Johan Reventberg, Chief Revenue Officer at Unit4, argues that consolidating business data in cloud-native applications is the fastest route to reliable, bias-free AI.

The pace of technological change can at times seem almost overwhelming, particularly as the progress with generative AI appears so rapid. This creates a challenge for every senior executive and CIO who is tasked with understanding where to place their bets in terms of innovations that will significantly move the needle. 

The key is knowing which technology will deliver tangible competitive advantage. So, when these executives hear about the potential of artificial intelligence (AI), both as a threat and an opportunity for their organisations, it is understandable there is a mixture of trepidation, confusion and some reluctance to be an early adopter as they look to qualify if this is the right investment.

I’ve found that conversations about AI resonate much more with business leaders that have already started their digital transformation journey. That’s logical – moving key systems of record to the cloud is a big step on the path to developing more innovative digital services. It signals a mindset shift and a willingness to modernise. Importantly, the cloud offers the ideal foundations for flexibility and scalability, as these leaders look to adopt new tools such as AI.

Becoming cloud native is a critical first step for AI strategies

For any organisation considering AI, this journey starts with becoming cloud-native. Some might say that (of course) I would say that, but my reasoning is based on extensive experience gained over many years working with companies looking at how to best modernise their IT infrastructures. 

The reality is that unless your core business applications – HR, finance, project management – can communicate with one another and share information; you will struggle to address the key requirement of any AI tool. Namely, access to a unified picture of all the data within your organisation.

This is crucial, because most AI models require this data for training. Without accurate data, the training could lead to bias and hallucinations in the answers the AI tool provides.

Therefore, becoming cloud-native is integral to your AI strategy, but I am well aware there are reasons why some organisations move more quickly than others to embrace the cloud.

One of the biggest barriers to change is the much-used argument: ‘Why fix something if it isn’t broken?’

Moving to the cloud overcomes technical debt

It’s true that many organisations have been operating the same applications for a long time, with seemingly little problems. However, this is building up one of the biggest challenges in IT – technical debt. 

By leaving older versions of an application in place, it makes it harder for these systems to interoperate, which over time makes it harder for users to interact with them. At a time when consumer applications are becoming voice-activated and more intuitive, having to deal with clunky business applications is frustrating and demoralising for employees, never mind a constraint on your organisation’s productivity.

A key consequence of relying on older systems is the risk of security vulnerabilities. Cyber-attacks can be very costly, and ensuring that systems are patched promptly and upgrades are applied is a constant battle. Craig Lawson, VP Analyst at Gartner, recently highlighted the dangers of leaving systems unpatched, “I’ve never seen anyone ever out patch threat actors, not one… So, you can meet your SLA [service level agreement] and waste a lot of time applying patches without actually improving your security posture…”

By moving to the cloud, organisations not only optimise their existing applications to reduce the threat of cyber-attacks, but they can also automate the patching process to speed up responses to potential vulnerabilities.

Embrace the cloud. Don’t get left behind

The other side of the argument in favour of moving to the cloud is competitive advantage. If you are a commercial organisation, can you really risk being left behind by rivals who are embracing digital services?

As I mentioned earlier, this requires applications to talk to each another, so data can be shared. With this single view of all the information within core applications, data duplications can be removed, and anomalies identified. This ensures the AI is working on accurate information and can therefore make the best decisions. By embedding AI alongside core applications in the cloud, organisations can expose internal data to conduct real-time trend analysis which may spot trends. This could also be married with external data sources to enable organisations to predict future market opportunities before competitors.

Beyond these initial use cases, we are already seeing examples of AI Agents collaborating autonomously identifying new ways to work or finding additional revenue streams. For example, this could be using AI as part of the customer service process to speed up access to the information customers need or using AI to automate the production of code so that developers can quickly produce new features customers want.

All this is possible, if you have put the right cloud-native foundations in place. These foundations give you the scalability and flexibility to dynamically introduce AI tools and ramp up their use. By unifying data within your organisation, you have access to big data lakes that can train your AI models to ensure you are delivering more accurate responses. Furthermore, this will break down silos between teams and create more transparency, leading to greater collaboration.

AI will likely have a significant impact on the way organisations do business moving forward. The way we work is changing. It requires new skills and a willingness to work through how it benefits your organisation. The potential is very exciting and there are plenty of opportunities to help employees work more productively and do more rewarding tasks. However, without the right cloud-native foundations, adoption of AI could be piecemeal and only exacerbate issues like technical debt. Built from the ground up, your AI strategy will have far more solid roots and chance of success.