Choosing the right AI business solutions
For Australian businesses exploring the potential of AI and assessing practical use cases, a deep knowledge of the landscape is required – and evaluating organisations and applying bespoke AI and data solutions is what Synechron has been doing globally for many years.
“When we engage with clients, we’re looking at the art of the possible” says Ryan Cox, senior director of information technology at Synechron.
Ryan Cox, senior director of information technology at Synechron.
“We look at the things that are unique to a company and, ultimately, what it is that they want to achieve,” says Cox.
“At Synechron, our strength lies not just in engineering excellence, but also in our strategic business consulting capabilities.
“We don’t just focus on the technical details; we consider the entire user journey from a strategic standpoint and then execute it effectively. This holistic approach enables us to seamlessly integrate AI where it matters most in that journey.”
Targeting efficiency
Synechron is now working with a client on a digital transformation program, with a focus on operational efficiency and reducing customer friction, he says.
“That means we can say ‘we know your systems, we know how you work, and we know where we can apply AI on top of that’,” says Cox.
Businesses right now are using AI predominantly to drive efficiency, looking for low-risk, high gain solutions – all the while considering the ethics of it and the desire to retain the human element.
“To make that happen, businesses need to get clean, usable data out of their systems,” he says.
“Our team crafts better code, generates more representative data, for testing at scale, and develops comprehensive test cases that cover the nuances of business requirements.
“From strategic consulting on best practices, to the technical execution of a client’s data infrastructure, we have the expertise. And, when it comes to cloud solutions, we prioritise not just setup, but also vital aspects like security and privacy. Ultimately, it’s this integrated approach to data and cloud expertise that will be a key accelerator for business, unlocking new dimensions in AI’s potential.”
Data fabric for real-time insights
One way of doing this is through the “data fabric” – an architectural concept that facilitates the end-to-end integration of various data pipelines and cloud environments using intelligent automation.
This makes it more flexible, scalable and enables more varied use cases; it bridges the gap between legacy and modern platforms, allowing data assets to be mapped out and recycled, says Cox.
Data fabric standardises complex data management tasks, enhances data agility, and supports real-time insights and self-service.
“Allied to this, you have governance, via ‘data products’ – the productisation of data into domain-owned products and the responsibility for consumer needs and governance – with centralised co-ordination only when absolutely necessary.
“The key for businesses looking to exploit AI effectively is to get clean, quality data they can use to improve efficiency, eliminating the superfluous elements.
“This is as much about a change of mindset for businesses as it is about technical architecture.”
Hyper-personalisation for better customer engagement
According to the Gallagher 2023 State of the Sector report, 55 per cent of organisations have identified hyper-personalisation as their internal comms priority over the next five years.
“Hyper-personalisation is all about using real-time data, AI machine learning, and predictive analytics to understand individual customer behaviors and make interactions, content, products and services more meaningful and relevant to them,” says Cox.
“There are real opportunities here for business but, again, data from multiple sources and devices – browsing, social media, purchase history, etc. (analysis of customer journeys and the profiles of individual customers) must be collected and sorted quickly and efficiently.
“With customers more likely to do business with companies offering hyper-personalisation (customers want to feel personally valued), companies can increase revenues and create dynamic customer engagement strategies. Crucially, you can’t do hyper-personalisation without the right data and detail underpinning it.”
Better data for increased efficiency
The ability of AI to identify patterns and insights that humans can misinterpret (or miss altogether) is already leading to better decision-making and, ultimately, new revenue-generating business models.
Right now, large language models (LLMs) are in the spotlight, but they’re just one tool in a broader toolkit.
“In the next few years, we’ll see LLMs continue to evolve as an interface for humans and machines, pulling it together such that there will be more seamless solutions, with higher quality and at a larger scale,” says Cox. “There will be more end-to-end process automation.”
As a tool to augment human capability in high-effort tasks, AI has already more than realised its potential, says Cox.
“From clients, we’re seeing a lot of operational focus and automation – in terms of reducing costs and enhancing productivity, that’s the number one business benefit of AI right now. Once these efficiencies are embedded, we can use AI for revenue growth – but we need that quality data before we can establish where we target revenue growth.”
To learn more, please visit www.synechron.com/en-au
