anymore. So that’s a more of a mature conversation that the workforce transformation itself is one that we’re hearing more about and we need to talk a lot more explicitly about.
Kirti Choudhary (04:05):
I think the piece I would add there is just culture and culture is just so important to organizations to both in which how do leaders signal that they’re AI first institutions that they want to make progress, but they want to make progress not at the cost of humans, but taking humans along on the journey. And in many ways, how do they signal and build that culture where organizations start to rally behind it? And again, don’t think that they’re being replaced, but think that they’re being augmented and that there will be new jobs which are needed in the AI era.
Chana Schoenberger (04:46):
Great. Great. Well, thank you so much for coming in. I really appreciate it.
Vikram Sivakumar (04:50):
Thanks for having us.
Kirti Choudhary (04:51):
Thank you.
