Right across industry sectors, organisations large and small are increasingly looking to technology to drive efficiency and competitive advantage.
So-called ‘digital transformations’ have been underway for some years, but the rapid pace of technological development demonstrated by the rise of artificial intelligence (AI) is throwing up particular challenges, says John O’Connell, director of software solutions at Expleo.
“You may find that a competitor has already cleaned up their data and so they can leapfrog you,” he said.
One notable example of a sector working to innovate is investment funds, something O’Connell sees in his role as vice-chair of the Irish Funds Emerging Tech and Innovation working group, with the funds industry at the forefront of considering new approaches to data management and digital transformation.
Areas where artificial intelligence is making significant inroads include onboarding, user experience, risk management, anti-money laundering (AML) and fraud detection.
Crucially, this tells us something that is applicable well outside funds or, indeed, the financial services sector at all: a successful digital transformation means being able to leverage data.
“Ultimately, it’s all about analytics,” said O’Connell.
Data protection and other legal issues were also important considerations, especially when implementing AI solutions in highly regulated environments such as funds, he said. However, whatever area is being worked on as part of a digital transformation, one fact remains central: if the goal is to make use of data, then that data has to be in good order.
“The question then becomes, how do you get started? Well, you need to put the work in: you need good data management and there are no shortcuts,” he said.
C-suite support is a must, he said, with this working down to become buy-in from the entire organisation. So, in the case of AI, establishing a culture of exploration and continuous learning becomes essential for successful implementation.
“Encourage your teams to experiment with it and learn how to do prompt engineering,” O’Connell said.
A lot of business leaders today complain of a shortage of skills and talent around AI. However, building internal capabilities through upskilling existing teams and creating cross-functional collaboration can help.
The question then becomes, how do you get started? You need good data management and there are no shortcuts
Having cleaned the data and got buy-in from the team, a digital transformation stands a greater chance of success, but it still requires deep strategic consideration.
“If you take the legal challenges, the skills shortage and the change management, and you need the business case, you can see that it really is a journey. Some may say they can jump right into it, but you need to start with the business case and look at the data you have; you could have hundreds of datasets.”
Some technologies, like Microsoft Fabric, make the taking of data from disparate sources much easier, but it remains the case that the transformation journey requires organisations to balance innovation with practical considerations around data quality, regulatory compliance, and organisational readiness.
Nevertheless, by focusing on strategic alignment between business objectives and technological capabilities, they can achieve meaningful efficiency gains while managing the risks associated with emerging technologies, O’Connell said.
In addition, the rapid pace of change in AI technologies means that organisations need to develop agile approaches to implementation rather than treating digital transformation as a one-time project.
As generative AI and large language models continue to evolve, organisations that have laid strong data foundations and developed adaptive implementation strategies will be best positioned to capitalise on the opportunities they present across the value chain, from client interactions to decision-making and compliance functions.
“Fundamentally, it is about business and digital alignment. Digital transformation is not a one shot: it’s going to be continuous. After all, every couple of months there are new models and they’re better than the last ones,” he said