Future AI: Transforming Enterprises

Jonathan McKay of La Fosse, Angie Ma of Faculty, Richard Davis of OfCom, Neil Taylor of Mastercard, Mike Bugembe of United Nations, Natalie Cramp of Untapped Asset Consulting, and Elisabeth Ling, a Strategic Product Advisor, came together to create an exceptional panel of speakers. Throughout the evening, the panel explored the strategic challenges enterprises face when adopting AI, the impact of AI on the job market and the essential ethical considerations.

“AI is now becoming a strategic importance for every business that’s looking to stay ahead, especially in this digital evolving world,” said Claudia Cohen, Associate Director at La Fosse, to kick off the evening.

The transformative power of AI

The panel considered what they are currently seeing in the market and how their organisations are navigating the challenges and opportunities presented by AI. 

“So we, over the 10 years, we’ve worked with over 300 businesses and organisations. So it’s really interesting to see their journey and how they use AI to improve their business,” Angie Ma, our Co-Founder said. “We see that people are rushing to implement AI tools but that’s kind of not really capturing the opportunity because that’s almost getting caught up with the hype cycle. It’s about how do you find that strategic transformative investment and get through that. So that’s one aspect. Second is that it is very much top of the agenda for a lot of board and leadership conversations […] there is a sense of urgency. But the board and the leadership find it hard to think strategically about it.”

Today, AI is the biggest driver of business reinvention, as it has the potential to make a difference in just about every industry. The panellists explored some of the use cases they are seeing in their own organisations, and how it’s making an impact.

“Even with the UN, we’re finding ways that we can help migrants that are on the move that are prone to abuse, just because of generative AI, we can employ those significantly quicker than we used to in the past,” said Mike Bugembe. “So I do think we do need to take a slightly different look at the way we look at Gen AI to find some of these use cases that perhaps we hadn’t thought of previously.” 

How to maximise value in GenAI

The panellists had plenty of ideas on how you could maximise the value of GenAI in your business. 

Angie Ma stressed how important it is to integrate AI into the backbone of your organisation and make sure you follow the right governance to promote the development of robust AI solutions. “What generates value is making sure that the AI solution is integrated in the process, core processes of an organisation, because if that’s not, then that’s not going to get value. Secondly, is making sure, so some of the organisations we see, the leaders will say, gosh, we’ve got hundreds of AI initiatives happening, but they’re everywhere, all over the place. If they’re not connected up, then you’re not going to get a lot of value out of it, and it also adds a lot of risk, risk of not having central governance, risk of not being able to, even this, things like biases. So making sure your systems are very connected, very integrated is certainly key, and I think the last point is for the AI solutions to really work, to have that, I think you were saying how important the governance nowadays is, that central, being able to have that oversight is the key”. 

The panellists covered how those adopting AI often don’t look at the bigger picture. 

“So, for example, GenAI people often think of chatbots, they can just throw in a chatbot to improve customer service, for example. But actually, if you care about the KPI of your customer satisfaction, you actually have to look at the entire customer service workflow. […] You actually almost reimagine that whole process of customer service. And I think those are where the most powerful and transformative results are, instead of throwing a chatbot at random places,” continued Angie Ma. 

The evolution of skills and the impact on jobs

Concerns surrounding the influence of AI on the job market prompted a discussion on how it is shifting jobs and changing the type of skills employers are looking for.

Natalie Cramp started the conversation by highlighting how the pace of change does not always meet expectations. “The first thing I always reflect on is my work for the London French Paralympics, my first sort of data job. […] And we have a few skill gaps, we have chefs, we have security guards, and we have customer service people. […] About four years, five years later, six years later, I sat on a board for Heathrow and their open skills, and the whole thing was jobs of the future, that’s what the shortages were, chefs, customer service, security, the same things. And so I think my little caution is that we think things will move faster than they do.” Natalie added “It will change jobs, it will create new jobs, and it will lose other jobs”.

“I had a robotic process automation team when I was at Lloyds banking group, and one of the teams I had there was looking at processing fraudulent applications for credit cards,” Richard Davis shared. […] “I said, how are people feeling about the robots coming in? She’d been working for Lloyd’s for 20 years at this point, and she said, it’s brilliant. I’m like, this is not what I was expecting. She said, we’ve become more human. I used to spend my whole time copying and pasting information, just there not talking to anyone, not doing anything. And she said, as a result, the robots coming in and taking over the simple things, she’s now stood up. She’s talking to people, doing more complex broad faces, looking at patterns and looking at things. It’s basically doing the things that humans are really good at, and the machines are the things that machines are good at. So will this take jobs? Absolutely. It will definitely take jobs. But it will also create a lot more, in the name of people, to do the things that people are good at, which is creativity and thinking.”

Neil Taylor emphasised how AI has uncovered the need for evolving skills rather than job losses. “We have about 13 and a half thousand individual models that manage our monthly forecasting and treasury functions. […] But that hasn’t taken away jobs in the finance function. It’s taken tasks away. That’s the difference is it’s tasks that are being taken over, not necessarily jobs. And what it’s done for us is change some of the skill sets that we ask for from prospective employees.”

GenAI in the next five years

Before the discussion was wrapped up in time for questions, the panel thought about what GenAI might look like in the next five years.

Neil Taylor concluded, “First of all, very briefly, on the technology side, the infrastructure, physical hardware, at the moment it’s packed. So it’s not been designed for what it’s actually doing. […] So I think there’s going to be quite a distinct refining in actually the physical technology that we build this AI on top of. Take a fair bet on that. And the other side of the coin is the data. We talk a lot about large language models. I think the next thing we’ll start to see is small language models that are just as good as the large ones, because at the moment you need vast amounts of data to train fairly rudimentary capabilities, whereas for a lot of industries, a lot of sectors, sub-sectors, they don’t have those vast amounts of data to fine-tune the models to their own environment. So I think we will see the development of small language models that will be just as good or close enough that will enable more sectors to take advantage of this style of technology.”

Would you like to learn more about the topics discussed in this panel discussion? Let’s talk about how we can support your organisation to get on the right track with AI. Click here to contact our team.